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Genome-wide analyses for personality traits identify six genomic loci and show correlations with psychiatric disorders

Nature Genetics volume 49, pages 152–156 (2017)Cite this article

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Abstract

Personality is influenced by genetic and environmental factors1 and associated with mental health. However, the underlying genetic determinants are largely unknown. We identified six genetic loci, including five novel loci2,3, significantly associated with personality traits in a meta-analysis of genome-wide association studies (N = 123,132–260,861). Of these genome-wide significant loci, extraversion was associated with variants in WSCD2 and near PCDH15, and neuroticism with variants on chromosome 8p23.1 and in L3MBTL2. We performed a principal component analysis to extract major dimensions underlying genetic variations among five personality traits and six psychiatric disorders (N = 5,422–18,759). The first genetic dimension separated personality traits and psychiatric disorders, except that neuroticism and openness to experience were clustered with the disorders. High genetic correlations were found between extraversion and attention-deficit–hyperactivity disorder (ADHD) and between openness and schizophrenia and bipolar disorder. The second genetic dimension was closely aligned with extraversion–introversion and grouped neuroticism with internalizing psychopathology (e.g., depression or anxiety).

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Figure 1: Manhattan plots for personality traits in the combined sample of 23andMe and GPC data (discovery–stage1 sample).
Figure 2: Regional association plot.
Figure 3: Genetic correlations between personality traits (23andMe sample) and psychiatric disorders.

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Acknowledgements

We thank the customers, research participants and employees of 23andMe for making this work possible. This project was funded by National Institute of Mental Health R01MH100351 (M.-T.L., N.S. and C.-H.C.), NARSAD Young Investigator award (C.-H.C.), South-East Norway Regional Health Authority (2016-064) (O.B.S.), and Research Council of Norway through a FRIPRO Mobility Grant, contract no. 251134 (Y.W.). The FRIPRO Mobility grant scheme (FRICON) is cofunded by the European Union's Seventh Framework Programme for research, technological development and demonstration under Marie Curie grant agreement no. 608695. D.J.S. is supported by a Lister Institute Prize fellowship. The research leading to deCODE results was supported in part by the US National Institutes of Health NIDA (R01-DA017932 and R01-DA034076) and the Innovative Medicines Initiative Joint Undertaking under grant agreement no. 115008, of which resources are composed of a European Federation of Pharmaceutical Industries and Associations (EFPIA) in-kind contribution and financial contribution from the European Union's Seventh Framework Programme (FP7/2007-2013) and EU-funded FP7-People-2011-IAPP grant PsychDPC (GA 28613) (H.S., G.B., T.E.T. and K.S.).

Author information

Authors and Affiliations

  1. Department of Radiology, University of California, San Diego, La Jolla, California, USA.,

    Min-Tzu Lo, Chun-Chieh Fan, Andrew Schork, Karolina Kauppi, Nilotpal Sanyal, Linda K McEvoy, Anders M Dale & Chi-Hua Chen

  2. 23andMe, Inc., Mountain View, California, USA

    David A Hinds & Joyce Y Tung

  3. Department of Psychiatry, University of California, San Diego, La Jolla, California, USA.,

    Carol Franz & Anders M Dale

  4. Department of Cognitive Science, University of California, San Diego, La Jolla, California, USA.,

    Chun-Chieh Fan & Andrew Schork

  5. Department of Neurosciences, University of California, San Diego, La Jolla, California, USA.,

    Yunpeng Wang, Dominic Holland & Anders M Dale

  6. NORMENT, KG Jebsen Centre for Psychosis Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway

    Yunpeng Wang, Olav B Smeland & Ole A Andreassen

  7. Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway

    Yunpeng Wang, Olav B Smeland & Ole A Andreassen

  8. Department of Radiation Sciences, Umea University, Sweden

    Karolina Kauppi

  9. MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, UK

    Valentina Escott-Price & Michael O'Donovan

  10. Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK

    Daniel J Smith

  11. deCODE Genetics/Amgen, Reykjavik, Iceland

    Hreinn Stefansson, Gyda Bjornsdottir, Thorgeir E Thorgeirsson & Kari Stefansson

Authors
  1. Min-Tzu Lo
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Contributions

C.-H.C., M.-T.L. and O.A.A. designed the study. M.-T.L. and C.-H.C. analyzed data and wrote the manuscript. D.A.H. and J.Y.T. analyzed the 23andMe data. V.E.-P., D.J.S. and M.O. analyzed the UK Biobank data. H.S., G.B., T.E.T. and K.S. analyzed the deCODE data. C.F., C.-C.F., Y.W., O.B.S., A.S., D.H., K.K., N.S., L.K.M., A.M.D. and O.A.A. contributed to manuscript preparation. All authors commented on and approved the manuscript.

Corresponding author

Correspondence to Chi-Hua Chen.

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Competing interests

H.S., T.E.T., G.B. and K.S. are employees of deCODE Genetics/Amgen. D.A.H. and J.Y.T. are employees of 23andMe, Inc.

Integrated supplementary information

Supplementary Figure 1 Genetic correlations of five personality traits between 23andMe discovery and GPC samples.

(a) The values in the colored squares are genetic correlations (rg); (b) P values of genetic correlations are shown in the table with values less than 0.05 written in bold. Asterisks further denote degree of significance: * P < 0.05; ** P < 0.002 (Bonferroni correction threshold). Note that Bonferroni correction is conservative here because of dependence among these tests. The estimated rg were highly significant (rg = 0.86-0.96), with the exception of agreeableness, for which heritability estimate was too low to allow reliable estimation of rg.

Supplementary Figure 2 SNP concordant test for the top GWAS signals.

The heat map illustrates the proportions of concordant (same direction) effect size for top SNPs (P < 10-4) between phenotypes. The values in the colored squares correspond to the proportions. The range of the total numbers of top SNPs for pairwise phenotypes in concordant test (denominator of the proportion) is 68-412 and the median is 149. The range of the numbers of top SNPs with concordant effect size for pairwise phenotypes in concordant test (numerator of the proportion) is 25-310 and the median is 70. The expected proportion under the null hypothesis is 0.5. Asterisks denote proportions significantly different from 0.5: * P < 0.05; ** P < 0.00091 (Bonferroni correction threshold).

Supplementary Figure 3 Hierarchical clustering for personality traits (23andMe discovery sample) and psychiatric disorders.

The dendrogram shows that two major clusters correspond to the second quadrant versus the first and forth quadrants in the loading plot (Fig. 3b).

Supplementary Figure 4 Regional association and annotation plots for eight LD-independent SNPs identified in the discovery analysis.

The figure shows the distribution of -log10(P value) of SNPs within ± 1 Mb of the significant SNP for conscientiousness, extraversion and neuroticism in the combined analysis. The most significant SNP is shown as a red diamond. Many genes are located in the neighborhood of 8p23.1 and 22q13.2 (c, g and h). The upper and middle panels have the same format as Fig. 2 (see Online Methods). In the bottom panel, annotation tracks were generated by a web-based application, LocusTrack1, and retrieved from UCSC Genome Browser on Human hg19 assembly. The SNP track displays the top 5% associated SNPs within the region and is depicted by colors of association, r2, with the top SNP. The Gene track shows gene annotation including protein-coding, non-coding and pseudo- genes from GENCODE version 19. The GWAS track exhibits SNPs in NHGRI (National Human Genome Research Institute) Catalog of published GWAS. The Conservation track reflects 100 vertebrate conserved elements in terms of transformed log-odds scores (logarithm of probability of under the conserved model relative to the non-conserved model) from 0 to 10002. The TFBS track contains computational transcription factor binding sites conserved across human, mouse and rat. The Brain histone track maps the genome-wide distribution of H3K4me3 (trimethylated histone H3K4) in neuronal and non-neuronal prefrontal cortex chromatin3. DNaseI HS shows DNaseI hypersensitivity site related to chromatin accessibility for transcription factors binding4. The Chromatin track displays regulatory activity predictions for 15 states in H1 human embryonic stem cells5.

Supplementary Figure 5 Quantile–quantile plots of covariate-adjusted personality phenotypes in the 23andMe discovery sample.

Supplementary Figure 6 Quantile–quantile plots and genomic inflation factors (λ) for the 23andMe discovery sample.

The genomic inflation factors are close to 1, indicating that the GWAS results are not inflated by population stratification or cryptic relatedness. λ close to 1 is consistent with the Q-Q plots lying along the expected null line for large values of P (P > 10-3).

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–6, Supplementary Tables 1–5, and Supplementary Note (PDF 2185 kb)

Supplementary Data Set 1

Agreeableness (TXT 640 kb)

Supplementary Data Set 2

Conscientiousness (TXT 777 kb)

Supplementary Data Set 3

Extraversion (TXT 778 kb)

Supplementary Data Set 4

Neuroticism (TXT 775 kb)

Supplementary Data Set 5

Openness (TXT 776 kb)

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Lo, MT., Hinds, D., Tung, J. et al. Genome-wide analyses for personality traits identify six genomic loci and show correlations with psychiatric disorders. Nat Genet 49, 152–156 (2017). https://doi.org/10.1038/ng.3736

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