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The serotonin theory of depression: a systematic umbrella review of the evidence

Affiliations.

• 1 Division of Psychiatry, University College London, London, UK. [email protected].
• 2 Research and Development Department, Goodmayes Hospital, North East London NHS Foundation Trust, Essex, UK. [email protected].
• 3 Faculty of Education, Health and Human Sciences, University of Greenwich, London, UK.
• 4 Psychiatry-UK, Cornwall, UK.
• 5 Department of Dynamic and Clinical Psychology, and Health Studies, Faculty of Medicine and Psychology, Sapienza University of Rome, Rome, Italy.
• 6 Department of Applied Psychology, Zurich University of Applied Sciences, Zurich, Switzerland.
• 7 Division of Psychiatry, University College London, London, UK.
• 8 Research and Development Department, Goodmayes Hospital, North East London NHS Foundation Trust, Essex, UK.
• PMID: 35854107
• PMCID: PMC10618090
• DOI: 10.1038/s41380-022-01661-0

The serotonin hypothesis of depression is still influential. We aimed to synthesise and evaluate evidence on whether depression is associated with lowered serotonin concentration or activity in a systematic umbrella review of the principal relevant areas of research. PubMed, EMBASE and PsycINFO were searched using terms appropriate to each area of research, from their inception until December 2020. Systematic reviews, meta-analyses and large data-set analyses in the following areas were identified: serotonin and serotonin metabolite, 5-HIAA, concentrations in body fluids; serotonin 5-HT 1A receptor binding; serotonin transporter (SERT) levels measured by imaging or at post-mortem; tryptophan depletion studies; SERT gene associations and SERT gene-environment interactions. Studies of depression associated with physical conditions and specific subtypes of depression (e.g. bipolar depression) were excluded. Two independent reviewers extracted the data and assessed the quality of included studies using the AMSTAR-2, an adapted AMSTAR-2, or the STREGA for a large genetic study. The certainty of study results was assessed using a modified version of the GRADE. We did not synthesise results of individual meta-analyses because they included overlapping studies. The review was registered with PROSPERO (CRD42020207203). 17 studies were included: 12 systematic reviews and meta-analyses, 1 collaborative meta-analysis, 1 meta-analysis of large cohort studies, 1 systematic review and narrative synthesis, 1 genetic association study and 1 umbrella review. Quality of reviews was variable with some genetic studies of high quality. Two meta-analyses of overlapping studies examining the serotonin metabolite, 5-HIAA, showed no association with depression (largest n = 1002). One meta-analysis of cohort studies of plasma serotonin showed no relationship with depression, and evidence that lowered serotonin concentration was associated with antidepressant use (n = 1869). Two meta-analyses of overlapping studies examining the 5-HT 1A receptor (largest n = 561), and three meta-analyses of overlapping studies examining SERT binding (largest n = 1845) showed weak and inconsistent evidence of reduced binding in some areas, which would be consistent with increased synaptic availability of serotonin in people with depression, if this was the original, causal abnormaly. However, effects of prior antidepressant use were not reliably excluded. One meta-analysis of tryptophan depletion studies found no effect in most healthy volunteers (n = 566), but weak evidence of an effect in those with a family history of depression (n = 75). Another systematic review (n = 342) and a sample of ten subsequent studies (n = 407) found no effect in volunteers. No systematic review of tryptophan depletion studies has been performed since 2007. The two largest and highest quality studies of the SERT gene, one genetic association study (n = 115,257) and one collaborative meta-analysis (n = 43,165), revealed no evidence of an association with depression, or of an interaction between genotype, stress and depression. The main areas of serotonin research provide no consistent evidence of there being an association between serotonin and depression, and no support for the hypothesis that depression is caused by lowered serotonin activity or concentrations. Some evidence was consistent with the possibility that long-term antidepressant use reduces serotonin concentration.

© 2022. The Author(s).

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Conflict of interest statement

All authors have completed the Unified Competing Interest form at http://www.icmje.org/coi_disclosure.pdf (available on request from the corresponding author). SA declares no conflicts of interest. MAH reports being co-founder of a company in April 2022, aiming to help people safely stop antidepressants in Canada. MPH reports royalties from Palgrave Macmillan, London, UK for his book published in December, 2021, called “Evidence-biased Antidepressant Prescription.” JM receives royalties for books about psychiatric drugs, reports grants from the National Institute of Health Research outside the submitted work, that she is co-chairperson of the Critical Psychiatry Network (an informal group of psychiatrists) and a board member of the unfunded organisation, the Council for Evidence-based Psychiatry. Both are unpaid positions. TS is co-chairperson of the Critical Psychiatry Network. RC is an unpaid board member of the International Institute for Psychiatric Drug Withdrawal.

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Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) flow diagramme.

• Putting serotonin in its place-again. Menkes DB. Menkes DB. BMJ. 2022 Oct 5;379:o2357. doi: 10.1136/bmj.o2357. BMJ. 2022. PMID: 36198406 No abstract available.
• Is the serotonin hypothesis/theory of depression still relevant? Methodological reflections motivated by a recently published umbrella review. Möller HJ, Falkai P. Möller HJ, et al. Eur Arch Psychiatry Clin Neurosci. 2023 Feb;273(1):1-3. doi: 10.1007/s00406-022-01549-8. Eur Arch Psychiatry Clin Neurosci. 2023. PMID: 36790577 Free PMC article. No abstract available.
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• Reply to: "The serotonin theory of depression: a systematic umbrella review of the evidence" published by Moncrieff J, Cooper RE, Stockmann T, Amendola S, Hengartner MP, Horowitz MA in Molecular Psychiatry (2022 Jul 20. doi: 10.1038/s41380-022-01661-0). Bartova L, Lanzenberger R, Rujescu D, Kasper S. Bartova L, et al. Mol Psychiatry. 2023 Aug;28(8):3153-3154. doi: 10.1038/s41380-023-02093-0. Epub 2023 Jun 16. Mol Psychiatry. 2023. PMID: 37322062 No abstract available.
• Although serotonin is not a major player in depression, its precursor is. Almulla AF, Maes M. Almulla AF, et al. Mol Psychiatry. 2023 Aug;28(8):3155-3156. doi: 10.1038/s41380-023-02092-1. Epub 2023 Jun 16. Mol Psychiatry. 2023. PMID: 37322063 No abstract available.
• The serotonin hypothesis of depression: both long discarded and still supported? Moncrieff J, Cooper RE, Stockmann T, Amendola S, Hengartner MP, Plöderl M, Horowitz MA. Moncrieff J, et al. Mol Psychiatry. 2023 Aug;28(8):3160-3163. doi: 10.1038/s41380-023-02094-z. Epub 2023 Jun 16. Mol Psychiatry. 2023. PMID: 37322064 No abstract available.
• A leaky umbrella has little value: evidence clearly indicates the serotonin system is implicated in depression. Jauhar S, Arnone D, Baldwin DS, Bloomfield M, Browning M, Cleare AJ, Corlett P, Deakin JFW, Erritzoe D, Fu C, Fusar-Poli P, Goodwin GM, Hayes J, Howard R, Howes OD, Juruena MF, Lam RW, Lawrie SM, McAllister-Williams H, Marwaha S, Matuskey D, McCutcheon RA, Nutt DJ, Pariante C, Pillinger T, Radhakrishnan R, Rucker J, Selvaraj S, Stokes P, Upthegrove R, Yalin N, Yatham L, Young AH, Zahn R, Cowen PJ. Jauhar S, et al. Mol Psychiatry. 2023 Aug;28(8):3149-3152. doi: 10.1038/s41380-023-02095-y. Epub 2023 Jun 16. Mol Psychiatry. 2023. PMID: 37322065 Free PMC article.
• Neither serotonin disorder is at the core of depression nor dopamine at the core of schizophrenia; still these are biologically based mental disorders. Fountoulakis KN, Tsapakis EM. Fountoulakis KN, et al. Mol Psychiatry. 2024 Jan;29(1):198-199. doi: 10.1038/s41380-024-02458-z. Epub 2024 Feb 19. Mol Psychiatry. 2024. PMID: 38374355 No abstract available.
• The involvement of serotonin in major depression: nescience in disguise? Arnone D, Wise T, Fitzgerald PB, Harmer CJ. Arnone D, et al. Mol Psychiatry. 2024 Jan;29(1):200-202. doi: 10.1038/s41380-024-02459-y. Epub 2024 Feb 19. Mol Psychiatry. 2024. PMID: 38374356 No abstract available.
• Methodological concerns in umbrella review of serotonin and depression. Smith AL, Carvalho AF, Solmi M. Smith AL, et al. Mol Psychiatry. 2024 Jan;29(1):203-204. doi: 10.1038/s41380-024-02460-5. Epub 2024 Feb 19. Mol Psychiatry. 2024. PMID: 38374357 No abstract available.
• Letter to the editor concerning: "The serotonin theory of depression: a systematic umbrella review of the evidence". Ahmed DR. Ahmed DR. Mol Psychiatry. 2024 Jan;29(1):205. doi: 10.1038/s41380-024-02461-4. Epub 2024 Feb 19. Mol Psychiatry. 2024. PMID: 38374358 No abstract available.

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Evolution and Emerging Trends in Depression Research From 2004 to 2019: A Literature Visualization Analysis

1 School of Traditional Chinese Medicine, Beijing University of Chinese Medicine, Beijing, China

Xuemei Tian

2 School of Life Sciences, Beijing University of Chinese Medicine, Beijing, China

Xianrui Wang

Associated data.

The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author/s.

Depression has become a major threat to human health, and researchers around the world are actively engaged in research on depression. In order to promote closer research, the study of the global depression knowledge map is significant. This study aims to map the knowledge map of depression research and show the current research distribution, hotspots, frontiers, and trends in the field of depression research, providing researchers with worthwhile information and ideas. Based on the Web of Science core collection of depression research from 2004 to 2019, this study systematically analyzed the country, journal, category, author, institution, cited article, and keyword aspects using bibliometric and data visualization methods. A relationship network of depression research was established, highlighting the highly influential countries, journals, categories, authors, institutions, cited articles, and keywords in this research field. The study identifies great research potential in the field of depression, provides scientific guidance for researchers to find potential collaborations through collaboration networks and coexistence networks, and systematically and accurately presents the hotspots, frontiers, and shortcomings of depression research through the knowledge map of global research on depression with the help of information analysis and fusion methods, which provides valuable information for researchers and institutions to determine meaningful research directions.

Introduction

Health issues are becoming more and more important to people due to the continuous development of health care. The social pressures on people are becoming more and more pronounced in a social environment that is developing at an increasing rate. Prolonged exposure to stress can have a negative impact on brain development ( 1 ), and depression is one of the more typical disorders that accompany it. Stress will increase the incidence of depression ( 2 ), depression has become a common disease ( 3 ), endangering people's physical health. Depression is a debilitating mental illness with mood disorders, also known as major depression, clinical depression, or melancholia. In human studies of the disease, it has been found that depression accounts for a large proportion of the affected population. According to the latest data from the World Health Organization (WHO) statistics in 2019, there are more than 350 million people with depression worldwide, with an increase of about 18% in the last decade and an estimated lifetime prevalence of 15% ( 4 ), it is a major cause of global disability and disease burden ( 5 ), and depression has quietly become a disease that threatens hundreds of millions of people worldwide.

Along with the rise of science communication research, the quantification of science is also flourishing. As a combination of “data science” and modern science, bibliometrics takes advantage of the explosive growth of research output in the era of big data, and uses topics, authors, publications, keywords, references, citations, etc. as research targets to reveal the current status and impact of the discipline more accurately and scientifically. Whereas, there is not a wealth of bibliometric studies related to depression. Fusar-Poli et al. ( 6 ) used bibliometrics to systematically evaluate cross-diagnostic psychiatry. Hammarström et al. ( 7 ) used bibliometrics to analyze the scientific quality of gender-related explanatory models of depression in the medical database PubMed. Tran et al. ( 8 ) used the bibliometric analysis of research progress and effective interventions for depression in AIDS patients. Wang et al. ( 9 ) used bibliometric methods to analyze scientific studies on the comorbidity of pain and depression. Shi et al. ( 10 ) performed a bibliometric analysis of the top 100 cited articles on biomarkers in the field of depression. Dongping et al. ( 11 ) used bibliometric analysis of studies on the association between depression and gut flora. An Chunping et al. ( 12 ) analyzed the literature on acupuncture for depression included in PubMed based on bibliometrics. Yi and Xiaoli ( 13 ) used a bibliometric method to analyze the characteristics of the literature on the treatment of depression by Chinese medicine in the last 10 years. Zhou and Yan ( 14 ) used bibliometric method to analyze the distribution of scientific and technological achievements on depression in Peoples R China. Guaijuan ( 15 ) performed a bibliometric analysis of the interrelationship between psoriasis and depression. Econometric analysis of the relationship between vitamin D deficiency and depression was performed by Yunzhi et al. ( 16 ) and Shauni et al. ( 17 ) performed a bibliometric analysis of domestic and international research papers on depression-related genes from 2003 to 2007. A previous review of depression-related bibliometric studies revealed that there is no bibliometric analysis of global studies in the field of depression, including country network analysis, journal network analysis, category network analysis, author network analysis, institutional network analysis, literature co-citation analysis, keyword co-presentation analysis, and cluster analysis.

The aim of this study was to conduct a comprehensive and systematic literature-based data mining and metrics analysis of depression-related research. More specifically, this analysis focuses on cooperative network and co-presentation analysis, based on the 36,477 papers included in the Web of Science Core Collection database from 2004 to 2019, and provides an in-depth analysis of cooperative network, co-presentation network, and co-citation through modern metrics and data visualization methods. Through the mining of key data, the data correlation is further explored, and the results obtained can be used to scientifically and reasonably predict the depression-related information. This study aims to show the spatial and temporal distribution of research countries, journals, authors, and institutions in the field of depression in a more concise manner through a relational network. A deeper understanding of the internal structure of the research community will help researchers and institutions to establish more accurate and effective global collaborations, in line with the trend of human destiny and globalization. In addition, the study will allow for the timely identification of gaps in current research. A more targeted research direction will be established, a more complete picture of the new developments in the field of depression today will be obtained, and the research protocol will be informed for further adjustments. The results of these analyses will help researchers understand the evolution of this field of study. Overall, this paper uses literature data analysis to find research hotspots in the field of depression, analyze the knowledge structure within different studies, and provide a basis for predicting research frontiers. This study analyzed the literature in the field of depression using CiteSpace 5.8.R2 (64-bit) to analyze collaborative networks, including country network analysis, journal network analysis, category network analysis, researcher network analysis, and institutional network analysis using CiteSpace 5.8.R2 (64-bit). In addition, literature co-citation, keyword co-presentation, and cluster analysis of depression research hotspots were also performed. Thus, exploring the knowledge dimensions of the field, quantifying the research patterns in the field, and uncovering emerging trends in the field will help to obtain more accurate and complete information. The large amount of current research results related to depression will be presented more intuitively and accurately with the medium of information technology, and the scientific evaluation of research themes and trend prediction will be provided from a new perspective.

Data Sources

The data in this paper comes from the Web of Science (WoS) core collection. The time years were selected as 2004–2019. First, the literature was retrieved after entering “depression” using the title search method. A total of 73,829 articles, excluding “depression” as “suppression,” “decline,” “sunken,” “pothole,” “slump,” “low pressure,” “frustration.” The total number of articles with other meanings such as “depression” was 5,606, and the total number of valid articles related to depression was 68,223. Next, the title search method was used to search for studies related to “major depressive disorder” not “depression,” and a total of 8,070 articles were retrieved. For the two search strategies, a total of 76,293 records were collected. The relevant literature retrieved under the two methods were combined and exported in “plain text” file format. The exported records included: “full records and references cited.” CiteSpace processed the data to obtain 41,408 valid records, covering all depression-related research articles for the period 2004–2019, and used this as the basis for analysis.

Processing Tools

CiteSpace ( 18 ), developed by Chao-Mei Chen, a professor in the School of Information Science and Technology at Drexel University, is a Java-based program with powerful data visualization capabilities and is one of the most widely used knowledge mapping tools. The software version used in this study is CiteSpace 5.8.R2 (64-bit).

Methods of Analysis

This study uses bibliometrics and data visualization as analytical methods. First, the application of bibliometrics to the field of depression helped to identify established and emerging research clusters, demonstrating the value of research in this area. Second, data visualization provides multiple perspectives on the data, presenting correlations in a clearer “knowledge graph” that can reveal underestimated and overlooked trends, patterns, and differences ( 19 ). CiteSpace is mainly based on the “co-occurrence clustering idea,” which extracts the information units (keywords, authors, institutions, countries, journals, etc.) in the data by classification, and then further reconstructs the data in the information units to form networks based on different types and strengths of connections (e.g., keyword co-occurrence, author collaboration, etc.). The resulting networks include nodes and links, where the nodes represent the information units of the literature and the links represent the existence of connections (co-occurrence) between the nodes. Finally, the network is measured, statistically analyzed, and presented in a visual way. The analysis needs to focus on: the overall structure of the network, key nodes and paths. The key evaluation indicators in this study are: betweenness centrality, year, keyword frequency, and burst strength. Betweenness centrality (BC) is the number of times a node acts as the shortest bridge between two other nodes. The higher the number of times a node acts as an “intermediary,” the greater its betweenness centrality. Betweenness centrality is a measure of the importance of articles found and measured by nodes in the network by labeling the category (or authors, journals, institutions, etc.) with purple circles. There may be many shortest paths between two nodes in the network, and by counting all the shortest paths of any two nodes in the network, if many of the shortest paths pass through a node, then the node is considered to have high betweenness centrality. In CiteSpace, nodes with betweenness centrality over 0.1 are called critical nodes. Year, which represents the publication time of the article. Frequency, which represents the number of occurrences. Burst strength, an indicator used to measure articles with sudden rise or sudden decline in citations. Nodes with high burst strength usually represent a shift in a certain research area and need to be focused on, and the burst article points are indicated in red. The nodes and their sizes and colors are first analyzed initially, and further analyzed by betweenness centrality indicators for evaluation. Each node represents an article, and the larger the node, the greater the frequency of the keyword word and the greater the relevance to the topic. Similarly, the color of the node represents time: the warmer the color, the more recent the time; the colder the color, the older the era; the node with a purple outer ring is a node with high betweenness centrality; the color of each annual ring can determine the time distribution: the color of the annual ring represents the corresponding time, and the thickness of one annual ring is proportional to the number of articles within the corresponding time division; the dominant color can reflect the relative concentration of the emergence time; the node The appearance of red annual rings in the annual rings means hot spots, and the frequency of citations has been or is still increasing rapidly.

Large-Scale Assessment

Country analysis.

During the period 2004–2019, a total of 157 countries/territories have conducted research on depression, which is about 67.38% of 233 countries/territories worldwide. This shows that depression is receiving attention from many countries/regions around the world. Figure 1 shows the geographical distribution of published articles for 157 countries. The top 15 countries are ranked according to the number of articles published. Table 1 lists the top 15 countries with the highest number of publications in the field of depression worldwide from 2004 to 2019. These 15 countries include 4 Asian countries (Peoples R China, Japan, South Korea, Turkey), 2 North American countries (USA, Canada), 1 South American country (Brazil), 7 European countries (UK, Germany, Netherlands, Italy, France, Spain, Sweden), and 1 Oceania country (Australia).

Geographical distributions of publications, 2004–2019.

The top 15 productive countries.

TP, total publications; TP R (%), the ratio of the amount of the publications in the country to the publications in the word during 2004–2019; BC, betweenness centrality; TPA (million), total publications in all areas; TPA R (%), the ratio of the amount of publications in depression to publications in all areas .

Overall, the main distribution of these articles is in USA and some European countries, such as UK, Germany, Netherlands, Italy, France, Spain, and Sweden. This means that these countries are more interested and focused on research on depression compared to others. The total number of publications across all research areas in the Web of Science core collection is similar to the distribution of depression research areas, with the trend toward USA, UK, and Peoples R China as leading countries being unmistakable, and USA has been a leader in the field of depression, with far more articles published than any other country. It can also be seen that USA is the country with the highest betweenness centrality in the network of national collaborations analyzed in this paper. USA research in the field of depression is closely linked to global research, and is an important part of the global collaborative network for depression research. As of 2019, the total number of articles published in depression performance research in USA represents 27.13% of the total number of articles published in depression worldwide, which is ~4 times more than the second-place country, UK, which is far ahead of other countries. Peoples R China, as the third most published country, has a dominant number of articles, but its betweenness centrality is 0.01, reflecting the fact that Peoples R China has less collaborative research with other countries, so Peoples R China should strengthen its foreign collaborative research and actively establish global scientific research partnerships to seek development and generate breakthroughs in cooperation. The average percentage of scientific research on depression in each country is about 0.19%, also highlighting the urgent need to address depression as one of the global human health problems. The four Asian countries included in the top 15 countries are Peoples R China, Japan, South Korea, and Turkey, with Peoples R China ranking third with 6.72% of the total number of all articles counted. The distribution may be explained by the fact that Peoples R China is the largest developing country with a rapid development rate as the largest. Along with the steady rise in the country's economic power, people are creating economic benefits and their health is becoming a consumable commodity. The lifetime prevalence and duration of depression varies by country and region ( 2 ), but the high prevalence and persistence of depression worldwide confirms the increasing severity of the disease worldwide. The WHO estimates that more than 300 million people, or 4.4% of the world's population, suffer from depression ( 20 ), with the number of people suffering from depression increasing at a patient rate of 18.4% between 2005 and 2015. Depression, one of the most prevalent mental illnesses of our time, has caused both physical and psychological harm to many people, and it has become the leading cause of disability worldwide today, and in this context, there is increased interest and focus on research into depression. It is expected that a more comprehensive understanding of depression and finding ways to prevent and cope with the occurrence of this disease can help people get rid of the pain and shadow brought by depression, obtain a healthy and comfortable physical and mental environment and physical health, and make Chinese contributions to the cause of human health. Undoubtedly, the occurrence of depressive illnesses in the context of irreversible human social development has stimulated a vigorous scientific research environment on depression in Peoples R China and other developing countries and contributed to the improvement of research capacity in these countries. Moreover, from a different perspective, the geographical distribution of articles in this field also represents the fundamental position of the country in the overall scientific and academic research field.

Growth Trend Analysis

Figure 2 depicts the distribution of 38,433 articles from the top 10 countries in terms of the number of publications and the trend of growth during 2004–2019.

The distribution of publications in top 10 productive countries, 2004–2019. Source: author's calculation. National development classification criteria refer to “Human Development Report 2020” ( 21 ).

First, the number of articles published per year for the top 10 countries in terms of productivity was counted and then the white bar chart in Figure 2 was plotted, with the year as the horizontal coordinate and total publications as the vertical coordinate, showing the distribution of the productivity of articles in the field of depression per year. The total number of publications for the period 2004–2019 is 38,433. Based on the white bars and line graphs in Figure 2 , we can divide this time period into three growth periods. The number of publications in each growth period is calculated based on the number of publications per year. As can be seen from the figure, the period 2004–2019 can be divided into three main growth periods, namely 2004–2009, 2010–2012, and 2013–2019, the first growth period being from 2004 to 2009, the number of publications totaled 6,749, accounting for 23.97% of all publications; from 2010 to 2012, the number of publications totaled 8,236, accounting for 17.56% of all publications; and from 2013 to 2019, the number of publications totaled 22,473, accounting for 58.47% of all publications. Of these, 2006 was the first year of sharp growth with an annual growth rate of 19.97%, 2009 was the second year of sharp growth with an annual growth rate of 17.64%, and 2008 was the third year of sharp growth with an annual growth rate of 16.09%. In the last 5 years, 2019 has also shown a sharp growth trend with a growth rate of 14.34%. Notably, in 2010 and 2013, there was negative growth with the growth rate of −3.39 and −1.45%. In the last 10 years, depression research has become one of the most valuable areas of human research. It can also be noted that the number of publications in the field of depression in these 10 countries has been increasing year after year.

Second, the analysis is conducted from the perspective of national development, divided into developed and developing countries, as shown in the orange bar chart in Figure 2 , where the horizontal coordinate is year and the vertical coordinate is total publications, comparing the article productivity variability between developed and developing countries. The top 10 most productive countries in the field of depression globally include nine developed countries and one developing country, respectively. During the period 2004–2019, 34,631 papers were published in developed countries and 3,802 papers were published in developing countries, with developed countries accounting for 90.11% of the 38,433 articles and developing countries accounting for 9.89%, and the total number of publications in developed countries was about 9 times higher than that in developing countries. During the period 2004–2019, the number of publications in developed countries showed negative growth in 2 years (2010 and 2013) with growth rates of −3.39 and −1.45%, respectively. The rest of the years showed positive growth with growth rates of 1.52% (2005), 19.97 (2006), 8.11 (2007), 12.70 (2008), 17.64 (2009), 13.22 (2011), 10.17 (2012), 16.09 (2014), 10.46 (2015), 4.10 (2016), 1.59 (2017), 3.91 (2018), and 14.34 (2019), showing three periods of positive growth: 2004–2009, 2011–2012, and 2014–2019, with the highest growth rate of 19.97% in 2006. Recent years have also shown a higher growth trend, with a growth rate of 14.34% in 2019. It is worth noting that developing countries have been showing positive growth in the number of articles in the period 2004–2019, with annual growth rates of 81.25 (2005), 17.24 (2006), 35.29 (2007), 19.57 (2008), 65.45 (2009), 13.19 (2010), 29.13 (2011), 54.89 (2012), 12.14 (2013), 36.36 (2014), 14.92 (2015), 16.02 (2016), 10.24 (2017), 21.17 (2018), and 31.37 (2019), with the highest growth rate of 81.25% in 2005. In the field of depression research, developed countries are still the main force and occupy an important position.

Further, 10 countries with the highest productivity in the field of depression are compared, total publications in the vertical coordinate, and the colored scatter plot contains 10 colored dots, representing 10 different countries. On the one hand, the variability of the contributions of different countries in the same time frame can be compared horizontally. On the other hand, it is possible to compare vertically the variability of the growth of different countries over time. Among them, USA, with about 40.29% of the world's publications in the field of depression, has always been a leader in the field of depression with its rich research results. Peoples R China, as the only developing country, ranks 3rd in the top 10 countries with high production of research papers in the field of depression, and Peoples R China's research in the field of depression has shown a rapid growth trend, and by 2016, it has jumped to become the 2nd largest country in the world, with the number of published papers increasing year by year, which has a broad prospect and great potential for development.

Distribution of Periodicals

Table 2 lists the top 15 journals in order of number of journal co-citations. In the field of depression, the top 15 cited journals accounted for 19.06% of the total number of co-citations, nearly one in five of the total number of journal co-citations. In particular, the top 3 journals were ARCH GEN PSYCHIAT (ARCHIVES OF GENERAL PSYCHIATRY), J AFFECT DISORDERS (JOURNAL OF AFFECTIVE DISORDERS), and AM J PSYCHIAT (AMERICAN JOURNAL OF PSYCHIATRY), with co-citation counts of 20,499, 20,302, and 20,143, with co-citation rates of 2.09, 2.07, and 2.06%, respectively. The main research area of ARCH GEN PSYCHIAT is Psychiatry; the main research area of the journal J AFFECT DISORDERS is Neurosciences and Neurology, Psychiatry; AM J PSYCHIAT is the main research area of Psychiatry, and the three journals have “psychiatry” in common, making them the most frequently co-cited journals in the field of depression.

The top 15 co-cited journals.

TP, total publications; TP R (%), the ratio of the amount of the journal's publications to the total publications; BC, betweenness centrality .

Figure 3 shows the network relationship graph of the cited journals from 2004 to 2019. The figure takes g-index as the selection criteria, the scale factor k = 25 to include more nodes. Each node of the graph represents each journal, the node size represents the number of citation frequencies, the label size represents the size of the betweenness centrality of the journal in the network, and the links between journals represent the co-citation relationships. The journal co-citation map reflects the structure of the journals, indicating that there are links between journals and that the journals include similar research topics. These journals included research topics related to neuroscience, psychiatry, neurology, and psychology. The journal with betweenness centrality size in the top 1 was ARCH GEN PSYCHIAT, with betweenness centrality size of 0.07, and impact shadows of 14.48. ARCH GEN PSYCHIAT, has research themes of Psychiatry. In all, these journals in Figure 3 occupy an important position in the journal's co-citation network and have strong links with other journals.

Prominent journals involved in depression. The betweenness centrality of a node in the network measures the importance of the position of the node in the network. Two types of nodes may have high betweenness centrality scores: (1) Nodes that are highly connected to other nodes, (2) Nodes are positioned between different groups of nodes. The lines represent the link between two different nodes.

Distribution of Categories

Table 3 lists the 15 most popular categories in the field of depression research during the period 2004–2019. In general, the main disciplines involved are neuroscience, psychology, pharmacy, medicine, and health care, which are closely related to human life and health issues. Of these, psychiatry accounted for 20.78%, or about one-five, making it the most researched category. The study of depression focuses on neuroscience, reflecting the essential characteristics of depression as a category of mental illness and better reflecting the fact that depression is an important link in the human public health care. In addition, Table 3 shows that the category with the highest betweenness centrality is Neuroscience, followed by Public, Environment & Occupational Health, and then Pharmacology & Pharmacy, with betweenness centrality of 0.16, 0.13, and 0.11, respectively. It is found that the research categories of depression are also centered on disciplines such as neuroscience, public health and pharmacology, indicating that research on depression requires a high degree of integration of multidisciplinary knowledge and integration of information from various disciplines in order to have a more comprehensive and in-depth understanding of the depression.

The top 15 productive categories, 2004–2019.

TP, total publications; TP R (%), the ratio of the amount of the category's publications to the total publications; BC, betweenness centrality .

Figure 4 shows the nine categories with the betweenness centrality in the category research network, with Neuroscience being the node with the highest betweenness centrality in this network, meaning that Neuroscience is most strongly linked to all research categories in the field of depression research. Depression is a debilitating psychiatric disorder with mood disorders. It is worth noting that the development of depression not only has psychological effects on humans, but also triggers many somatic symptoms that have a bad impact on their daily work and life, giving rise to the second major mediating central point of research with public health as its theme. The somatization symptoms of depression often manifest as abnormalities in the cardiovascular system, and many studies have looked at the pathology of the cardiovascular system in the hope of finding factors that influence the onset of depression, mechanisms that trigger it or new ways to treat it. Thus, depression involves not only the nervous system, but also interacts with the human cardiovascular system, for example, and the complexity of depression dictates that the study of depression is an in-depth study based on complex systems.

Prominent categories involved in depression, 2004–2019. The betweenness centrality of a node in the network measures the importance of the position of the node in the network. Two types of nodes may have high betweenness centrality scores: (1) Nodes that are highly connected to other nodes, (2) Nodes are positioned between different groups of nodes. The lines represent the link between two different nodes.

Author Statistics

The results of the analysis showed that there were many researchers working in the field of depression over the past 16 years, and 63 of the authors published at least 30 articles related to depression. Table 4 lists the 15 authors with the highest number of articles published. It includes the rank of the number of articles published, author, country, number of articles published in depression-related studies, total number of articles included in Web of Science, total number of citations, average number of citations, and H-index. According to the statistics, seven of the top 15 authors are from USA, three from the Netherlands, one from Canada, one from Australia, one from New Zealand, one from Italy, and one from Germany. From this, it can be seen that these productive authors are from developed countries, thus it can be inferred that developed countries have a better research environment, more advanced research technology and more abundant research funding. The evaluation indicators in the author co-occurrence network are frequency, betweenness centrality and time of first appearance. The higher the frequency, i.e., the higher the number of collaborative publications, the more collaboration, the higher the information dissemination rate, the three authors with the highest frequency in this author co-occurrence network are MAURIZIO FAVA, BRENDA W. J. H. PENNINX, MADHUKAR H. TRIVEDI; the higher the betweenness centrality, i.e., the closer the relationship with other authors, the more collaboration, the higher the information dissemination rate, the three authors with the highest betweenness centrality are the three authors with the highest betweenness centrality are MICHAEL E. THASE, A. JOHN RUSH; the time of first appearance, i.e., the longer the influence generated by the author's research, the higher the information dissemination rate; in addition, the impact factor and citations can also reflect the information dissemination efficiency of the authors.

The top 15 authors in network of co-authorship, 2004–2019.

BC, betweenness centrality; TP, total publications; AP, publications in all areas; DP (%), the ratio of the publications about depression in 2004–2019 to the publications about all areas in all times; TC, total citation; CPP (%), citations per publication .

The timezone view ( Figure 5 ) in the author co-occurrence network clearly shows the updates and interactions of author collaborations, for example. All nodes are positioned in a two-dimensional coordinate with the horizontal axis of time, and according to the time of first posting, the nodes are set in different time zones, and their positions are sequentially upward with the time axis, showing a left-to-right, bottom-up knowledge evolution diagram. The time period 2004–2019 is divided into 16 time zones, one for each year, and each circle in the figure represents an author, and the time zone in which the circle appears is the year when the author first published an article in the data set of this study. The closer the color, the warmer the color, the closer the time, the colder the color, the older the era, the thickness of an annual circle, and the number of articles within the corresponding time division is proportional, the dominant color can reflect the relative concentration of the emergence time, the nodes appear in the annual circle of the red annual circle, that is, on behalf of the hot spot, the frequency of being cited was or is still increasing sharply. Nodes with purple outer circles are nodes with high betweenness centrality. The time zone view demonstrates the growth of author collaboration in the field, and it can be found from the graph that the number of author collaborations increases over time, and the frequency of publications in the author collaboration network is high; observe that the thickness of the warm annual rings in the graph is much greater than the thickness of the cold annual rings, which represents the increase of collaboration in time; there are many authors in all time zones, which indicates that there are many research collaborations and achievements in the field, and the field is in a period of collaborative prosperity. The linkage relationship between the sub-time-periods can be seen by the linkage relationship between the time periods, and it can be found from the figure that there are many linkages in the field in all time periods, which indicates that the author collaboration in the field of depression research is strong.

Timezone view of the author's co-existing network in depression, 2004–2019. The circle represents the author, the time zone in which the circle appears is the year in which the author first published in this study dataset, the radius of the circle represents the frequency of appearance, the color represents the different posting times, the lines represent the connections between authors, and the time zone diagram shows the evolution of author collaboration.

Institutional Statistics

Table 5 lists the top 15 research institutions in network of co-authors' institutions. These include 10 American research institutions, two Netherlands research institutions, one UK research institution, one Canadian research institution and one Australian research institution, all of which, according to the statistics, are from developed countries. Of these influential research institutions, 66.7% are from USA. Figure 6 shows the collaborative network with these influential research institutions as nodes. Kings Coll London (0.2), Univ Michigan (0.17), Univ Toronto (0.15), Stanford Univ (0.14), Univ Penn (0.14), Univ Pittsburgh (0.14), Univ Melbourne (0.12), Virginia Commonwealth Univ (0.12), Columbia Univ (0.1), Duke Univ (0.1), Massachusetts Gen Hosp (0.1), Vrije Univ Amsterdam (0.1), with betweenness centrality >0.1. Kings Coll London has a central place in this collaborative network and is influential in the field of depression research. Table 6 lists the 15 institutions with the strong burst strength. The top 3 institutions are all from USA. Univ Copenhagen, Univ Illinois, Harvard Med Sch, Boston Univ, Univ Adelaide, Heidelberg Univ, Univ New South Wales, and Icahn Sch Med Mt Sinai have had strong burst strength in recent years. It suggests that these institutions may have made a greater contribution to the field of depression over the course of this year and more attention could be paid to their research.

The top 15 institutions in network of co-authors' institutions, 2004–2019.

TP, total publications; BC, betweenness centrality .

Prominent institutions involved in depression, 2004–2019. The betweenness centrality of a node in the network measures the importance of the position of the node in the network. Two types of nodes may have high betweenness centrality scores: (1) Nodes that are highly connected to other nodes, (2) Nodes are positioned between different groups of nodes. The lines represent the link between two different nodes.

The top 15 institutions with the strongest citation bursts, 2004–2019.

Burst denote the citation burst strength; blue thin lines denote the whole period of 2004962019, which provide a useful means to trace the development of research focus; the location and length of red thick lines denote the start and end time during the whole period of the bursts and how long the burst lasts .

Summing up the above analysis, it can be seen that the research institutions in USA are at the center of the depression research field, are at the top of the world in terms of quantity and quality of research, and are showing continuous growth in vitality. Research institutions in USA, as pioneers among all research institutions, lead and drive the development of depression research and play an important role in cutting-edge research in the field of depression.

Article Citations

Table 7 lists the 16 articles that have been cited more than 1,000 times within the statistical range of this paper from 2004 to 2019. As can be seen from the table, the most cited article was written by Dowlati et al. from Canada and published in BIOLOGICAL PSYCHIATRY 2010, which was cited 2,556 times. In addition, 11 of these 16 highly cited articles were from the USA. Notably, two articles by Kroenke, K as first author appear in this list, ranked 7th and 11th, respectively. In addition, there are three articles from Canada, one article from Switzerland, and one article from the UK. And interestingly, all of these countries are developed countries. It can be reflected that developed countries have ample research experience and high quality of research in the field of depression research. On the other hand, it also reflects that depression is a key concern in developed countries. These highly cited articles provide useful information to many researchers and are of high academic and exploratory value.

The top 15 frequency cited articles, 2004–2019.

TP, total publications (citations) .

Research Hotspots Ang Frontiers

Keyword analysis.

The keyword analysis of depression yielded the 25 most frequent keywords in Table 8 and the keyword co-occurrence network in Figure 7 . Also, the data from this study were detected by burst, the 25 keywords with the strongest burst strength were obtained in Table 9 . These results bring out the popular and cutting-edge research directions in the field clearly.

Top 25 frequent keywords in the period of 2004–2019.

Count, number of times the article has been cited; BC, betweenness centrality .

Keyword co-occurrence network in depression, 2004–2019.

Top 25 keywords with strongest citation bursts in the period of 2004–2019.

Burst denote the citation burst strength; blue thin lines denote the whole period of 2004–2019, which provide a useful means to trace the development of research focus; the location and length of red thick lines denote the start and end time during the whole period of the bursts and how long the burst lasts .

The articles on depression during 2004–2019 were analyzed in 1-year time slices, and the top 25 keywords with the highest frequency of occurrence were selected from each slice to obtain the keyword network shown in Table 8 . The top 25 keywords with the highest frequencies were: symptom, disorder, major depression, prevalence, meta-analysis, anxiety, risk, scale, association, quality of life, health, risk factor, stress, validity, validation, mental health, women, double blind, brain, population, disease, impact, primary care, mood, and efficacy. High-frequency nodes respond to popular keywords and are an important basis for the field of depression research.

Figure 7 shows the co-occurrence network mapping of keywords regarding depression research. Each circle in the figure is a node representing a keyword, and the greater the betweenness centrality, the more critical the position of the node in the network. The top 10 keywords in terms of betweenness centrality are: symptom (0.6), major depression (0.28), prevalence (0.27), disorder (0.25), double blind (0.18), risk factor (0.12), stress (0.11), children (0.1), schizophrenia (0.1), and expression (0.1). Nodes with high betweenness centrality reflect that the keyword forms a co-occurrence relationship with multiple other keywords in the domain. A higher betweenness centrality indicates that it is more related to other keywords, and therefore, the node plays an important role in the study. Relatively speaking, these nodes represent the main research directions in the field of depression; they are also the key research directions in this period, and to a certain extent, represent the research hotspots in this period.

Burst detection was performed on the keywords, and the 25 keywords with the strongest strength were extracted, as shown in Table 9 . These keywords contain: fluoxetine, community, follow up, illness, psychiatric disorder, dementia, trial, placebo, disability, serotonin reuptake inhibitor, myocardial infarction, hospital anxiety, antidepressant treatment, late life depression, United States, epidemiology, major depression, model, severity, adolescent, people, prefrontal cortex, management, meta-analysis, and expression. The keywords that burst earlier include fluoxetine (2004), community (2004), follow up (2004), illness (2004), and psychiatric disorder (2004), are keywords that imply that researchers focused on themes early in the field of depression. As researchers continue to explore, the study of depression is changing day by day, and the keywords that have burst in recent years are people (2015), prefrontal cortex (2016), management (2016), meta-analysis (2017), and expression (2017). Reflecting the fact that depression research in recent years has mainly focused on human subjects, the focus has been on the characterization of populations with depression onset. The relationship between depression and the brain has aroused the curiosity of researchers, what exactly are the causes that trigger depression and what are the effects of depression for the manifestation of depression have caused a wide range of discussions in the research community, and the topics related to it have become the most popular studies and have been the focus of research in recent years. All of these research areas showed considerable growth, indicating that research into this area is gaining traction, suggesting that it is becoming a future research priority. The keywords with the strongest burst strength are fluoxetine (111.2), community (110.08), antidepressant treatment (94.28), severity (88.35), meta-analysis (86.42), people (85.33), and follow up (84.46). The rapid growth of research based on these keywords indicates that these topics are the most promising and interesting. The keywords that has been around the longest burst are follow up (2004–2013), model (2013–2019), hospital anxiety (2008–2013), severity (2014–2019), and psychiatric disorder (2004–2008), researchers have invested a lot of research time in these research directions, making many research results, and responding to the exploratory value and significance of research on these topics. At the same time, the longer duration of burst also proves that these research directions have research potential and important value.

Research Hotspots

Hotspots must mainly have the characteristics of high frequency, high betweenness centrality, strong burst, and time of emergence can be used as secondary evaluation indicators. The higher the number of occurrences, the higher the degree of popularity and attention. The higher betweenness centrality means the greater the influence and the higher the importance. Nodes with strong burst usually represent key shift nodes and need to be focused on. The time can be dynamically adjusted according to the target time horizon of the analysis. Thus, based on the results of statistical analysis, it is clear that the research hotspots in the field of depression can be divided into four main areas: etiology (external factors, internal factors), impact (quality of life, disease symptoms, co-morbid symptoms), treatment (interventions, drug development, care modalities), and assessment (population, size, symptoms, duration of disease, morbidity, mortality, effectiveness).

Risk factors for depression include a family history of depression, early life abuse and neglect, and female sexuality and recent life stressors. Physical illnesses also increase the risk of depression, particularly increasing the prevalence associated with metabolic (e.g., cardiovascular disease) and autoimmune disorders.

Research on the etiology of depression can be divided into internal and external factors. In recent years, researchers have increasingly focused on the impact of external factors on depression. Depression is influenced by environmental factors related to social issues, such as childhood experiences, social interactions, and lifestyles. Adverse childhood experiences are risk factors for depression and anxiety in adolescence ( 37 ) and are a common pathway to depression in adults ( 38 ). Poor interpersonal relationships with classmates, family, teachers, and friends increase the prevalence of depression in adolescents ( 39 ). Related studies assessed three important, specific indicators of the self-esteem domain: social confidence, academic ability, and appearance ( 40 ). The results suggest that these three dimensions of self-esteem are key risk factors for increased depressive symptoms in Chinese adolescents. The vulnerability model ( 41 ) suggests that low self-esteem is a causal risk factor for depression, and low self-esteem is thought to be one of the main causes of the onset and progression of depression, with individuals who exhibit low self-esteem being more likely to develop social anxiety and social withdrawal, and thus having a sense of isolation ( 42 ), which in turn leads to subsequent depression. Loneliness predicts depression in adolescents. Individuals with high levels of loneliness experience more stress and tension from psychological and physical sources in their daily lives, which, combined with insufficient care from society, can lead to depression ( 43 ). A mechanism of association exists between life events and mood disorders, with negative life events being directly associated with depressive symptoms ( 44 ). In a cross-sectional study conducted in Shanghai, the prevalence of depression was higher among people who worked longer hours, and daily lifestyle greatly influenced the prevalence of depression ( 45 ). A number of studies in recent years have presented a number of interesting ideas, and they suggest that depression is related to different environmental factors, such as temperature, sunlight hours, and air pollution. Environmental factors have been associated with suicidal behavior. Traffic noise is a variable that triggers depression and is associated with personality disorders such as depression ( 46 ). The harmful effects of air pollution on mental health, inhalation of air pollutants can trigger neuroinflammation and oxidative stress and induce dopaminergic neurotoxicity. A study showed that depression was associated with an increase in ambient fine particulate matter (PM2.5) ( 47 ).

Increased inflammation is a feature of many diseases and even systemic disorders, such as some autoimmune diseases [e.g., type 1 diabetes ( 48 ) or rheumatoid arthritis ( 49 )] and infectious diseases [e.g., hepatitis and sepsis ( 50 )], are associated with an inflammatory response and have been found to increase the risk of depression. A growing body of evidence supports a bidirectional association between depression and inflammatory processes, with stressors and pathogens leading to excessive or prolonged inflammatory responses when combined with predisposing factors (e.g., childhood adversity and modifying factors such as obesity). The resulting illnesses (e.g., pain, sleep disorders), depressive symptoms, and negative health (e.g., poor diet, sedentary lifestyle) may act as mediating pathways leading to inflammation and depression. In terms of mechanistic pathways, cytokines induce depression by affecting different mood-related processes. Elevated inflammatory signals can dysregulate the metabolism of neurotransmitters, damaging neurons, and thus altering neural activity in the brain. In addition cytokines can modulate depression by regulating hormone levels. Inflammation can have different effects on different populations depending on individual physiology, and even lower levels of inflammation may have a depressive effect on vulnerable individuals. This may be due to lower parasympathetic activity, poorer sensitivity to glucocorticoid inhibitory feedback, a greater response to social threat in the anterior oral cortex or amygdala and a smaller hippocampus. Indeed, these are all factors associated with major depression that can affect the sensitivity to the inhibitory consequences of inflammatory stimuli.

Depression triggers many somatization symptoms, which can manifest as insomnia, menopausal syndrome, cardiovascular problems, pain, and other somatic symptoms. There is a link between sleep deprivation and depression, with insomnia being a trigger and maintenance of depression, and more severe insomnia and chronic symptoms predicting more severe depression. Major depression is considered to be an independent risk factor for the development of coronary heart disease and a predictor of cardiovascular events ( 51 ). Patients with depression are extremely sensitive to pain and have increased pain perception ( 52 ) and is associated with an increased risk of suicide ( 53 , 54 ), and generally the symptoms of these pains are not relieved by medication.

Studies have shown that depression triggers an inflammatory response, promoting an increase in cytokines in response to stressors vs. pathogens. For example, mild depressive symptoms have been associated with an amplified and prolonged inflammatory response ( 55 , 56 ) following influenza vaccination in older adults and pregnant women. Among women who have recently given birth, those with a lifetime history of major depression have greater increases in both serum IL-6 and soluble IL-6 receptors after delivery than women without a history of depression ( 57 ). Pro-inflammatory agents, such as interferon-alpha (IFN-alpha), for specific somatization disorders [e.g., hepatitis C or malignant melanoma ( 58 , 59 )], although effective for somatic disorders, pro-inflammatory therapy often leads to psychiatric side effects. Up to 80% of patients treated with IFN-α have been reported to suffer from mild to moderate depressive symptoms.

Clinical trials have shown better antidepressant treatment with anti-inflammatory drugs compared to placebo, either as monotherapy ( 60 , 61 ) or as an add-on treatment ( 62 – 65 ) to antidepressants ( 66 , 67 ). However, findings like whether NSAIDs can be safely used in combination with antidepressants are controversial. Patients with depression often suffer from somatic co-morbidities, which must be included in the benefit/risk assessment. It is important to consider the type of medication, duration of treatment, and dose, and always balance the potential treatment effect with the risk of adverse events in individual patients. Depression, childhood adversity, stressors, and diet all affect the gut microbiota and promote gut permeability, another pathway that enhances the inflammatory response, and effective depression treatment may have profound effects on mood, inflammation, and health. Early in life gut flora colonization is associated with hypothalamic-pituitary-adrenal (HPA) axis activation and affects the enteric nervous system, which is associated with the risk of major depression, gut flora dysbiosis leads to the onset of TLR4-mediated inflammatory responses, and pro-inflammatory factors are closely associated with depression. Clinical studies have shown that in the gut flora of depressed patients, pro-inflammatory bacteria such as Enterobacteriaceae and Desulfovibrio are enriched, while short-chain fatty acid producing bacteria are reduced, and some of these bacterial taxa may transmit peripheral inflammation into the brain via the brain-gut axis ( 68 ). In addition, gut flora can affect the immune system by modulating neurotransmitters (5-hydroxytryptamine, gamma-aminobutyric acid, norepinephrine, etc.), which in turn can influence the development of depression ( 69 ). Therefore, antidepressant drugs targeting gut flora are a future research direction, and diet can have a significant impact on mood by regulating gut flora.

As the molecular basis of clinical depression remains unclear, and treatments and therapeutic effects are limited and associated with side effects, researchers have worked to discover new treatment modalities for depression. High-amplitude low-frequency musical impulse stimulation as an additional treatment modality seems to produce beneficial effects ( 70 ). Studies have found electroconvulsive therapy to be one of the most effective antidepressant treatment therapies ( 71 ). Physical exercise can promote molecular changes that lead to a shift from a chronic pro-inflammatory to an anti-inflammatory state in the peripheral and central nervous system ( 72 ). Aromatherapy is widely used in the treatment of central nervous system disorders ( 73 ). By activating the parasympathetic nervous system, qigong can be effective in reducing depression ( 74 ). The exploration of these new treatment modalities provides more reference options for the treatment of depression.

Large-scale assessments of depression have found that the probability of developing depression varies across populations. Depression affects some specific populations more significantly, for example: adolescents, mothers, and older adults. Depression is one of the disorders that predispose to adolescence, and depression is associated with an increased risk of suicide among college students ( 75 ). Many women develop depression after childbirth. Depression that develops after childbirth is one of the most common complications for women in the postpartum period ( 76 ). The health of children born to mothers who suffer from postpartum depression can also be adversely affected ( 77 ). Depression can cause many symptoms within the central nervous system, especially in the elderly population ( 78 ).

Furthermore, one of the most consistent findings of the association between inflammation and depression is the elevated levels of peripheral pro-inflammatory markers in depressed individuals, and peripheral pro-inflammatory marker levels can also be used as a basis for the assessment of depressed patients. Studies have shown that the following pro-inflammatory markers have been found to be at increased levels in depressed individuals: CRP ( 79 , 80 ), IL-6 ( 22 , 79 , 81 , 82 ), TNF–α, and interleukin-1 receptor antagonist (IL-1ra) ( 79 , 82 ), however, this association is not unidirectional and the subsequent development of depression also increases pro-inflammatory markers ( 82 , 83 ). These biomarkers are of great interest, and depressed patients with increased inflammatory markers may represent a relatively drug-resistant population.

Frontier Analysis

The exploration and analysis of frontier areas of depression were based on the results of the analysis of the previous section on keywords. According to the evaluation index and analysis idea of this study, the frontier research topics need to have the following four characteristics: low to medium frequency, strong burst, high betweenness centrality, and the research direction in recent years. Therefore, combining the results of keyword analysis and these characteristics, it can be found that the frontier research on depression also becomes clear.

Research on Depression Characterized by Psychosexual Disorders

Exploration of biological mechanisms based on depression-associated neurological disorders and analysis of depression from a neurological perspective have always been the focus of research. Activation of neuroinflammatory pathways may contribute to the development of depression ( 84 ). A research model based on the microbial-gut-brain axis facilitates the neurobiology of depression ( 85 ). Some probiotics positively affect the central nervous system due to modulation of neuroinflammation and thus may be able to modulate depression ( 86 ). The combination of environmental issues and the neurobiological study of depression opens new research directions ( 46 ).

Research on Relevant Models of Depression

How to develop a model that meets the purpose of the study determines the outcome of the study and has become the direction that researchers have been exploring in recent years. Martínez et al. ( 87 ) developed a predictive model to assess factors that modify the treatment pathway for postpartum depression. Nie et al. ( 88 ) extended the work on predictive modeling of treatment-resistant depression to establish a predictive model for treatment-resistant depression. Rational modeling methods and behavioral testing facilitate a more comprehensive exploration of depression, with richer studies and more scientifically valid findings.

Research and Characterization of the Depressed Patient Population

Current research on special groups and depression has received much attention. In a study of a group of children, 4% were found to suffer from depression ( 89 ). The diagnosis and treatment of mental health disorders is an important component of pediatric care. Second, some studies of populations with distinct characteristics have been based primarily on female populations. Maternal perinatal depression is also a common mental disorder with a prevalence of over 10% ( 90 ). In addition, geriatric depression is a chronic and specific disorder ( 91 ). Studies based on these populations highlight the characteristics of the disorder more directly than large-scale population explorations and are useful for conducting extended explorations from specific to generalized.

Somatic Comorbidities Associated With Depression

Depression often accompanies the onset and development of many other disorders, making the study of physical comorbidities associated with depression a new landing place for depression research. Depression is a complication of many neurological or psychopathological disorders. Depression is a common co-morbidity of glioblastoma multiforme ( 92 ). Depression is an important disorder associated with stroke ( 93 ). Chronic liver disease is associated with depression ( 94 ). The link between depressive and anxiety states and cancer has been well-documented ( 95 ). In conclusion, depression is associated with an increased risk of lung, oral, prostate, and skin cancers, an increased risk of cancer-specific death from lung, bladder, breast, colorectal, hematopoietic system, kidney, and prostate cancers, and an increased risk of all-cause mortality in lung cancer patients. The early detection and effective intervention of depression and its complications has public health and clinical implications.

Research on Mechanisms of Depression

Research based on the mechanisms of depression includes the study of disease pathogenesis, the study of drug action mechanisms, and the study of disease treatment mechanisms. Research on the pathogenesis of depression has focused more on the study of the hypothalamic-pituitary-adrenal axis. Social pressure can change the hypothalamic-pituitary-adrenal axis ( 96 ). Studies on the mechanism of action of drugs are mostly based on their effects on the central nervous system. The antidepressant effects of Tanshinone IIA are mediated by the ERK-CREB-BDNF pathway in the hippocampus of mice ( 97 ). Research on the mechanisms of depression treatment has also centered on the central nervous system. It has been shown that the vagus nerve can transmit signals to the brain that can lead to a reduction in depressive behavior ( 98 ).

In this study, based on the 2004–2019 time period, this wealth of data is effectively integrated through data analysis and processing to reproduce the research process in a particular field and to co-present global trends in homogenous fields while organizing past research.

Journals that have made outstanding contributions in this field include ARCH GEN PSYCHIAT, J AFFECT DISORDERS and AM J PSYCHIAT. PSYCHIATRY, NEUROSCIENCES & NEUROLOGY and CLINICAL NEUROLOGY are the three most popular categories. The three researchers with the highest number of articles were MAURIZIO FAVA (USA), BRENDA W. J. H. PENNINX (NETHERLANDS) and MADHUKAR H TRIVEDI (USA). Univ Pittsburgh (USA), Kings Coll London (UK) and Harvard Univ (USA) are three of the most productive and influential research institutions. A Meta-Analysis of Cytokines in Major Depression, Evaluation of outcomes with citalopram for depression using measurement-based care in STAR*D: Implications for clinical practice and Deep brain stimulation for treatment-resistant depression are key articles. Through keyword analysis, a distribution network centered on depression was formed. Although there are good trends in the research on depression, there are still many directions to be explored in depth. Some recommendations regarding depression are as follows.

(1) The prevention of depression can be considered by focusing on treating external factors and guiding the individual.

Faced with the rising incidence of depression worldwide and the difficulty of treating depression, researchers can think more about how to prevent the occurrence of depression. Depressed moods are often the result of stress, not only social pressures on the individual, but also environmental pressures in the developmental process, which in turn have an unhealthy relationship with the body and increase the likelihood of depression. The correlation between external factors and depression is less well-studied, but the control of external factors may be more effective in the short term than in the long term, and may be guided by self-adjustment to avoid major depressive disorder.

(2) The measurement and evaluation of the degree of depression should be developed in the direction of precision.

In the course of research, it has been found that the Depression Rating Scale is mostly used for the detection and evaluation of depression. This kind of assessment is more objective, but it still lacks accuracy, and the research on measurement techniques and methods is less, which is still at a low stage. Patients with depression usually have a variety of causes, conditions, and duration of illness that determine the degree of depression. Therefore, whether these scales can truly accurately measure depression in depressed patients needs further consideration. Accurate measurement is an important basis for evidence-based treatment of depression, and thus how to achieve accurate measurement of depression is a research direction that researchers can move toward.

Therefore, there is an urgent need for further research to address these issues.

A systematic analysis of research in the field of depression in this study concludes that the distribution of countries, journals, categories, authors, institutions, and citations may help researchers and research institutions to establish closer collaboration, develop appropriate publication plans, grasp research hotspots, identify valuable research ideas, understand current emerging research, and determine research directions. In addition, there are still some limitations that can be overcome in future work. First, due to the lack of author and address information in older published articles, it may not be possible to accurately calculate their collaboration; second, although the data scope of this paper is limited to the Web of Science, it can adequately meet our objectives.

Data Availability Statement

Author contributions.

HW conceived and designed the analysis, collected the data, performed the analysis, and wrote the paper. XT, XW, and YW conceived and designed the analysis. All authors contributed to the article and approved the submitted version.

This work was supported by the National Natural Science Foundation of China under Grant No. 81973495.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher's Note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

September Issues of APA Journals Cover Depression Risk Factors and Treatments, Noninvasive Brain Stimulation Treatments and the Evidence for School-Based Services

• September 06, 2024

WASHINGTON, D.C. — The latest issues of two American Psychiatric Association journals, The American Journal of Psychiatry and Psychiatric Services, are now available online.

The September issue of The American Journal of Psychiatry brings together research on depression, both therapeutic insights and contributing risk factors, and an overview and look at the promise of noninvasive brain stimulation. Highlights include:

• Entactogen Effects of Ketamine: A Reverse-Translational Study.
•   
• Peer Social Genetic Effects and the Etiology of Substance Use Disorders, Major Depression, and Anxiety Disorder in a Swedish National Sample. (Lead author Jessica Salvatore, Ph.D., is the featured guest in the AJP Audio podcast and AJP Deputy Editor Danny Pine, M.D., highlights the study in this video .)
• rTMS as a Next Step in Antidepressant Nonresponders: A Randomized Comparison With Current Antidepressant Treatment Approaches. (AJP Deputy Editor Danny Pine highlights the study in this video .)
• Association Between Intrauterine System Hormone Dosage and Depression Risk. Toward Precision Noninvasive Brain Stimulation.
• Closed-Loop Transcranial Alternating Current Stimulation for the Treatment of Major Depressive Disorder: An Open-Label Pilot Study.

The September issue of Psychiatric Services features :

• Effects of Recreational Cannabis Legalization on Mental Health: Scoping Review.
• The Need to Adapt the Psychiatric Clinical Assessment to the Digital Age: A Practical Approach.
• Reimbursement for a Broader Array of Services in Coordinated Specialty Care for Early Psychosis.
• Comparative Effectiveness of Clinician- Versus Peer-Supported Problem-Solving Therapy for Rural Older Adults With Depression.
• Self-Pay Outpatient Mental Health Care for Children and Adolescents, by Socioeconomic Status.
• Assessing the Evidence Base for School-Based Promotion and Prevention Interventions.

Journalists who wish to access the publications should email [email protected] .

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The American Psychiatric Association, founded in 1844, is the oldest medical association in the country. The APA is also the largest psychiatric association in the world with more than 38,900 physician members specializing in the diagnosis, treatment, prevention and research of mental illnesses. APA’s vision is to ensure access to quality psychiatric diagnosis and treatment. For more information, please visit www.psychiatry.org.

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Depression articles from across Nature Portfolio

Depression refers to a state of low mood that can be accompanied with loss of interest in activities that the individual normally perceived as pleasurable, altered appetite and sleep/wake balance. Its severe form, major depression is classified as a mood disorder.

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An Exploratory Study of Students with Depression in Undergraduate Research Experiences

• Katelyn M. Cooper
• Logan E. Gin
• M. Elizabeth Barnes
• Sara E. Brownell

*Address correspondence to: Katelyn M. Cooper ( E-mail Address: [email protected] ).

Department of Biology, University of Central Florida, Orlando, FL, 32816

Search for more papers by this author

Biology Education Research Lab, Research for Inclusive STEM Education Center, School of Life Sciences, Arizona State University, Tempe, AZ 85281

Depression is a top mental health concern among undergraduates and has been shown to disproportionately affect individuals who are underserved and underrepresented in science. As we aim to create a more inclusive scientific community, we argue that we need to examine the relationship between depression and scientific research. While studies have identified aspects of research that affect graduate student depression, we know of no studies that have explored the relationship between depression and undergraduate research. In this study, we sought to understand how undergraduates’ symptoms of depression affect their research experiences and how research affects undergraduates’ feelings of depression. We interviewed 35 undergraduate researchers majoring in the life sciences from 12 research-intensive public universities across the United States who identify with having depression. Using inductive and deductive coding, we identified that students’ depression affected their motivation and productivity, creativity and risk-taking, engagement and concentration, and self-perception and socializing in undergraduate research experiences. We found that students’ social connections, experiencing failure in research, getting help, receiving feedback, and the demands of research affected students’ depression. Based on this work, we articulate an initial set of evidence-based recommendations for research mentors to consider in promoting an inclusive research experience for students with depression.

INTRODUCTION

Depression is described as a common and serious mood disorder that results in persistent feelings of sadness and hopelessness, as well as a loss of interest in activities that one once enjoyed ( American Psychiatric Association [APA], 2013 ). Additional symptoms of depression include weight changes, difficulty sleeping, loss of energy, difficulty thinking or concentrating, feelings of worthlessness or excessive guilt, and suicidality ( APA, 2013 ). While depression results from a complex interaction of psychological, social, and biological factors ( World Health Organization, 2018 ), studies have shown that increased stress caused by college can be a significant contributor to student depression ( Dyson and Renk, 2006 ).

Depression is one of the top undergraduate mental health concerns, and the rate of depression among undergraduates continues to rise ( Center for Collegiate Mental Health, 2017 ). While we cannot discern whether these increasing rates of depression are due to increased awareness or increased incidence, it is clear that is a serious problem on college campuses. The percent of U.S. college students who self-reported a diagnosis with depression was recently estimated to be about 25% ( American College Health Association, 2019 ). However, higher rates have been reported, with one study estimating that up to 84% of undergraduates experience some level of depression ( Garlow et al. , 2008 ). Depression rates are typically higher among university students compared with the general population, despite being a more socially privileged group ( Ibrahim et al. , 2013 ). Prior studies have found that depression is negatively correlated with overall undergraduate academic performance ( Hysenbegasi et al. , 2005 ; Deroma et al. , 2009 ; American College Health Association, 2019 ). Specifically, diagnosed depression is associated with half a letter grade decrease in students’ grade point average ( Hysenbegasi et al. , 2005 ), and 21.6% of undergraduates reported that depression negatively affected their academic performance within the last year ( American College Health Association, 2019 ). Provided with a list of academic factors that may be affected by depression, students reported that depression contributed to lower exam grades, lower course grades, and not completing or dropping a course.

Students in the natural sciences may be particularly at risk for depression, given that such majors are noted to be particularly stressful due to their competitive nature and course work that is often perceived to “weed students out”( Everson et al. , 1993 ; Strenta et al. , 1994 ; American College Health Association, 2019 ; Seymour and Hunter, 2019 ). Science course instruction has also been described to be boring, repetitive, difficult, and math-intensive; these factors can create an environment that can trigger depression ( Seymour and Hewitt, 1997 ; Osborne and Collins, 2001 ; Armbruster et al ., 2009 ; Ceci and Williams, 2010 ). What also distinguishes science degree programs from other degree programs is that, increasingly, undergraduate research experiences are being proposed as an essential element of a science degree ( American Association for the Advancement of Science, 2011 ; President’s Council of Advisors on Science and Technology, 2012 ; National Academies of Sciences, Engineering, and Medicine [NASEM], 2017 ). However, there is some evidence that undergraduate research experiences can add to the stress of college for some students ( Cooper et al. , 2019c ). Students can garner multiple benefits from undergraduate research, including enhanced abilities to think critically ( Ishiyama, 2002 ; Bauer and Bennett, 2003 ; Brownell et al. , 2015 ), improved student learning ( Rauckhorst et al. , 2001 ; Brownell et al. , 2015 ), and increased student persistence in undergraduate science degree programs ( Jones et al. , 2010 ; Hernandez et al. , 2018 ). Notably, undergraduate research experiences are increasingly becoming a prerequisite for entry into medical and graduate programs in science, particularly elite programs ( Cooper et al. , 2019d ). Although some research experiences are embedded into formal lab courses as course-based undergraduate research experiences (CUREs; Auchincloss et al. , 2014 ; Brownell and Kloser, 2015 ), the majority likely entail working with faculty in their research labs. These undergraduate research experiences in faculty labs are often added on top of a student’s normal course work, so they essentially become an extracurricular activity that they have to juggle with course work, working, and/or personal obligations ( Cooper et al. , 2019c ). While the majority of the literature surrounding undergraduate research highlights undergraduate research as a positive experience ( NASEM, 2017 ), studies have demonstrated that undergraduate research experiences can be academically and emotionally challenging for students ( Mabrouk and Peters, 2000 ; Seymour et al. , 2004 ; Cooper et al. , 2019c ; Limeri et al. , 2019 ). In fact, 50% of students sampled nationally from public R1 institutions consider leaving their undergraduate research experience prematurely, and about half of those students, or 25% of all students, ultimately leave their undergraduate research experience ( Cooper et al. , 2019c ). Notably, 33.8% of these individuals cited a negative lab environment and 33.3% cited negative relationships with their mentors as factors that influenced their decision about whether to leave ( Cooper et al. , 2019c ). Therefore, students’ depression may be exacerbated in challenging undergraduate research experiences, because studies have shown that depression is positively correlated with student stress ( Hish et al. , 2019 ).

While depression has not been explored in the context of undergraduate research experiences, depression has become a prominent concern surrounding graduate students conducting scientific research. A recent study that examined the “graduate student mental health crisis” ( Flaherty, 2018 ) found that work–life balance and graduate students’ relationships with their research advisors may be contributing to their depression ( Evans et al. , 2018 ). Specifically, this survey of 2279 PhD and master’s students from diverse fields of study, including the biological/physical sciences, showed that 39% of graduate students have experienced moderate to severe depression. Fifty-five percent of the graduate students with depression who were surveyed disagreed with the statement “I have good work life balance,” compared to only 21% of students with depression who agreed. Additionally, the study highlighted that more students with depression disagreed than agreed with the following statements: their advisors provided “real” mentorship, their advisors provided ample support, their advisors positively impacted their emotional or mental well-being, their advisors were assets to their careers, and they felt valued by their mentors. Another recent study identified that depression severity in biomedical doctoral students was significantly associated with graduate program climate, a perceived lack of employment opportunities, and the quality of students’ research training environment ( Nagy et al. , 2019 ). Environmental stress, academic stress, and family and monetary stress have also been shown to be predictive of depression severity in biomedical doctoral students ( Hish et al. , 2019 ). Further, one study found that self-esteem is negatively correlated and stress is positively correlated with graduate student depression; presumably research environments that challenge students’ self-esteem and induce stress are likely contributing to depressive symptoms among graduate students ( Kreger, 1995 ). While these studies have focused on graduate students, and there are certainly notable distinctions between graduate and undergraduate research, the research-related factors that affect graduate student depression, including work–life balance, relationships with mentors, research environment, stress, and self-esteem, may also be relevant to depression among undergraduates conducting research. Importantly, undergraduates in the United States have reported identical levels of depression as graduate students but are often less likely to seek mental health care services ( Wyatt and Oswalt, 2013 ), which is concerning if undergraduate research experiences exacerbate depression.

Based on the literature on the stressors of undergraduate research experiences and the literature identifying some potential causes of graduate student depression, we identified three aspects of undergraduate research that may exacerbate undergraduates’ depression. Mentoring: Mentors can be an integral part of a students’ research experience, bolstering their connections with others in the science community, scholarly productivity, and science identity, as well as providing many other benefits ( Thiry and Laursen, 2011 ; Prunuske et al. , 2013 ; Byars-Winston et al. , 2015 ; Aikens et al. , 2016 , 2017 ; Thompson et al. , 2016 ; Estrada et al. , 2018 ). However, recent literature has highlighted that poor mentoring can negatively affect undergraduate researchers ( Cooper et al. , 2019c ; Limeri et al. , 2019 ). Specifically, one study of 33 undergraduate researchers who had conducted research at 10 institutions identified seven major ways that they experienced negative mentoring, which included absenteeism, abuse of power, interpersonal mismatch, lack of career support, lack of psychosocial support, misaligned expectations, and unequal treatment ( Limeri et al. , 2019 ). We hypothesize negative mentoring experiences may be particularly harmful for students with depression, because support, particularly social support, has been shown to be important for helping individuals with depression cope with difficult circumstances ( Aneshensel and Stone, 1982 ; Grav et al. , 2012 ). Failure: Experiencing failure has been hypothesized to be an important aspect of undergraduate research experiences that may help students develop some the most distinguishing abilities of outstanding scientists, such as coping with failure, navigating challenges, and persevering ( Laursen et al. , 2010 ; Gin et al. , 2018 ; Henry et al. , 2019 ). However, experiencing failure and the stress and fatigue that often accompany it may be particularly tough for students with depression ( Aldwin and Greenberger, 1987 ; Mongrain and Blackburn, 2005 ). Lab environment: Fairness, inclusion/exclusion, and social support within one’s organizational environment have been shown to be key factors that cause people to either want to remain in the work place and be productive or to want to leave ( Barak et al. , 2006 ; Cooper et al. , 2019c ). We hypothesize that dealing with exclusion or a lack of social support may exacerbate depression for some students; patients with clinical depression react to social exclusion with more pronounced negative emotions than do individuals without clinical depression ( Jobst et al. , 2015 ). While there are likely other aspects of undergraduate research that affect student depression, we hypothesize that these factors have the potential to exacerbate negative research experiences for students with depression.

Depression has been shown to disproportionately affect many populations that are underrepresented or underserved within the scientific community, including females ( American College Health Association, 2018 ; Evans et al. , 2018 ), first-generation college students ( Jenkins et al. , 2013 ), individuals from low socioeconomic backgrounds ( Eisenberg et al. , 2007 ), members of the LGBTQ+ community ( Eisenberg et al. , 2007 ; Evans et al. , 2018 ), and people with disabilities ( Turner and Noh, 1988 ). Therefore, as the science community strives to be more diverse and inclusive ( Intemann, 2009 ), it is important that we understand more about the relationship between depression and scientific research, because negative experiences with depression in scientific research may be contributing to the underrepresentation of these groups. Specifically, more information is needed about how the research process and environment of research experiences may affect depression.

Given the high rate of depression among undergraduates, the links between depression and graduate research, the potentially challenging environment of undergraduate research, and how depression could disproportionately impact students from underserved communities, it is imperative to begin to explore the relationship between scientific research and depression among undergraduates to create research experiences that could maximize student success. In this exploratory interview study, we aimed to 1) describe how undergraduates’ symptoms of depression affect their research experiences, 2) understand how undergraduate research affects students’ feelings of depression, and 3) identify recommendations based on the literature and undergraduates’ reported experiences to promote a positive research experience for students with depression.

This study was done with an approved Arizona State University Institutional Review Board protocol #7247.

In Fall 2018, we surveyed undergraduate researchers majoring in the life sciences across 25 research-intensive (R1) public institutions across the United States (specific details about the recruitment of the students who completed the survey can be found in Cooper et al. (2019c) ). The survey asked students for their opinions about their undergraduate research experiences and their demographic information and whether they would be interested in participating in a follow-up interview related to their research experiences. For the purpose of this study, we exclusively interviewed students about their undergraduate research experiences in faculty member labs; we did not consider students’ experiences in CUREs. Of the 768 undergraduate researchers who completed the survey, 65% ( n = 496) indicated that they would be interested in participating in a follow-up interview. In Spring 2019, we emailed the 496 students, explaining that we were interested in interviewing students with depression about their experiences in undergraduate research. Our specific prompt was: “If you identify as having depression, we would be interested in hearing about your experience in undergraduate research in a 30–60 minute online interview.” We did not define depression in our email recruitment because we conducted think-aloud interviews with four undergraduates who all correctly interpreted what we meant by depression ( APA, 2013 ). We had 35 students agree to participate in the interview study. The interview participants represented 12 of the 25 R1 public institutions that were represented in the initial survey.

Student Interviews

We developed an interview script to explore our research questions. Specifically, we were interested in how students’ symptoms of depression affect their research experiences, how undergraduate research negatively affects student depression, and how undergraduate research positively affects student depression.

We recognized that mental health, and specifically depression, can be a sensitive topic to discuss with undergraduates, and therefore we tried to minimize any discomfort that the interviewees might experience during the interview. Specifically, we conducted think-aloud interviews with three graduate students who self-identified with having depression at the time of the interview. We asked them to note whether any interview questions made them uncomfortable. We also sought their feedback on questions given their experiences as persons with depression who had once engaged in undergraduate research. We revised the interview protocol after each think-aloud interview. Next, we conducted four additional think-aloud interviews with undergraduates conducting basic science or biology education research who identified with having depression to establish cognitive validity of the questions and to elicit additional feedback about any questions that might make someone uncomfortable. The questions were revised after each think-aloud interview until no question was unclear or misinterpreted by the students and we were confident that the questions minimized students’ potential discomfort ( Trenor et al. , 2011 ). A copy of the final interview script can be found in the Supplemental Material.

All interviews were individually conducted by one of two researchers (K.M.C. and L.E.G.) who conducted the think-aloud interviews together to ensure that their interviewing practices were as similar as possible. The interviews were approximately an hour long, and students received a $15 gift card for their participation.

Personal, Research, and Depression Demographics

All student demographics and information about students’ research experiences were collected using the survey distributed to students in Fall 2018. We collected personal demographics, including the participants’ gender, race/ethnicity, college generation status, transfer status, financial stability, year in college, major, and age. We also collected information about the students’ research experiences, including the length of their first research experiences, the average number of hours they spend in research per week, how they were compensated for research, who their primary mentors were, and the focus areas of their research.

In the United States, mental healthcare is disproportionately unavailable to Black and Latinx individuals, as well as those who come from low socioeconomic backgrounds ( Kataoka et al. , 2002 ; Howell and McFeeters, 2008 ; Santiago et al. , 2013 ). Therefore, to minimize a biased sample, we invited anyone who identified with having depression to participate in our study; we did not require students to be diagnosed with depression or to be treated for depression in order to participate. However, we did collect information about whether students had been formally diagnosed with depression and whether they had been treated for depression. After the interview, all participants were sent a link to a short survey that asked them if they had ever been diagnosed with depression and how, if at all, they had ever been treated for depression. A copy of these survey questions can be found in the Supplemental Material. The combined demographic information of the participants is in Table 1 . The demographics for each individual student can be found in the Supplemental Material.

a Students reported the time they had spent in research 6 months before being interviewed and only reported on the length of time of their first research experiences.

b Students were invited to report multiple ways in which they were treated for their depression; other treatments included lifestyle changes and meditation.

c Students were invited to report multiple means of compensation for their research if they had been compensated for their time in different ways.

d Students were asked whether they felt financially stable, particularly during the undergraduate research experience.

e Students reported who they work/worked with most closely during their research experiences.

f Staff members included lab coordinators or lab managers.

g Other focus areas of research included sociology, linguistics, psychology, and public health.

Interview Analysis

The initial interview analysis aimed to explore each idea that a participant expressed ( Charmaz, 2006 ) and to identify reoccurring ideas throughout the interviews. First, three authors (K.M.C., L.E.G., and S.E.B.) individually reviewed a different set of 10 interviews and took detailed analytic notes ( Birks and Mills, 2015 ). Afterward, the authors compared their notes and identified reoccurring themes throughout the interviews using open coding methods ( Saldaña, 2015 ).

Once an initial set of themes was established, two researchers (K.M.C. and L.E.G.) individually reviewed the same set of 15 randomly selected interviews to validate the themes identified in the initial analysis and to screen for any additional themes that the initial analysis may have missed. Each researcher took detailed analytic notes throughout the review of an interview, which they discussed after reviewing each interview. The researchers compared what quotes from each interview they categorized into each theme. Using constant comparison methods, they assigned quotes to each theme and constantly compared the quotes to ensure that each quote fit within the description of the theme ( Glesne and Peshkin, 1992 ). In cases in which quotes were too different from other quotes, a new theme was created. This approach allowed for multiple revisions of the themes and allowed the authors to define a final set of codes; the researchers created a final codebook with refined definitions of emergent themes (the final coding rubric can be found in the Supplemental Material). Once the final codebook was established, the researchers (K.M.C. and L.E.G.) individually coded seven additional interviews (20% of all interviews) using the coding rubric. The researchers compared their codes, and their Cohen’s κ interrater score for these seven interviews was at an acceptable level (κ  =  0.88; Landis and Koch, 1977 ). One researcher (L.E.G.) coded the remaining 28 out of 35 interviews. The researchers determined that data saturation had been reached with the current sample and no further recruitment was needed ( Guest et al. , 2006 ). We report on themes that were mentioned by at least 20% of students in the interview study. In the Supplemental Material, we provide the final coding rubric with the number of participants whose interview reflected each theme ( Hannah and Lautsch, 2011 ). Reporting the number of individuals who reported themes within qualitative data can lead to inaccurate conclusions about the generalizability of the results to a broader population. These qualitative data are meant to characterize a landscape of experiences that students with depression have in undergraduate research rather than to make claims about the prevalence of these experiences ( Glesne and Peshkin, 1992 ). Because inferences about the importance of these themes cannot be drawn from these counts, they are not included in the results of the paper ( Maxwell, 2010 ). Further, the limited number of interviewees made it not possible to examine whether there were trends based on students’ demographics or characteristics of their research experiences (e.g., their specific area of study). Quotes were lightly edited for clarity by inserting clarification brackets and using ellipses to indicate excluded text. Pseudonyms were given to all students to protect their privacy.

The Effect of Depressive Symptoms on Undergraduate Research

We asked students to describe the symptoms associated with their depression. Students described experiencing anxiety that is associated with their depression; this could be anxiety that precedes their depression or anxiety that results from a depressive episode or a period of time when an individual has depression symptoms. Further, students described difficulty getting out of bed or leaving the house, feeling tired, a lack of motivation, being overly self-critical, feeling apathetic, and having difficulty concentrating. We were particularly interested in how students’ symptoms of depression affected their experiences in undergraduate research. During the think-aloud interviews that were conducted before the interview study, graduate and undergraduate students consistently described that their depression affected their motivation in research, their creativity in research, and their productivity in research. Therefore, we explicitly asked undergraduate researchers how, if at all, their depression affected these three factors. We also asked students to describe any additional ways in which their depression affected their research experiences. Undergraduate researchers commonly described five additional ways in which their depression affected their research; for a detailed description of each way students’ research was affected and for example quotes, see Table 2 . Students described that their depression negatively affected their productivity in the lab. Commonly, students described that their productivity was directly affected by a lack of motivation or because they felt less creative, which hindered the research process. Additionally, students highlighted that they were sometimes less productive because their depression sometimes caused them to struggle to engage intellectually with their research or caused them to have difficulty remembering or concentrating; students described that they could do mundane or routine tasks when they felt depressed, but that they had difficulty with more complex and intellectually demanding tasks. However, students sometimes described that even mundane tasks could be difficult when they were required to remember specific steps; for example, some students struggled recalling a protocol from memory when their depression was particularly severe. Additionally, students noted that their depression made them more self-conscious, which sometimes held them back from sharing research ideas with their mentors or from taking risks such as applying to competitive programs. In addition to being self-conscious, students highlighted that their depression caused them to be overly self-critical, and some described experiencing imposter phenomenon ( Clance and Imes, 1978 ) or feeling like they were not talented enough to be in research and were accepted into a lab by a fluke or through luck. Finally, students described that depression often made them feel less social, and they struggled to socially engage with other members of the lab when they were feeling down.

The Effect of Undergraduate Research Experiences on Student Depression

We also wanted to explore how research impacted students’ feelings of depression. Undergraduates described how research both positively and negatively affected their depression. In the following sections, we present aspects of undergraduate research and examine how each positively and/or negatively affected students’ depression using embedded student quotes to highlight the relationships between related ideas.

Lab Environment: Relationships with Others in the Lab.

Some aspects of the lab environment, which we define as students’ physical, social, or psychological research space, could be particularly beneficial for students with depression.

Specifically, undergraduate researchers perceived that comfortable and positive social interactions with others in the lab helped their depression. Students acknowledged how beneficial their relationships with graduate students and postdocs could be.

Marta: “I think always checking in on undergrads is important. It’s really easy [for us] to go a whole day without talking to anybody in the lab. But our grad students are like ‘Hey, what’s up? How’s school? What’s going on?’ (…) What helps me the most is having that strong support system. Sometimes just talking makes you feel better, but also having people that believe in you can really help you get out of that negative spiral. I think that can really help with depression.”

Kelley: “I know that anytime I need to talk to [my postdoc mentors] about something they’re always there for me. Over time we’ve developed a relationship where I know that outside of work and outside of the lab if I did want to talk to them about something I could talk to them. Even just talking to someone about hobbies and having that relationship alone is really helpful [for depression].”

In addition to highlighting the importance of developing relationships with graduate students or postdocs in the lab, students described that forming relationships with other undergraduates in the lab also helped their depression. Particularly, students described that other undergraduate researchers often validated their feelings about research, which in turn helped them realize that what they are thinking or feeling is normal, which tended to alleviate their negative thoughts. Interestingly, other undergraduates experiencing the same issues could sometimes help buffer them from perceiving that a mentor did not like them or that they were uniquely bad at research. In this article, we use the term “mentor” to refer to anyone who students referred to in the interviews as being their mentors or managing their research experiences; this includes graduate students, postdoctoral scholars, lab managers, and primary investigators (PIs).

Abby: “One of my best friends is in the lab with me.  A lot of that friendship just comes from complaining about our stress with the lab and our annoyance with people in the lab. Like when we both agree like, ‘Yeah, the grad students were really off today, it wasn’t us,’ that helps. ‘It wasn’t me, it wasn’t my fault that we were having a rough day in lab; it was the grad students.’ Just being able to realize, ‘Hey, this isn’t all caused by us,’ you know? (…) We understand the stresses in the lab. We understand the details of what each other are doing in the lab, so when something doesn’t work out, we understand that it took them like eight hours to do that and it didn’t work. We provide empathy on a different level.”

Meleana: “It’s great to have solidarity in being confused about something, and it’s just that is a form of validation for me too. When we leave a lab meeting and I look at [another undergrad] I’m like, ‘Did you understand anything that they were just saying?’ And they’re like, ‘Oh, no.’ (…) It’s just really validating to hear from the other undergrads that we all seem to be struggling with the same things.”

Developing positive relationships with faculty mentors or PIs also helped alleviate some students’ depressive feelings, particularly when PIs shared their own struggles with students. This also seemed to normalize students’ concerns about their own experiences.

Alexandra: “[Talking with my PI] is helpful because he would talk about his struggles, and what he faced. A lot of it was very similar to my struggles.  For example, he would say, ‘Oh, yeah, I failed this exam that I studied so hard for. I failed the GRE and I paid so much money to prepare for it.’ It just makes [my depression] better, like okay, this is normal for students to go through this. It’s not an out of this world thing where if you fail, you’re a failure and you can’t move on from it.”

Students’ relationships with others in the lab did not always positively impact their depression. Students described instances when the negative moods of the graduate students and PIs would often set the tone of the lab, which in turn worsened the mood of the undergraduate researchers.

Abby: “Sometimes [the grad students] are not in a good mood. The entire vibe of the lab is just off, and if you make a joke and it hits somebody wrong, they get all mad. It really depends on the grad students and the leadership and the mood that they’re in.”

Interviewer: “How does it affect your depression when the grad students are in a bad mood?”

Abby: “It definitely makes me feel worse. It feels like, again, that I really shouldn’t go ask them for help because they’re just not in the mood to help out. It makes me have more pressure on myself, and I have deadlines I need to meet, but I have a question for them, but they’re in a bad mood so I can’t ask. That’s another day wasted for me and it just puts more stress, which just adds to the depression.”

Additionally, some students described even more concerning behavior from research mentors, which negatively affected their depression.

Julie: “I had a primary investigator who is notorious in the department for screaming at people, being emotionally abusive, unreasonable, et cetera. (…) [He was] kind of harassing people, demeaning them, lying to them, et cetera, et cetera. (…) Being yelled at and constantly demeaned and harassed at all hours of the day and night, that was probably pretty bad for me.”

While the relationships between undergraduates and graduate, postdoc, and faculty mentors seemed to either alleviate or worsen students’ depressive symptoms, depending on the quality of the relationship, students in this study exclusively described their relationships with other undergraduates as positive for their depression. However, students did note that undergraduate research puts some of the best and brightest undergraduates in the same environment, which can result in students comparing themselves with their peers. Students described that this comparison would often lead them to feel badly about themselves, even though they would describe their personal relationship with a person to be good.

Meleana: “In just the research field in general, just feeling like I don’t really measure up to the people around me [can affect my depression]. A lot of the times it’s the beginning of a little spiral, mental spiral. There are some past undergrads that are talked about as they’re on this pedestal of being the ideal undergrads and that they were just so smart and contributed so much to the lab. I can never stop myself from wondering like, ‘Oh, I wonder if I’m having a contribution to the lab that’s similar or if I’m just another one of the undergrads that does the bare minimum and passes through and is just there.’”

Natasha: “But, on the other hand, [having another undergrad in the lab] also reminded me constantly that some people are invested in this and meant to do this and it’s not me. And that some people know a lot more than I do and will go further in this than I will.”

While students primarily expressed that their relationships with others in the lab affected their depression, some students explained that they struggled most with depression when the lab was empty; they described that they did not like being alone in the lab, because a lack of stimulation allowed their minds to be filled with negative thoughts.

Mia: “Those late nights definitely didn’t help [my depression]. I am alone, in the entire building.  I’m left alone to think about my thoughts more, so not distracted by talking to people or interacting with people. I think more about how I’m feeling and the lack of progress I’m making, and the hopelessness I’m feeling. That kind of dragged things on, and I guess deepened my depression.”

Freddy: “Often times when I go to my office in the evening, that is when I would [ sic ] be prone to be more depressed. It’s being alone. I think about myself or mistakes or trying to correct mistakes or whatever’s going on in my life at the time. I become very introspective. I think I’m way too self-evaluating, way too self-deprecating and it’s when I’m alone when those things are really, really triggered. When I’m talking with somebody else, I forget about those things.”

In sum, students with depression highlighted that a lab environment full of positive and encouraging individuals was helpful for their depression, whereas isolating or competitive environments and negative interactions with others often resulted in more depressive feelings.

Doing Science: Experiencing Failure in Research, Getting Help, Receiving Feedback, Time Demands, and Important Contributions.

In addition to the lab environment, students also described that the process of doing science could affect their depression. Specifically, students explained that a large contributor to their depression was experiencing failure in research.

Interviewer: “Considering your experience in undergraduate research, what tends to trigger your feelings of depression?”

Heather: “Probably just not getting things right. Having to do an experiment over and over again. You don’t get the results you want. (…) The work is pretty meticulous and it’s frustrating when I do all this work, I do a whole experiment, and then I don’t get any results that I can use. That can be really frustrating. It adds to the stress. (…) It’s hard because you did all this other stuff before so you can plan for the research, and then something happens and all the stuff you did was worthless basically.”

Julie: “I felt very negatively about myself [when a project failed] and pretty panicked whenever something didn’t work because I felt like it was a direct reflection on my effort and/or intelligence, and then it was a big glaring personal failure.”

Students explained that their depression related to failing in research was exacerbated if they felt as though they could not seek help from their research mentors. Perceived insufficient mentor guidance has been shown to be a factor influencing student intention to leave undergraduate research ( Cooper et al. , 2019c ). Sometimes students talked about their research mentors being unavailable or unapproachable.

Michelle: “It just feels like [the graduate students] are not approachable. I feel like I can’t approach them to ask for their understanding in a certain situation. It makes [my depression] worse because I feel like I’m stuck, and that I’m being limited, and like there’s nothing I can do. So then I kind of feel like it’s my fault that I can’t do anything.”

Other times, students described that they did not seek help in fear that they would be negatively evaluated in research, which is a fear of being judged by others ( Watson and Friend, 1969 ; Weeks et al. , 2005 ; Cooper et al. , 2018 ). That is, students fear that their mentor would think negatively about them or judge them if they were to ask questions that their mentor thought they should know the answer to.

Meleana: “I would say [my depression] tends to come out more in being more reserved in asking questions because I think that comes more like a fear-based thing where I’m like, ‘Oh, I don’t feel like I’m good enough and so I don’t want to ask these questions because then my mentors will, I don’t know, think that I’m dumb or something.’”

Conversely, students described that mentors who were willing to help them alleviated their depressive feelings.

Crystal: “Yeah [my grad student] is always like, ‘Hey, I can check in on things in the lab because you’re allowed to ask me for that, you’re not totally alone in this,’ because he knows that I tend to take on all this responsibility and I don’t always know how to ask for help. He’s like, ‘You know, this is my lab too and I am here to help you as well,’ and just reminds me that I’m not shouldering this burden by myself.”

Ashlyn: “The graduate student who I work with is very kind and has a lot of patience and he really understands a lot of things and provides simple explanations. He does remind me about things and he will keep on me about certain tasks that I need to do in an understanding way, and it’s just because he’s patient and he listens.”

In addition to experiencing failure in science, students described that making mistakes when doing science also negatively affected their depression.

Abby: “I guess not making mistakes on experiments [is important in avoiding my depression]. Not necessarily that your experiment didn’t turn out to produce the data that you wanted, but just adding the wrong enzyme or messing something up like that. It’s like, ‘Oh, man,’ you know? You can get really down on yourself about that because it can be embarrassing.”

Commonly, students described that the potential for making mistakes increased their stress and anxiety regarding research; however, they explained that how other people responded to a potential mistake was what ultimately affected their depression.

Briana: “Sometimes if I made a mistake in correctly identifying an eye color [of a fly], [my PI] would just ridicule me in front of the other students. He corrected me but his method of correcting was very discouraging because it was a ridicule. It made the others laugh and I didn’t like that.”

Julie: “[My PI] explicitly [asked] if I had the dedication for science. A lot of times he said I had terrible judgment. A lot of times he said I couldn’t be trusted. Once I went to a conference with him, and, unfortunately, in front of another professor, he called me a klutz several times and there was another comment about how I never learn from my mistakes.”

When students did do things correctly, they described how important it could be for them to receive praise from their mentors. They explained that hearing praise and validation can be particularly helpful for students with depression, because their thoughts are often very negative and/or because they have low self-esteem.

Crystal: “[Something that helps my depression is] I have text messages from [my graduate student mentor] thanking me [and another undergraduate researcher] for all of the work that we’ve put in, that he would not be able to be as on track to finish as he is if he didn’t have our help.”

Interviewer: “Why is hearing praise from your mentor helpful?”

Crystal: “Because a lot of my depression focuses on everybody secretly hates you, nobody likes you, you’re going to die alone. So having that validation [from my graduate mentor] is important, because it flies in the face of what my depression tells me.”

Brian: “It reminds you that you exist outside of this negative world that you’ve created for yourself, and people don’t see you how you see yourself sometimes.”

Students also highlighted how research could be overwhelming, which negatively affected their depression. Particularly, students described that research demanded a lot of their time and that their mentors did not always seem to be aware that they were juggling school and other commitments in addition to their research. This stress exacerbated their depression.

Rose: “I feel like sometimes [my grad mentors] are not very understanding because grad students don’t take as many classes as [undergrads] do. I think sometimes they don’t understand when I say I can’t come in at all this week because I have finals and they’re like, ‘Why though?’”

Abby: “I just think being more understanding of student life would be great. We have classes as well as the lab, and classes are the priority. They forget what it’s like to be a student. You feel like they don’t understand and they could never understand when you say like, ‘I have three exams this week,’ and they’re like, ‘I don’t care. You need to finish this.’”

Conversely, some students reported that their research labs were very understanding of students’ schedules. Interestingly, these students talked most about how helpful it was to be able to take a mental health day and not do research on days when they felt down or depressed.

Marta: “My lab tech is very open, so she’ll tell us, ‘I can’t come in today. I have to take a mental health day.’ So she’s a really big advocate for that. And I think I won’t personally tell her that I’m taking a mental health day, but I’ll say, ‘I can’t come in today, but I’ll come in Friday and do those extra hours.’ And she’s like, ‘OK great, I’ll see you then.’  And it makes me feel good, because it helps me take care of myself first and then I can take care of everything else I need to do, which is amazing.”

Meleana: “Knowing that [my mentors] would be flexible if I told them that I’m crazy busy and can’t come into work nearly as much this week [helps my depression]. There is flexibility in allowing me to then care for myself.”

Interviewer: “Why is the flexibility helpful given the depression?”

Meleana: “Because sometimes for me things just take a little bit longer when I’m feeling down. I’m just less efficient to be honest, and so it’s helpful if I feel like I can only go into work for 10 hours in a week. It declutters my brain a little bit to not have to worry about all the things I have to do in work in addition the things that I need to do for school or clubs, or family or whatever.”

Despite the demanding nature of research, a subset of students highlighted that their research and research lab provided a sense of stability or familiarity that distracted them from their depression.

Freddy: “I’ll [do research] to run away from those [depressive] feelings or whatever. (…) I find sadly, I hate to admit it, but I do kind of run to [my lab]. I throw myself into work to distract myself from the feelings of depression and sadness.”

Rose: “When you’re sad or when you’re stressed you want to go to things you’re familiar with. So because lab has always been in my life, it’s this thing where it’s going to be there for me I guess. It’s like a good book that you always go back to and it’s familiar and it makes you feel good. So that’s how lab is. It’s not like the greatest thing in the world but it’s something that I’m used to, which is what I feel like a lot of people need when they’re sad and life is not going well.”

Many students also explained that research positively affects their depression because they perceive their research contribution to be important.

Ashlyn: “I feel like I’m dedicating myself to something that’s worthy and something that I believe in. It’s really important because it contextualizes those times when I am feeling depressed. It’s like, no, I do have these better things that I’m working on. Even when I don’t like myself and I don’t like who I am, which is again, depression brain, I can at least say, ‘Well, I have all these other people relying on me in research and in this area and that’s super important.’”

Jessica: “I mean, it just felt like the work that I was doing had meaning and when I feel like what I’m doing is actually going to contribute to the world, that usually really helps with [depression] because it’s like not every day you can feel like you’re doing something impactful.”

In sum, students highlighted that experiencing failure in research and making mistakes negatively contributed to depression, especially when help was unavailable or research mentors had a negative reaction. Additionally, students acknowledged that the research could be time-consuming, but that research mentors who were flexible helped assuage depressive feelings that were associated with feeling overwhelmed. Finally, research helped some students’ depression, because it felt familiar, provided a distraction from depression, and reminded students that they were contributing to a greater cause.

We believe that creating more inclusive research environments for students with depression is an important step toward broadening participation in science, not only to ensure that we are not discouraging students with depression from persisting in science, but also because depression has been shown to disproportionately affect underserved and underrepresented groups in science ( Turner and Noh, 1988 ; Eisenberg et al. , 2007 ; Jenkins et al. , 2013 ; American College Health Association, 2018 ). We initially hypothesized that three features of undergraduate research—research mentors, the lab environment, and failure—may have the potential to exacerbate student depression. We found this to be true; students highlighted that their relationships with their mentors as well as the overall lab environment could negatively affect their depression, but could also positively affect their research experiences. Students also noted that they struggled with failure, which is likely true of most students, but is known to be particularly difficult for students with depression ( Elliott et al. , 1997 ). We expand upon our findings by integrating literature on depression with the information that students provided in the interviews about how research mentors can best support students. We provide a set of evidence-based recommendations focused on mentoring, the lab environment, and failure for research mentors wanting to create more inclusive research environments for students with depression. Notably, only the first recommendation is specific to students with depression; the others reflect recommendations that have previously been described as “best practices” for research mentors ( NASEM, 2017 , 2019 ; Sorkness et al. , 2017 ) and likely would benefit most students. However, we examine how these recommendations may be particularly important for students with depression. As we hypothesized, these recommendations directly address three aspects of research: mentors, lab environment, and failure. A caveat of these recommendations is that more research needs to be done to explore the experiences of students with depression and how these practices actually impact students with depression, but our national sample of undergraduate researchers with depression can provide an initial starting point for a discussion about how to improve research experiences for these students.

Recommendations to Make Undergraduate Research Experiences More Inclusive for Students with Depression

Recognize student depression as a valid illness..

Allow students with depression to take time off of research by simply saying that they are sick and provide appropriate time for students to recover from depressive episodes. Also, make an effort to destigmatize mental health issues.

Undergraduate researchers described both psychological and physical symptoms that manifested as a result of their depression and highlighted how such symptoms prevented them from performing to their full potential in undergraduate research. For example, students described how their depression would cause them to feel unmotivated, which would often negatively affect their research productivity. In cases in which students were motivated enough to come in and do their research, they described having difficulty concentrating or engaging in the work. Further, when doing research, students felt less creative and less willing to take risks, which may alter the quality of their work. Students also sometimes struggled to socialize in the lab. They described feeling less social and feeling overly self-critical. In sum, students described that, when they experienced a depressive episode, they were not able to perform to the best of their ability, and it sometimes took a toll on them to try to act like nothing was wrong, when they were internally struggling with depression. We recommend that research mentors treat depression like any other physical illness; allowing students the chance to recover when they are experiencing a depressive episode can be extremely important to students and can allow them to maximize their productivity upon returning to research ( Judd et al. , 2000 ). Students explained that if they are not able to take the time to focus on recovering during a depressive episode, then they typically continue to struggle with depression, which negatively affects their research. This sentiment is echoed by researchers in psychiatry who have found that patients who do not fully recover from a depressive episode are more likely to relapse and to experience chronic depression ( Judd et al. , 2000 ). Students described not doing tasks or not showing up to research because of their depression but struggling with how to share that information with their research mentors. Often, students would not say anything, which caused them anxiety because they were worried about what others in the lab would say to them when they returned. Admittedly, many students understood why this behavior would cause their research mentors to be angry or frustrated, but they weighed the consequences of their research mentors’ displeasure against the consequences of revealing their depression and decided it was not worth admitting to being depressed. This aligns with literature that suggests that when individuals have concealable stigmatized identities, or identities that can be hidden and that carry negative stereotypes, such as depression, they will often keep them concealed to avoid negative judgment or criticism ( Link and Phelan, 2001 ; Quinn and Earnshaw, 2011 ; Jones and King, 2014 ; Cooper and Brownell, 2016 ; Cooper et al. , 2019b ; Cooper et al ., unpublished data ). Therefore, it is important for research mentors to be explicit with students that 1) they recognize mental illness as a valid sickness and 2) that students with mental illness can simply explain that they are sick if they need to take time off. This may be useful to overtly state on a research website or in a research syllabus, contract, or agreement if mentors use such documents when mentoring undergraduates in their lab. Further, research mentors can purposefully work to destigmatize mental health issues by explicitly stating that struggling with mental health issues, such as depression and anxiety, is common. While we do not recommend that mentors ask students directly about depression, because this can force students to share when they are not comfortable sharing, we do recommend providing opportunities for students to reveal their depression ( Chaudoir and Fisher, 2010 ). Mentors can regularly check in with students about how they’re doing, and talk openly about the importance of mental health, which may increase the chance that students may feel comfortable revealing their depression ( Chaudoir and Quinn, 2010 ; Cooper et al ., unpublished data ).

Foster a Positive Lab Environment.

Encourage positivity in the research lab, promote working in shared spaces to enhance social support among lab members, and alleviate competition among undergraduates.

Students in this study highlighted that the “leadership” of the lab, meaning graduate students, postdocs, lab managers, and PIs, were often responsible for establishing the tone of the lab; that is, if they were in a bad mood it would trickle down and negatively affect the moods of the undergraduates. Explicitly reminding lab leadership that their moods can both positively and negatively affect undergraduates may be important in establishing a positive lab environment. Further, students highlighted how they were most likely to experience negative thoughts when they were alone in the lab. Therefore, it may be helpful to encourage all lab members to work in a shared space to enhance social interactions among students and to maximize the likelihood that undergraduates have access to help when needed. A review of 51 studies in psychiatry supported our undergraduate researchers’ perceptions that social relationships positively impacted their depression; the study found that perceived emotional support (e.g., someone available to listen or give advice), perceived instrumental support (e.g., someone available to help with tasks), and large diverse social networks (e.g., being socially connected to a large number of people) were significantly protective against depression ( Santini et al. , 2015 ). Additionally, despite forming positive relationships with other undergraduates in the lab, many undergraduate researchers admitted to constantly comparing themselves with other undergraduates, which led them to feel inferior, negatively affecting their depression. Some students talked about mentors favoring current undergraduates or talking positively about past undergraduates, which further exacerbated their feelings of inferiority. A recent study of students in undergraduate research experiences highlighted that inequitable distribution of praise to undergraduates can create negative perceptions of lab environments for students (Cooper et al. , 2019). Further, the psychology literature has demonstrated that when people feel insecure in their social environments, it can cause them to focus on a hierarchical view of themselves and others, which can foster feelings of inferiority and increase their vulnerability to depression ( Gilbert et al. , 2009 ). Thus, we recommend that mentors be conscious of their behaviors so that they do not unintentionally promote competition among undergraduates or express favoritism toward current or past undergraduates. Praise is likely best used without comparison with others and not done in a public way, although more research on the impact of praise on undergraduate researchers needs to be done. While significant research has been done on mentoring and mentoring relationships in the context of undergraduate research ( Byars-Winston et al. , 2015 ; Aikens et al. , 2017 ; Estrada et al. , 2018 ; Limeri et al. , 2019 ; NASEM, 2019 ), much less has been done on the influence of the lab environment broadly and how people in nonmentoring roles can influence one another. Yet, this study indicates the potential influence of many different members of the lab, not only their mentors, on students with depression.

Develop More Personal Relationships with Undergraduate Researchers and Provide Sufficient Guidance.

Make an effort to establish more personal relationships with undergraduates and ensure that they perceive that they have access to sufficient help and guidance with regard to their research.

When we asked students explicitly how research mentors could help create more inclusive environments for undergraduate researchers with depression, students overwhelmingly said that building mentor–student relationships would be extremely helpful. Students suggested that mentors could get to know students on a more personal level by asking about their career interests or interests outside of academia. Students also remarked that establishing a more personal relationship could help build the trust needed in order for undergraduates to confide in their research mentors about their depression, which they perceived would strengthen their relationships further because they could be honest about when they were not feeling well or their mentors might even “check in” with them in times where they were acting differently than normal. This aligns with studies showing that undergraduates are most likely to reveal a stigmatized identity, such as depression, when they form a close relationship with someone ( Chaudoir and Quinn, 2010 ). Many were intimidated to ask for research-related help from their mentors and expressed that they wished they had established a better relationship so that they would feel more comfortable. Therefore, we recommend that research mentors try to establish relationships with their undergraduates and explicitly invite them to ask questions or seek help when needed. These recommendations are supported by national recommendations for mentoring ( NASEM, 2019 ) and by literature that demonstrates that both social support (listening and talking with students) and instrumental support (providing students with help) have been shown to be protective against depression ( Santini et al. , 2015 ).

Treat Undergraduates with Respect and Remember to Praise Them.

Avoid providing harsh criticism and remember to praise undergraduates. Students with depression often have low self-esteem and are especially self-critical. Therefore, praise can help calibrate their overly negative self-perceptions.

Students in this study described that receiving criticism from others, especially harsh criticism, was particularly difficult for them given their depression. Multiple studies have demonstrated that people with depression can have an abnormal or maladaptive response to negative feedback; scientists hypothesize that perceived failure on a particular task can trigger failure-related thoughts that interfere with subsequent performance ( Eshel and Roiser, 2010 ). Thus, it is important for research mentors to remember to make sure to avoid unnecessarily harsh criticisms that make students feel like they have failed (more about failure is described in the next recommendation). Further, students with depression often have low self-esteem or low “personal judgment of the worthiness that is expressed in the attitudes the individual holds towards oneself” ( Heatherton et al. , 2003 , p. 220; Sowislo and Orth, 2013 ). Specifically, a meta-analysis of longitudinal studies found that low self-esteem is predictive of depression ( Sowislo and Orth, 2013 ), and depression has also been shown to be highly related to self-criticism ( Luyten et al. , 2007 ). Indeed, nearly all of the students in our study described thinking that they are “not good enough,” “worthless,” or “inadequate,” which is consistent with literature showing that people with depression are self-critical ( Blatt et al. , 1982 ; Gilbert et al. , 2006 ) and can be less optimistic of their performance on future tasks and rate their overall performance on tasks less favorably than their peers without depression ( Cane and Gotlib, 1985 ). When we asked students what aspects of undergraduate research helped their depression, students described that praise from their mentors was especially impactful, because they thought so poorly of themselves and they needed to hear something positive from someone else in order to believe it could be true. Praise has been highlighted as an important aspect of mentoring in research for many years ( Ashford, 1996 ; Gelso and Lent, 2000 ; Brown et al. , 2009 ) and may be particularly important for students with depression. In fact, praise has been shown to enhance individuals’ motivation and subsequent productivity ( Hancock, 2002 ; Henderlong and Lepper, 2002 ), factors highlighted by students as negatively affecting their depression. However, something to keep in mind is that a student with depression and a student without depression may process praise differently. For a student with depression, a small comment that praises the student’s work may not be sufficient for the student to process that comment as praise. People with depression are hyposensitive to reward or have reward-processing deficits ( Eshel and Roiser, 2010 ); therefore, praise may affect students without depression more positively than it would affect students with depression. Research mentors should be mindful that students with depression often have a negative view of themselves, and while students report that praise is extremely important, they may have trouble processing such positive feedback.

Normalize Failure and Be Explicit about the Importance of Research Contributions.

Explicitly remind students that experiencing failure is expected in research. Also explain to students how their individual work relates to the overall project so that they can understand how their contributions are important. It can also be helpful to explain to students why the research project as a whole is important in the context of the greater scientific community.

Experiencing failure has been thought to be a potentially important aspect of undergraduate research, because it may provide students with the potential to develop integral scientific skills such as the ability to navigate challenges and persevere ( Laursen et al. , 2010 ; Gin et al. , 2018 ; Henry et al. , 2019 ). However, in the interviews, students described that when their science experiments failed, it was particularly tough for their depression. Students’ negative reaction to experiencing failure in research is unsurprising, given recent literature that has predicted that students may be inadequately prepared to approach failure in science ( Henry et al. , 2019 ). However, the literature suggests that students with depression may find experiencing failure in research to be especially difficult ( Elliott et al. , 1997 ; Mongrain and Blackburn, 2005 ; Jones et al. , 2009 ). One potential hypothesis is that students with depression may be more likely to have fixed mindsets or more likely to believe that their intelligence and capacity for specific abilities are unchangeable traits ( Schleider and Weisz, 2018 ); students with a fixed mindset have been hypothesized to have particularly negative responses to experiencing failure in research, because they are prone to quitting easily in the face of challenges and becoming defensive when criticized ( Forsythe and Johnson, 2017 ; Dweck, 2008 ). A study of life sciences undergraduates enrolled in CUREs identified three strategies of students who adopted adaptive coping mechanisms, or mechanisms that help an individual maintain well-being and/or move beyond the stressor when faced with failure in undergraduate research: 1) problem solving or engaging in strategic planning and decision making, 2) support seeking or finding comfort and help with research, and 3) cognitive restructuring or reframing a problem from negative to positive and engaging in self encouragement ( Gin et al. , 2018 ). We recommend that, when undergraduates experience failure in science, their mentors be proactive in helping them problem solve, providing help and support, and encouraging them. Students also explained that mentors sharing their own struggles as undergraduate and graduate students was helpful, because it normalized failure. Sharing personal failures in research has been recommended as an important way to provide students with psychosocial support during research ( NASEM, 2019 ). We also suggest that research mentors take time to explain to students why their tasks in the lab, no matter how small, contribute to the greater research project ( Cooper et al. , 2019a ). Additionally, it is important to make sure that students can explain how the research project as a whole is contributing to the scientific community ( Gin et al. , 2018 ). Students highlighted that contributing to something important was really helpful for their depression, which is unsurprising, given that studies have shown that meaning in life or people’s comprehension of their life experiences along with a sense of overarching purpose one is working toward has been shown to be inversely related to depression ( Steger, 2013 ).

Limitations and Future Directions

This work was a qualitative interview study intended to document a previously unstudied phenomenon: depression in the context of undergraduate research experiences. We chose to conduct semistructured interviews rather than a survey because of the need for initial exploration of this area, given the paucity of prior research. A strength of this study is the sampling approach. We recruited a national sample of 35 undergraduates engaged in undergraduate research at 12 different public R1 institutions. Despite our representative sample from R1 institutions, these findings may not be generalizable to students at other types of institutions; lab environments, mentoring structures, and interactions between faculty and undergraduate researchers may be different at other institution types (e.g., private R1 institutions, R2 institutions, master’s-granting institutions, primarily undergraduate institutions, and community colleges), so we caution against making generalizations about this work to all undergraduate research experiences. Future work could assess whether students with depression at other types of institutions have similar experiences to students at research-intensive institutions. Additionally, we intentionally did not explore the experiences of students with specific identities owing to our sample size and the small number of students in any particular group (e.g., students of a particular race, students with a graduate mentor as the primary mentor). We intend to conduct future quantitative studies to further explore how students’ identities and aspects of their research affect their experiences with depression in undergraduate research.

The students who participated in the study volunteered to be interviewed about their depression; therefore, it is possible that depression is a more salient part of these students’ identities and/or that they are more comfortable talking about their depression than the average population of students with depression. It is also important to acknowledge the personal nature of the topic and that some students may not have fully shared their experiences ( Krumpal, 2013 ), particularly those experiences that may be emotional or traumatizing ( Kahn and Garrison, 2009 ). Additionally, our sample was skewed toward females (77%). While females do make up approximately 60% of students in biology programs on average ( Eddy et al. , 2014 ), they are also more likely to report experiencing depression ( American College Health Association, 2018 ; Evans et al. , 2018 ). However, this could be because women have higher rates of depression or because males are less likely to report having depression; clinical bias, or practitioners’ subconscious tendencies to overlook male distress, may underestimate depression rates in men ( Smith et al. , 2018 ). Further, females are also more likely to volunteer to participate in studies ( Porter and Whitcomb, 2005 ); therefore, many interview studies have disproportionately more females in the data set (e.g., Cooper et al. , 2017 ). If we had been able to interview more male students, we might have identified different findings. Additionally, we limited our sample to life sciences students engaged in undergraduate research at public R1 institutions. It is possible that students in other majors may have different challenges and opportunities for students with depression, as well as different disciplinary stigmas associated with mental health.

In this exploratory interview study, we identified a variety of ways in which depression in undergraduates negatively affected their undergraduate research experiences. Specifically, we found that depression interfered with students’ motivation and productivity, creativity and risk-taking, engagement and concentration, and self-perception and socializing. We also identified that research can negatively affect depression in undergraduates. Experiencing failure in research can exacerbate student depression, especially when students do not have access to adequate guidance. Additionally, being alone or having negative interactions with others in the lab worsened students’ depression. However, we also found that undergraduate research can positively affect students’ depression. Research can provide a familiar space where students can feel as though they are contributing to something meaningful. Additionally, students reported that having access to adequate guidance and a social support network within the research lab also positively affected their depression. We hope that this work can spark conversations about how to make undergraduate research experiences more inclusive of students with depression and that it can stimulate additional research that more broadly explores the experiences of undergraduate researchers with depression.

Important note

If you or a student experience symptoms of depression and want help, there are resources available to you. Many campuses provide counseling centers equipped to provide students, staff, and faculty with treatment for depression, as well as university-dedicated crisis hotlines. Additionally, there are free 24/7 services such as Crisis Text Line, which allows you to text a trained live crisis counselor (Text “CONNECT” to 741741; Text Depression Hotline , 2019 ), and phone hotlines such as the National Suicide Prevention Lifeline at 1-800-273-8255 (TALK). You can also learn more about depression and where to find help near you through the Anxiety and Depression Association of American website: https://adaa.org ( Anxiety and Depression Association of America, 2019 ) and the Depression and Biopolar Support Alliance: http://dbsalliance.org ( Depression and Biopolar Support Alliance, 2019 ).

ACKNOWLEDGMENTS

We are extremely grateful to the undergraduate researchers who shared their thoughts and experiences about depression with us. We acknowledge the ASU LEAP Scholars for helping us create the original survey and Rachel Scott for her helpful feedback on earlier drafts of this article. L.E.G. was supported by a National Science Foundation (NSF) Graduate Fellowship (DGE-1311230) and K.M.C. was partially supported by a Howard Hughes Medical Institute (HHMI) Inclusive Excellence grant (no. 11046) and an NSF grant (no. 1644236). Any opinions, findings, conclusions, or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the NSF or HHMI.

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Submitted: 4 November 2019 Revised: 24 February 2020 Accepted: 6 March 2020

© 2020 K. M. Cooper, L. E. Gin, et al. CBE—Life Sciences Education © 2020 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

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Neurobiological research on N,N -dimethyltryptamine (DMT) and its potentiation by monoamine oxidase (MAO) inhibition: from ayahuasca to synthetic combinations of DMT and MAO inhibitors

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The potent hallucinogen N,N- dimethyltryptamine (DMT) has garnered significant interest in recent years due to its profound effects on consciousness and its therapeutic psychopotential. DMT is an integral (but not exclusive) psychoactive alkaloid in the Amazonian plant-based brew ayahuasca, in which admixture of several β -carboline monoamine oxidase A (MAO-A) inhibitors potentiate the activity of oral DMT, while possibly contributing in other respects to the complex psychopharmacology of ayahuasca. Irrespective of the route of administration, DMT alters perception, mood, and cognition, presumably through agonism at serotonin (5-HT) 1A/2A/2C receptors in brain, with additional actions at other receptor types possibly contributing to its overall psychoactive effects. Due to rapid first pass metabolism, DMT is nearly inactive orally, but co-administration with β -carbolines or synthetic MAO-A inhibitors (MAOIs) greatly increase its bioavailability and duration of action. The synergistic effects of DMT and MAOIs in ayahuasca or synthetic formulations may promote neuroplasticity, which presumably underlies their promising therapeutic efficacy in clinical trials for neuropsychiatric disorders, including depression, addiction, and post-traumatic stress disorder. Advances in neuroimaging techniques are elucidating the neural correlates of DMT-induced altered states of consciousness, revealing alterations in brain activity, functional connectivity, and network dynamics. In this comprehensive narrative review, we present a synthesis of current knowledge on the pharmacology and neuroscience of DMT, β -carbolines, and ayahuasca, which should inform future research aiming to harness their full therapeutic potential.

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Introduction

Because of their profound effects on the human mind, psychedelic substances have been the object of fascination in the Western world since the 1950s [ 1 ], when Humphrey Osmond coined the term psychedelic. Despite pioneering work by Alexander and Ann Shulgin on the synthesis and subjective effects of phenylethylamines and tryptamines [ 2 , 3 ], a long-standing moratorium on funding of psychedelics research impeded progress in understanding basic aspects of the physiology and phenomenology of psychedelic substances. In this narrative review, we summarize the state of knowledge of N,N -dimethyltryptamine (DMT), which has been used for millennia by indigenous peoples of South and Mesoamerica for healing and spiritual purposes in the form of the herbal brew variously known as yajé or ayahuasca [ 4 , 5 ]. Footnote 1 Uniquely, ayahuasca brew often contains a mixture of DMT along with several β -carboline alkaloids, which together enhance the bioavailability of orally administered DMT by blocking its first pass metabolism by monoamine oxidase A (MAO-A) in the gut and other organs. Whereas oral DMT alone is nearly inactive, DMT is potently psychoactive when inhaled as vapor [ 6 ], and when taken via intravenous administration [ 7 , 8 ], i.e., routes that circumvent the first-pass metabolism.

The classical psychedelics lysergic acid- N,N -diethylamide (LSD) [ 9 ] and psilocybin (prodrug of the psychoactive substance psilocin) are agonists or partial agonists at 5-hydroxytryptamine (serotonin) 2A (5-HT 2A ) receptors in brain [ 1 ], which are the key mediators of their psychedelic effects. While DMT is generally included among the classical psychedelics, as shall emerge below, it is not yet certain that 5-HT 2A receptor agonism exclusively mediates DMT/ayahuasca effects. Investigations of ayahuasca’s pharmacological effects and therapeutic potential are at a relatively nascent stage, mainly confined to its use in naturalistic and traditional settings.

Like classical psychedelics, consumption of ayahuasca leads to profound alterations in consciousness, characterized by changes in perception and the “inner (cognitive and emotional) experiences” [ 5 , 10 , 11 ], with “visuals, kaleidoscopic lights, geometrical forms, tunnels, animals, humans and supernatural beings coinciding with sensations of peace, harmony and inner calm” [ 12 ]. Other commonly experienced phenomena include synesthesia [ 13 ], decentered introspective states [ 14 ], emotional release [ 15 ], attribution of meaning [ 14 , 16 ], alterations in meaningful, guiding values in life [ 14 , 17 ], ego dissolution, better understanding of oneself and others, acceptance of oneself and past life events [ 14 , 18 ], and expansive states with transpersonal experiences [ 19 ]. Unlike other psychedelics, ayahuasca effects also include notable physical sensations like nausea and vomiting, which may be integral to its traditional use in healing and spiritual rituals [ 20 ]. Indigenous and neo-shamanic groups attribute transformative healing properties to the spirit of ayahuasca, often experienced through vivid encounters with plant spirits in a culturally rich ritual setting [ 21 ].

Recent pre-clinical and observational studies have shown encouraging results with ayahuasca in treating a variety of conditions and their animal models, including depression, anxiety, PTSD [ 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 ], substance use disorders [ 34 , 35 , 36 , 37 , 38 ], eating disorders [ 39 , 40 ], and grief [ 41 , 42 ]. In an initial clinical trial, ayahuasca has shown efficacy against depression and anxiety symptoms [ 28 ] and in altering brain network dynamics linked to depression pathophysiology [ 43 ]. In a randomized placebo-controlled trial (RCT) conducted in Brazil, a single ayahuasca dose produced rapid antidepressant effects persisting for weeks in (n = 29) patients with treatment-resistant depression [ 30 ]. In a recent observational study, the majority of (n = 20) individuals with initial diagnosis of major depression disorder (MDD) enjoyed remission lasting a year after their participation in a ritual with administration of botanical ayahuasca analogues (i.e., various plant sources of DMT and β -carbolines) in the context of an ayahuasca ritual [ 32 ]. Preclinical and in vitro investigations suggest that ayahuasca chemical constituents may also possess neuroprotective properties in neurodegenerative disease models [ 44 , 45 , 46 ]. Thus, a comprehensive review of 21 clinical and preclinical studies with chemical constituents of ayahuasca revealed consistent findings of anxiolytic, antidepressant, anti-addictive, and neuroprotective properties [ 47 ].

Psychological support is critically important during a therapeutic ayahuasca experience, given the influence of contextual factors on mental health outcomes [ 48 ]. The burgeoning interest in ayahuasca's therapeutic benefits marks a pivotal shift from traditional to clinical contexts, opening new avenues for research and application in Western medicine. Its uniquely complex blend of pharmacological, psychological, and cultural elements makes ayahuasca an intriguing research area for scientists from various disciplines. Our objective in this narrative review is to bridge the gap between the phenomenology of the ayahuasca experience and western models of neuropharmacology and brain function. Therefore, we have compiled the current state of knowledge of the pharmacology, biochemistry, and neuroscience of DMT, emphasizing its synergism with MAOIs in the contexts of ayahuasca and its botanical and synthetic analogs. We first summarize the historical and cultural background of ayahuasca, and then elaborate upon the known pharmacological, molecular, cellular, and functional mechanisms of action of the DMT/MAOI combination from studies in vitro and imaging studies in vivo.

Ayahuasca: traditional botanical forms

Ayahuasca (also known as yajé, hoasca, etc.) is a Hispanicized term borrowed from Quechuan dialects of the Amazon basin, which refers to the woody vine (liana) Banisteriopsis caapi and its decoctions, as used for ritual and healing purposes [ 5 ]. The psychoactive beverage is prepared by extensive boiling of the B. caapi bark, resulting in a thick, brown, and oily liquid [ 49 ]. The prolonged boiling process is necessary to extract the plants’ alkaloids, which have low solubility in water. Indeed, the β -carboline harmine mainly resides in the solid phase of the ayahuasca brew [ 50 ]. Recipes for traditional ayahuasca differ between indigenous peoples and geographic regions [ 51 ]. Some traditional shamanic rituals using ayahuasca as a sacred medicine employ decoctions mainly from B. caapi , which contains β -carboline MAOIs, but little or no DMT. Traditional ayahuasca decoctions often contain DMT derived from the leaves of plants such as Psychotria viridis, P. carthagenensis, or the amazonian shrub Diplopterys cabrerana [ 52 , 53 ] . In popular conception, the B. caapi MAOIs serve only to enhance the bioavailability of DMT derived from other ayahuasca components. However, DMT-containing plants are not always included in ayahuasca brews; some indigenous groups in the Amazon basin use B. caapi alone for initiation or healing practices , without admixture of any other plant material [ 54 , 55 ]. Furthermore, some ayahuasca decoctions contain tobacco or other psychoactive plants [ 56 ]. Nonetheless, we suppose that a binary DMT/MAOI model may best capture the complex ayahuasca experience that derives from ancient traditional knowledge of indigenous people who have used these brews in one form or another since millennia [ 57 ].

The essential ayahuasca component B. caapi contains several β -carbolines from the harmala alkaloid family of tryptophan metabolites [ 58 ], which may be psychoactive in their own right [ 59 ], in addition to their inhibition of DMT metabolism by MAO-A [ 60 ]. The various β -carbolines in B. caapi , especially harmine and harmaline, enable the attainment of sufficient plasma DMT concentrations to evoke psychedelic effects lasting 4–6 h [ 5 , 61 ]. Re-dosing four hours after the first ayahuasca administration prolongs the subjective effects, likely due to accumulation of alkaloid concentrations in the body [ 62 ] (repeated dosing is typical of traditional ayahuasca rituals). Tetrahydroharmine (THH), the second-most abundant B. caapi β -carboline, is also a weak inhibitor of plasma membrane serotonin transporters (SERT) [ 63 ], i.e., the site of action of selective serotonin reuptake inhibitor (SSRI) antidepressants. THH may also contribute to net MAO inhibition despite its weaker affinity as compared to harmine and harmaline [ 10 , 64 ]. The B. caapi β -carbolines are almost exclusively MAO-A inhibitors, with 100-fold lower affinity for MAO-B [ 65 , 66 ]. However, it is by no means certain that DMT and β -carbolines are the only pharmacologically relevant compounds in ayahuasca; the chemical diversity in the plant matrix predicts an “entourage effect” [ 67 ] that remains uninvestigated. For the present, we focus on the most abundant ayahuasca β- carbolines (harmine, THH and harmaline) and their interactions with DMT [ 68 ].

β -carbolines and DMT concentrations in ayahuasca samples

We summarize in Table  1 findings of studies reporting concentrations of harmine, harmaline, THH, and DMT in ayahuasca samples from different geographical and indigenous origins. In considering the results of these field sample studies, there is clearly no standard alkaloid composition or standard dose, and that factors such as quantity and quality of used plants, the geographic region, and likewise the cultural affiliations of the people producing ayahuasca all contribute to its varying composition [ 69 ] . The rank order of β -carboline concentrations is generally harmine ≥ THH > harmaline, where harmine concentrations tended to only slightly exceed the THH concentrations, and harmaline was overall the least-abundant β -carboline alkaloid. Indeed, the reported concentrations range from 0.06 to 22.9 mg/mL harmine, 0–1.72 mg/mL harmaline, 0.02–23.8 mg/mL THH and 0.05–14.2 mg/mL DMT (Table  1 ). Despite considerable variability, the analytical findings generally predict that one cup (200 mL) of typical ayahuasca brew would contain alkaloid doses up to a few hundred mg. During the extended boiling process of ayahuasca preparation, harmine converts via consecutive reduction reactions to harmaline and then to THH, thus shifting the β -carboline ratios as compared to the untreated B. caapi [ 70 ]. Furthermore, THH is more chemically stable than harmine/harmaline, surviving in ayahuasca stored for nine days at 37 °C [ 71 ]. Variable DMT concentrations likely reflect the proportion of P. viridis to the total plant material, which ranged from 7 to 20%, depending on the preparation recipe [ 70 ]. It remains unknown if alkaloid concentrations in B. caapi differ across geographic regions or depending on season of harvest.

Ayahuasca analogues and pharmahuasca

The eponymic harmala β -carboline alkaloids in B. caapi also occur in plants such as Peganum harmala (Syrian rue), which is native to Eurasia and northern Africa, or the flowers of the mainly American Passiflora incarnata (passionflower). DMT in ayahuasca often derives from plants of genera Psychotria , the Brazilian/Mesoamerican Mimosa hostilis (jurema), or Anadenanthera and Diplopterys [ 53 , 77 ]. The ubiquity of these alkaloids likely reflects their derivation from the amino acid tryptophan, but there is evidence that tryptamine alkaloids confer increased resistance against herbivores or other predators [ 78 , 79 ]. Brews comprising plant sources other than B. caapi and Psychotria are ayahuasca analogues, whereas synthetic formulations are commonly known as “pharmahuasca” [ 53 , 56 ]. Ayahuasca analogue formulations commonly include P. harmala as a β -carboline source and M. hostilis or A. confusa as a DMT source [ 53 , 56 , 80 ]. P. harmala (mainly its seeds) has traditional medicinal uses in Iran [ 81 ] for its supposed cardiovascular, neurologic, antimicrobial, gastrointestinal (GI), and antidiabetic effects [ 82 ], and M. hostilis finds use in South and meso-American spiritual and shamanic rituals [ 83 , 84 ].

In the 1960s, Claudio Naranjo reported on the use of harmaline for Western psychotherapy [ 85 ], highlighting its potential therapeutic benefits for facilitating introspection, emotional release, self-awareness, and personality integration. It remains uncertain if such effects derive from MAOI or other pharmacological properties of harmaline. Advancements in DMT synthesis and the broader availability of pharmaceutical MAOIs were drivers for the increasing popularity of pharmahuasca. Particularly in Europe, ayahuasca analogues and pharmahuasca are often less costly and more accessible than authentic ayahuasca [ 53 , 86 , 87 ]. Furthermore, uncontrolled harvesting of B. caapi is a recognized threat to its viability in the wild [ 88 ]. While ayahuasca analogues and pharmahuasca can produce experiences akin to traditional ayahuasca, their specific effects differ according to the alkaloid composition [ 86 , 87 ]. Synthetic formulations potentially offer more standard alkaloid composition and a better safety profile, notably with respect to the occurrence of emesis (a”purge” is considered an essential and therapeutic aspect of the ayahuasca ritual) [ 89 ]. Indeed, having a standard composition remains a key requirement for inclusion of medicine in an approved Western pharmacopeia, although there is not yet a consensus on the optimal composition of ayahuasca alkaloids.

N,N- dimethyltryptamine (DMT)

DMT derives from tryptamine, which forms by decarboxylation of L -tryptophan catalyzed by the enzyme aromatic amino acid decarboxylase (AAADC; commonly known as DOPA decarboxylase) (Fig.  1 ). As first described by Axelrod [ 90 ], DMT biosynthesis proceeds by a two-step process from tryptamine via the enzyme indolethylamine N -methyltransferase (INMT), a transmethylation enzyme using S -adenosyl- L -methionine (SAM) as methyl donor. The product N -methyltryptamine (NMT) undergoes further methylation by the same enzyme to give DMT. In situ hybridization studies revealed expression of INMT in neurons, co-localizing with DOPA decarboxylase in presumably DMT-synthesizing neurons in cerebral cortex, and in choroid plexus, but with highest concentration in lung tissue [ 91 , 92 ]. However, INMT knockout in a rodent model, failed to ablate tryptamine methylation in brain and lung tissue, suggesting the presence of alternate enzymatic pathways [ 93 ]. DMT is present in many mammalian tissues. Indeed, the interstitial DMT concentration in rodent brain was approximately 1 nM to cerebral microdialysis coupled with HPLC [ 92 ]. Cerebral microdialysis analysis of canonical biogenic monoamine neurotransmitter concentrations (e.g., serotonin, dopamine, norepinephrine) showed similar concentrations in the range of ~ 1–4 nM [ 94 ]. UHPLC-MS analysis of brain tissue extracts indicated DMT concentrations ranging from zero to 30–60 nM [ 95 , 96 ]. The detection of DMT in the pineal gland [ 97 ] inspired the concept that pineal DMT release might induce vivid dreams, or near-death and other mystical-type experiences [ 98 ], but the total quantity of pineal DMT seems insufficient to evoke such effects. Studies of endogenous DMT concentrations in body fluids (mainly blood and urine) are generally uninformative about the cellular sites of DMT production in biologically significant amounts [ 98 ].

Molecular structures of N,N- dimethlytryptamine (DMT) and other psychedelics, the main ayahuasca β -carbolines, and key metabolic pathways. A Indole and benzene rings (gray) are the chemical scaffolds of the two main categories of psychedelics, i.e. tryptamines (red) and phenethylamines (yellow). Serotonin, DMT and 5-MeO-DMT are structurally similar; LSD, while also containing the tryptamine (and phenethylamine) motif, is an ergoline derivative. Among the phenethylamine psychedelics, we present the structures of 4-bromo-2,5-dimethoxyphenethylamine (2C-B) and mescaline. B The β -carboline scaffold of harmine, harmaline, and tetrahydroharmine (THH) are shown in blue. C) These main β -carbolines in ayahuasca undergo demethylation to harmol, tetrahydroharmalol, and harmalol, respectively. Several cytochrome (CYP) enzymes are implicated in the demethylation of harmine and harmaline, but details are lacking for THH. Harmine and harmaline can also undergo ring-hydroxylation catalyzed by CYP450 [ 107 , 108 ]. An additional metabolic route of harmaline is its oxidation to harmine. DMT is predominantly metabolized by oxidative deamination via monoamine oxidase type A (MAO-A), followed by formation of indole-3-acetic acid (3-IAA) by non-specific aldehyde dehydrogenases. Alternately, DMT is oxidised to DMT- N -oxide (DMT-NO) by CYP450 or demethylated by CYP2D6 and CYP2C19 to N- methyltryptamine (NMT), or hydroxylated to 6-hydroxy-DMT by yet unknown enzymes [ 60 , 107 , 109 , 110 ]. Red arrows indicate inhibition of DMT metabolism by the β -carboline MAO-A inhibitors, resulting in lesser formation of 3-IAA

Exogenous DMT rapidly accumulates in the rat brain after i.p. or i.v. administration, transiently attaining a brain:blood partition ratio of approx. 5–6:1, followed by rapid clearance from the brain and circulation [ 96 , 99 , 100 , 101 ]. Nonetheless, DMT remained detectable in the rabbit CNS up to seven days after peripheral administration, while urinary excretion was not detectable after 24 h [ 102 ], which could be consistent with storage in a very stable vesicular pool. After i.p. administration, there was DMT accumulation in the cerebral cortex, amygdala, and caudate-putamen, while medulla oblongata and cerebellum only showed low uptake [ 101 ], suggesting compartmentation within specific neuronal populations. We have reported spatially heterogeneous DMT accumulation in rat brain after i.p. administration, with 50% higher concentrations in the frontal cortex than in the cerebellum [ 103 ], again suggesting some mechanism for its retention in brain tissue. Indeed, DMT can enter serotonin neurons via SERT, and then accumulate in synaptic vesicles as a substrate for the vesicular monoamine transporter 2 (VMAT2) [ 104 ]. Storage in a vesicular compartment would protect DMT from MAO degradation, and might support its release from serotonin fibers as a “false neurotransmitter” [ 101 ]. To qualify as a classical neurotransmitter, an endogenous substance must be present in physiologically significant amounts, with release in a calcium-dependent manner after presynaptic depolarization, and then evoking responses at specific post-synaptic sites [ 105 ]. Given the current evidence, endogenous DMT may meet these criteria [ 106 ], despite its low affinity at 5-HT 2A receptors. For an extensive discussion of DMT as a candidate neurotransmitter, see [ 106 ].

MAO inhibitors

MAO enzymes (enzyme commission number EC 1.4.3.4) are amine oxidoreductases, with main expression in the outer mitochondrial membrane of mammalian cells. MAO substrates include the biogenic monoamine neurotransmitters dopamine, epinephrine, norepinephrine, and serotonin, and the exogenous psychedelics DMT, psilocin and mescaline. The MAO-reaction consumes molecular oxygen in the restoration of the reduced FADH 2 cofactor to its active FAD form; the imine intermediate spontaneously eliminates ammonia, and the resultant aldehyde is oxidised to the carboxylic acid by non-specific NAD + -dependent dehydrogenase enzymes [ 111 ]. The two isoforms of MAO, which arose from a gene duplication event, have very similar amino acid sequences [ 112 ], but somewhat distinct primary substrates. Whereas serotonin and DMT are preferred substrates for MAO-A, phenylethylamine is a MAO-B substrate; both isozymes metabolize dopamine and tyramine with little selectivity [ 113 , 114 ]. MAO-A occurs in the brain, GI tract, liver, the vasculature of the lungs, as well as in the placenta, while MAO-B mainly occurs in blood platelets [ 111 ], astrocytes [ 115 ], and certain specific populations of neurons [ 116 ]. With respect to ayahuasca, MAO-A in the GI tract is the principal determinant of DMT absorption.

Whereas harmine and moclobemide are reversible MAO-A inhibitors, certain propargyl compounds form a covalent bond with the enzyme, rendering it permanently inactive. The non-selective irreversible MAOIs phenelzine, isocarbaxazid, and tranylcypromine emerged in the mid-twentieth century as the first effective pharmacotherapeutic agents for depression [ 117 ]. These medications have since largely fallen out of favor due to the perceived risk of interactions with dietary vasoactive amines (the”cheese effect”) or the serotonin syndrome, a potentially fatal crisis of hypertension, fever, delirium, and rhabdomyolysis that can occur upon co-administration of direct or indirect serotonin agonists. As such, irreversible MAOIs now seldom serve as first or second line antidepressants, but remain in use in certain severe and treatment-resistant cases, which calls for strict observation of dietary restrictions [ 118 ]. However, serotonin syndrome and hypertensive crisis are exceedingly rare events in patients treated with irreversible MAO blockers [ 118 ].

The reversible MAO-A inhibitor moclobemide is an antidepressant with some efficacy in treating social anxiety, being notable for its favorable side-effect profile and relatively brief plasma half-life. Moclobemide has occasionally been detected in neo-shamanic recipes in Europe [ 53 ]. In general, pretreatment with any inhibitor of MAO-A, reversible or irreversible, would likely serve for potentiation of DMT bioavailability after oral administration, we are not aware of MAOIs other than harmine and moclobemide finding use in pharmahuasca.

Safety and risks associated with ayahuasca or DMT use

Despite the theoretical risk of serotonin syndrome, there are preclinical reports showing potentiation of DMT effects by co-administration of irreversible MAO inhibitors iproniazid or pargyline treatment [ 119 , 120 ]. In an ayahuasca neurotoxicity study, some rats showed behavioral signs of serotonin syndrome and eventually died after receiving doses some 30- and 50-fold the typical human doses [ 121 ]. However, only at such extreme doses can the reversible MAOIs in ayahuasca (or generally also pharmahuasca) evoke the nearly complete inhibition that may be a precondition for the serotonin syndrome. Observational studies have not raised major safety concerns for ayahuasca practitioners taking SSRIs [ 122 ].

Neither short-term nor long-term ayahuasca use led to dependency, and its use in controlled settings such as ceremonial contexts suggests an acceptable safety profile [ 49 , 76 , 123 ]. Acute treatment-emergent adverse events (TEAEs), mainly nausea and vomiting (69.9%), typically resolved without an intervention, with few (2.3%) such participants needing medical attention [ 124 , 125 ]. The American National Poison Data System (NPDS) registered 538 adverse events for ayahuasca between 2005 and 2015, with 28 cases requiring intubation, four cases of cardiac arrest, 12 seizures, and three fatalities [ 126 ]. When considering the global prevalence of ayahuasca use, estimated to be over 4 million annually, the number of deaths (n = 58) reported in association with its use is low. Notably, those fatalities have not been linked to traditional ayahuasca ingredients but may involve toxic plant admixtures, drug interactions, or pre-existing conditions [ 127 ].

On the other hand, challenging psychedelic experiences are common (55.9%), with adverse psychological reactions typically subsiding within a few days; however, 12% of such individuals sought additional professional support [ 124 , 125 ]. Severe psychological distress, including severe depression and psychotic episodes, can occur with ayahuasca use [ 128 , 129 ]. Contemporary neo-shamanic and tourist-oriented settings therefore adopted a broad spectrum of general safety and good practice guidelines. However, some participants in contemporary ayahuasca rituals may lack adequate cultural support and guidance [ 129 , 131 ]. Traditional indigenous settings usually provide structure and safety within ancestral medicinal practices (e.g. plant dietas) contemporary touristic settings. While certain structured approaches like specific dietary protocols, careful attendance, and setting might mitigate risks and enhance the experience [ 130 ], the Western concept of psychological support may not neatly align with such Indigenous methods. Traditional indigenous settings often lack formal health screenings and discussions on medication interactions, challenging the assumption that they are inherently safer for tourists.

Importantly, there is need to integrate safety measures for interactions between ayahuasca with prescription medications (i.e., SSRIs or dopaminergic stimulants), other drugs of abuse, or specific foods rich in tyramines such as overripe fruits, fermented food, tofu, or nuts, which might conceivably increase the risk of serotonin syndrome [ 11 , 128 ]. The use of ayahuasca is not recommended for individuals with uncontrolled hypertension, cardiovascular or cerebrovascular diseases, epilepsy, glaucoma, and liver or gastrointestinal diseases (e.g. ulcers or gastritis), and during pregnancy [ 131 ]. Furthermore, ayahuasca may be risky for individuals with severe psychiatric conditions, including bipolar or psychotic disorders [ 131 ].

Mechanisms of action: ayahuasca and DMT alone

Pharmacological mechanisms, human pharmacokinetics and pharmacodynamics of dmt and ayahuasca.

In the 1950s, the Hungarian chemist and psychiatrist Stephen Szára undertook the first investigations of psychological and hallucinogenic effects of DMT, which he self-administered intramuscularly (i.m.) as an extract from M. hostilis [ 132 ]. In the 1970s, Dittrich, Bickel, and colleagues presented the first systematic psychological investigations of i.m. DMT administration [ 133 , 134 ]. Rick Strassmann reported that intravenous (i.v.) DMT at doses ranging from 0.03 to 0.25 mg/kg DMT freebase (as fumarate) induced peak psychedelic effects at five minutes for the 0.25 mg/kg dose, with plasma DMT concentrations peaking at 16 ng/mL (85 nM) [ 135 ]. Subjective effects returned to baseline by 30 min. Recent studies tested i.v. DMT with different administration regimens. Such protocols entailed 0–19.2 mg bolus 0.5–0.8 mg/min constant infusion of DMT freebase (as hemifumarate) for up to 90 min (Basel) [ 7 ], 11.2 mg bolus 1.2 mg/min infusion of DMT freebase (as fumarate) for up to 30 min (London) [ 8 ], and constant infusion totaling 13.4 mg DMT freebase (as fumarate) over 10 min (London) [ 110 ]). The Basel study showed dose-dependent increases in heart rate up to 119 BPM and blood pressure up to 159/98 mmHg [ 7 ], peaking shortly after the bolus administration and stabilizing within 10–15 min. This aligns with findings from the London study [ 8 ], suggesting a good physiological safety margin in individuals without cardiovascular disease or hypertension. In the first randomized controlled trial of a standardized ayahuasca-analogue formulation containing DMT/harmine, oral doses included up to 38.4 mg DMT freebase (as hemifumarate) and 250 mg  harmine, or up to 69.1 mg intranasal DMT freebase (as hemifumarate) [ 89 ]. DMT was given in 7.7 mg portions at 15 min intervals intranasally, in combination with buccal harmine (up to 200 mg). Autonomic parameters increased transiently after DMT administration and returned to baseline within 120–180 min, with fewer side-effects (e.g. nausea, headache) compared with botanical ayahuasca. In recent intravenous DMT studies, peak plasma concentrations (C max ) were 61 ng/mL at T max (2.9 min) [ 7 ], 32 ng/mL after 11.2 mg DMT bolus followed by 1.2 mg/min [ 8 ], and 63 ng/mL after constant infusion of 1.34 mg/min DMT (freebase weight) [ 110 ]. These C max values correspond to DMT concentration range of 170–335 nM, with apparent plasma half-life (t 1/2 ) of 5–12 min [ 8 , 109 ]. In comparison, C max for intranasal DMT (combined with buccal harmine) was 33 ng/mL at 130–140 min after first administration of the highest dose combination [ 89 ]. Surprisingly, the intravenous DMT studies revealed large inter-individual variability in plasma concentrations [ 7 , 110 ]. This is likely due to individual differences in whole body MAO activity, suggesting a need for personalized dosing. The intranasal/buccal routes of administration considerably improved upon the PK variability of combined oral DMT/harmine [ 89 ]. However, determining the appropriate extent of MAO inhibition to optimize DMT bioavailabilty, remains challenging due to inter-individual differences in harmine metabolism (i.e. rapid vs. slow metabolizers [ 136 ]). Overall, i.v. DMT and parenteral DMT/harmine administration routes can evoke subjective states of controlled intensity and duration, but further refinement of dosing protocols is needed.

The pharmacokinetics of ayahuasca decoctions, which contain a mixture of β-carboline alkaloids, are more complex than for pharmaceutical combinations of DMT and harmine. The presence of THH and harmaline also influence the pharmacodynamics of DMT, while possibly having psychoactive effects unrelated to MAO inhibition. Administration of natural ayahuasca at doses corresponding to 1.4 mg/kg DMT, 4.6 mg/kg harmine, 0.75 mg/kg harmaline and 5.4 mg/kg THH evoked C max values of 25 ng/mL DMT and 110 ng/mL harmine [ 137 ], which are comparable with C max values from the highest dose in the DMT/harmine PK study [ 89 ]. We suppose that THH, given its C max of 329 ng/mL (1.5 µM) from natural ayahuasca, could well contribute to ayahuasca psychopharmacology. An earlier study with administration of lyophilized ayahuasca capsules reported significant plasma concentrations of DMT and THH, but no detectable harmine and harmaline, despite their presence in the capsules [ 61 ]. Indeed, the concentrations of DMT and THH were lower than expected by the authors, based on the ayahuasca PK study conducted earlier by Callaway and colleagues [ 10 ]. The authors interpreted the disparate plasma results as reflecting differing bioavailability of alkaloids in the lyophilized capsules as compared to the botanical ayahuasca brew [ 61 ]. In another study involving administration of two successive ayahuasca doses at four hours apart, there was substantial potentiation of DMT plasma concentrations (approximately 25% higher C max after the second dose) and subjective effects after the second dose [ 62 ]. These results suggest a lack of acute tolerance to subjective effects, and furthermore indicate that carryover of alkaloids from the first dose augments the MAO inhibition from the second dose, which is consistent with the 3–5 h plasma half-lives of harmine and harmaline (40 mg/kg, i.p.) seen in rats [ 138 ]. Indeed, repeated dosing schemes are very common in the ayahuasca ritual, with (anecdotally) little or no development of tolerance on a time scale of days. Such a lacking rapid tolerance development contrasts with LSD or psilocybin, which show significantly declining subjective effects when taken on consecutive days, in association with cross-tolerance [ 139 , 140 ]. On the other hand, the continuous i.v. DMT administration studies reported the strongest subjective effects directly after onset, which subsequently declined despite increasing blood plasma DMT levels over time [ 7 , 8 ]. Such results imply the occurrence of partial acute short-term tolerance to DMT alone, even though there is a general correspondence between pharmacodynamic subjective effects induced by DMT and ayahuasca with the plasma concentrations of the relevant alkaloids. This holds especially well for plasma DMT curves, which are in good accord with the T max for overall intensity, visual effects, side effects, and other subjective acute effects [ 8 , 10 , 61 , 89 , 110 , 137 , 141 ].

Metabolism of ayahuasca alkaloids

The metabolic pathways for DMT and the β -carbolines in ayahuasca are well understood (Fig.  1 ). In additional to the extensive first pass metabolism or oral DMT, there is also rapid second pass oxidative deamination via MAO-A in brain [ 103 ] and other tissues, irrespective of the route of administration. After oxidative deamination, the second-most important metabolic route for DMT is to DMT- N -oxide (DMT-NO) via unspecified hepatic cytochrome P450 (CYP450) enzymes, with minor routes resulting in the production of N -methyltryptamine (NMT) or 6-hydroxy-DMT (Fig.  1 ). Of these metabolites, the former compound is anecdotally psychoactive, according to Shulgin [ 3 ]. Recent studies indicate that the CPY2D6 and CYP2C19 cytochrome oxidase isoforms can contribute to the formation of NMT from DMT [ 109 , 110 ]. However, the specific isoform/s responsible for the conversion of DMT to 6-hydroxy-DMT remain unknown. Inhibition of MAO-A, by reducing or slowing the production of 3-IAA, shifts the branching ratio in favor of the secondary metabolic pathways. Thus, MAO inhibition augments the formation of DMT-NO, NMT, and 6-hydroxy-DMT [ 107 ]. In a rat study with DMT administration alone (1 mg/kg i.p.), the brain concentration of 3-IAA at 100 min was ~ 50-fold higher than that of unmetabolized DMT. However, with co-administration of harmine (1 mg/kg i.p.), the brain exogenous alkaloid concentrations were 34% DMT, 65% 3-IAA, and 1% DMT-NO [ 103 ]. Thus, even with substantial (but incomplete) MAO inhibition, 3-IAA remained the main metabolite in brain. In an analysis of 24-h urine samples collected after ayahuasca administration, there was 1% recovery of unchanged DMT, versus 55% as 3-IAA and 12% as DMT-NO [ 108 ], suggesting that DMT-NO formation may be more important systemically than in brain (DMT-NO is unlikely to cross the blood–brain-barrier). In another urine analysis study, there was 97% excretion of the DMT dose as 3-IAA and 3% as DMT-NO after oral administration [ 6 ]. In contrast, that study showed significantly higher generation of DMT-NO (28%) after smoking, with 63% excreted as 3-IAA and 10% leaving the body unchanged. Despite the lacking MAO-A inhibition in that study, renal elimination as DMT-NO exceeded that seen after ayahuasca administration.

Harmine and harmaline are metabolized in the body to hydroxy-harmine or and hydroxy-harmaline by enzymes from the CYP450 family, or to harmol and harmalol [ 107 ]. Similarly to harmine and harmaline, THH is preponderantly metabolized to tetrahydroharmol [ 107 , 108 ], but the responsible enzymes remain to be established. In 24-h urine samples collected after ayahuasca administration, there were low total recoveries of harmine, THH, and their metabolites as compared to DMT and harmaline recovery, which comprised approximately two-thirds of the administered dose [ 108 ].

Molecular and cellular mechanisms

Molecular targets of dmt and ayahuasca.

Conventional understanding links the psychedelic properties of DMT (and ayahuasca) to agonism at brain serotonin 5-HT 2A receptors [ 52 ]. However, DMT has only modest affinity at these receptors in vitro (K i  = 127–1200 nM and IC 50  = 75–360 nM) [ 142 , 143 , 144 , 145 , 146 ]. Additional binding at serotonin 5-HT 1A (K i  = 183 nM, IC 50  = 170 nM) and 5-HT 2C receptors (K i  = 360–2630 nM, IC 50  = 360 nM), along with other receptor subtypes, have been proposed to contribute to the overall psychoactive effects of DMT [ 142 , 143 , 144 , 145 , 146 , 147 , 148 , 149 , 150 ]. 5-HT 1A receptors predominantly occur in the limbic system and brain regions that receive projections from other parts of the limbic system, such as the amygdala, hippocampus, cingulate cortex, and certain other neocortex regions [ 151 , 152 ]. In these regions, the 5-HT 1A receptors have post-synaptic localization, while 5-HT 1A receptors in the raphe nuclei are pharmacologically distinct autoreceptor sites that control serotonin release and firing rate [ 153 ]. The 5-HT 1A receptors are mechanistically relevant for the biological understanding of depression [ 151 , 152 ], as 5-HT 1A agonism proposedly improves stress resilience [ 154 ], and modulates HPA axis functioning [ 155 ] and neuroplasticity [ 156 ]. Not only DMT, but also the ayahuasca β- carbolines influence serotonin neurotransmission, either directly (DMT as a 5-HT 1A/2A/2C agonist) or indirectly (THH as a SERT blocker and weak MAO-A inhibitor, and harmine and harmaline as potent MAO-A inhibitors), which could relate to reported anti-depressant effects of ayahuasca [ 157 ]. Interestingly, the co-administration of the 5-HT 1A/1B receptor partial agonist pindolol potentiated the subjective effects of DMT in a human trial [ 135 ], suggesting an autoreceptor regulation of the post-synaptic effects of DMT.

5-HT 2A receptors have highest expression in brain in layer 5 pyramidal neurons in the neocortex, but also occur in limbic and basal brain structures [ 154 ]. As noted above, DMT shows moderate affinity towards 5-HT 2A sites, as does harmine (K i  = 230 nM), whereas harmaline and THH show very low 5-HT 2A affinities of 7.8 and > 10 µM, respectively [ 158 , 159 ]. Νotably, pre-administration of the serotonin 5-HT 2A/C blocker ketanserin (as tartrate, 40 mg) significantly diminished (but did not ablate) the neurophysiological and subjective effects of ayahuasca reported by participants via the hallucinogen rating scale (HRS) and the altered states of consciousness (ASC) questionnaire [ 141 ]. There were significant reductions in the HRS subscales affect, perception and intensity, and in the ASC subscale “visionary restructuralization” upon ketanserin pretreatment. However, these subscale scores were still significantly higher than on study days without ayahuasca administration, which implies that 5-HT 2A receptors may not be the solitary site of DMT action. There was no significant ex vivo occupancy by DMT plus harmine (1 mg/kg, each) at rat cortical 5-HT 2A receptors labelled with [ 3 H]ketanserin [ 103 ], a close analogue of the PET ligand [ 18 F]altanserin [ 160 ]). In the rat study higher doses of DMT plus harmine (3 mg/kg, each) also evoked no detectable occupancy at binding sites for [ 18 F]MHMZ, a 5-HT 2A antagonist PET ligand with higher selectivity and binding signal than [ 18 F]altanserin/[ 3 H]ketanserin. Those negative results may call into question the contention that DMT acts exclusively via serotonin 5-HT 2A receptors. In another study, administration to rats of ayahuasca at doses containing 0.3 mg/kg DMT led to extinction of contextual freezing behavior [ 161 ]. With repeated ayahuasca doses, the co-administration of the 5-HT 2A receptor antagonist MDL-11,939 or the 5-HT 1A receptor antagonist WAY-100635 in the limbic cortex blocked the fear extinction effects, again suggesting an action at both receptor types [ 161 ]. The 5-HT 2C receptors have expression in epithelial cells in the choroid plexus and GABAergic neurons in prelimbic prefrontal cortex (PFC), and in other cortical, limbic, and basal ganglia regions, where they may present targets for various neuropsychiatric disorders [ 162 ]. DMT and harmine both show low affinity to 5-HT 2C receptors [ 158 ], but we cannot presently exclude an action of ayahuasca at these sites.

While LSD interacts at dopamine D 2/3 receptors in vitro [ 143 , 163 ] and in vivo [ 164 ], DMT has little affinity at dopamine receptors [ 128 ]. However, the indisputable involvement of brain dopamine in affective disorders, reward learning, and avoidance behaviors in relation to anhedonia [ 165 , 166 ], we may infer an indirect action of ayahuasca at dopaminergic pathways. While ayahuasca β -carbolines likewise have little affinity for dopamine receptors [ 167 ], they may yet mediate indirect effects on brain dopamine via MAO-A inhibition [ 157 ]. Thus, for example, ayahuasca administration increased the dopamine concentration in amygdala of rats [ 168 ]. Nonetheless, as noted above, complete blockade of both forms of MAO did not potentiate the amphetamine-evoked dopamine release in the [ 11 C]raclopride PET competition paradigm [ 169 , 170 ]. On the other hand, local application of harmine (300 nM) substantially increased the electrically evoked release of dopamine in nucleus accumbens brain slices, in a manner seemingly unrelated to MAO inhibition, but apparently involving 5-HT 2A receptors [ 171 ]. Harmine may inhibit dopamine reuptake via DAT [ 107 ] and may somehow contribute to the normalization of aberrant DAT membrane trafficking and DA reuptake rate in addictive disorders [ 172 , 173 ]. Sigma-1 receptors, which are abundant throughout the CNS [ 157 , 174 ], are another potential site of DMT action. However, the reported affinities for DMT towards sigma-1 receptors (K D  = 14 µM [ 174 ], K i  = 5.2–15.1 µM [ 143 , 175 ]) may not suffice to impart significant effects. Nonetheless, DMT induced reductions in electrophysiological measures (spreading depolarization), which were normalized by co-administration of sigma-1 antagonists NE-100 and asenapine [ 175 ]. The selective sigma-1 receptor agonist PRE-048 evoked a similar reduction in spreading depolarization. Additional immunohistochemistry results in the same study indicate that DMT might have neuroprotective properties against hypoxia or ischemic stroke [ 175 ].

The β -carbolines harmine and harmaline are antagonists at alpha-1 adrenergic receptors, with IC 50 values in the range 31–36 µM [ 176 ], and may inhibit acetylcholinesterase, which would thereby potentiate cholinergic neurotransmission [ 157 ]. Other possible actions of harmine include modulation of GABAergic neuronal transmission [ 177 ] and inhibition of intracellular protein aggregation (perhaps relevant in neurodegeneration models) [ 178 ], which may call for further investigation of therapeutic mechanisms [ 157 ]. Harmine exerts anti-inflammatory, neuroprotective, antidiabetic, and antitumor effects in various models [ 179 , 180 , 181 , 182 ]. Overall, the ayahuasca β -carbolines may have effects extending beyond simple MAO-A inhibition, but with uncertain relevance to ayahuasca psychopharmacology.

Neuroplasticity induced by DMT and β -carbolines

Recent research addresses the possibility that psychedelic substances can induce or reinstate neuroplasticity, e.g., by altering gene and protein expression, post-translational processes, synapse formation, or neurogenesis. While most such studies have concerned psilocybin, there are a few reports on neuroplastic effects of DMT and the ayahuasca β -carbolines (for review, see [ 183 ]. Especially in human research, plasma levels of brain-derived neurotrophic factor (BDNF), a neurotrophin known to regulate synaptic plasticity and neuronal growth [ 184 ], have served as a marker for potential effects of neurogenesis in the context of antidepressant treatment [ 185 ]. While one study showing increased plasma BDNF levels after ayahuasca intake by healthy and depressed individuals [ 186 ], other studies with ayahuasca or DMT showed no significant changes [ 7 , 187 ]. In a preclinical study, there was likewise no increase in plasma BDNF after DMT administration. However, co-treatment with an antagonist of tropomyosin receptor kinase B (TrkB, the high affinity receptor for BDNF), or with an inhibitor of downstream target of TrkB signaling (mTOR), completely blocked the neuroplastic effects of DMT, suggesting significant engagement of the BDNF signaling pathway in mediating neuroplasticity [ 188 ]. In that same study, a single treatment i.p. with DMT (10 mg/kg as free base) increased dendritic spine density and neuronal excitability in PFC neurons, which might explain the antidepressant and fear extinction effects reported in another rat study with DMT [ 189 ]. Increased dendritic spine growth was observed after activation of intracellular 5-HT 2A receptors with DMT, psilocin or psilocybin. These intracellular receptors are mostly inaccessible by endogenous serotonin, thus suggesting that DMT might induce neuroplasticity via an intracellular mechanism, possibly also at the low endogenous concentrations [ 190 ]. Chronic microdosing (0.77 mg/kg DMT freebase (as hemifumarate) 2–3 times per week for 7 weeks) did not alter BDNF levels or 5-HT 2A receptor expression in rats, but nonetheless exerted antidepressant-like behavioral effects and improved fear extinction learning without other seemingly negative behavioral changes [ 191 ]. Interestingly, the authors also reported retraction of dendritic spines in the PFC, but only in female DMT-treated rats. These latter effects may raise concern about the possibility of unfavorable effects with excessive or prolonged microdosing regimens [ 191 ]. Many of the presented findings potentially link to biomolecular underpinnings of affective disorders, e.g. decreased BDNF levels or TrkB signaling could underly depression, or neuroinflammation due to immunological hyperactivity could mediate anxiety symptomatology [ 25 , 185 , 192 , 193 ]. DMT treatment enhanced performance in memory tests and spatial learning in adult mice, while promoting neurogenesis in the subgranular zone of the hippocampus in vitro (tested after 7 days) and in vivo (2 mg/kg repeated doses of DMT either daily over 4 days, or every other day for 21 days) [ 194 ]. Co-administration of a sigma-1 receptor antagonist blocked these effects, which may belie the low affinity reported for DMT at that binding site.

Preclinical studies have implicated harmine as an enhancer of BDNF signaling in rat hippocampus, in association with antidepressant-like effects in a behavioral assay, both for acute and chronic administrations [ 25 , 193 ]. However, other rat studies showed that a high dose of harmine (15 mg/kg as harmine hydrochloride) induced anhedonia in the sucrose preference test, and reduced locomotor activity, without increasing hippocampal BDNF levels [ 195 ]. All three main β -carboline alkaloids in B. caapi promoted neurogenesis in an in vitro assay with progenitor cells from the subventricular and subgranular zone, which are the main niches of adult neurogenesis in mice. Harmine, harmaline and THH all significantly increased stem cell proliferation, migration, and eventual differentiation into neurons to assays in vitro [ 196 ]. Complementing these findings, earlier studies in chick embryo cells [ 197 ] and human neural progenitor cells [ 44 ] showed that harmine (2–5 µM in chick embryo and 7.5–22.5 µM in human progenitor cells) increased mitosis rates. In a mouse model of anxiety, harmine (20 mg/kg i.p. daily for 7 days) reduced anxiety-like behavioral effects and blunted neuroinflammation in the basolateral amygdala [ 192 ].

We emphasize that some studies have reported adverse effects from very high or repeated doses of DMT or ayahuasca [ 121 , 191 , 195 ], in keeping with Paracelsus’ dictum dosis sola facit venenum (only the dose makes the poison). As with any medication, exceeding some therapeutic dose range may offset beneficial effects of appropriate dosage regimens. The involvement of BDNF signaling in the effects of DMT/ayahuasca seem relevant to the association of BDNF with models of depression and anxiety disorders arising from a hyperactive immune system and chronic low-grade inflammation [ 25 , 185 , 192 , 193 ]. As substantiated by the burgeoning publications on neuroplasticity in the psychedelics literature [ 183 ], there is growing interest in the basic biological mechanisms of action of psychedelic substances. A simple model in which DMT and other ayahuasca constituents act exclusively at serotonin 5-HT 2A receptors falls short of explaining the full spectrum of acute and chronic effects.

Functional mechanisms—human brain imaging and EEG studies

We now give a narrative account of the available molecular imaging, fMRI, and EEG studies reporting effects of ayahuasca (14) or DMT (9) on human brain function. We present the studies in chronological order in Supplementary Table 1, including a brief description of the study design, sample, and interventions, along with key results, with a more detailed discussion in the following section.

Neuroimaging studies with ayahuasca and DMT

The first ayahuasca neuroimaging study used single photon emission tomography (SPECT) to determine the acute effects of lyophilized ayahuasca capsules on regional cerebral blood flow (CBF) [ 198 ], a surrogate marker for neuronal network activation. Ayahuasca administration increased perfusion in the right hemisphere anterior cingulate cortex (ACC) and medial frontal gyrus, bilaterally in the anterior insula and inferior frontal gyrus, and in the left amygdala and parahippocampal gyrus. These regions are thought to play key roles in interoception, body awareness, and emotional processing [ 199 , 200 ], well aligning with the acute subjective effects of ayahuasca [ 46 , 201 ]. A similar SPECT study in depressed patients showed significantly increased perfusion in the left nucleus accumbens (NAc), right insula and left subgenual area 8 h after ayahuasca treatment compared to baseline [ 29 ]. Additionally, acute reductions in depressive symptoms (80–180 min after administration) persisted up to three weeks. Previous neuroimaging studies (deep brain stimulation, PET, fMRI) have shown hypoactivity in precisely these regions in depressed patients, which rectified upon treatment with conventional antidepressants such as SSRIs or deep brain stimulation [ 202 , 203 , 204 , 205 , 206 ]. Post-acute results from the depressed group showed only partial overlap (in the right insula) with the acute effects of ayahuasca on cerebral perfusion in the healthy volunteer study [ 29 , 198 ], which might reflect changes in neuronal responsivity to the pharmacological challenge or time-dependent measurement differences.

In two task-based fMRI studies during acute DMT (i.v.), the first study showed no significant changes in blood oxygenation level dependent (BOLD) signal, despite the participants’ reduced reaction time to stimuli [ 207 ], whereas the second study showed signal reductions in brain regions associated with processing visual and auditory information in addition to reduced reaction time [ 208 ]. These combined behavioral and fMRI results recapitulated earlier behavioral findings with two different DMT doses [ 209 ]. Participants in another study with somewhat higher doses of i.v. DMT reported experiencing pronounced elementary and complex imagery [ 8 ], which might explain the reduced capability to focus on such attention-based tasks.

Another fMRI study investigating mental imagery during acute ayahuasca effects reported increased BOLD signal in many brain regions compared to baseline, including bilateral cuneus and left precuneus, lingual gyrus, fusiform, parahippocampal and temporal, occipital and frontal gyri [ 210 ]. These changes occurred during an imagery experience and may underly the often-reported vivid internal visual alterations with closed eyes. Partially overlapping results were reported in [ 198 ], and correspond to functional representations such as the peripheral visual field, retrieval of episodic memories, processing of contextual associations, and mental imagery. Changes in functional connectivity during mental imagery after ayahuasca intake, indicate alternations in the top down temporal information flow between frontal and occipital regions. Visions produced by ayahuasca seemingly arise in the primary visual cortex (V1) [ 210 ] and propagate to higher order visual regions. Another report of the same study sample showed changes in the default mode network (DMN) with task-based (verbal fluency) and with resting-state (rs) fMRI recordings [ 43 ]. Six of the nine pre-defined DMN regions showed significant activity decreases when comparing rest to task periods and ayahuasca to baseline. Two of the remaining DMN ROIs (left MFG and left MTG, involved in language processing [ 211 ]), also showed significant BOLD signal decreases. Additionally, functional connectivity declined within PCC/precuneus after ayahuasca intake. These findings suggest that experienced ayahuasca users achieve a brain state that occurs with decreased mind-wandering, allowing them to observe their thoughts and feelings without judgment, similar to experienced meditators [ 212 ].

In a follow-up analysis of the same rs-fMRI data increases of global entropy (Shannon entropy, expressing the uncertainty or variability in stochastic variables) were identified. Increases of local integration and decreases of global integration in various brain networks [ 213 ] imply that ayahuasca altered the modular structures of resting state networks. These results align with the entropic brain hypothesis , which proposes that psychedelic states entail higher entropy than ordinary waking consciousness [ 214 ].

A proton magnetic resonance spectroscopy ([ 1 H]-MRS) and rs-fMRI study with baseline and post-acute measurements one day after ayahuasca ingestion showed decreased glutamate + glutamine, creatinine + phosphocreatinine, and N -acetylaspartate +  N -acetylaspartylglutamate signals in the PCC [ 215 ]. These lower metabolite levels indicate higher neuronal activity during acute ayahuasca intake [ 215 ]. Indeed, other psychedelics evoked decreased inhibitory alpha-waves in similar brain regions as in ayahuasca studies [ 141 , 216 , 217 ], and similar MRS changes occur in in patients successfully treated for depression with cognitive behavioral therapy (CBT) or SSRIs [ 218 ]. Complementary rs-fMRI measurements revealed enhanced crosstalk between the ACC (associated with executive and cognitive-emotional processing) and the PCC and limbic structures (highly relevant for emotion and memory processing), which may relate to the antidepressant effects of ayahuasca [ 215 ]. Parts of the salience (SAL; ACC) and the DMN (PCC) networks are habitually anti-correlated in normal waking consciousness [ 219 ], but enhanced coupling may occur during ayahuasca and other psychedelic experiences [ 220 ]. A later study replicated those findings of post-acute increased connectivity between the SAL and the DMN one day after administration of ayahuasca to healthy volunteers [ 221 ]. In accordance with previous reports, increased ACC connectivity within the salience network and decreased connectivity in the PCC within the DMN were identified [ 221 ]. A novel approach was adopted in a rs-fMRI study in a group setting with members of the Santo Daime church presenting “connectome fingerprints” for each participant, based on the idea that functional connectivity is more consistent within the same person across repeated scans than between different subjects [ 222 ]. Participants showed greater alignment between connectomes during the acute ayahuasca phase than during the placebo scans. After ayahuasca treatment, network stability decreased in the SAL, and increased in the dorsal attention network (DAN). Between-network stability mostly decreased from the SAL and visual network (VIS), extending to the other five large-scale brain networks defined by Yeo and colleagues [ 223 ].

Similarly, i.v. DMT administration decreased within-network integrity in five (VIS, somatomotor network (SM), DAN, fronto-parietal network (FP) and DMN) of the seven Yeo networks, and increased within-network functional connectivity in the SAL, FP and DMN [ 224 ]. An increased between-network functional connectivity between the FP, DMN, and SAL networks, and the other Yeo networks, suggest that DMT mainly affects networks integrating and processing higher cognitive functions. Additionally, DMT flattened the principal cortical gradient acutely [ 224 ] (which ranges from areas for processing sensory and motor information to regions subserving higher cognitive processing [ 225 ]). These findings suggest that DMT transiently dysregulates functional hierarchies, enabling greater cross-communication between brain regions and networks as compared to ordinary consciousness.

Another task-based fMRI study testing implicit aversive stimulation showed longer reaction times to aversive compared to neutral images at baseline, whereas during the ayahuasca scan reaction times did not differ according to emotional valence of the visual stimulus [ 226 ]. Furthermore, in the ayahuasca condition, there was decreased activation of the bilateral amygdala and increased activation of bilateral insula and right dorsolateral PFC upon exposure to aversive images. These findings align with previous ayahuasca studies, showing activation of regions involved in emotion processing, such as the amygdala, ACC, and insula, possibly related to the intensified emotional experience [ 29 , 198 ].

EEG studies with ayahuasca and DMT

The first open-label EEG study during the ayahuasca ritual among healthy members of the Santo Daime church reported increases in gamma power in the left posterior temporal cortex and the left occipital lobe with close eyes and increased gamma power in the central, parietal, and occipital lobes with open eyes compared to baseline [ 227 ]. Gamma is a high frequency (30–80 Hz) band modulated by external sensory inputs and internal processes such as working memory and attention; as such, their EEG findings bear some relation to fMRI findings of increased activity (e.g., in visual cortex, fusiform gyrus or prefrontal cortex) during a mental imagery task after ayahuasca administration [ 210 ]. A later study found a dose-dependent reduction in EEG power across all frequency bands, peaking between 90 and 120 min after ayahuasca administration [ 228 ]. Additional EEG analyses focussing on peak effects at 60 and 90 min after high doses [ 229 ] showed widespread bilateral decreases in alpha and delta power in somatosensory, auditory, and visual association cortices. At 90 min even greater reductions in beta, delta, and theta power occurred in cortical regions relevant for emotion and memory processing. Similar decreases in lower frequency (delta and theta) power have been observed after treatment with other psychedelics, or psychostimulants [ 230 , 231 ].

Delta waves usually increase during deep sleep, or in meditative and relaxed states, so decreased delta power might suggest an excitatory effect of ayahuasca [ 229 ]. This would be in accordance with animal studies showing excitatory postsynaptic potential and currents after psychedelics administration [ 232 ]. Although delta and theta power in EEG recordings was unchanged in a later study up to two hours after ayahuasca intake [ 137 ], alpha power declined in parieto-occipital regions at 50 min. Some cortical regions showed increased slow-gamma power between 75 and 125 min, while fast-gamma power had decreased in four clusters during the same time window. DMT and β -carboline plasma levels showed positive correlations with EEG power in the beta, gamma and delta bands, and a negative correlation with alpha power. Specifically, DMT and harmine levels correlated more strongly with early phase alpha power decreases, while the harmaline and THH concentrations correlated more strongly with the late phase gamma band increases. These changes in β -carboline profiles matched earlier pharmacokinetics findings [ 10 , 11 ].

In an EEG study using transfer entropy (TE) to measure directed information transfer ayahuasca administration resulted in decreased information flow from frontal to posterior brain regions and increased flow from posterior to frontal regions [ 233 ]. These changes, observed at various time points after administration, suggest that ayahuasca disrupts the usual neural hierarchies between higher order frontal regions and more sensory-related posterior regions, aligning with similar findings from fMRI studies with i.v. DMT [ 224 ].

An EEG study that tested the effects of ayahuasca and ketanserin in a 2 × 2 design found decreases in alpha, delta, and theta frequency bands after 90 min [ 141 ], much as in the above-mentioned earlier studies [ 137 , 228 , 229 ]. Ketanserin alone had opposite effects, with unchanged alpha power but increased delta and theta powers compared to placebo. When combined, ketanserin and ayahuasca led to stronger increases in delta and theta power, counteracting ayahuasca’s effects. Ketanserin before ayahuasca reduced, but did not completely block all subjective effects, possibly related to changes in EEG bands.

Performance of a cognitive mismatch negativity (MMN, a brain response to violations of a rule) EEG task decreased dose-dependently during i.v. DMT administrations compared to baseline [ 234 ]. After the low DMT dose, there was diminished N1 peak amplitude (~ 150 ms after stimulus), indicating decreased attention to visual stimuli [ 235 ], and attenuated MMN signal in the right hemisphere. Similarly, psilocybin treatment also reduced N1 peak activity, albeit with stronger effects on MMN [ 236 , 237 ].

A more recent EEG study with i.v. DMT showed significantly increased signal diversity and delta and gamma powers, while decreasing alpha and posterior beta powers, correlating with intensity ratings and DMT plasma levels [ 238 ]. A cortical travelling wave analysis revealed increased forward waves (FW) and decreased backward waves (BW) [ 239 ]. After DMT administration, the frequency of the travelling waves decreased for alpha and beta and increased for delta and theta, matching previously reported frequency band power changes. These changes resembled those seen during visual stimulation [ 240 ], suggesting a mechanism for DMT-induced visual hallucinations [ 8 , 241 ]. Another analysis modelled the relationship between alpha and beta power, signal complexity and simulated DMT plasma levels, identifying specific concentrations evoking half-maximal (IC 50 ) band reductions in alpha (71 nM) and beta power (137 nM), and the EC 50 for signal complexity (54 nM). These results constitute the first dose–response relationship for EEG signal strength with DMT.

EEG recordings after self-administration of DMT by smoking in a naturalistic setting recapitulated findings [ 238 ] of a widespread reduction in alpha power lasting several minutes, along with reduced delta and gamma power in occipital, parietal, temporal and antero-central regions during the same time window [ 242 ]. In a separate reanalysis of these data, the same pattern of power changes was found alongside a negative correlation with subjective effects only with theta power changes [ 243 ].

An additional analysis of the study presented above [ 224 ] focused on the relationships between EEG and simultaneous fMRI findings after i.v. DMT administration. EEG data showed reduced alpha and beta power, decreased fractal spectral power below 30 Hz, and increased signal complexity. Significant negative correlations were found between intensity ratings and plasma DMT concentrations with alpha- and beta-power and positive correlations with delta- and theta-power, much as reported in [ 238 ]. The cross-model analysis showed positive correlations between frontal delta power and negative correlations between parietal alpha-power with GFC in most RSNs, along with positive correlations between gamma power and signal diversity in a few RSNs. This study reinforced preceding EEG findings with additional fMRI data, demonstrating the benefits of multimodal neuroimaging.

In reviewing EEG studies on ayahuasca and DMT, two main findings consistently appear: (1) a reduction in alpha frequency power, and (2) an increase in signal complexity. These effects occur 60–120 min after ayahuasca administration and shortly after i.v. or inhaled DMT [ 137 , 141 , 224 , 228 , 229 , 238 , 242 , 243 ]. Reduced alpha power has been linked to increased brain metabolism [ 244 , 245 , 246 ], which could explain the increased BOLD signal in the visual cortex [ 210 ], and the vivid visual effects often reported with these substances. The alpha band is the most prominent feature of resting-state EEG recordings in adults [ 247 ], and is linked to high-level psychological functioning [ 248 , 249 ] and top-down brain regulation [ 250 , 251 ], both of which are generally modified by psychedelics [ 224 , 233 , 252 , 253 ]. While changes in other frequency bands are less consistent, the increase in signal complexity supports the idea of decreased top-down regulation and hierarchical processing of neural information during the psychedelic state [ 214 , 252 ].

Neuroimaging and EEG studies on DMT and ayahuasca vary widely in their designs, dosages, administration routes, and settings, which can make comparisons difficult. However, many studies focused on resting-state EEG or fMRI, which are useful for examining brain activity without specific tasks and can be easily compared. Despite these caveats, these studies have informed several models of psychedelic action emerging over the past few years. These models include the entropic brain hypotheses as noted above [ 214 ] and its generalization, the REBUS (relaxed beliefs under psychedelics and the anarchic brain) model [ 252 ], the cortico-striato-thalamocortical (CSTC) model [ 254 ], the strong priors (SP) model [ 255 ], and the cortico-claustro-cortical (CCC) model [ 256 ]. The CSTC and the CCC model mainly rely on the assumption that 5-HT 2A receptor agonism is the key driver for psychedelic effects, which is less than certain for the case of DMT/harmine. The REBUS model proposes that psychedelics reduce the influence of top-down processes (like expectations or prior beliefs) and thereby enhance bottom-up sensory and emotional information flow potentially facilitating therapeutic change processes. We prefer the REBUS model because it explains several observed effects such as the reduction of a cortical gradient (fMRI), modulations of RSNs (especially the DMN), increased signal complexity (EEG) or altered direction of cortical traveling waves in the alpha band [ 257 ].

For a comprehensive integration of these models into general neuroscientific research on psychedelics, see [ 258 ]. Several systematic reviews have examined neuroimaging studies with various psychedelic substances, e.g., Gattuso et al. [ 259 ] and McCulloch et al. [ 260 ]. These reviews highlight the modulation of the DMN and resting-state brain activity under the influence of psychedelics, using various imaging techniques (e.g. fMRI, EGG, MEG). However, there is a notable lack of molecular imaging studies specifically examining the actions of DMT and ayahuasca.

Long-term psychological and neuroanatomical changes after ayahuasca use

In a cross-sectional study, Bouso et al. [ 261 ] compared long-term ayahuasca users (n = 127) of various ayahuasca churches in Brazil with a religious control group (n = 115) that abstains from substance consumption. Psychometric assessments were conducted at study inclusion (T1) and one year later (T2). The ayahuasca group showed significantly lower Harm Avoidance and Self-Directedness, higher Self-Transcendence, and lower general subjective symptoms, which suggests that consumption in religious contexts is beneficial for mental and physical health. Additionally, ayahuasca users scored higher on all subscales of the Spiritual Orientation Inventory [ 262 ] at both time-points, indicating a reinforcement of spiritual beliefs and attitudes. They also performed better in neuropsychological tests of conflict monitoring, executive function, and working memory at both time-points.

Structural MRI provides quantitative measures of brain volume and cortical thickness, which can indicate structural changes due to aging, neurotoxicity, or neuroplasticity. Bouso et al. [ 263 ] reported on cortical thickness in experienced ayahuasca users from the Santo Daime with a matched control group. The habitual ayahuasca users showed significant cortical thinning in middle and inferior frontal gyrus, precuneus, superior frontal gyrus, PCC, and superior occipital gyrus, along with cortical thickening in the precentral gyrus and ACC. Cortical thinning in the PCC negatively correlated with lifetime and years of ayahuasca use. Neuropsychological tests revealed the same differences as the cross-sectional study mentioned above. The cortical thinning in key nodes of the DMN might imply long-term downregulation of DMN activity, although no direct evidence links this to reduced within-DMN connectivity [ 43 , 224 ]. The negative correlation of PCC thickness and self-transcendence might imply an anatomical basis for the increased religiosity often reported by ayahuasca users. Overall, Bouso’s studies suggest that regular, long-term ayahuasca use in religious contexts benefits brain health, though these findings may not necessarily apply to a secular or psychiatric use. The general abstinence from other drugs among ayahuasca church members may support the cognitive benefits attributed to ritual use.

Another analysis of the same MRI study tested the hypothesis that regular ayahuasca use would lead to thickening of fiber tracts in the corpus callosum, the bundle connecting the cerebral hemispheres [ 264 ]. Results showed thickening in the isthmus of the corpus callosum, correlating with ayahuasca use frequency, although these findings did not hold after multiple testing corrections. The implicated callosal regions are positioned to mediate increased interhemispheric connectivity between motor and somatosensory regions [ 265 ]. Obtaining such an effect might be beneficial for motor function, various neurodegenerative disorders, e.g. amyotrophic lateral sclerosis (ALS), and for stroke rehabilitation [ 265 , 266 ].

A more recent cross-sectional structural MRI study assessed morphometric similarity (MS), an approach whereby anatomical connectivity is analyzed by considering multiple brain structural features (e.g. grey matter volume, and cortical curvature and thickness) [ 267 ], in 24 frequent ayahuasca users from the Santo Daime church and 24 matched controls [ 268 ]. The ayahuasca group showed overall reduced MS compared to controls, with lower MS in sensorimotor cortices (inferior frontal gyrus, precuneus, pre and post central gyrus) and higher MS in the orbitofrontal, entorhinal, cingulate, and anterior insular cortices. Lower MS indicates decreased anatomical connectivity between a region and the rest of the cortex [ 268 ]. The findings of increased MS in the ACC align with an earlier MRI study showing thinning [ 263 ]. MS analysis with the seven RSNs defined by Yeo and colleagues [ 223 ] revealed reduced MS in the sensorimotor, dorsal attention, and default mode networks for the ayahuasca group, with increased MS in the limbic network. Additional correlations with gene expression maps in the ayahuasca group revealed 18 genes relevant to DMT or ayahuasca effects (with either positive or negative weightings) on MS findings. Notably, 5-HT 2A receptor gene downregulation in sensorimotor cortices correlated with lower MS, suggesting that repeated ayahuasca use may lead to sustained downregulation and desensitization, similar to LSD tolerance [ 269 ]. Since ayahuasca or DMT do not seem to evoke rapid tolerance [ 62 ], it is questionable if such 5-HT 2A receptor downregulation could mediate tolerance. Earlier neuropsychology studies showed that regular ayahuasca users had better integrity of executive functions than less experienced users [ 270 ], which might relate to 5-HT 2A receptor desensitization or downregulation, a matter for future PET studies.

Pharmacological models alone may not fully explain the anatomic/functional associations observed in ayahuasca studies. For example, religiosity in Christian church members showed associations with a widespread pattern of greater cortical thickness [ 271 ], compared to the more diverse findings of cortical thickness changes in ayahuasca users. The cross-sectional studies of Santo Daime church members, who abstain from other drugs, provide a unique opportunity to study repeated ayahuasca use. However, these cross-sectional studies cannot infer causality. Larger, longitudinal studies are needed to confirm the structural and functional brain changes linked to ayahuasca use.

Conclusions and future directions

With this narrative review and synthesis, we summarize the current state of research with DMT, β -carbolines, and ayahuasca. While DMT is the main psychedelic constituent, the diverse β -carboline alkaloids in ayahuasca contribute to its unique (adverse) effects, creating an entourage effect that distinguishes it from synthetic formulations. The combination of DMT with MAO inhibitors enhances its bioavailability and duration and offers alternatives to inhaled or injectable routes of administration, which lead to short but intense DMT experiences. We emphasize the need to distinguish between a reductionist view of ayahuasca as a mixture of chemical substances and its full context as a cultural practice, often affiliated with traditional and syncretic religions. The findings presented herein mostly fall within the broad field of neurobiology, and do not adequately accommodate the cultural and botanical knowledge associated with indigenous usage of ayahuasca for therapeutic and ritualistic purposes.

Current understanding does not definitively implicate a singular molecular target that could explain the subjective effects of DMT or ayahuasca. Key candidates include several serotonin receptor subtypes (5-HT 1A/2A/2C and potentially others), an indirect influence on dopamine transmission due to β- carbolines, and potential roles of TrkB and sigma-1 receptors. Better qualifying the importance of 5-HT 2A receptor activation by DMT (alone or in combination with MAOIs) shall call for dedicated pre-clinical and clinical molecular imaging studies.

Neuroimaging and EEG studies have consistently shown reductions in alpha frequency power and increased signal complexity after ayahuasca or DMT administration. These findings are in line with brain models of decreased top–down regulation and enhanced neural communication during the psychedelic state. Functional neuroimaging studies have revealed changes in brain network dynamics, such as increased connectivity between the salience and default mode networks, and activations of brain areas associated with processing of emotions and autobiographical memories. Understanding these mechanisms is crucial for developing targeted therapeutic applications. The preponderance of imaging studies and clinical studies have been exploratory with open-label designs. There is a pressing need for larger-scale, controlled clinical trials to establish the dose-dependence and persistence of long-term therapeutic benefits and neurobiological effects induced by ayahuasca or DMT. Such studies should integrate clinical scoring with advanced imaging methods. We also see a need for comparative studies with other classical psychedelics, aiming to understand better the neurobiological basis of their differing phenomenology. Promising findings that DMT and ayahuasca evoke neuroplastic effects call for consolidation with comparable results seen with other psychedelic compounds. The bulk of such research has hitherto entailed studies in vitro and in preclinical research, without translation to the human clinical context. Multimodal neuroimaging techniques such as diffusion tensor imaging (DTI) could serve to investigate changes in white matter tracts in conjunction with MRS to follow changes in specific neurometabolites acutely or over time [ 272 ]. Recent advances in neuroimaging data processing, e.g. the development of a modality-overarching neuroimaging data structure [ 273 ], standardization of fMRI preprocessing pipelines [ 274 ], and the development of sophisticated computational approaches should enable streamlining and standardization of neuroimaging results to facilitate easier interpretation between studies.

Additionally, molecular imaging studies, including PET, are essential to further explore receptor occupancy and neuroplasticity mechanisms in vivo. Neuroplasticity in response to ayahuasca or its constituents might be amenable to investigation by PET with a ligand for synaptic vesicle protein 2A (SV2A), as shown autoradiographically for the case of psilocybin in experimental animals [ 275 ]. PET studies with the serotonin 5-HT 2A/2C receptor agonist radioligand [ 11 C]Cimbi-36 [ 276 ] (i.e., the psychedelic phenylethylamine generally known as 25B-NBOMe [ 277 ]) may be better suited than antagonist radioligands for establishing competition from the exogenous agonist DMT in vivo, as is the case for dopamine D 2/3 receptors [ 278 ]. Similarly, an agonist PET ligand for 5-HT 1A receptors might serve to detect occupancy by DMT at this receptor in human brain. As noted above, the complex alkaloid composition of ayahuasca calls for consideration of the entourage effect, a concept originally known from cannabis research [ 67 ], and indeed in consideration of the polypharmacology of tobacco smoke, which evokes inhibition of MAO-A in human organs to [ 11 C]clorgyline PET [ 279 ]. There were no effects in a pilot study of low dose harmine/DMT on energy metabolism in rat brain to [ 18 F]FDG PET [ 103 ], but we are currently undertaking human [ 18 F]FDG PET studies of pharmahuasca. Results of this ongoing neuroenergetics study could prove informative regarding the interpretation of the extensive fMRI/EEG literature on ayahuasca reviewed above.

In conclusion, the therapeutic potential of ayahuasca constituents to promote neuroplasticity and treat neuropsychiatric disorders, including depression, addiction, and PTSD, is gaining empirical support. Additionally, early evidence suggests a potential role of DMT in the treatment of acute brain injury such as ischemic stroke, which opens promising paths for future pharmacotherapeutic developments. Standardized formulations of DMT and harmala alkaloids present certain advantages for clinical investigations and basic research into the molecular pathways and mechanisms of action by offering more predictable pharmacokinetic and pharmacodynamic profiles, as well as better control of potential adverse effects, compared with botanical ayahuasca preparations. In addition to the molecular and neurophysiological perspective, we note the importance of processes of psychological change, alongside clinical and contextual factors such as supportive set and setting. While extending beyond this review’s original scope, we hold that such considerations are essential for obtaining a comprehensive understanding of the therapeutic potential of ayahuasca.

Data availability

Not applicable.

DMT is also present in a hallucinogenic snuff (known as yopo) derived from seeds of the South American trees Anadenanthera peregrina or A. columbina , along with the psychoactive tryptamines 5-methoxy-DMT (5-MeO-DMT) and 5-hydroxy-DMT (bufotenin) [ 280 ].

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Egger, K., Aicher, H.D., Cumming, P. et al. Neurobiological research on N,N -dimethyltryptamine (DMT) and its potentiation by monoamine oxidase (MAO) inhibition: from ayahuasca to synthetic combinations of DMT and MAO inhibitors. Cell. Mol. Life Sci. 81 , 395 (2024). https://doi.org/10.1007/s00018-024-05353-6

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ORIGINAL RESEARCH article

Evolution and emerging trends in depression research from 2004 to 2019: a literature visualization analysis.

• 1 School of Traditional Chinese Medicine, Beijing University of Chinese Medicine, Beijing, China
• 2 School of Life Sciences, Beijing University of Chinese Medicine, Beijing, China

Depression has become a major threat to human health, and researchers around the world are actively engaged in research on depression. In order to promote closer research, the study of the global depression knowledge map is significant. This study aims to map the knowledge map of depression research and show the current research distribution, hotspots, frontiers, and trends in the field of depression research, providing researchers with worthwhile information and ideas. Based on the Web of Science core collection of depression research from 2004 to 2019, this study systematically analyzed the country, journal, category, author, institution, cited article, and keyword aspects using bibliometric and data visualization methods. A relationship network of depression research was established, highlighting the highly influential countries, journals, categories, authors, institutions, cited articles, and keywords in this research field. The study identifies great research potential in the field of depression, provides scientific guidance for researchers to find potential collaborations through collaboration networks and coexistence networks, and systematically and accurately presents the hotspots, frontiers, and shortcomings of depression research through the knowledge map of global research on depression with the help of information analysis and fusion methods, which provides valuable information for researchers and institutions to determine meaningful research directions.

Introduction

Health issues are becoming more and more important to people due to the continuous development of health care. The social pressures on people are becoming more and more pronounced in a social environment that is developing at an increasing rate. Prolonged exposure to stress can have a negative impact on brain development ( 1 ), and depression is one of the more typical disorders that accompany it. Stress will increase the incidence of depression ( 2 ), depression has become a common disease ( 3 ), endangering people's physical health. Depression is a debilitating mental illness with mood disorders, also known as major depression, clinical depression, or melancholia. In human studies of the disease, it has been found that depression accounts for a large proportion of the affected population. According to the latest data from the World Health Organization (WHO) statistics in 2019, there are more than 350 million people with depression worldwide, with an increase of about 18% in the last decade and an estimated lifetime prevalence of 15% ( 4 ), it is a major cause of global disability and disease burden ( 5 ), and depression has quietly become a disease that threatens hundreds of millions of people worldwide.

Along with the rise of science communication research, the quantification of science is also flourishing. As a combination of “data science” and modern science, bibliometrics takes advantage of the explosive growth of research output in the era of big data, and uses topics, authors, publications, keywords, references, citations, etc. as research targets to reveal the current status and impact of the discipline more accurately and scientifically. Whereas, there is not a wealth of bibliometric studies related to depression. Fusar-Poli et al. ( 6 ) used bibliometrics to systematically evaluate cross-diagnostic psychiatry. Hammarström et al. ( 7 ) used bibliometrics to analyze the scientific quality of gender-related explanatory models of depression in the medical database PubMed. Tran et al. ( 8 ) used the bibliometric analysis of research progress and effective interventions for depression in AIDS patients. Wang et al. ( 9 ) used bibliometric methods to analyze scientific studies on the comorbidity of pain and depression. Shi et al. ( 10 ) performed a bibliometric analysis of the top 100 cited articles on biomarkers in the field of depression. Dongping et al. ( 11 ) used bibliometric analysis of studies on the association between depression and gut flora. An Chunping et al. ( 12 ) analyzed the literature on acupuncture for depression included in PubMed based on bibliometrics. Yi and Xiaoli ( 13 ) used a bibliometric method to analyze the characteristics of the literature on the treatment of depression by Chinese medicine in the last 10 years. Zhou and Yan ( 14 ) used bibliometric method to analyze the distribution of scientific and technological achievements on depression in Peoples R China. Guaijuan ( 15 ) performed a bibliometric analysis of the interrelationship between psoriasis and depression. Econometric analysis of the relationship between vitamin D deficiency and depression was performed by Yunzhi et al. ( 16 ) and Shauni et al. ( 17 ) performed a bibliometric analysis of domestic and international research papers on depression-related genes from 2003 to 2007. A previous review of depression-related bibliometric studies revealed that there is no bibliometric analysis of global studies in the field of depression, including country network analysis, journal network analysis, category network analysis, author network analysis, institutional network analysis, literature co-citation analysis, keyword co-presentation analysis, and cluster analysis.

The aim of this study was to conduct a comprehensive and systematic literature-based data mining and metrics analysis of depression-related research. More specifically, this analysis focuses on cooperative network and co-presentation analysis, based on the 36,477 papers included in the Web of Science Core Collection database from 2004 to 2019, and provides an in-depth analysis of cooperative network, co-presentation network, and co-citation through modern metrics and data visualization methods. Through the mining of key data, the data correlation is further explored, and the results obtained can be used to scientifically and reasonably predict the depression-related information. This study aims to show the spatial and temporal distribution of research countries, journals, authors, and institutions in the field of depression in a more concise manner through a relational network. A deeper understanding of the internal structure of the research community will help researchers and institutions to establish more accurate and effective global collaborations, in line with the trend of human destiny and globalization. In addition, the study will allow for the timely identification of gaps in current research. A more targeted research direction will be established, a more complete picture of the new developments in the field of depression today will be obtained, and the research protocol will be informed for further adjustments. The results of these analyses will help researchers understand the evolution of this field of study. Overall, this paper uses literature data analysis to find research hotspots in the field of depression, analyze the knowledge structure within different studies, and provide a basis for predicting research frontiers. This study analyzed the literature in the field of depression using CiteSpace 5.8.R2 (64-bit) to analyze collaborative networks, including country network analysis, journal network analysis, category network analysis, researcher network analysis, and institutional network analysis using CiteSpace 5.8.R2 (64-bit). In addition, literature co-citation, keyword co-presentation, and cluster analysis of depression research hotspots were also performed. Thus, exploring the knowledge dimensions of the field, quantifying the research patterns in the field, and uncovering emerging trends in the field will help to obtain more accurate and complete information. The large amount of current research results related to depression will be presented more intuitively and accurately with the medium of information technology, and the scientific evaluation of research themes and trend prediction will be provided from a new perspective.

Data Sources

The data in this paper comes from the Web of Science (WoS) core collection. The time years were selected as 2004–2019. First, the literature was retrieved after entering “depression” using the title search method. A total of 73,829 articles, excluding “depression” as “suppression,” “decline,” “sunken,” “pothole,” “slump,” “low pressure,” “frustration.” The total number of articles with other meanings such as “depression” was 5,606, and the total number of valid articles related to depression was 68,223. Next, the title search method was used to search for studies related to “major depressive disorder” not “depression,” and a total of 8,070 articles were retrieved. For the two search strategies, a total of 76,293 records were collected. The relevant literature retrieved under the two methods were combined and exported in “plain text” file format. The exported records included: “full records and references cited.” CiteSpace processed the data to obtain 41,408 valid records, covering all depression-related research articles for the period 2004–2019, and used this as the basis for analysis.

Processing Tools

CiteSpace ( 18 ), developed by Chao-Mei Chen, a professor in the School of Information Science and Technology at Drexel University, is a Java-based program with powerful data visualization capabilities and is one of the most widely used knowledge mapping tools. The software version used in this study is CiteSpace 5.8.R2 (64-bit).

Methods of Analysis

This study uses bibliometrics and data visualization as analytical methods. First, the application of bibliometrics to the field of depression helped to identify established and emerging research clusters, demonstrating the value of research in this area. Second, data visualization provides multiple perspectives on the data, presenting correlations in a clearer “knowledge graph” that can reveal underestimated and overlooked trends, patterns, and differences ( 19 ). CiteSpace is mainly based on the “co-occurrence clustering idea,” which extracts the information units (keywords, authors, institutions, countries, journals, etc.) in the data by classification, and then further reconstructs the data in the information units to form networks based on different types and strengths of connections (e.g., keyword co-occurrence, author collaboration, etc.). The resulting networks include nodes and links, where the nodes represent the information units of the literature and the links represent the existence of connections (co-occurrence) between the nodes. Finally, the network is measured, statistically analyzed, and presented in a visual way. The analysis needs to focus on: the overall structure of the network, key nodes and paths. The key evaluation indicators in this study are: betweenness centrality, year, keyword frequency, and burst strength. Betweenness centrality (BC) is the number of times a node acts as the shortest bridge between two other nodes. The higher the number of times a node acts as an “intermediary,” the greater its betweenness centrality. Betweenness centrality is a measure of the importance of articles found and measured by nodes in the network by labeling the category (or authors, journals, institutions, etc.) with purple circles. There may be many shortest paths between two nodes in the network, and by counting all the shortest paths of any two nodes in the network, if many of the shortest paths pass through a node, then the node is considered to have high betweenness centrality. In CiteSpace, nodes with betweenness centrality over 0.1 are called critical nodes. Year, which represents the publication time of the article. Frequency, which represents the number of occurrences. Burst strength, an indicator used to measure articles with sudden rise or sudden decline in citations. Nodes with high burst strength usually represent a shift in a certain research area and need to be focused on, and the burst article points are indicated in red. The nodes and their sizes and colors are first analyzed initially, and further analyzed by betweenness centrality indicators for evaluation. Each node represents an article, and the larger the node, the greater the frequency of the keyword word and the greater the relevance to the topic. Similarly, the color of the node represents time: the warmer the color, the more recent the time; the colder the color, the older the era; the node with a purple outer ring is a node with high betweenness centrality; the color of each annual ring can determine the time distribution: the color of the annual ring represents the corresponding time, and the thickness of one annual ring is proportional to the number of articles within the corresponding time division; the dominant color can reflect the relative concentration of the emergence time; the node The appearance of red annual rings in the annual rings means hot spots, and the frequency of citations has been or is still increasing rapidly.

Large-Scale Assessment

Country analysis.

During the period 2004–2019, a total of 157 countries/territories have conducted research on depression, which is about 67.38% of 233 countries/territories worldwide. This shows that depression is receiving attention from many countries/regions around the world. Figure 1 shows the geographical distribution of published articles for 157 countries. The top 15 countries are ranked according to the number of articles published. Table 1 lists the top 15 countries with the highest number of publications in the field of depression worldwide from 2004 to 2019. These 15 countries include 4 Asian countries (Peoples R China, Japan, South Korea, Turkey), 2 North American countries (USA, Canada), 1 South American country (Brazil), 7 European countries (UK, Germany, Netherlands, Italy, France, Spain, Sweden), and 1 Oceania country (Australia).

Figure 1 . Geographical distributions of publications, 2004–2019.

Table 1 . The top 15 productive countries.

Overall, the main distribution of these articles is in USA and some European countries, such as UK, Germany, Netherlands, Italy, France, Spain, and Sweden. This means that these countries are more interested and focused on research on depression compared to others. The total number of publications across all research areas in the Web of Science core collection is similar to the distribution of depression research areas, with the trend toward USA, UK, and Peoples R China as leading countries being unmistakable, and USA has been a leader in the field of depression, with far more articles published than any other country. It can also be seen that USA is the country with the highest betweenness centrality in the network of national collaborations analyzed in this paper. USA research in the field of depression is closely linked to global research, and is an important part of the global collaborative network for depression research. As of 2019, the total number of articles published in depression performance research in USA represents 27.13% of the total number of articles published in depression worldwide, which is ~4 times more than the second-place country, UK, which is far ahead of other countries. Peoples R China, as the third most published country, has a dominant number of articles, but its betweenness centrality is 0.01, reflecting the fact that Peoples R China has less collaborative research with other countries, so Peoples R China should strengthen its foreign collaborative research and actively establish global scientific research partnerships to seek development and generate breakthroughs in cooperation. The average percentage of scientific research on depression in each country is about 0.19%, also highlighting the urgent need to address depression as one of the global human health problems. The four Asian countries included in the top 15 countries are Peoples R China, Japan, South Korea, and Turkey, with Peoples R China ranking third with 6.72% of the total number of all articles counted. The distribution may be explained by the fact that Peoples R China is the largest developing country with a rapid development rate as the largest. Along with the steady rise in the country's economic power, people are creating economic benefits and their health is becoming a consumable commodity. The lifetime prevalence and duration of depression varies by country and region ( 2 ), but the high prevalence and persistence of depression worldwide confirms the increasing severity of the disease worldwide. The WHO estimates that more than 300 million people, or 4.4% of the world's population, suffer from depression ( 20 ), with the number of people suffering from depression increasing at a patient rate of 18.4% between 2005 and 2015. Depression, one of the most prevalent mental illnesses of our time, has caused both physical and psychological harm to many people, and it has become the leading cause of disability worldwide today, and in this context, there is increased interest and focus on research into depression. It is expected that a more comprehensive understanding of depression and finding ways to prevent and cope with the occurrence of this disease can help people get rid of the pain and shadow brought by depression, obtain a healthy and comfortable physical and mental environment and physical health, and make Chinese contributions to the cause of human health. Undoubtedly, the occurrence of depressive illnesses in the context of irreversible human social development has stimulated a vigorous scientific research environment on depression in Peoples R China and other developing countries and contributed to the improvement of research capacity in these countries. Moreover, from a different perspective, the geographical distribution of articles in this field also represents the fundamental position of the country in the overall scientific and academic research field.

Growth Trend Analysis

Figure 2 depicts the distribution of 38,433 articles from the top 10 countries in terms of the number of publications and the trend of growth during 2004–2019.

Figure 2 . The distribution of publications in top 10 productive countries, 2004–2019. Source: author's calculation. National development classification criteria refer to “Human Development Report 2020” ( 21 ).

First, the number of articles published per year for the top 10 countries in terms of productivity was counted and then the white bar chart in Figure 2 was plotted, with the year as the horizontal coordinate and total publications as the vertical coordinate, showing the distribution of the productivity of articles in the field of depression per year. The total number of publications for the period 2004–2019 is 38,433. Based on the white bars and line graphs in Figure 2 , we can divide this time period into three growth periods. The number of publications in each growth period is calculated based on the number of publications per year. As can be seen from the figure, the period 2004–2019 can be divided into three main growth periods, namely 2004–2009, 2010–2012, and 2013–2019, the first growth period being from 2004 to 2009, the number of publications totaled 6,749, accounting for 23.97% of all publications; from 2010 to 2012, the number of publications totaled 8,236, accounting for 17.56% of all publications; and from 2013 to 2019, the number of publications totaled 22,473, accounting for 58.47% of all publications. Of these, 2006 was the first year of sharp growth with an annual growth rate of 19.97%, 2009 was the second year of sharp growth with an annual growth rate of 17.64%, and 2008 was the third year of sharp growth with an annual growth rate of 16.09%. In the last 5 years, 2019 has also shown a sharp growth trend with a growth rate of 14.34%. Notably, in 2010 and 2013, there was negative growth with the growth rate of −3.39 and −1.45%. In the last 10 years, depression research has become one of the most valuable areas of human research. It can also be noted that the number of publications in the field of depression in these 10 countries has been increasing year after year.

Second, the analysis is conducted from the perspective of national development, divided into developed and developing countries, as shown in the orange bar chart in Figure 2 , where the horizontal coordinate is year and the vertical coordinate is total publications, comparing the article productivity variability between developed and developing countries. The top 10 most productive countries in the field of depression globally include nine developed countries and one developing country, respectively. During the period 2004–2019, 34,631 papers were published in developed countries and 3,802 papers were published in developing countries, with developed countries accounting for 90.11% of the 38,433 articles and developing countries accounting for 9.89%, and the total number of publications in developed countries was about 9 times higher than that in developing countries. During the period 2004–2019, the number of publications in developed countries showed negative growth in 2 years (2010 and 2013) with growth rates of −3.39 and −1.45%, respectively. The rest of the years showed positive growth with growth rates of 1.52% (2005), 19.97 (2006), 8.11 (2007), 12.70 (2008), 17.64 (2009), 13.22 (2011), 10.17 (2012), 16.09 (2014), 10.46 (2015), 4.10 (2016), 1.59 (2017), 3.91 (2018), and 14.34 (2019), showing three periods of positive growth: 2004–2009, 2011–2012, and 2014–2019, with the highest growth rate of 19.97% in 2006. Recent years have also shown a higher growth trend, with a growth rate of 14.34% in 2019. It is worth noting that developing countries have been showing positive growth in the number of articles in the period 2004–2019, with annual growth rates of 81.25 (2005), 17.24 (2006), 35.29 (2007), 19.57 (2008), 65.45 (2009), 13.19 (2010), 29.13 (2011), 54.89 (2012), 12.14 (2013), 36.36 (2014), 14.92 (2015), 16.02 (2016), 10.24 (2017), 21.17 (2018), and 31.37 (2019), with the highest growth rate of 81.25% in 2005. In the field of depression research, developed countries are still the main force and occupy an important position.

Further, 10 countries with the highest productivity in the field of depression are compared, total publications in the vertical coordinate, and the colored scatter plot contains 10 colored dots, representing 10 different countries. On the one hand, the variability of the contributions of different countries in the same time frame can be compared horizontally. On the other hand, it is possible to compare vertically the variability of the growth of different countries over time. Among them, USA, with about 40.29% of the world's publications in the field of depression, has always been a leader in the field of depression with its rich research results. Peoples R China, as the only developing country, ranks 3rd in the top 10 countries with high production of research papers in the field of depression, and Peoples R China's research in the field of depression has shown a rapid growth trend, and by 2016, it has jumped to become the 2nd largest country in the world, with the number of published papers increasing year by year, which has a broad prospect and great potential for development.

Distribution of Periodicals

Table 2 lists the top 15 journals in order of number of journal co-citations. In the field of depression, the top 15 cited journals accounted for 19.06% of the total number of co-citations, nearly one in five of the total number of journal co-citations. In particular, the top 3 journals were ARCH GEN PSYCHIAT (ARCHIVES OF GENERAL PSYCHIATRY), J AFFECT DISORDERS (JOURNAL OF AFFECTIVE DISORDERS), and AM J PSYCHIAT (AMERICAN JOURNAL OF PSYCHIATRY), with co-citation counts of 20,499, 20,302, and 20,143, with co-citation rates of 2.09, 2.07, and 2.06%, respectively. The main research area of ARCH GEN PSYCHIAT is Psychiatry; the main research area of the journal J AFFECT DISORDERS is Neurosciences and Neurology, Psychiatry; AM J PSYCHIAT is the main research area of Psychiatry, and the three journals have “psychiatry” in common, making them the most frequently co-cited journals in the field of depression.

Table 2 . The top 15 co-cited journals.

Figure 3 shows the network relationship graph of the cited journals from 2004 to 2019. The figure takes g-index as the selection criteria, the scale factor k = 25 to include more nodes. Each node of the graph represents each journal, the node size represents the number of citation frequencies, the label size represents the size of the betweenness centrality of the journal in the network, and the links between journals represent the co-citation relationships. The journal co-citation map reflects the structure of the journals, indicating that there are links between journals and that the journals include similar research topics. These journals included research topics related to neuroscience, psychiatry, neurology, and psychology. The journal with betweenness centrality size in the top 1 was ARCH GEN PSYCHIAT, with betweenness centrality size of 0.07, and impact shadows of 14.48. ARCH GEN PSYCHIAT, has research themes of Psychiatry. In all, these journals in Figure 3 occupy an important position in the journal's co-citation network and have strong links with other journals.

Figure 3 . Prominent journals involved in depression. The betweenness centrality of a node in the network measures the importance of the position of the node in the network. Two types of nodes may have high betweenness centrality scores: (1) Nodes that are highly connected to other nodes, (2) Nodes are positioned between different groups of nodes. The lines represent the link between two different nodes.

Distribution of Categories

Table 3 lists the 15 most popular categories in the field of depression research during the period 2004–2019. In general, the main disciplines involved are neuroscience, psychology, pharmacy, medicine, and health care, which are closely related to human life and health issues. Of these, psychiatry accounted for 20.78%, or about one-five, making it the most researched category. The study of depression focuses on neuroscience, reflecting the essential characteristics of depression as a category of mental illness and better reflecting the fact that depression is an important link in the human public health care. In addition, Table 3 shows that the category with the highest betweenness centrality is Neuroscience, followed by Public, Environment & Occupational Health, and then Pharmacology & Pharmacy, with betweenness centrality of 0.16, 0.13, and 0.11, respectively. It is found that the research categories of depression are also centered on disciplines such as neuroscience, public health and pharmacology, indicating that research on depression requires a high degree of integration of multidisciplinary knowledge and integration of information from various disciplines in order to have a more comprehensive and in-depth understanding of the depression.

Table 3 . The top 15 productive categories, 2004–2019.

Figure 4 shows the nine categories with the betweenness centrality in the category research network, with Neuroscience being the node with the highest betweenness centrality in this network, meaning that Neuroscience is most strongly linked to all research categories in the field of depression research. Depression is a debilitating psychiatric disorder with mood disorders. It is worth noting that the development of depression not only has psychological effects on humans, but also triggers many somatic symptoms that have a bad impact on their daily work and life, giving rise to the second major mediating central point of research with public health as its theme. The somatization symptoms of depression often manifest as abnormalities in the cardiovascular system, and many studies have looked at the pathology of the cardiovascular system in the hope of finding factors that influence the onset of depression, mechanisms that trigger it or new ways to treat it. Thus, depression involves not only the nervous system, but also interacts with the human cardiovascular system, for example, and the complexity of depression dictates that the study of depression is an in-depth study based on complex systems.

Figure 4 . Prominent categories involved in depression, 2004–2019. The betweenness centrality of a node in the network measures the importance of the position of the node in the network. Two types of nodes may have high betweenness centrality scores: (1) Nodes that are highly connected to other nodes, (2) Nodes are positioned between different groups of nodes. The lines represent the link between two different nodes.

Author Statistics

The results of the analysis showed that there were many researchers working in the field of depression over the past 16 years, and 63 of the authors published at least 30 articles related to depression. Table 4 lists the 15 authors with the highest number of articles published. It includes the rank of the number of articles published, author, country, number of articles published in depression-related studies, total number of articles included in Web of Science, total number of citations, average number of citations, and H-index. According to the statistics, seven of the top 15 authors are from USA, three from the Netherlands, one from Canada, one from Australia, one from New Zealand, one from Italy, and one from Germany. From this, it can be seen that these productive authors are from developed countries, thus it can be inferred that developed countries have a better research environment, more advanced research technology and more abundant research funding. The evaluation indicators in the author co-occurrence network are frequency, betweenness centrality and time of first appearance. The higher the frequency, i.e., the higher the number of collaborative publications, the more collaboration, the higher the information dissemination rate, the three authors with the highest frequency in this author co-occurrence network are MAURIZIO FAVA, BRENDA W. J. H. PENNINX, MADHUKAR H. TRIVEDI; the higher the betweenness centrality, i.e., the closer the relationship with other authors, the more collaboration, the higher the information dissemination rate, the three authors with the highest betweenness centrality are the three authors with the highest betweenness centrality are MICHAEL E. THASE, A. JOHN RUSH; the time of first appearance, i.e., the longer the influence generated by the author's research, the higher the information dissemination rate; in addition, the impact factor and citations can also reflect the information dissemination efficiency of the authors.

Table 4 . The top 15 authors in network of co-authorship, 2004–2019.

The timezone view ( Figure 5 ) in the author co-occurrence network clearly shows the updates and interactions of author collaborations, for example. All nodes are positioned in a two-dimensional coordinate with the horizontal axis of time, and according to the time of first posting, the nodes are set in different time zones, and their positions are sequentially upward with the time axis, showing a left-to-right, bottom-up knowledge evolution diagram. The time period 2004–2019 is divided into 16 time zones, one for each year, and each circle in the figure represents an author, and the time zone in which the circle appears is the year when the author first published an article in the data set of this study. The closer the color, the warmer the color, the closer the time, the colder the color, the older the era, the thickness of an annual circle, and the number of articles within the corresponding time division is proportional, the dominant color can reflect the relative concentration of the emergence time, the nodes appear in the annual circle of the red annual circle, that is, on behalf of the hot spot, the frequency of being cited was or is still increasing sharply. Nodes with purple outer circles are nodes with high betweenness centrality. The time zone view demonstrates the growth of author collaboration in the field, and it can be found from the graph that the number of author collaborations increases over time, and the frequency of publications in the author collaboration network is high; observe that the thickness of the warm annual rings in the graph is much greater than the thickness of the cold annual rings, which represents the increase of collaboration in time; there are many authors in all time zones, which indicates that there are many research collaborations and achievements in the field, and the field is in a period of collaborative prosperity. The linkage relationship between the sub-time-periods can be seen by the linkage relationship between the time periods, and it can be found from the figure that there are many linkages in the field in all time periods, which indicates that the author collaboration in the field of depression research is strong.

Figure 5 . Timezone view of the author's co-existing network in depression, 2004–2019. The circle represents the author, the time zone in which the circle appears is the year in which the author first published in this study dataset, the radius of the circle represents the frequency of appearance, the color represents the different posting times, the lines represent the connections between authors, and the time zone diagram shows the evolution of author collaboration.

Institutional Statistics

Table 5 lists the top 15 research institutions in network of co-authors' institutions. These include 10 American research institutions, two Netherlands research institutions, one UK research institution, one Canadian research institution and one Australian research institution, all of which, according to the statistics, are from developed countries. Of these influential research institutions, 66.7% are from USA. Figure 6 shows the collaborative network with these influential research institutions as nodes. Kings Coll London (0.2), Univ Michigan (0.17), Univ Toronto (0.15), Stanford Univ (0.14), Univ Penn (0.14), Univ Pittsburgh (0.14), Univ Melbourne (0.12), Virginia Commonwealth Univ (0.12), Columbia Univ (0.1), Duke Univ (0.1), Massachusetts Gen Hosp (0.1), Vrije Univ Amsterdam (0.1), with betweenness centrality >0.1. Kings Coll London has a central place in this collaborative network and is influential in the field of depression research. Table 6 lists the 15 institutions with the strong burst strength. The top 3 institutions are all from USA. Univ Copenhagen, Univ Illinois, Harvard Med Sch, Boston Univ, Univ Adelaide, Heidelberg Univ, Univ New South Wales, and Icahn Sch Med Mt Sinai have had strong burst strength in recent years. It suggests that these institutions may have made a greater contribution to the field of depression over the course of this year and more attention could be paid to their research.

Table 5 . The top 15 institutions in network of co-authors' institutions, 2004–2019.

Figure 6 . Prominent institutions involved in depression, 2004–2019. The betweenness centrality of a node in the network measures the importance of the position of the node in the network. Two types of nodes may have high betweenness centrality scores: (1) Nodes that are highly connected to other nodes, (2) Nodes are positioned between different groups of nodes. The lines represent the link between two different nodes.

Table 6 . The top 15 institutions with the strongest citation bursts, 2004–2019.

Summing up the above analysis, it can be seen that the research institutions in USA are at the center of the depression research field, are at the top of the world in terms of quantity and quality of research, and are showing continuous growth in vitality. Research institutions in USA, as pioneers among all research institutions, lead and drive the development of depression research and play an important role in cutting-edge research in the field of depression.

Article Citations

Table 7 lists the 16 articles that have been cited more than 1,000 times within the statistical range of this paper from 2004 to 2019. As can be seen from the table, the most cited article was written by Dowlati et al. from Canada and published in BIOLOGICAL PSYCHIATRY 2010, which was cited 2,556 times. In addition, 11 of these 16 highly cited articles were from the USA. Notably, two articles by Kroenke, K as first author appear in this list, ranked 7th and 11th, respectively. In addition, there are three articles from Canada, one article from Switzerland, and one article from the UK. And interestingly, all of these countries are developed countries. It can be reflected that developed countries have ample research experience and high quality of research in the field of depression research. On the other hand, it also reflects that depression is a key concern in developed countries. These highly cited articles provide useful information to many researchers and are of high academic and exploratory value.

Table 7 . The top 15 frequency cited articles, 2004–2019.

Research Hotspots Ang Frontiers

Keyword analysis.

The keyword analysis of depression yielded the 25 most frequent keywords in Table 8 and the keyword co-occurrence network in Figure 7 . Also, the data from this study were detected by burst, the 25 keywords with the strongest burst strength were obtained in Table 9 . These results bring out the popular and cutting-edge research directions in the field clearly.

Table 8 . Top 25 frequent keywords in the period of 2004–2019.

Figure 7 . Keyword co-occurrence network in depression, 2004–2019.

Table 9 . Top 25 keywords with strongest citation bursts in the period of 2004–2019.

The articles on depression during 2004–2019 were analyzed in 1-year time slices, and the top 25 keywords with the highest frequency of occurrence were selected from each slice to obtain the keyword network shown in Table 8 . The top 25 keywords with the highest frequencies were: symptom, disorder, major depression, prevalence, meta-analysis, anxiety, risk, scale, association, quality of life, health, risk factor, stress, validity, validation, mental health, women, double blind, brain, population, disease, impact, primary care, mood, and efficacy. High-frequency nodes respond to popular keywords and are an important basis for the field of depression research.

Figure 7 shows the co-occurrence network mapping of keywords regarding depression research. Each circle in the figure is a node representing a keyword, and the greater the betweenness centrality, the more critical the position of the node in the network. The top 10 keywords in terms of betweenness centrality are: symptom (0.6), major depression (0.28), prevalence (0.27), disorder (0.25), double blind (0.18), risk factor (0.12), stress (0.11), children (0.1), schizophrenia (0.1), and expression (0.1). Nodes with high betweenness centrality reflect that the keyword forms a co-occurrence relationship with multiple other keywords in the domain. A higher betweenness centrality indicates that it is more related to other keywords, and therefore, the node plays an important role in the study. Relatively speaking, these nodes represent the main research directions in the field of depression; they are also the key research directions in this period, and to a certain extent, represent the research hotspots in this period.

Burst detection was performed on the keywords, and the 25 keywords with the strongest strength were extracted, as shown in Table 9 . These keywords contain: fluoxetine, community, follow up, illness, psychiatric disorder, dementia, trial, placebo, disability, serotonin reuptake inhibitor, myocardial infarction, hospital anxiety, antidepressant treatment, late life depression, United States, epidemiology, major depression, model, severity, adolescent, people, prefrontal cortex, management, meta-analysis, and expression. The keywords that burst earlier include fluoxetine (2004), community (2004), follow up (2004), illness (2004), and psychiatric disorder (2004), are keywords that imply that researchers focused on themes early in the field of depression. As researchers continue to explore, the study of depression is changing day by day, and the keywords that have burst in recent years are people (2015), prefrontal cortex (2016), management (2016), meta-analysis (2017), and expression (2017). Reflecting the fact that depression research in recent years has mainly focused on human subjects, the focus has been on the characterization of populations with depression onset. The relationship between depression and the brain has aroused the curiosity of researchers, what exactly are the causes that trigger depression and what are the effects of depression for the manifestation of depression have caused a wide range of discussions in the research community, and the topics related to it have become the most popular studies and have been the focus of research in recent years. All of these research areas showed considerable growth, indicating that research into this area is gaining traction, suggesting that it is becoming a future research priority. The keywords with the strongest burst strength are fluoxetine (111.2), community (110.08), antidepressant treatment (94.28), severity (88.35), meta-analysis (86.42), people (85.33), and follow up (84.46). The rapid growth of research based on these keywords indicates that these topics are the most promising and interesting. The keywords that has been around the longest burst are follow up (2004–2013), model (2013–2019), hospital anxiety (2008–2013), severity (2014–2019), and psychiatric disorder (2004–2008), researchers have invested a lot of research time in these research directions, making many research results, and responding to the exploratory value and significance of research on these topics. At the same time, the longer duration of burst also proves that these research directions have research potential and important value.

Research Hotspots

Hotspots must mainly have the characteristics of high frequency, high betweenness centrality, strong burst, and time of emergence can be used as secondary evaluation indicators. The higher the number of occurrences, the higher the degree of popularity and attention. The higher betweenness centrality means the greater the influence and the higher the importance. Nodes with strong burst usually represent key shift nodes and need to be focused on. The time can be dynamically adjusted according to the target time horizon of the analysis. Thus, based on the results of statistical analysis, it is clear that the research hotspots in the field of depression can be divided into four main areas: etiology (external factors, internal factors), impact (quality of life, disease symptoms, co-morbid symptoms), treatment (interventions, drug development, care modalities), and assessment (population, size, symptoms, duration of disease, morbidity, mortality, effectiveness).

Risk factors for depression include a family history of depression, early life abuse and neglect, and female sexuality and recent life stressors. Physical illnesses also increase the risk of depression, particularly increasing the prevalence associated with metabolic (e.g., cardiovascular disease) and autoimmune disorders.

Research on the etiology of depression can be divided into internal and external factors. In recent years, researchers have increasingly focused on the impact of external factors on depression. Depression is influenced by environmental factors related to social issues, such as childhood experiences, social interactions, and lifestyles. Adverse childhood experiences are risk factors for depression and anxiety in adolescence ( 37 ) and are a common pathway to depression in adults ( 38 ). Poor interpersonal relationships with classmates, family, teachers, and friends increase the prevalence of depression in adolescents ( 39 ). Related studies assessed three important, specific indicators of the self-esteem domain: social confidence, academic ability, and appearance ( 40 ). The results suggest that these three dimensions of self-esteem are key risk factors for increased depressive symptoms in Chinese adolescents. The vulnerability model ( 41 ) suggests that low self-esteem is a causal risk factor for depression, and low self-esteem is thought to be one of the main causes of the onset and progression of depression, with individuals who exhibit low self-esteem being more likely to develop social anxiety and social withdrawal, and thus having a sense of isolation ( 42 ), which in turn leads to subsequent depression. Loneliness predicts depression in adolescents. Individuals with high levels of loneliness experience more stress and tension from psychological and physical sources in their daily lives, which, combined with insufficient care from society, can lead to depression ( 43 ). A mechanism of association exists between life events and mood disorders, with negative life events being directly associated with depressive symptoms ( 44 ). In a cross-sectional study conducted in Shanghai, the prevalence of depression was higher among people who worked longer hours, and daily lifestyle greatly influenced the prevalence of depression ( 45 ). A number of studies in recent years have presented a number of interesting ideas, and they suggest that depression is related to different environmental factors, such as temperature, sunlight hours, and air pollution. Environmental factors have been associated with suicidal behavior. Traffic noise is a variable that triggers depression and is associated with personality disorders such as depression ( 46 ). The harmful effects of air pollution on mental health, inhalation of air pollutants can trigger neuroinflammation and oxidative stress and induce dopaminergic neurotoxicity. A study showed that depression was associated with an increase in ambient fine particulate matter (PM2.5) ( 47 ).

Increased inflammation is a feature of many diseases and even systemic disorders, such as some autoimmune diseases [e.g., type 1 diabetes ( 48 ) or rheumatoid arthritis ( 49 )] and infectious diseases [e.g., hepatitis and sepsis ( 50 )], are associated with an inflammatory response and have been found to increase the risk of depression. A growing body of evidence supports a bidirectional association between depression and inflammatory processes, with stressors and pathogens leading to excessive or prolonged inflammatory responses when combined with predisposing factors (e.g., childhood adversity and modifying factors such as obesity). The resulting illnesses (e.g., pain, sleep disorders), depressive symptoms, and negative health (e.g., poor diet, sedentary lifestyle) may act as mediating pathways leading to inflammation and depression. In terms of mechanistic pathways, cytokines induce depression by affecting different mood-related processes. Elevated inflammatory signals can dysregulate the metabolism of neurotransmitters, damaging neurons, and thus altering neural activity in the brain. In addition cytokines can modulate depression by regulating hormone levels. Inflammation can have different effects on different populations depending on individual physiology, and even lower levels of inflammation may have a depressive effect on vulnerable individuals. This may be due to lower parasympathetic activity, poorer sensitivity to glucocorticoid inhibitory feedback, a greater response to social threat in the anterior oral cortex or amygdala and a smaller hippocampus. Indeed, these are all factors associated with major depression that can affect the sensitivity to the inhibitory consequences of inflammatory stimuli.

Depression triggers many somatization symptoms, which can manifest as insomnia, menopausal syndrome, cardiovascular problems, pain, and other somatic symptoms. There is a link between sleep deprivation and depression, with insomnia being a trigger and maintenance of depression, and more severe insomnia and chronic symptoms predicting more severe depression. Major depression is considered to be an independent risk factor for the development of coronary heart disease and a predictor of cardiovascular events ( 51 ). Patients with depression are extremely sensitive to pain and have increased pain perception ( 52 ) and is associated with an increased risk of suicide ( 53 , 54 ), and generally the symptoms of these pains are not relieved by medication.

Studies have shown that depression triggers an inflammatory response, promoting an increase in cytokines in response to stressors vs. pathogens. For example, mild depressive symptoms have been associated with an amplified and prolonged inflammatory response ( 55 , 56 ) following influenza vaccination in older adults and pregnant women. Among women who have recently given birth, those with a lifetime history of major depression have greater increases in both serum IL-6 and soluble IL-6 receptors after delivery than women without a history of depression ( 57 ). Pro-inflammatory agents, such as interferon-alpha (IFN-alpha), for specific somatization disorders [e.g., hepatitis C or malignant melanoma ( 58 , 59 )], although effective for somatic disorders, pro-inflammatory therapy often leads to psychiatric side effects. Up to 80% of patients treated with IFN-α have been reported to suffer from mild to moderate depressive symptoms.

Clinical trials have shown better antidepressant treatment with anti-inflammatory drugs compared to placebo, either as monotherapy ( 60 , 61 ) or as an add-on treatment ( 62 – 65 ) to antidepressants ( 66 , 67 ). However, findings like whether NSAIDs can be safely used in combination with antidepressants are controversial. Patients with depression often suffer from somatic co-morbidities, which must be included in the benefit/risk assessment. It is important to consider the type of medication, duration of treatment, and dose, and always balance the potential treatment effect with the risk of adverse events in individual patients. Depression, childhood adversity, stressors, and diet all affect the gut microbiota and promote gut permeability, another pathway that enhances the inflammatory response, and effective depression treatment may have profound effects on mood, inflammation, and health. Early in life gut flora colonization is associated with hypothalamic-pituitary-adrenal (HPA) axis activation and affects the enteric nervous system, which is associated with the risk of major depression, gut flora dysbiosis leads to the onset of TLR4-mediated inflammatory responses, and pro-inflammatory factors are closely associated with depression. Clinical studies have shown that in the gut flora of depressed patients, pro-inflammatory bacteria such as Enterobacteriaceae and Desulfovibrio are enriched, while short-chain fatty acid producing bacteria are reduced, and some of these bacterial taxa may transmit peripheral inflammation into the brain via the brain-gut axis ( 68 ). In addition, gut flora can affect the immune system by modulating neurotransmitters (5-hydroxytryptamine, gamma-aminobutyric acid, norepinephrine, etc.), which in turn can influence the development of depression ( 69 ). Therefore, antidepressant drugs targeting gut flora are a future research direction, and diet can have a significant impact on mood by regulating gut flora.

As the molecular basis of clinical depression remains unclear, and treatments and therapeutic effects are limited and associated with side effects, researchers have worked to discover new treatment modalities for depression. High-amplitude low-frequency musical impulse stimulation as an additional treatment modality seems to produce beneficial effects ( 70 ). Studies have found electroconvulsive therapy to be one of the most effective antidepressant treatment therapies ( 71 ). Physical exercise can promote molecular changes that lead to a shift from a chronic pro-inflammatory to an anti-inflammatory state in the peripheral and central nervous system ( 72 ). Aromatherapy is widely used in the treatment of central nervous system disorders ( 73 ). By activating the parasympathetic nervous system, qigong can be effective in reducing depression ( 74 ). The exploration of these new treatment modalities provides more reference options for the treatment of depression.

Large-scale assessments of depression have found that the probability of developing depression varies across populations. Depression affects some specific populations more significantly, for example: adolescents, mothers, and older adults. Depression is one of the disorders that predispose to adolescence, and depression is associated with an increased risk of suicide among college students ( 75 ). Many women develop depression after childbirth. Depression that develops after childbirth is one of the most common complications for women in the postpartum period ( 76 ). The health of children born to mothers who suffer from postpartum depression can also be adversely affected ( 77 ). Depression can cause many symptoms within the central nervous system, especially in the elderly population ( 78 ).

Furthermore, one of the most consistent findings of the association between inflammation and depression is the elevated levels of peripheral pro-inflammatory markers in depressed individuals, and peripheral pro-inflammatory marker levels can also be used as a basis for the assessment of depressed patients. Studies have shown that the following pro-inflammatory markers have been found to be at increased levels in depressed individuals: CRP ( 79 , 80 ), IL-6 ( 22 , 79 , 81 , 82 ), TNF–α, and interleukin-1 receptor antagonist (IL-1ra) ( 79 , 82 ), however, this association is not unidirectional and the subsequent development of depression also increases pro-inflammatory markers ( 82 , 83 ). These biomarkers are of great interest, and depressed patients with increased inflammatory markers may represent a relatively drug-resistant population.

Frontier Analysis

The exploration and analysis of frontier areas of depression were based on the results of the analysis of the previous section on keywords. According to the evaluation index and analysis idea of this study, the frontier research topics need to have the following four characteristics: low to medium frequency, strong burst, high betweenness centrality, and the research direction in recent years. Therefore, combining the results of keyword analysis and these characteristics, it can be found that the frontier research on depression also becomes clear.

Research on Depression Characterized by Psychosexual Disorders

Exploration of biological mechanisms based on depression-associated neurological disorders and analysis of depression from a neurological perspective have always been the focus of research. Activation of neuroinflammatory pathways may contribute to the development of depression ( 84 ). A research model based on the microbial-gut-brain axis facilitates the neurobiology of depression ( 85 ). Some probiotics positively affect the central nervous system due to modulation of neuroinflammation and thus may be able to modulate depression ( 86 ). The combination of environmental issues and the neurobiological study of depression opens new research directions ( 46 ).

Research on Relevant Models of Depression

How to develop a model that meets the purpose of the study determines the outcome of the study and has become the direction that researchers have been exploring in recent years. Martínez et al. ( 87 ) developed a predictive model to assess factors that modify the treatment pathway for postpartum depression. Nie et al. ( 88 ) extended the work on predictive modeling of treatment-resistant depression to establish a predictive model for treatment-resistant depression. Rational modeling methods and behavioral testing facilitate a more comprehensive exploration of depression, with richer studies and more scientifically valid findings.

Research and Characterization of the Depressed Patient Population

Current research on special groups and depression has received much attention. In a study of a group of children, 4% were found to suffer from depression ( 89 ). The diagnosis and treatment of mental health disorders is an important component of pediatric care. Second, some studies of populations with distinct characteristics have been based primarily on female populations. Maternal perinatal depression is also a common mental disorder with a prevalence of over 10% ( 90 ). In addition, geriatric depression is a chronic and specific disorder ( 91 ). Studies based on these populations highlight the characteristics of the disorder more directly than large-scale population explorations and are useful for conducting extended explorations from specific to generalized.

Somatic Comorbidities Associated With Depression

Depression often accompanies the onset and development of many other disorders, making the study of physical comorbidities associated with depression a new landing place for depression research. Depression is a complication of many neurological or psychopathological disorders. Depression is a common co-morbidity of glioblastoma multiforme ( 92 ). Depression is an important disorder associated with stroke ( 93 ). Chronic liver disease is associated with depression ( 94 ). The link between depressive and anxiety states and cancer has been well-documented ( 95 ). In conclusion, depression is associated with an increased risk of lung, oral, prostate, and skin cancers, an increased risk of cancer-specific death from lung, bladder, breast, colorectal, hematopoietic system, kidney, and prostate cancers, and an increased risk of all-cause mortality in lung cancer patients. The early detection and effective intervention of depression and its complications has public health and clinical implications.

Research on Mechanisms of Depression

Research based on the mechanisms of depression includes the study of disease pathogenesis, the study of drug action mechanisms, and the study of disease treatment mechanisms. Research on the pathogenesis of depression has focused more on the study of the hypothalamic-pituitary-adrenal axis. Social pressure can change the hypothalamic-pituitary-adrenal axis ( 96 ). Studies on the mechanism of action of drugs are mostly based on their effects on the central nervous system. The antidepressant effects of Tanshinone IIA are mediated by the ERK-CREB-BDNF pathway in the hippocampus of mice ( 97 ). Research on the mechanisms of depression treatment has also centered on the central nervous system. It has been shown that the vagus nerve can transmit signals to the brain that can lead to a reduction in depressive behavior ( 98 ).

In this study, based on the 2004–2019 time period, this wealth of data is effectively integrated through data analysis and processing to reproduce the research process in a particular field and to co-present global trends in homogenous fields while organizing past research.

Journals that have made outstanding contributions in this field include ARCH GEN PSYCHIAT, J AFFECT DISORDERS and AM J PSYCHIAT. PSYCHIATRY, NEUROSCIENCES & NEUROLOGY and CLINICAL NEUROLOGY are the three most popular categories. The three researchers with the highest number of articles were MAURIZIO FAVA (USA), BRENDA W. J. H. PENNINX (NETHERLANDS) and MADHUKAR H TRIVEDI (USA). Univ Pittsburgh (USA), Kings Coll London (UK) and Harvard Univ (USA) are three of the most productive and influential research institutions. A Meta-Analysis of Cytokines in Major Depression, Evaluation of outcomes with citalopram for depression using measurement-based care in STAR*D: Implications for clinical practice and Deep brain stimulation for treatment-resistant depression are key articles. Through keyword analysis, a distribution network centered on depression was formed. Although there are good trends in the research on depression, there are still many directions to be explored in depth. Some recommendations regarding depression are as follows.

(1) The prevention of depression can be considered by focusing on treating external factors and guiding the individual.

Faced with the rising incidence of depression worldwide and the difficulty of treating depression, researchers can think more about how to prevent the occurrence of depression. Depressed moods are often the result of stress, not only social pressures on the individual, but also environmental pressures in the developmental process, which in turn have an unhealthy relationship with the body and increase the likelihood of depression. The correlation between external factors and depression is less well-studied, but the control of external factors may be more effective in the short term than in the long term, and may be guided by self-adjustment to avoid major depressive disorder.

(2) The measurement and evaluation of the degree of depression should be developed in the direction of precision.

In the course of research, it has been found that the Depression Rating Scale is mostly used for the detection and evaluation of depression. This kind of assessment is more objective, but it still lacks accuracy, and the research on measurement techniques and methods is less, which is still at a low stage. Patients with depression usually have a variety of causes, conditions, and duration of illness that determine the degree of depression. Therefore, whether these scales can truly accurately measure depression in depressed patients needs further consideration. Accurate measurement is an important basis for evidence-based treatment of depression, and thus how to achieve accurate measurement of depression is a research direction that researchers can move toward.

Therefore, there is an urgent need for further research to address these issues.

A systematic analysis of research in the field of depression in this study concludes that the distribution of countries, journals, categories, authors, institutions, and citations may help researchers and research institutions to establish closer collaboration, develop appropriate publication plans, grasp research hotspots, identify valuable research ideas, understand current emerging research, and determine research directions. In addition, there are still some limitations that can be overcome in future work. First, due to the lack of author and address information in older published articles, it may not be possible to accurately calculate their collaboration; second, although the data scope of this paper is limited to the Web of Science, it can adequately meet our objectives.

Data Availability Statement

The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author/s.

Author Contributions

HW conceived and designed the analysis, collected the data, performed the analysis, and wrote the paper. XT, XW, and YW conceived and designed the analysis. All authors contributed to the article and approved the submitted version.

This work was supported by the National Natural Science Foundation of China under Grant No. 81973495.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher's Note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

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Keywords: depression, major depressive disorder, bibliometrics, visual analysis, knowledge graphs, CiteSpace

Citation: Wang H, Tian X, Wang X and Wang Y (2021) Evolution and Emerging Trends in Depression Research From 2004 to 2019: A Literature Visualization Analysis. Front. Psychiatry 12:705749. doi: 10.3389/fpsyt.2021.705749

Received: 06 May 2021; Accepted: 05 October 2021; Published: 29 October 2021.

Reviewed by:

Copyright © 2021 Wang, Tian, Wang and Wang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Yun Wang, wangyun@bucm.edu.cn

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