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[Preprint]. 2025 May 19:2025.05.16.648988.
doi: 10.1101/2025.05.16.648988.

Robust inference and widespread genetic correlates from a large-scale genetic association study of human personality

Ted Schwaba  1 Margaret L Clapp Sullivan  2 Wonuola A Akingbuwa  3   4 Kerli Ilves  5 Peter T Tanksley  6 Camille M Williams  7 Yavor Dragostinov  2   8 Wangjingyi Liao  9 Lindsay S Ackerman  1 Josephine C M Fealy  1 Gibran Hemani  10   11 Javier de la Fuente  2 Priya Gupta  12 Murray B Stein  13 Joel Gelernter  12 Daniel F Levey  12 Urmo Võsa  5 Liisi Ausmees  14 Anu Realo  14   15   16 Estonian Biobank Research TeamMariliis Vaht  5 Jüri Allik  14 Tõnu Esko  5 René Mõttus  14   17 Uku Vainik  5   14   18 Gudrun A Jonsdottir  19 Gudmar Thorleifsson  19 Árni Freyr Gunnarsson  19 Gyda Bjornsdottir  19 Thorgeir E Thorgeirsson  19 Hreinn Stefansson  19 Kari Stefansson  19 Rosa Cheesman  20   21 Qi Qin  20 Elizabeth C Corfield  10   21   22 Helga Ask  20   21 Fartein Ask Torvik  20   23 Eivind Ystrom  20   21   24 Martin Tesli  25   26 Dorret I Boomsma  27 Eco J C de Geus  3   4 Jouke-Jan Hottenga  3 Dener Cardoso Melo  28 Harold Snieder  29 Catharina A Hartman  17   28 Charley Xia  17   30 Archie Campbell  31 Michelle Luciano  17 Ian J Deary  17   30 W David Hill  17   30 Seon-Kyeong Jang  32 Scott I Vrieze  33   34 Gonçalo Abecasis  35 Michelle K Lupton  36   37   38 Brittany L Mitchell  36   37   38 Petra V Viher  36 Lucía Colodro-Conde  36 Nicholas G Martin  36 Sarah E Medland  36 Eske M Derks  36 Briar Wormington  36 Jaakko Kaprio  39 Karri Silventoinen  40 Teemu Palviainen  39 Agnieszka Gidziela  9 Kaili Rimfeld  41   42 Robert Plomin  42 Margherita Malanchini  9 Danielle M Dick  43   44 Fazil Aliev  44 COGA Collaborators, The Spit for Science Working GroupLaura W Wesseldijk  45   46   47 Fredrik Ullén  45   46 Miriam A Mosing  46   48   49 Henry R Kranzler  50 Yaira Nunez  51 Sarah Beck  51 Renato Polimanti  51 Tobias Edwards  33 Alexandros Giannelis  33 Emily A Willoughby  33 James J Lee  33 Matt McGue  33 Antonio Terracciano  52   53 Michele Marongiu  54 Edoardo Fiorillo  54 Francesco Cucca  55 Angelina R Sutin  56 Peter J van der Most  29 Albertine J Oldehinkel  28 Tina Kretschmer  57 Andrey A Shabalin  58 Anna R Docherty  58 Robert F Krueger  33 Colin D Freilich  33 Binisha H Mishra  59   60   61 Terho Lehtimäki  59   60   61 Olli T Raitakari  62   63   64   65 Mika Kähönen  60   66 Aino Saarinen  67 Henrik Dobewall  68 Liisa Keltikangas-Järvinen  67 Klaus Berger  69 Marisol Herrera-Rivero  69   70 Fabian Streit  71   72   73 Swapnil Awasthi  74 Stephanie H Witt  75 Johanna Tuhkanen  76 Katri Räikkönen  76 Johan G Eriksson  77   78   79 Jari Lahti  76   78 Gail Davies  30 Paul Redmond  30 Adele Taylor  30 Janie Corley  30 Tom C Russ  80   81 Marina Ciullo  82 Teresa Nutile  82 Jun Ding  83 Yong Qian  83 Toshiko Tanaka  83 Luigi Ferrucci  83 Lea Zillich  75 Lea Sirignano  75 K Paige Harden  2 Erhan Genç  84 Patrick D Gajewski  85 Stephan Getzmann  85 Christoph Fraenz  84 Javier E Schneider Peñate  86 Stefanie Lis  87   88 Alisha S M Hall  75   89   90 Christian Schmahl  87 Sabine C Herpertz  91 Abdel Abdellaoui  47   92 Michel G Nivard  10   11 Elliot M Tucker-Drob  2   8
Affiliations

Robust inference and widespread genetic correlates from a large-scale genetic association study of human personality

Ted Schwaba et al. bioRxiv. .

Abstract

Personality traits describe stable differences in how individuals think, feel, and behave and how they interact with and experience their social and physical environments. We assemble data from 46 cohorts including 611K-1.14M participants with European-like and African-like genomes for genome-wide association studies (GWAS) of the Big Five personality traits (extraversion, agreeableness, conscientiousness, neuroticism, and openness to experience), and data from 51K participants for within-family GWAS. We identify 1,257 lead genetic variants associated with personality, including 823 novel variants. Common genetic variants explain 4.8%-9.3% of the variance in each trait, and 10.5%-16.2% accounting for measurement unreliability. Genetic effects on personality are highly consistent across geography, reporter (self vs. close other), age group, and measurement instrument, and we find minimal spousal assortment for personality in recent history. In stark contrast to many other social and behavioral traits, within-family GWAS and polygenic index analyses indicate little to no shared environmental confounding in genetic associations with personality. Polygenic prediction, genetic correlation, and Mendelian randomization analyses indicate that personality genetics have widespread, potentially causal associations with a wide range of consequential behaviors and life outcomes. The genetic architecture of personality is robust and fundamental to being a human.

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Figures

Figure 1.
Figure 1.. Manhattan plots of Genome-Wide Associations for each Big Five personality trait (A-E) and genetic correlations across traits (F).
Genome wide significance is denoted with a red line at p = 5×10−8. A selection of genes containing or nearby the most significant lead SNPs are annotated in each panel (Supplementary Tables S23–S27). Genetic correlations in panel F were estimated among EUR participants using LDSC; standard errors are in parentheses.
Figure 2.
Figure 2.. Polygenic prediction and additional genetic associations.
Ext = Extraversion. Agr = Agreeableness. Con = Conscientiousness. Neu = Neuroticism. Ope = Openness to Experience. Panel A depicts standardized prediction of phenotypic personality trait scores among EUR and AFR participants in five cohorts using PGI weights derived from the EUR population-level GWAS. In panel B, betas for continuous traits are standardized and have point estimates depicted with circles, and betas for binary traits are logistic betas and have point estimates depicted with diamonds; percentage affirmative responses are noted in parentheses. † = questions asked only among a subgroup of participants (see Supplementary Text). Panel C depicts correlations between PGIs for each pair of family members. ‡ = Educational Attainment estimates come from Torvik et al. (2022), estimated across spouses in the MoBa cohort. In panel D, accelerometer activity indexes physical movement across a 24-hour period; see Grotzinger et al. (2022b) for complete details. Panel E depicts associations between PGI and census area of residence at age 50+, controlling for birthplace in addition to sex, age, array, and genetic principal components. Only associations that are significant at p < .01 after application of Benjamini-Hochberg false-discovery rate correction and sign-concordant within sibship are plotted. In all panels, error bars depict 95% confidence intervals. * = p < .01.
Figure 3.
Figure 3.. Genetic correlations between the Big Five personality traits and 67 behaviors and outcomes across 9 domains.
E = Extraversion. A = Agreeableness. C = Conscientiousness. N = Neuroticism. O = Openness to experience. COVID = Coronavirus disease. HDL = High-density lipoprotein. LDL = Low-density lipoprotein. ADHD = Attention deficit hyperactivity disorder. Letters corresponding to personality traits represent correlation point estimates. Error bars represent 95% confidence intervals. Associations not significant at p < .01 are depicted in gray. Associations estimated using LDSC among EUR participants. Full description of each behavior and outcome are available in Supplementary Tables S31 and S32.
Figure 4.
Figure 4.. Evaluating environmental confounding in genetic associations with personality.
In panel A, the magnitude of PGI prediction from the EUR population-level GWAS is presented for population-level and within-family analyses in two cohorts: Netherlands Twin Registry (NTR) and Twins Early Development Study (TEDS). In panel B, the magnitude of total PGI prediction from the EUR population-level GWAS among offspring in the deCODE cohort (with significance asterisks below the corresponding bar) is decomposed into directly transmitted and indirectly transmitted (non-inherited, with significance asterisks above the corresponding bar) genetic effects from parents (Supplementary Table S39). Comparison estimates for Educational Attainment (EA) come from a PGI constructed from the Okbay et al. (2022) GWAS of EA with deCODE and 23&Me cohorts held out. In panel C, h2SNP estimates estimated with LDSC from the within-family GWAS (“Wit.”) are presented alongside full EUR population-level GWAS (“Full pop.,” Table 1) and matched population-level (“Pop.”) GWAS in cohorts that contributed to within-family GWAS (Supplementary Table S42). rg below each pair of traits indicates their genetic correlation estimated with LDSC, with deviation from rg = 1 tested using a nested chi-square model in Genomic SEM. p-values above each pair of traits indicates results of a test for differences in heritability between population and within-family estimates. In all panels, error bars depict 95% confidence intervals and standard errors are in parentheses. ns = p ≥ .05. * = p < .05. ** = p < .01. *** = p < .001.

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