Personality can be thought of as a set of characteristics that influence people's thoughts, feelings and behavior across a variety of settings. Variation in personality is predictive of many outcomes in life, including mental health. Here we report on a meta-analysis of genome-wide association (GWA) data for personality in 10 discovery samples (17 375 adults) and five in silico replication samples (3294 adults). All participants were of European ancestry. Personality scores for Neuroticism, Extraversion, Openness to Experience, Agreeableness and Conscientiousness were based on the NEO Five-Factor Inventory. Genotype data of ∼2.4M single-nucleotide polymorphisms (SNPs; directly typed and imputed using HapMap data) were available. In the discovery samples, classical association analyses were performed under an additive model followed by meta-analysis using the weighted inverse variance method. Results showed genome-wide significance for Openness to Experience near the RASA1 gene on 5q14.3 (rs1477268 and rs2032794, P2.8 × 10 -8 and 3.1 × 10 -8) and for Conscientiousness in the brain-expressed KATNAL2 gene on 18q21.1 (rs2576037, P4.9 × 10 -8). We further conducted a gene-based test that confirmed the association of KATNAL2 to Conscientiousness. In silico replication did not, however, show significant associations of the top SNPs with Openness and Conscientiousness, although the direction of effect of the KATNAL2 SNP on Conscientiousness was consistent in all replication samples. Larger scale GWA studies and alternative approaches are required for confirmation of KATNAL2 as a novel gene affecting Conscientiousness.
Bibliographical noteFunding Information:
Abbreviations: BLSA, Baltimore Longitudinal Study of Aging; EGPUT, Estonian Genome Project of University of Tartu; ERF, Erasmus Rucphen Family; GWAS, genome-wide association studies; HBCS, Helsinki Birth Cohort Study; HWE, Hardy– Weinberg equilibrium; LBC, Lothian Birth Cohort; MAF, minor allele frequency; NAG/IRPG, Nicotine Addiction Genetics/ Interactive Research Project Grant; NTR/NESDA, Netherlands Twin Register/Netherlands Study of Depression and Anxiety; QIMR, Queensland Institute of Medical Research; SAGE, Study of Addiction: Genetics and Environment; s.d., standard deviation; SNP, single-nucleotide polymorphism; —, no threshold applied.
Abbreviations: BLSA, Baltimore Longitudinal Study of Aging; EGPUT, Estonian Genome Project of University of Tartu; ERF, Erasmus Rucphen Family; GWAS, genome-wide association studies; HBCS, Helsinki Birth Cohort Study; LBC, Lothian Birth Cohort; NAG/IRPG, Nicotine Addiction Genetics/Interactive Research Project Grant; NTR/NESDA, Netherlands Twin Register/Netherlands Study of Depression and Anxiety; QIMR, Queensland Institute of Medical Research; SAGE, Study of Addiction: Genetics and Environment; s.d., standard deviation.
Addiction: Genetics and Environment (SAGE) is part of the Gene Environment Association Studies initiative funded by the National Human Genome Research Institute. The sample consists of Diagnostic and Statistical Manual of Mental Disorders, 4th Edition alcohol-dependent cases and -nondependent controls.39 The original SAGE sample included 4121 unrelated individuals. Of these, 2223 subjects had data available from the NEO Five-Factor Inventory (NEO-FFI). We removed 476 subjects owing to non-European ancestry, eight individuals were removed owing to missing genotypes and 139 were removed because their genotyping consent did not include the use of their personality data. This resulted in a final sample size of 1600. Of these 1600, 60.1% were women. The mean age of all participants was 39.6 (s.d. = 9), of the men 40.4 (s.d. = 10) and of the women 39.0 (s.d. = 9).
We would like to thank the individuals who participated in the studies. Meta-analysis and statistical analyses for the NAG/IPRG, QIMR and NTR/NESDA studies were carried out on the Genetic Cluster Computer (http://www.geneticcluster.org), which is financially supported by the Netherlands Organization for Scientific Research (NWO 480-05-003). 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 No. NO1-AG-1-2109 to the SardiNIA (‘ProgeNIA’) team. NTR/NESDA: We acknowledge financial support from the Netherlands Organization for Scientific Research (NWO): Grants 575-25-006, 480-04-004, 904-61-090; 904-61-193, 400-05-717 and Spinozapremie SPI 56-464-14192. MHMdeM is financially supported by ZonMW (Addiction) Grant No. 311-60008. We further acknowledge financial support from the Center for Medical Systems Biology (NWO Genomics), the Centre for Neurogenomics and Cognitive Research (CNCR-VU); EU/QLRT-2001-01254; NIMH R01 MH059160; Geestk-racht program of ZonMW (10-000-1002); matching funds from universities and mental healthcare institutes involved in NESDA. Genotyping was funded by the Genetic Association Information Network (GAIN) of the Foundation for the US National Institutes of Health, and analysis was supported by grants from Genetic Association Information Network and the NIMH (MH081802). Genotype data were obtained from dbGaP (http://www.ncbi.nlm.nih.gov/ dbgap, accession number phs000020.v1.p1). ERF: The genotyping for the ERF study was supported by EUROSPAN (European Special Populations Research Network) and the European Commission FP6 STRP Grant (018947; LSHG-CT-2006-01947). The ERF study was further supported by grants from the Netherlands Organization for Scientific Research, Erasmus MC, the Centre for Medical Systems Biology (CMSB) and the Netherlands Brain Foundation (HersenStichting Nederland). We are grateful to all patients and their relatives, general practitioners and neurologists for their contributions and to P Veraart for her help in genealogy, Jeannette Vergeer for the supervision of the laboratory work and P Snijders for his help in data collection. SAGE: 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 under GEI. Assistance with phenotype harmonization and genotype cleaning, as well as with general study coordination, was provided by the Gene Environment Association Studies initiative Coordinating Center (U01 HG004446). Assistance with data cleaning was provided by the National Center for Biotechnology Information. Support for collection of data sets and samples was provided by the Collaborative Study on the Genetics of Alcoholism (U10 AA008401), the Collaborative Genetic Study of Nicotine Dependence (P01 CA089392) and the Family Study of Cocaine Dependence (R01 DA013423). 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 geno-typing for studying the genetic contributions to human disease’ (HHSN268200782096C). The Collaborative Study on the Genetics of Alcoholism, principal investigators: B Porjesz, V Hesselbrock, H Edenberg, LJ 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 (LJ 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, 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 project is a collaborative research group and part of the NIDA Genetics Consortium. Subject collection was supported by NIH Grant CA89392 (PI—LJ Bierut) from the National Cancer Institute. Genotyping work at Perle-gen Sciences was performed under NIDA Contract HHSN271200477471C. Phenotypic and genotypic data are stored in the NIDA Center for Genetic Studies (NCGS) at http://zork.wustl.edu/ under NIDA Contract HHSN271200477451C (PIs—J Tischfield and J Rice). Genotyping services were also provided by the Center for Inherited Disease Research (CIDR). CIDR is fully funded through a federal contract from the National Institutes of Health to The Johns Hopkins University, Contract No. HHSN268200782096. 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. Lead investigators directing data collection are LJ Bierut, Naomi Breslau, Dorothy Hatsukami and Eric Johnson. We thank Heidi Kromrei and Tracey Richmond for their assistance in data collection. 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 (EuroS-TRESS), the Wellcome Trust (Grant No. 89061/Z/09/Z and 089062/Z/09/Z) and the Signe and Ane Gyllen-berg 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. QIMR: We thank Marlene Grace and Ann Eldridge for sample collection; Anjali Henders, Megan Campbell, Lisa Bowdler, Steven Crooks and staff of the Molecular Epidemiology Laboratory for sample processing and preparation; Harry Beeby, David Smyth and Daniel Park for IT support. We acknowledge support from the Australian Research Council (A7960034, A79906588, A79801419, DP0212016, DP0343921), Beyond Blue and the Borderline Personality Disorder Research Foundation. Genotyping was funded by the National Health and Medical Research Council (Medical Bioinformatics Genomics Proteomics Program, 389891). Further, we gratefully acknowledge Drs Dale R Nyholt and especially Scott Gordon for their substantial efforts involving the QC and preparation of the QIMR and NAG/IRPG GWA data sets. Dr Nyholt also contributed 8% of the NAG/IRPG GWA cohort (NHMRC IDs 339462, 442981, 389938, 496739). LBC1936: We thank David Liewald and Paul Red-mond 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 genotyping was performed; staff at the Lothian Health Board, and the 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). GWA 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). Baltimore Longitudinal Study of Aging: 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, ECO-GENE (No. 205419, EBC)) and OpenGENE. AM and TE also received targeted financing from Estonian Government SF0180142s08 and by EU via the European Regional Development Fund, in the frame of Centre of Excellence in Genomics. The genotyping of the Estonian Genome Project samples were performed in Estonian Biocentre Genotyping Core Facility, AM and TE thank Mari Nelis and Viljo Soo for their contributions. AR and JA were supported by a grant from the Estonian Ministry of Science and Education (SF0180029s08).
- Five-Factor Model
- genetic variants
- genome-wide association