Abstract
Depression is more frequent among individuals exposed to traumatic events. Both trauma exposure and depression are heritable. However, the relationship between these traits, including the role of genetic risk factors, is complex and poorly understood. When modelling trauma exposure as an environmental influence on depression, both gene-environment correlations and gene-environment interactions have been observed. The UK Biobank concurrently assessed Major Depressive Disorder (MDD) and self-reported lifetime exposure to traumatic events in 126,522 genotyped individuals of European ancestry. We contrasted genetic influences on MDD stratified by reported trauma exposure (final sample size range: 24,094–92,957). The SNP-based heritability of MDD with reported trauma exposure (24%) was greater than MDD without reported trauma exposure (12%). Simulations showed that this is not confounded by the strong, positive genetic correlation observed between MDD and reported trauma exposure. We also observed that the genetic correlation between MDD and waist circumference was only significant in individuals reporting trauma exposure (rg = 0.24, p = 1.8 × 10−7 versus rg = −0.05, p = 0.39 in individuals not reporting trauma exposure, difference p = 2.3 × 10−4). Our results suggest that the genetic contribution to MDD is greater when reported trauma is present, and that a complex relationship exists between reported trauma exposure, body composition, and MDD.
This is a preview of subscription content, access via your institution
Access options
Subscribe to this journal
Receive 12 print issues and online access
$259.00 per year
only $21.58 per issue
Buy this article
- Purchase on SpringerLink
- Instant access to full article PDF
Prices may be subject to local taxes which are calculated during checkout
Similar content being viewed by others
Code availability
Analytical code underlying this project will be made available at https://github.com/tnggroup.
Change history
18 May 2020
A Correction to this paper has been published: https://doi.org/10.1038/s41380-020-0779-4
References
GBD 2016 Disease and Injury Incidence and Prevalence Collaborators. Global, regional, and national incidence, prevalence, and years lived with disability for 328 diseases and injuries for 195 countries, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016. Lancet. 2017;390:1211–59.
McManus S, Bebbington P, Jenkins R, Brugha T. Mental health and wellbeing in England: Adult Psychiatric Morbidity Survey 2014: a survey carried out for NHS Digital by NatCen Social Research and the Department of Health Sciences, University of Leicester. NHS Digital, 2016.
Green JG, McLaughlin KA, Berglund PA, Gruber MJ, Sampson NA, Zaslavsky AM, et al. Childhood adversities and adult psychiatric disorders in the national comorbidity survey replication I: associations with first onset of DSM-IV disorders. Arch Gen Psychiatry. 2010;67:113–23.
Nanni V, Uher R, Danese A. Childhood maltreatment predicts unfavorable course of illness and treatment outcome in depression: a meta-analysis. Am J Psychiatry. 2012;169:141–51.
Kessler RC. The effects of stressful life events on depression. Annu Rev Psychol. 1997;48:191–214.
McLaughlin KA, Conron KJ, Koenen KC, Gilman SE. Childhood adversity, adult stressful life events, and risk of past-year psychiatric disorder: a test of the stress sensitization hypothesis in a population-based sample of adults. Psychol Med. 2010;40:1647–58.
Kessler RC, Davis CG, Kendler KS. Childhood adversity and adult psychiatric disorder in the US National Comorbidity Survey. Psychol Med. 1997;27:1101–19.
Collishaw S, Pickles A, Messer J, Rutter M, Shearer C, Maughan B. Resilience to adult psychopathology following childhood maltreatment: evidence from a community sample. Child Abus Negl. 2007;31:211–29.
Baldwin JR, Reuben A, Newbury JB, Danese A. Agreement between prospective and retrospective measures of childhood maltreatment: a systematic review and meta-analysis. JAMA Psychiatry. 2019. https://doi.org/10.1001/jamapsychiatry.2019.0097.
Kendler KS, Karkowski LM, Prescott CA. Causal relationship between stressful life events and the onset of major depression. Am J Psychiatry. 1999;156:837–41.
Kendler KS, Karkowski-Shuman L. Stressful life events and genetic liability to major depression: genetic control of exposure to the environment? Psychol Med. 1997;27:539–47.
Polderman TJC, Benyamin B, de Leeuw CA, Sullivan PF, van Bochoven A, Visscher PM, et al. Meta-analysis of the heritability of human traits based on fifty years of twin studies. Nat Genet. 2015;47:702–9.
Yang J, Zeng J, Goddard ME, Wray NR, Visscher PM. Concepts, estimation and interpretation of SNP-based heritability. Nat Genet. 2017;49:1304–10.
Hyde CL, Nagle MW, Tian C, Chen X, Paciga SA, Wendland JR, et al. Identification of 15 genetic loci associated with risk of major depression in individuals of European descent. Nat Genet. 2016;48:1031–6.
Wray NR, Ripke S, Mattheisen M, Trzaskowski M, Byrne EM, Abdellaoui A, et al. Genome-wide association analyses identify 44 risk variants and refine the genetic architecture of major depression. Nat Genet. 2018;50:668–81.
Jang KL, Vernon PA, Livesley WJ, Stein MB, Wolf H. Intra- and extra-familial influences on alcohol and drug misuse: a twin study of gene-environment correlation. Addiction. 2001;96:1307–18.
Stein MB, Jang KL, Taylor S, Vernon PA, Livesley WJ. Genetic and environmental influences on trauma exposure and posttraumatic stress disorder symptoms: a twin study. Am J Psychiatry. 2002;159:1675–81.
Lyons MJ, Goldberg J, Eisen SA, True W, Tsuang MT, Meyer JM, et al. Do genes influence exposure to trauma? A twin study of combat. Am J Med Genet. 1993;48:22–7.
Power RA, Wingenbach T, Cohen-Woods S, Uher R, Ng MY, Butler AW, et al. Estimating the heritability of reporting stressful life events captured by common genetic variants. Psychol Med. 2013;43:1965–71.
Dunn EC, Brown RC, Dai Y, Rosand J, Nugent NR, Amstadter AB, et al. Genetic determinants of depression: recent findings and future directions. Harv Rev Psychiatry. 2015;23:1–18.
Schraedley PK, Turner RJ, Gotlib IH. Stability of retrospective reports in depression: traumatic events, past depressive episodes, and parental psychopathology. J Health Soc Behav. 2002;43:307–16.
Dunn EC, Wiste A, Radmanesh F, Almli LM, Gogarten SM, Sofer T, et al. Genome-wide association study (GWAS) and genome-wide by environment interaction study (GWEIS) of depressive symptoms in african american and hispanic/latina women. Depress Anxiety. 2016;33:265–80.
Peterson RE, Cai N, Dahl AW, Bigdeli TB, Edwards AC, Webb BT, et al. Molecular genetic analysis subdivided by adversity exposure suggests etiologic heterogeneity in major depression. Am J Psychiatry. 2018;175:545–54.
Peyrot WJ, Milaneschi Y, Abdellaoui A, Sullivan PF, Hottenga JJ, Boomsma DI, et al. Effect of polygenic risk scores on depression in childhood trauma. Br J Psychiatry. 2014;205:113–9.
Mullins N, Power RA, Fisher HL, Hanscombe KB, Euesden J, Iniesta R, et al. Polygenic interactions with environmental adversity in the aetiology of major depressive disorder. Psychol Med. 2016;46:759–70.
Peyrot WJ, Van der Auwera S, Milaneschi Y, Dolan CV, Madden PAF, Sullivan PF et al. Does childhood trauma moderate polygenic risk for depression? A meta-analysis of 5765 subjects from the Psychiatric Genomics Consortium. Biol Psychiatry. 2017. https://doi.org/10.1016/j.biopsych.2017.09.009.
Jaffee SR, Price TS. Gene-environment correlations: a review of the evidence and implications for prevention of mental illness. Mol Psychiatry. 2007;12:432–42.
Lau JYF, Eley TC. Disentangling gene-environment correlations and interactions on adolescent depressive symptoms. J Child Psychol Psychiatry. 2008;49:142–50.
Thapar A, Harold G, McGuffin P. Life events and depressive symptoms in childhood–shared genes or shared adversity? A research note. J Child Psychol Psychiatry. 1998;39:1153–8.
Boardman JD, Alexander KB, Stallings MC. Stressful life events and depression among adolescent twin pairs. Biodemogr Soc Biol. 2011;57:53–66.
Davis KAS, Coleman JRI, Adams M, Allen N, Breen G, Cullen B, et al. Mental health in UK Biobank: development, implementation and results from an online questionnaire completed by 157 366 participants. BJPsych Open. 2018;4:83–90.
Allen NE, Sudlow C, Peakman T, Collins R, Biobank UK. UK biobank data: come and get it. Sci Transl Med. 2014;6:224ed4.
Smith DJ, Nicholl BI, Cullen B, Martin D, Ul-Haq Z, Evans J, et al. Prevalence and characteristics of probable major depression and bipolar disorder within UK biobank: cross-sectional study of 172,751 participants. PLoS One. 2013;8:e75362.
Bellis MA, Hughes K, Leckenby N, Perkins C, Lowey H. National household survey of adverse childhood experiences and their relationship with resilience to health-harming behaviors in England. BMC Med. 2014;12:72.
Bernstein DP, Fink L, Handelsman L, Foote J, Lovejoy M, Wenzel K, et al. Initial reliability and validity of a new retrospective measure of child abuse and neglect. Am J Psychiatry. 1994;151:1132–6.
Grabe HJ, Schulz A, Schmidt CO, Appel K, Driessen M, Wingenfeld K, et al. A brief instrument for the assessment of childhood abuse and neglect: the childhood trauma screener (CTS). Psychiatr Prax. 2012;39:109–15.
Townsend P, Phillimore P, Beattie A. Health and deprivation: inequality and the north. London: Croom Helm; 1988.
Bycroft C, Freeman C, Petkova D, Band G, Elliott LT, Sharp K, et al. The UK Biobank resource with deep phenotyping and genomic data. Nature. 2018;562:203–9.
McCarthy S, Das S, Kretzschmar W, Delaneau O, Wood AR, Teumer A, et al. A reference panel of 64,976 haplotypes for genotype imputation. Nat Genet. 2016;48:1279–83.
Walter K, Min JL. UK10K Consortium et al. The UK10K project identifies rare variants in health and disease. Nature. 526:82–90.
Manichaikul A, Mychaleckyj JC, Rich SS, Daly K, Sale M, Chen W-M. Robust relationship inference in genome-wide association studies. Bioinformatics. 2010;26:2867–73.
Warren HR, Evangelou E, Cabrera CP, Gao H, Ren M, Mifsud B, et al. Genome-wide association analysis identifies novel blood pressure loci and offers biological insights into cardiovascular risk. Nat Genet. 2017;49:403–15.
Abraham G, Qiu Y, Inouye M. FlashPCA2: principal component analysis of Biobank-scale genotype datasets. Bioinformatics. 2017;33:2776–8.
Dudbridge F, Gusnanto A. Estimation of significance thresholds for genomewide association scans. Genet Epidemiol. 2008;32:227–34.
Chang CC, Chow CC, Tellier LC, Vattikuti S, Purcell SM, Lee JJ. Second-generation PLINK: rising to the challenge of larger and richer datasets. Gigascience. 2015;4:7.
Lloyd-Jones LR, Robinson MR, Yang J, Visscher PM. Transformation of summary statistics from linear mixed model association on all-or-none traits to odds ratio. Genetics. 2018. https://doi.org/10.1534/genetics.117.300360.
Marioni RE, Harris SE, Zhang Q, McRae AF, Hagenaars SP, Hill WD, et al. GWAS on family history of Alzheimer’s disease. Transl Psychiatry. 2018;8:99.
Team RC. R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing; 2014. 2014.
Loh P-R, Kichaev G, Gazal S, Schoech AP, Price AL. Mixed-model association for biobank-scale datasets. Nat Genet. 2018;50:906–8.
Lee SH, Goddard ME, Wray NR, Visscher PM. A better coefficient of determination for genetic profile analysis. Genet Epidemiol. 2012;36:214–24.
Bulik-Sullivan BK, Loh P-R, Finucane HK, Ripke S, Yang J, Schizophrenia Working Group of the Psychiatric Genomics Consortium. et al. LD Score regression distinguishes confounding from polygenicity in genome-wide association studies. Nat Genet. 2015;47:291–5.
Bulik-Sullivan B, Finucane HK, Anttila V, Gusev A, Day FR, Loh P-R, et al. An atlas of genetic correlations across human diseases and traits. Nat Genet. 2015;47:1236–41.
Daniel WW and Cross CL. Biostatistics: A Foundation for Analysis in the Health Sciences, 11th ed. Hoboken, NJ: John Wiley & Sons; 2018.
Tukey WJ. Bias and confidence in not-quite large samples. Ann Math Stat. 1958;29:614.
Quenouille MH. Notes on bias in estimation. Biometrika. 1956;43:353–60.
Schizophrenia Working Group of the Psychiatric Genomics Consortium. Biological insights from 108 schizophrenia-associated genetic loci. Nature. 2014;511:421–7.
Psychiatric GWAS Consortium Bipolar Disorder Working Group. Large-scale genome-wide association analysis of bipolar disorder identifies a new susceptibility locus near ODZ4. Nat Genet. 2011;43:977–83.
Locke AE, Kahali B, Berndt SI, Justice AE, Pers TH, Day FR, et al. Genetic studies of body mass index yield new insights for obesity biology. Nature. 2015;518:197–206.
Soranzo N, Sanna S, Wheeler E, Gieger C, Radke D, Dupuis J, et al. Common variants at 10 genomic loci influence hemoglobin A1(C) levels via glycemic and nonglycemic pathways. Diabetes. 2010;59:3229–39.
Euesden J, Lewis CM, O’Reilly PF. PRSice: Polygenic Risk Score software. Bioinformatics. 2015;31:1466–8.
Choi SW, O’Reilly PF PRSice-2: Polygenic Risk Score software for biobank-scale data. Gigascience. 2019;8. https://doi.org/10.1093/gigascience/giz082.
Keller MC. Gene × environment interaction studies have not properly controlled for potential confounders: the problem and the (simple) solution. Biol Psychiatry. 2014;75:18–24.
Yzerbyt VY, Muller D, Judd CM. Adjusting researchers’ approach to adjustment: on the use of covariates when testing interactions. J Exp Soc Psychol. 2004;40:424–31.
Turley P, Walters RK, Maghzian O, Okbay A, Lee JJ, Fontana MA et al. Multi-trait analysis of genome-wide association summary statistics using MTAG. Nat Genet. 2018;50:229–37.
Howard DM, Adams MJ, Shirali M, Clarke T-K, Marioni RE, Davies G, et al. Genome-wide association study of depression phenotypes in UK Biobank identifies variants in excitatory synaptic pathways. Nat Commun. 2018;9:1470.
Smith DJ, Escott-Price V, Davies G, Bailey MES, Colodro-Conde L, Ward J, et al. Genome-wide analysis of over 106 000 individuals identifies 9 neuroticism-associated loci. Mol Psychiatry. 2016;21:749–57.
Luciano M, Hagenaars SP, Davies G, Hill WD, Clarke T-K, Shirali M, et al. Association analysis in over 329,000 individuals identifies 116 independent variants influencing neuroticism. Nat Genet. 2018;50:6–11.
Okbay A, Baselmans BML, De Neve J-E, Turley P, Nivard MG, Fontana MA, et al. Genetic variants associated with subjective well-being, depressive symptoms, and neuroticism identified through genome-wide analyses. Nat Genet. 2016;48:624–33.
Nagel M, Jansen PR, Stringer S, Watanabe K, de Leeuw CA, Bryois J, et al. Meta-analysis of genome-wide association studies for neuroticism in 449,484 individuals identifies novel genetic loci and pathways. Nat Genet. 2018;50:920–7.
Weissbrod O, Flint J, Rosset S. Estimating SNP-based heritability and genetic correlation in case-control studies directly and with summary statistics. Am J Hum Genet. 2018;103:89–99.
Golan D, Lander ES, Rosset S. Measuring missing heritability: inferring the contribution of common variants. Proc Natl Acad Sci USA. 2014;111:E5272–81.
Munafò MR, Tilling K, Taylor AE, Evans DM, Davey Smith G. Collider scope: when selection bias can substantially influence observed associations. Int J Epidemiol. 2018;47:226–35.
Fry A, Littlejohns TJ, Sudlow C, Doherty N, Allen NE. OP41 The representativeness of the UK Biobank cohort on a range of sociodemographic, physical, lifestyle and health-related characteristics. J Epidemiol Community Health. 2016;70:A26–A26.
Martin AR, Gignoux CR, Walters RK, Wojcik GL, Neale BM, Gravel S, et al. Human demographic history impacts genetic risk prediction across diverse populations. Am J Hum Genet. 2017;100:635–49.
Haro JM, Arbabzadeh-Bouchez S, Brugha TS, de Girolamo G, Guyer ME, Jin R, et al. Concordance of the Composite International Diagnostic Interview Version 3.0 (CIDI 3.0) with standardized clinical assessments in the WHO World Mental Health surveys. Int J Methods Psychiatr Res. 2006;15:167–80.
Kessler RC, Wittchen H-U, Abelson JM, Mcgonagle K, Schwarz N, Kendler KS, et al. Methodological studies of the Composite International Diagnostic Interview (CIDI) in the US national comorbidity survey (NCS). Int J Methods Psychiatr Res. 1998;7:33–55.
Nusslock R, Alloy LB. Reward processing and mood-related symptoms: an RDoC and translational neuroscience perspective. J Affect Disord. 2017;216:3–16.
Meehl PE. Schizotaxia, schizotypy, schizophrenia. Am Psychol. 1962;17:827–38.
Bleuler M. Conception of schizophrenia within the last fifty years and today [abridged]. Proc R Soc Med. 1963;56:945.
Rosenthal D. A suggested conceptual framework. In: Rosenthal D editor. The Genain quadruplets: a case study and theoretical analysis of heredity and environment in schizophrenia. New York, NY, US: Basic Books, xiv; 1963, p. 505–11.
Nussey DH, Wilson AJ, Brommer JE. The evolutionary ecology of individual phenotypic plasticity in wild populations. J Evol Biol. 2007;20:831–44.
Wright AGC, Simms LJ. Stability and fluctuation of personality disorder features in daily life. J Abnorm Psychol. 2016;125:641–56.
Fuemmeler BF, Dedert E, McClernon FJ, Beckham JC. Adverse childhood events are associated with obesity and disordered eating: results from a U.S. population-based survey of young adults. J Trauma Stress. 2009;22:329–33.
Metzler M, Merrick MT, Klevens J, Ports KA, Ford DC. Adverse childhood experiences and life opportunities: shifting the narrative. Child Youth Serv Rev. 2017;72:141–9.
Jaffee SR, Ambler A, Merrick M, Goldman-Mellor S, Odgers CL, Fisher HL, et al. Childhood maltreatment predicts poor economic and educational outcomes in the transition to adulthood. Am J Public Health. 2018;108:1142–7.
Danese A, Tan M. Childhood maltreatment and obesity: systematic review and meta-analysis. Mol Psychiatry. 2014;19:544–54.
Cross-Disorder Group of the Psychiatric Genomics Consortium Identification of risk loci with shared effects on five major psychiatric disorders: a genome-wide analysis. Lancet. 2013;381:1371.
Hill WD, Hagenaars SP, Marioni RE, Harris SE, Liewald DCM, Davies G, et al. Molecular genetic contributions to social deprivation and household income in UK Biobank. Curr Biol. 2016;26:3083–9.
Acknowledgements
We thank the members of the UK Biobank Mental Health Genetics Group for their valuable discussion and feedback on this work. We are also deeply indebted to the scientists involved in the construction of the UK Biobank, and to the investigators who comprise the PGC. Finally, we thank the hundreds of thousands of subjects who have shared their life experiences with investigators in the UK Biobank and the PGC. This research has been conducted using the UK Biobank Resource, as an approved extension to application 16577 (Dr Breen). This study represents independent research funded by the National Institute for Health Research (NIHR) Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King’s College London. The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health and Social Care. High performance computing facilities were funded with capital equipment grants from the GSTT Charity (TR130505) and Maudsley Charity (980). WJP was funded by NWO Veni grant 91619152. KLP acknowledges funding from the Alexander von Humboldt Foundation. KWC was funded in part by the National Institute of Mental Health (T32MH017119). NRW acknowledges funding from the Australian National Health and Medical Research Council (1078901 and 1087889). PGC has received major funding from the US National Institute of Mental Health and the US National Institute of Drug Abuse (U01 MH109528 and U01 MH1095320).
Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium
Naomi R. Wray17,18, Stephan Ripke19,20,21, Manuel Mattheisen22,23,24, Maciej Trzaskowski17, Enda M. Byrne17, Abdel Abdellaoui25, Mark J. Adams26, Esben Agerbo27,28,29, Tracy M. Air30, Till F. M. Andlauer31,32, Silviu-Alin Bacanu33, Marie Bækvad-Hansen29,34, Aartjan T. F. Beekman35, Tim B. Bigdeli33,36, Elisabeth B. Binder31,37, Julien Bryois38, Henriette N. Buttenschøn29,39,40, Jonas Bybjerg-Grauholm29,34, Na Cai41,42, Enrique Castelao43, Jane Hvarregaard Christensen24,29,40, Toni-Kim Clarke26, Jonathan R. I. Coleman44, Lucía Colodro-Conde45, Baptiste Couvy-Duchesne18,46, Nick Craddock47, Gregory E. Crawford48,49, Gail Davies50, Ian J. Deary50, Franziska Degenhardt51, Eske M. Derks45, Nese Direk52,53, Conor V. Dolan25, Erin C. Dunn54,55,56, Thalia C. Eley44, Valentina Escott-Price57, Farnush Farhadi Hassan Kiadeh58, Hilary K. Finucane59,60, Jerome C. Foo61, Andreas J. Forstner51,62,63,64, Josef Frank61, Héléna A. Gaspar44, Michael Gill65, Fernando S. Goes66, Scott D. Gordon45, Jakob Grove24,29,40,67, Lynsey S. Hall26,68, Christine Søholm Hansen29,34, Thomas F. Hansen69,70,71, Stefan Herms51,63, Ian B. Hickie72, Per Hoffmann51,63, Georg Homuth73, Carsten Horn74, Jouke-Jan Hottenga25, David M. Hougaard29, David M. Howard26,44, Marcus Ising75, Rick Jansen35, Ian Jones76, Lisa A. Jones77, Eric Jorgenson78, James A. Knowles79, Isaac S. Kohane80,81,82, Julia Kraft20, Warren W. Kretzschmar83, Zoltán Kutalik84,85, Yihan Li83, Penelope A. Lind45, Donald J. MacIntyre86,87, Dean F. MacKinnon66, Robert M. Maier18, Wolfgang Maier88, Jonathan Marchini89, Hamdi Mbarek25 Patrick McGrath90, Peter McGuffin44, Sarah E. Medland45, Divya Mehta18,91, Christel M. Middeldorp25,92,93, Evelin Mihailov94, Yuri Milaneschi35, Lili Milani94, Francis M. Mondimore66, Grant W. Montgomery17, Sara Mostafavi95,96, Niamh Mullins44, Matthias Nauck97,98, Bernard Ng96, Michel G. Nivard25, Dale R. Nyholt99, Paul F. O’Reilly44, Hogni Oskarsson100, Michael J. Owen76, Jodie N. Painter45, Carsten Bøcker Pedersen27,28,29, Marianne Giørtz Pedersen27,28,29, Roseann E. Peterson33,101, Erik Pettersson38, Wouter J. Peyrot35, Giorgio Pistis43, Danielle Posthuma102,103, Jorge A. Quiroz104, Per Qvist24,29,40, John P. Rice105, Brien P. Riley33, Margarita Rivera44,106, Saira Saeed Mirza52, Robert Schoevers107, Eva C. Schulte108,109, Ling Shen78, Jianxin Shi110, Stanley I. Shyn111, Engilbert Sigurdsson112, Grant C. B. Sinnamon113, Johannes H. Smit35, Daniel J. Smith114, Hreinn Stefansson115, Stacy Steinberg115, Fabian Streit61, Jana Strohmaier61, Katherine E. Tansey116, Henning Teismann117, Alexander Teumer118, Wesley Thompson29,70,119,120, Pippa A. Thomson121, Thorgeir E. Thorgeirsson115, Matthew Traylor122, Jens Treutlein61, Vassily Trubetskoy20, Andrés G. Uitterlinden123, Daniel Umbricht124, Sandra Van der Auwera125, Albert M. van Hemert126, Alexander Viktorin38, Peter M. Visscher17,18, Yunpeng Wang29,70,120, Bradley T. Webb127, Shantel Marie Weinsheimer29,70, Jürgen Wellmann117, Gonneke Willemsen25, Stephanie H. Witt61, Yang Wu17, Hualin S. Xi128, Jian Yang18,129, Futao Zhang17, Volker Arolt130, Bernhard T. Baune131,132,133, Klaus Berger117, Dorret I. Boomsma25, Sven Cichon51,63,134,135, Udo Dannlowski130, E. J. C. de Geus25,136, J. Raymond DePaulo66, Enrico Domenici137, Katharina Domschke138,139, Tõnu Esko21,94, Hans J. Grabe125, Steven P. Hamilton140, Caroline Hayward141, Andrew C. Heath105, Kenneth S. Kendler33, Stefan Kloiber75,142,143, Glyn Lewis144, Qingqin S. Li145, Susanne Lucae75, Pamela A. F. Madden105, Patrik K. Magnusson38, Nicholas G. Martin45, Andrew M. McIntosh26,50, Andres Metspalu94,146, Ole Mors29,147, Preben Bo Mortensen27,28,29,40, Bertram Müller-Myhsok31,148,149, Merete Nordentoft29,150, Markus M. Nöthen51, Michael C. O’Donovan76, Sara A. Paciga151, Nancy L. Pedersen38, Brenda W. J. H. Penninx35, Roy H. Perlis54,152, David J. Porteous121, James B. Potash153, Martin Preisig43, Marcella Rietschel61, Catherine Schaefer78, Thomas G. Schulze61,109,154,155,156, Jordan W. Smoller54,55,56, Kari Stefansson115,157, Henning Tiemeier52,158,159, Rudolf Uher160, Henry Völzke118, Myrna M. Weissman90,161, Thomas Werge29,70,162, Cathryn M. Lewis44,163, Douglas F. Levinson164, Gerome Breen44,165, Anders D. Børglum24,29,40, Patrick F. Sullivan38,166,167
Author information
Authors and Affiliations
Consortia
Corresponding authors
Ethics declarations
Conflict of interest
The authors declare that they have no conflict of interest.
Additional information
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Consortium members are listed at the end of the paper.
Supplementary information
Rights and permissions
About this article
Cite this article
Coleman, J.R.I., Peyrot, W.J., Purves, K.L. et al. Genome-wide gene-environment analyses of major depressive disorder and reported lifetime traumatic experiences in UK Biobank. Mol Psychiatry 25, 1430–1446 (2020). https://doi.org/10.1038/s41380-019-0546-6
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1038/s41380-019-0546-6
This article is cited by
-
Genotype × environment interactions in gene regulation and complex traits
Nature Genetics (2024)
-
Principled distillation of UK Biobank phenotype data reveals underlying structure in human variation
Nature Human Behaviour (2024)
-
Estimating the direct effects of the genetic liabilities to bipolar disorder, schizophrenia, and behavioral traits on suicide attempt using a multivariable Mendelian randomization approach
Neuropsychopharmacology (2024)
-
Using Alternative Definitions of Controls to Increase Statistical Power in GWAS
Behavior Genetics (2024)
-
Genetic predisposition for negative affect predicts mental health burden during the COVID-19 pandemic
European Archives of Psychiatry and Clinical Neuroscience (2024)