Beyond Statistics: Genomics and the Genetic Construction of Depression
DOI:
https://doi.org/10.5007/1808-1711.2025.e102682Keywords:
Disease Genomics, Precision Psychiatry, Depression, Genetic Bases of Depression, Depression Genomics, Depression GeneticsAbstract
The global increase in the incidence of depression has sparked debates about a potential "epidemic". Within this context, there is academic criticism directed at the current state of psychiatric practice and knowledge, particularly concerning the validity of depression diagnostic criteria. Precision Psychiatry, combined with Disease Genomics, emerges as a potential solution to enhance diagnostic accuracy. Our research involves a methodological and epistemological analysis of the biological bases of depression as framed by Disease Genomics, focusing on the strategies used to study depression and their relationship to the development of diagnostic and treatment technologies. We found a scenario where non-significant associations between genetic variants and depression diagnosis in initial genomic studies were interpreted as methodological failures and challenges in statistical power. Consequently, efforts have aimed to increase statistical power through statistical strategies, conceptualizing depression as a genetically-based condition, albeit simplified and decontextualized. This focus on identifying specific genetic bases is also justified by the goal of developing more precise diagnoses and more effective treatments. Finally, we pose the question of whether these strategies truly aim to clarify the boundaries of diagnosis, heavily criticized for pathologizing "normal" human suffering, or rather to deepen this trend towards a more biologically and genetically oriented understanding of depression.
References
American Psychiatric Association - APA. 2013. Diagnostic and statistical manual of mental disorders. 5th ed. https://doi.org/10.1176/appi.books.9780890425596
Arribas-Ayllon, M. 2016. After geneticization. Social science & medicine (1982) 159: 132–139. https://doi.org/10.1016/j.socscimed.2016.05.011
Avissar, S.; Schreiber, G. 2002. Toward molecular diagnostics of mood disorders in psychiatry. Trends in molecular medicine 8(6): 294–300. https://doi.org/10.1016/s1471-4914(02)02351-1
Bolton, D. 2013. What is Mental Illness?. In: K. W. M. Fulford; M. Davies; R. G. T. Gipps; G. Graham; J. Z. Sadler; G. Stanghellini; T. Thornton (Eds.), The Oxford Handbook of Philosophy and Psychiatry, p.434-450. Oxford: Oxford University Press.
Bousman, C. A.; Bengesser, S. A.; Aitchison, K. J.; Amare, A. T.; Aschauer, H.; Baune, B. T.; ...; Müller, D. J. 2021. Review and consensus on pharmacogenomic testing in psychiatry. Pharmacopsychiatry 54(01): 5-17. https://doi.org/10.1055/a-1288-1061
Cai, N.; Choi, K. W.; Fried, E. I. 2020. Reviewing the genetics of heterogeneity in depression: operationalizations, manifestations and etiologies. Human molecular genetics 29(R1): R10–R18. https://doi.org/10.1093/hmg/ddaa115
Caponi, S. 2009. Un análisis epistemológico del diagnóstico de depresión. Interface - Comunicação, Saúde, Educação 13(29): 327-338. https://doi.org/10.1590/S1414-32832009000200007
Caponi, S. 2021. Sobre la llamada revolución psicofarmacológica: el descubrimiento de la clorpromazina y la gestión de la locura. História, Ciências, Saúde 28: 661-683. https://doi.org/10.1590/S0104-59702021000300003
Caponi, S. 2022. Necropolítica y psiquiatrización de la infancia en tiempos de pandemia. Revista De Psicología Universidad De Antioquia 13(2): 1–16. https://doi.org/10.17533/udea.rp.e346020
Chesler, P. 2023. Mujeres y locura. Edición en Español. Madrid: La pasión de Mary Read.
CONVERGE consortium. 2015. Sparse whole-genome sequencing identifies two loci for major depressive disorder. Nature 523(7562): 588–591. https://doi.org/10.1038/nature14659
Cooper, R. 2004. What is Wrong with the DSM?. History of Psychiatry 15(1): 5–25. https://doi.org/10.1177/0957154X04039343
Courgeau, D. 2017. La génétique du comportement peut-elle améliorer la démographie?. Revue d’études des Populations 2: 17.
COVID-19 Mental Disorders Collaborators. 2021. Global prevalence and burden of depressive and anxiety disorders in 204 countries and territories in 2020 due to the COVID-19 pandemic. Lancet 398(10312): 1700–1712. https://doi.org/10.1016/S0140-6736(21)02143-7
Cuthbert, B. N.; Insel, T. R. 2013. Toward the future of psychiatric diagnosis: the seven pillars of RDoC. BMC medicine 11: 126. https://doi.org/10.1186/1741-7015-11-126
Davies, J. 2021. Sedated: How Modern Capitalism Created our Mental Health Crisis. London: Atlantic Books.
De Haan, S. 2020. An Enactive Approach to Psychiatry. Philosophy, Psychiatry, & Psychology 27(1): 3–25. https://doi.org/10.1353/ppp.2020.000
Dell'Acqua, C.; Palomba, D.; Patron, E.; Messerotti Benvenuti, S. 2023. Rethinking the risk for depression using the RDoC: A psychophysiological perspective. Frontiers in psychology 14: 1108275. https://doi.org/10.3389/fpsyg.2023.1108275
Delvitto, A.; Lavagnino, N.J. 2023. Limitaciones de la complejidad en las ciencias ómicas: simplificación epistemológica en el abordaje de enfermedades. Principia 27(2): 165–194. https://doi.org/10.5007/1808-1711.2023.e85523
Deng, J.; Zhou, F.; Hou, W.; Heybati, K.; Lohit, S.; Abbas, U.; Silver, Z.; Wong, C. Y.; Chang, O.; Huang, E.; Zuo, Q. K.; Moskalyk, M.; Ramaraju, H. B.; Heybati, S. 2023. Prevalence of mental health symptoms in children and adolescents during the COVID-19 pandemic: A meta-analysis. Annals of the New York Academy of Sciences 1520(1): 53–73. https://doi.org/10.1111/nyas.14947
Flint, J. 2023. The genetic basis of major depressive disorder. Molecular psychiatry 28(6): 2254–2265. https://doi.org/10.1038/s41380-023-01957-9
Frances, A. 2013. Saving normal: An insider's revolt against out-of-control psychiatric diagnosis, DSM-5, Big Pharma, and the medicalization of ordinary life. New York: William Morrow & Co.
Friedrich, M. J. 2017. Depression Is the Leading Cause of Disability Around the World. JAMA 317(15): 1517. https://doi.org/10.1001/jama.2017.3826
Fry, A.; Littlejohns, T. J.; Sudlow, C.; Doherty, N.; Adamska, L.; Sprosen, T.; ...; Allen, N. E. 2017. Comparison of sociodemographic and health-related characteristics of UK Biobank participants with those of the general population. American journal of epidemiology 186(9): 1026-1034. https://doi.org/10.1093/aje/kwx246
Fusar-Poli, P.; Manchia, M.; Koutsouleris, N.; Leslie, D.; Woopen, C.; Calkins, M. E.; ...; PSMD EBRA cluster (annex 1). 2022. Ethical considerations for precision psychiatry: A roadmap for research and clinical practice. European neuropsychopharmacology: the journal of the European College of Neuropsychopharmacology 63: 17–34. https://doi.org/10.1016/j.euroneuro.2022.08.001
GBD 2015 Disease and Injury Incidence and Prevalence Collaborators. 2016. Global, regional, and national incidence, prevalence, and years lived with disability for 310 diseases and injuries, 1990-2015: a systematic analysis for the Global Burden of Disease Study 2015. Lancet 388(10053): 1545–1602. https://doi.org/10.1016/S0140-6736(16)31678-6
Giannakopoulou, O.; Lin, K.; Meng, X.; Su, M. H.; Kuo, P. H.; ...; Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium. 2021. The Genetic Architecture of Depression in Individuals of East Asian Ancestry: A Genome-Wide Association Study. JAMA psychiatry 78(11): 1258–1269. https://doi.org/10.1001/jamapsychiatry.2021.2099
Gómez-Carrillo, A.; Paquin, V.; Dumas, G.; Kirmayer, L. J. 2023. Restoring the missing person to personalized medicine and precision psychiatry. Frontiers in neuroscience: 17; 1041433. https://doi.org/10.3389/fnins.2023.1041433
Green, S.; Carusi, A.; Hoeyer, K. 2022. Plastic diagnostics: The remaking of disease and evidence in personalized medicine. Social science & medicine (1982) 304: 112318. https://doi.org/10.1016/j.socscimed.2019.05.023
Hall, L. S.; Adams, M. J.; Arnau-Soler, A.; Clarke, T. K.; Howard, D. M.; Zeng; ...; McIntosh, A. M. 2018. Genome-wide meta-analyses of stratified depression in Generation Scotland and UK Biobank. Translational psychiatry 8(1): 9. https://doi.org/10.1038/s41398-017-0034-1.
Healy, D. 1997. The antidepressant era. Cambridge, MA y Londres: Harvard University Press.
Healy, D. 2015. Serotonin and depression. The marketing of a myth. BMJ (Clinical research ed.) 350: h1771. https://doi.org/10.1136/bmj.h1771.
Hek, K.; Demirkan, A.; Lahti, J.; Terracciano, A.; Teumer, A.; Cornelis, M. C.; ...; Murabito, J. 2013. A genome-wide association study of depressive symptoms. Biological psychiatry 73(7): 667–678. https://doi.org/10.1016/j.biopsych.2012.09.033
Horwitz, A.; Wakefield, J. 2007. The Loss of Sadness: How Psychiatry Transformed Normal Sorrow Into Depressive Disorder. Oxford: Oxford University Press.
Howard, D. M.; Adams, M. J.; Clarke, T. K.; Hafferty, J. D.; Gibson, J.; Shirali, M.; ...; McIntosh, A. M. 2019. Genome-wide meta-analysis of depression identifies 102 independent variants and highlights the importance of the prefrontal brain regions. Nature neuroscience 22(3): 343–352. https://doi.org/10.1038/s41593-018-0326-7
Howard, D. M.; Adams, M. J.; Shirali, M.; Clarke, T. K.; Marioni, R. E.; Davies, G.; ...; McIntosh, A. M. 2018. Genome-wide association study of depression phenotypes in UK Biobank identifies variants in excitatory synaptic pathways. Nature communications 9(1): 1470. https://doi.org/10.1038/s41467-018-03819-3
Hyde, C. L.; Nagle, M. W.; Tian, C.; Chen, X.; Paciga, S. A.; Wendland, J. R.; ...; Winslow, A. R. 2016. Identification of 15 genetic loci associated with risk of major depression in individuals of European descent. Nature genetics 48(9): 1031–1036. https://doi.org/10.1038/ng.3623
Insel T. R. 2014. The NIMH Research Domain Criteria (RDoC) Project: precision medicine for psychiatry. The American Journal of Psychiatry 171(4): 395–397. https://doi.org/10.1176/appi.ajp.2014.14020138
Insel, T. R.; Cuthbert, B. N. 2015. Medicine. Brain disorders? Precisely. Science 348(6234): 499–500. https://doi.org/10.1126/science.aab2358
Insel, T.; Cuthbert, B.; Garvey, M.; Heinssen, R.; Pine, D. S.; Quinn, K.; Sanislow, C.; Wang, P. 2010. Research domain criteria (RDoC): toward a new classification framework for research on mental disorders. The American journal of psychiatry 167(7): 748–751. https://doi.org/10.1176/appi.ajp.2010.09091379
Joseph, J. 2013. The Use of the Classical Twin Method in the Social and Behavioral Sciences: The Fallacy Continues. The Journal of Mind and Behavior 34(1): 1–39. http://www.jstor.org/stable/43854465
Jutel, A.; Nettleton, S. 2011. Towards a sociology of diagnosis: reflections and opportunities. Social science & medicine 73(6): 793-800.
Kauhanen, L.; Wan Mohd Yunus, W. M. A.; Lempinen, L.; Peltonen, K.; Gyllenberg, D.; Mishina, K.; Gilbert, S.; Bastola, K.; Brown, J. S. L.; Sourander, A. 2023. A systematic review of the mental health changes of children and young people before and during the COVID-19 pandemic. European child & adolescent psychiatry 32(6): 995–1013. https://doi.org/10.1007/s00787-022-02060-0
Kazantseva, A.; Davydova, Y.; Enikeeva, R.; Mustafin, R.; Malykh, S.; Lobaskova; ...; Khusnutdinova, E. 2023. A Combined Effect of Polygenic Scores and Environmental Factors on Individual Differences in Depression Level. Genes 14(7): 1355. https://doi.org/10.3390/genes14071355.
Kessler, R. C.; Bromet, E. J. 2013. The epidemiology of depression across cultures. Annual review of public health 34: 119–138. https://doi.org/10.1146/annurev-publhealth-031912-114409
Leiva-Peña, V.; Rubí-González, P.; Vicente-Parada, B. 2021. Determinantes sociales de la salud mental: políticas públicas desde el modelo biopsicosocial en países latinoamericanos. Revista panamericana de salud publica = Pan American journal of public health 45: e158. https://doi.org/10.26633/RPSP.2021.158
Levey, D. F.; Stein, M. B.; Wendt, F. R.; Pathak, G. A.; Zhou, H.; Aslan, M.; ...; Gelernter, J. 2021. Bi-ancestral depression GWAS in the Million Veteran Program and meta-analysis in >1.2 million individuals highlight new therapeutic directions. Nature neuroscience 24(7): 954–963. https://doi.org/10.1038/s41593-021-00860-2
Levín, S. 2018. La psiquiatría en la encrucijada. Buenos Aires: Eudeba.
Levinson, D. F.; Mostafavi, S.; Milaneschi, Y.; Rivera, M.; Ripke, S.; Wray, N. R.; Sullivan, P. F. 2014. Genetic studies of major depressive disorder: why are there no genome-wide association study findings and what can we do about it?. Biological psychiatry 76(7): 510–512. https://doi.org/10.1016/j.biopsych.2014.07.029
Levy Yeyati, E. 2022. Trastorno por duelo prolongado: un nuevo diagnóstico en el DSM-5TR. Vertex Revista Argentina De Psiquiatría 33(156, abr.-jun.): 51–55. https://doi.org/10.53680/vertex.v33i156.179
Lewontin, R. C.; Rose, S.; Kamin, L. J. 1987. No está en los genes: racismo, genética e ideología. 1a ed. Barcelona: Crítica.
Lippman A. 1991. Prenatal genetic testing and screening: constructing needs and reinforcing inequities. American journal of law & medicine 17(1-2): 15–50.
Lippman A. 1992. Led (astray) by genetic maps: the cartography of the human genome and health care. Social science & medicine (1982) 35(12): 1469–1476. https://doi.org/10.1016/0277-9536(92)90049-v
Lippman, A. 1998. The politics of health: geneticization versus health promotion. In: S. Sherwin (ed.), The Politics of Women’s Health: Exploring Agency and Autonomy, p.64-82. Philadelphia: Temple University Press.
Liu, Q.; He, H.; Yang, J.; Feng, X.; Zhao, F.; Lyu, J. 2020. Changes in the global burden of depression from 1990 to 2017: Findings from the Global Burden of Disease study. Journal of psychiatric research 126: 134–140. https://doi.org/10.1016/j.jpsychires.2019.08.002
Lord, S. J.; Gebski, V. J.; Keech, A. C. 2004. Multiple analyses in clinical trials: sound science or data dredging?. Medical journal of Australia 181(8): 452.
Major Depressive Disorder Working Group of the Psychiatric GWAS Consortium; Ripke, S.; Wray, N. R.; Lewis, C. M.; Hamilton, S. P.; Weissman, M. M.; ...; Sullivan, P. F. 2013. A mega-analysis of genome-wide association studies for major depressive disorder. Molecular psychiatry 18(4): 497–511. https://doi.org/10.1038/mp.2012.21
Malik, S.; Singh, R.; Arora, G.; Dangol, A.; Goyal, S. 2021. Biomarkers of Major Depressive Disorder: Knowing is Half the Battle. Clinical psychopharmacology and neuroscience: the official scientific journal of the Korean College of Neuropsychopharmacology 19(1): 12–25. https://doi.org/10.9758/cpn.2021.19.1.12
McHenry, L. 2010. Of sophists and spin-doctors: industry-sponsored ghostwriting and the crisis of academic medicine. Mens Sana Monographs 8(1): 129. https://doi.org/10.4103%2F0973-1229.58824
Moncrieff, J.; Cooper, R. E.; Stockmann, T.; Amendola, S.; Hengartner, M. P.; Horowitz, M. A. 2023. The serotonin theory of depression: a systematic umbrella review of the evidence. Molecular psychiatry 28(8): 3243–3256. https://doi.org/10.1038/s41380-022-01661-0
Monterde Fuertes, A. 2022a. The Epidemic of Depression: When Science Doesn’t Correct Itself. ArtefaCToS. Revista De Estudios Sobre La Ciencia Y La tecnología 11(2): 5–28. https://doi.org/10.14201/art2022112528
Monterde Fuertes, A. 2022b. Disease mongering y la epidemia de la depresión: una revisión histórica del desarrollo del tratamiento psiquiátrico de la depresión y su relación con el proceso de promoción de enfermedades. Eikasía Revista De Filosofía (107): 57–92. https://doi.org/10.57027/eikasia.107.297
Moore, D. S.; Shenk, D. 2017. The heritability fallacy. Wiley interdisciplinary reviews. Cognitive science 8(1-2): 10.1002/wcs.1400. https://doi.org/10.1002/wcs.1400.
Mullins, N.; Lewis, C. M. 2017. Genetics of Depression: Progress at Last. Current psychiatry reports 19(8): 43. https://doi.org/10.1007/s11920-017-0803-9
Nguyen, T. D.; Harder, A.; Xiong, Y.; Kowalec, K.; Hägg, S.; Cai, N.; Kuja-Halkola, R.; ...; Lu, Y. 2022. Genetic heterogeneity and subtypes of major depression. Molecular psychiatry 27(3): 1667–1675. https://doi.org/10.1038/s41380-021-01413-6
OECD. 2023. Health at a Glance 2023: OECD Indicators. Paris: OECD Publishing. https://doi.org/10.1787/7a7afb35-en.
Ostergaard, S. D.; Jensen, S. O.; Bech, P. 2011. The heterogeneity of the depressive syndrome: when numbers get serious. Acta psychiatrica Scandinavica 124(6): 495–496. https://doi.org/10.1111/j.1600-0447.2011.01744.x
Otte, C.; Gold, S. M.; Penninx, B. W.; Pariante, C. M.; Etkin, A.; Fava; ...; Schatzberg, A. F. 2016. Major depressive disorder. Nature reviews. Disease primers 2: 16065. https://doi.org/10.1038/nrdp.2016.65
Penchaszadeh V. B. 2016. Reflexiones de un genetista sobre la influencia de los genes en los trastornos psiquiátricos [Reflections of a geneticist on the influence of genes in psychiatric disorders]. Vertex (Buenos Aires, Argentina) XXVII(129): 357–367.
Robette, N.; Génin, E.; Clerget-Darpoux, F. 2022. Heritability: What's the point? What is it not for? A human genetics perspective. Genetica 150(3-4): 199–208. https://doi.org/10.1007/s10709-022-00149-7.
Rose S. P. 2006. Commentary: heritability estimates--long past their sell-by date. International journal of epidemiology 35(3): 525–527. https://doi.org/10.1093/ije/dyl064
Rose, N. 2016. Neuroscience and the future for mental health?. Epidemiology and psychiatric sciences 25(2): 95–100. https://doi.org/10.1017/S2045796015000621
Rosenberg, C. E. 2006. Contested boundaries: psychiatry, disease, and diagnosis. Perspectives in biology and medicine 49(3): 407–424. https://doi.org/10.1353/pbm.2006.0046
Ross, J. S.; Ginsburg, G. S. 2003. The Integration of Molecular Diagnostics With Therapeutics. American Journal of Clinical Pathology 119(1): 26–36. doi:10.1309/VMLL66Y5KHQ35KUE
Sarkar, S. 1998. The obsession with heritability. In: Genetics and Reductionism, p.71-100. Cambridge Studies in Philosophy and Biology. Cambridge: Cambridge University Press.
Schoeler, T.; Speed, D.; Porcu, E.; Pirastu, N.; Pingault, J. B.; Kutalik, Z. 2023. Participation bias in the UK Biobank distorts genetic associations and downstream analyses. Nature Human Behaviour 7(7): 1216-1227. https://doi.org/10.1038/s41562-023-01579-9
Schwabe, I.; Milaneschi, Y.; Gerring, Z.; Sullivan, P. F.; Schulte, E.; Suppli, N. P.; ...; Middeldorp, C. M. 2019. Unraveling the genetic architecture of major depressive disorder: merits and pitfalls of the approaches used in genome-wide association studies. Psychological medicine 49(16): 2646–2656. https://doi.org/10.1017/S0033291719002502
Shorter, E. 2008. Before prozac: The troubled history of mood disorders in psychiatry. Nueva York: Oxford University Press.
Strawbridge, R.; Young, A. H.; Cleare, A. J. 2017. Biomarkers for depression: recent insights, current challenges and future prospects. Neuropsychiatric disease and treatment 13: 1245–1262. https://doi.org/10.2147/NDT.S114542
Stucchi-Portocarrero, S. 2017. ¿Realmente existe una “epidemia de depresión”?. Revista de Neuropsiquiatría 80(4): 261-264. https://doi.org/10.20453/rnp.v80i4.3240
Sullivan, P. F.; Kendler, K. S.; Neale, M. C. 2003. Schizophrenia as a complex trait: evidence from a meta-analysis of twin studies. Archives of general psychiatry 60(12): 1187–1192. https://doi.org/10.1001/archpsyc.60.12.1187
Sullivan, P. F.; Neale, M. C.; Kendler, K. S. 2000. Genetic epidemiology of major depression: review and meta-analysis. The American journal of psychiatry 157(10): 1552–1562. https://doi.org/10.1176/appi.ajp.157.10.1552
Summerfield, D. 2006. Depression: epidemic or pseudo-epidemic?. Journal of the Royal Society of Medicine 99(3): 161–162. https://doi.org/10.1177/014107680609900323
Suppli, N. P.; Andersen, K. K.; Agerbo, E.; Rajagopal, V. M.; Appadurai, V.; Coleman, J. R. I.; ...; Musliner, K. L. 2021. Genome-wide by Environment Interaction Study of Stressful Life Events and Hospital-Treated Depression in the iPSYCH2012 Sample. Biological psychiatry global open science 2(4): 400–410. https://doi.org/10.1016/j.bpsgos.2021.11.003
Thalamuthu, A.; Mills, N. T.; Berger, K.; Minnerup, H.; Grotegerd, D.; Dannlowski, U.; ...; Baune, B. T. 2022. Genome-wide interaction study with major depression identifies novel variants associated with cognitive function. Molecular psychiatry 27(2): 1111–1119. https://doi.org/10.1038/s41380-021-01379-5
van den Berg, S. M.; de Moor, M. H.; McGue, M.; Pettersson, E.; Terracciano, A.; Verweij; ...; Boomsma, D. I. 2014. Harmonization of Neuroticism and Extraversion phenotypes across inventories and cohorts in the Genetics of Personality Consortium: an application of Item Response Theory. Behavior genetics 44(4): 295–313. https://doi.org/10.1007/s10519-014-9654-x
Wakefield, J. C. 2016. Diagnostic Issues and Controversies in DSM-5: Return of the False Positives Problem. Annual Review of Clinical Psychology 12(1): 105–132. https://doi.org/10.1146/annurevclinpsy-032814-112800
Wakefield, J.; Demazeux, S. 2016. Sadness or Depression?: International perspectives on the depression epidemic and its meaning. Amsterdam: Springer.
Whitaker, R.; Cosgrove, L. 2015. Psychiatry under the influence: institutional corruption, social injury, and prescriptions for reform. Londres: Palgrave MacMillan.
Wikinski, S. 2008. Psicofármacos y teorías etiopatogénicas en Psiquiartría. Del contexto de descubrimiento al obstáculo epistemológico. Vertex 19(80): 196–200.
Wikinski, S. 2020. Fisiopatogenia en Psiquiatría: ¿descubrimiento, construcción o descubrimiento + construcción? El “caso” de la depresión. Vertex Revista Argentina De Psiquiatría 31: 155–164.
Woody, M. L.; Gibb, B. E. 2015. Integrating NIMH Research Domain Criteria (RDoC) into Depression Research. Current opinion in psychology 4: 6–12. https://doi.org/10.1016/j.copsyc.2015.01.004
World Health Organization. 2017. Depression and other common mental disorders. WHO/MSD/MER/2017.2, 1-24.
Wray, N. R.; Pergadia, M. L.; Blackwood, D. H.; Penninx, B. W.; Gordon, S. D.; Nyholt, D. R.; ...; Sullivan, P. F. 2012. Genome-wide association study of major depressive disorder: new results, meta-analysis, and lessons learned. Molecular psychiatry 17(1): 36–48. https://doi.org/10.1038/mp.2010.109
Wray, N. R.; Ripke, S.; Mattheisen, M.; Trzaskowski, M.; Byrne, E. M.; Abdellaoui, A.; ...; Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium. 2018. Genome-wide association analyses identify 44 risk variants and refine the genetic architecture of major depression. Nature genetics 50(5): 668–681. https://doi.org/10.1038/s41588-018-0090-3
Zimmerman, M.; Ellison, W.; Young, D.; Chelminski, I.; Dalrymple, K. 2015. How many different ways do patients meet the diagnostic criteria for major depressive disorder?. Comprehensive psychiatry 56: 29–34. https://doi.org/10.1016/j.comppsych.2014.09.007
Downloads
Published
Issue
Section
License
Copyright (c) 2025 Ailin Delvitto, María Alejandra Petino Zappala, Nicolás José Lavagnino, Sandra Caponi
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Principia http://www.periodicos.ufsc.br/index.php/principia/index is licenced under a Creative Commons - Atribuição-Uso Não-Comercial-Não a obras derivadas 3.0 Unported.
Base available in www.periodicos.ufsc.br.
