The genetic association between personality and major depressi0on or bipolar disorder. A polygenic score analysis using genome-wide association data

C. M. Middeldorp, M. H M De Moor, L. M. McGrath, S. D. Gordon, D. H. Blackwood, P. T. Costa, A. Terracciano, R. F. Krueger, E. J C De Geus, D. R. Nyholt, T. Tanaka, T. Esko, P. A F Madden, J. Derringer, N. Amin, G. Willemsen, J. J. Hottenga, M. A. Distel, M. Uda, S. SannaP. Spinhoven, C. A. Hartman, S. Ripke, P. F. Sullivan, A. Realo, J. Allik, A. C. Heath, M. L. Pergadia, A. Agrawal, P. Lin, R. A. Grucza, E. Widen, D. L. Cousminer, J. G. Eriksson, A. Palotie, J. H. Barnett, P. H. Lee, M. Luciano, A. Tenesa, G. Davies, L. M. Lopez, N. K. Hansell, S. E. Medland, L. Ferrucci, D. Schlessinger, G. W. Montgomery, M. J. Wright, Y. S. Aulchenko, A. C J W Janssens, B. A. Oostra, A. Metspalu, G. R. Abecasis, I. J. Deary, K. Räikkönen, L. J. Bierut, N. G. Martin, N. R. Wray, C. M. Van Duijn, J. W. Smoller, B. W J H Penninx, D. I. Boomsma

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Abstract

The relationship between major depressive disorder (MDD) and bipolar disorder (BD) remains controversial. Previous research has reported differences and similarities in risk factors for MDD and BD, such as predisposing personality traits. For example, high neuroticism is related to both disorders, whereas openness to experience is specific for BD. This study examined the genetic association between personality and MDD and BD by applying polygenic scores for neuroticism, extraversion, openness to experience, agreeableness and conscientiousness to both disorders. Polygenic scores reflect the weighted sum of multiple single-nucleotide polymorphism alleles associated with the trait for an individual and were based on a meta-analysis of genome-wide association studies for personality traits including 13 835 subjects. Polygenic scores were tested for MDD in the combined Genetic Association Information Network (GAIN-MDD) and MDD2000 samples (N=8921) and for BD in the combined Systematic Treatment Enhancement Program for Bipolar Disorder and Wellcome Trust Case-Control Consortium samples (N=6329) using logistic regression analyses. At the phenotypic level, personality dimensions were associated with MDD and BD. Polygenic neuroticism scores were significantly positively associated with MDD, whereas polygenic extraversion scores were significantly positively associated with BD. The explained variance of MDD and BD, ∼0.1%, was highly comparable to the variance explained by the polygenic personality scores in the corresponding personality traits themselves (between 0.1 and 0.4%). This indicates that the proportions of variance explained in mood disorders are at the upper limit of what could have been expected. This study suggests shared genetic risk factors for neuroticism and MDD on the one hand and for extraversion and BD on the other.

Original languageEnglish (US)
Article numbere50
JournalTranslational psychiatry
Volume1
DOIs
StatePublished - 2011

Bibliographical note

Funding Information:
Acknowledgements. This study makes use of data generated by the Wellcome Trust Case–Control Consortium. A full list of the investigators who contributed to the generation of the WTCCC data is available from http://www. wtccc.org.uk. Funding for the WTCCC project was provided by the Wellcome Trust under award 076113. NESDA/NTR: Funding support was provided by the Netherlands Scientific Organization (904-61-090, 904-61-193, 480-04-004, 400-05-717, 912-100-20) Centre for Medical Systems Biology (NWO Genomics), the Neuroscience Campus Amsterdam (NCA) and the EMGO + Institute; the European Union (EU/WLRT-2001-01254), ZonMW (Geestkracht program, 10-000-1002), NIMH (RO1 MH059160) and matching funds from participating institutes in NESDA and NTR. The NTR controls in MDD2000 + were genotyped in the Genomics platform (certified service provider (CSPro(R)) for Illumina) at the LIFE and BRAIN Center, Bonn (funded by NWO-SPI 56-464-1419). Statistical analyses were carried out on the Genetic Cluster Computer (http://www.geneticcluster.org), which is financially supported by the NWO (480-05-003). MHM de Moor and CM Middeldorp are financially supported by the Netherlands Organization for Scientific Research (NWO) (ZonMW Addiction program, grant 31160008, VENI-016-115-035 and VENI grant 916-76-125). MDD2000 + /QIMR: Funding was provided by the Australian National Health and Medical Research Council (241944, 339462, 389927, 389875, 389891, 389892, 389938, 442915, 442981, 496675,496739, 552485, 552498, 613608), the FP-5 GenomEUtwin Project (QLG2-CT-2002-01254), and the US National Institutes of Health (NIH grants AA07535, AA10248, AA13320, AA13321, AA13326, AA14041, MH66206, DA12854, DA019951). A portion of the genotyping on which this study was based (Illumina 370K scans on 4300 individuals) was carried out at the Center for Inherited Disease Research, Baltimore (CIDR), through an access award to our late colleague Dr Richard Todd (Psychiatry, Washington University School of Medicine, St Louis). GW Montgomery is supported by the National Health and Medical Research Council (NHMRC) Fellowship Scheme. NRWray and DR Nyholt are supported by the Australian Research Council Future Fellowship Scheme. The ERF study was supported by grants from The Netherlands Organization for Scientific Research (NWO), Erasmus MC and the Netherlands Genomics Initiative (NGI)-sponsored Center of Medical Systems Biology (CMSB). Funding support for the Study of Addiction: Genetics and Environment (SAGE) was provided through the NIH Genes, Environment and Health Initiative (GEI) (U01 HG004422). SAGE is one of the genome-wide association studies funded as part of the Gene Environment Association Studies (GENEVA) under GEI. Assistance with phenotype harmonization and genotype cleaning, as well as with general study coordination, was provided by the GENEVA Coordinating Center (U01 HG004446). Assistance with data cleaning was provided by the National Center for Biotechnology Information. Support for collection of datasets and samples was provided by the Collaborative Study on the Genetics of Alcoholism (COGA; U10 AA008401), the Collaborative Genetic Study of Nicotine Dependence (COGEND; P01 CA089392) and the Family Study of Cocaine Dependence (FSCD; R01 DA013423, R01 DA019963). Funding support for genotyping, which was performed at the Johns Hopkins University Center for Inherited Disease Research, was provided by the NIH GEI (U01HG004438), the National Institute on Alcohol Abuse and Alcoholism, the National Institute on Drug Abuse and the NIH contract ‘High throughput genotyping for studying the genetic contributions to human disease’ (HHSN268200782096C). The Collaborative Study on the Genetics of Alcoholism (COGA) Principal Investigators: B Porjesz, V Hesselbrock, H Edenberg, L Bierut, includes 10 different centers: University of Connecticut (V Hesselbrock); Indiana University (HJ Edenberg, J Nurnberger Jr., T Foroud); University of Iowa (S Kuperman, J Kramer); SUNY Downstate (B Porjesz); Washington University in St Louis (L Bierut, A Goate, J Rice, K Bucholz); University of California at San Diego (M Schuckit); Rutgers University (J Tischfield); Southwest Foundation (L Almasy), Howard University (R Taylor) and Virginia Commonwealth University (D Dick). A Parsian and M Reilly are the NIAAA Staff Collaborators. We continue to be inspired by our memories of Henri Begleiter and Theodore Reich, founding PI and Co-PI of COGA, and also owe a debt of gratitude to other past organizers of COGA, including Ting-Kai Li, currently a consultant with COGA, P Michael Conneally, Raymond Crowe and Wendy Reich, for their critical contributions. This national collaborative study is supported by NIH Grant U10AA008401 from the National Institute on Alcohol Abuse and Alcoholism (NIAAA) and the National Institute on Drug Abuse (NIDA). The Collaborative Genetic Study of Nicotine Dependence (COGEND) project is a collaborative research group and part of the NIDA Genetics Consortium. Lead investigators directing data collection are Laura Bierut, Naomi Breslau, Dorothy Hatsukami and Eric Johnson. We thank Heidi Kromrei and Tracey Richmond for their assistance in data collection. In memory of Theodore Reich, founding Principal Investigator of COGEND, we are indebted to his leadership in the establishment and nurturing of COGEND and acknowledge with great admiration his seminal scientific contributions to the field. COGEND is supported by the NIH grant P01CA89392 from the National Cancer Institute. SardiNIA: We acknowledge support from the Intramural Research Program of the NIH, National Institute on Aging. Funding was provided by the National Institute on Aging, NIH contract NO1-AG-1-2109 to the SardiNIA (‘ProgeNIA’) team. HBCS: We acknowledge financial support from the Academy of Finland (grant no. 120315 and 129287 to EW, 1129457 and 1216965 to KR, 120386 and 125876 to JGE), the European Science Foundation (EuroSTRESS), the Wellcome Trust (grant no. 89061/Z/09/Z and 089062/Z/09/Z) and the Signe and Ane Gyllenberg foundation. NAG/IRPG: This study is supported by NIH grants DA12854 (to PAFM), AA07728, AA07580, AA11998, AA13320 and AA13321 (to ACH); and grants from the Australian National Health and Medical Research Council; MLP is supported by DA019951. LBC36: We thank David Liewald and Paul Redmond for technical assistance; the study Secretary Paula Davies; Alan Gow, Michelle Taylor, Janie Corley, Caroline Brett and Caroline Cameron for data collection and data entry; nurses and staff at the Wellcome Trust Clinical Research Facility, where subjects were tested and at the genotyping was performed; staff at the Lothian Health Board and staff at the SCRE Centre, University of Glasgow. The research was supported by a program grant from Research Into Ageing. The research continues with program grants from Help the Aged/Age Concern (The Disconnected Mind). GWAS funding awarded by the Biotechnology and Biological Sciences Research Council (BBSRC) to IJD and AT. ML is a Royal Society of Edinburgh/Lloyds TSB Foundation for Scotland Personal Research Fellow. The study was conducted within the University of Edinburgh Centre for Cognitive Ageing and Cognitive Epidemiology, supported by the (BBSRC), Engineering and Physical Sciences Research Council (EPSRC), Economic and Social Research Council (ESRC) and Medical Research Council (MRC), as part of the cross-council Lifelong Health and Wellbeing Initiative. This work has made use of the resources provided by the Edinburgh Compute and Data Facility (ECDF) (http://www.ecdf.ed.ac.uk/). The ECDF is partially supported by the eDIKT initiative (http://www.edikt.org.uk). BLSA: We acknowledge support from the Intramural Research Program of the NIH, National Institute on Aging. We thank Robert McCrae. EGPUT: AM and TE received support from FP7 grants (201413 ENGAGE, 212111 BBMRI, ECOGENE (no. 205419, EBC)). AM and TE also received targeted financing from Estonian Government SF0180142s08 and by EU through the European Regional Development Fund, in the frame of Centre of Excellence in Genomics. The genotyping of the Estonian Genome Project samples was performed in Estonian Biocentre Genotyping Core Facility, AM and TE thank Mari Nelis and Viljo Soo for their contributions. A Realo and J Allik are supported by a grant from the Estonian Ministry of Science and Education (SF0180029s08). STEP-BD: JH Barnett was funded by the Parke-Davis Exchange Fellowship. JW Smoller and LM McGrath were supported in part by NIMH grant R01 MH-079799 (Dr Smoller, PI).

Keywords

  • bipolar disorder
  • genetic correlation
  • genome-wide association
  • personality-major depression
  • polygenic score analysis

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