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Association analysis in over 329,000 individuals identifies 116 independent variants influencing neuroticism


Neuroticism is a relatively stable personality trait characterized by negative emotionality (for example, worry and guilt)1; heritability estimated from twin studies ranges from 30 to 50%2, and SNP-based heritability ranges from 6 to 15%3,4,5,6. Increased neuroticism is associated with poorer mental and physical health7,8, translating to high economic burden9. Genome-wide association studies (GWAS) of neuroticism have identified up to 11 associated genetic loci3,4. Here we report 116 significant independent loci from a GWAS of neuroticism in 329,821 UK Biobank participants; 15 of these loci replicated at P < 0.00045 in an unrelated cohort (N = 122,867). Genetic signals were enriched in neuronal genesis and differentiation pathways, and substantial genetic correlations were found between neuroticism and depressive symptoms (rg = 0.82, standard error (s.e.) = 0.03), major depressive disorder (MDD; rg = 0.69, s.e. = 0.07) and subjective well-being (rg = –0.68, s.e. = 0.03) alongside other mental health traits. These discoveries significantly advance understanding of neuroticism and its association with MDD.

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Change history

  • 29 January 2019

    In the version of this article initially published, in Table 2, the descriptions of pathways and definitions in the first and last columns did not correctly correspond to the values in the other columns. The error has been corrected in the HTML and PDF versions of the article.


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This research has been conducted using the UK Biobank Resource (application numbers 10279 and 4844). Generation Scotland received core support from the Chief Scientist Office of the Scottish Government Health Directorates (CZD/16/6) and the Scottish Funding Council (HR03006). Ethical approval for the GS:SFHS study was obtained from the Tayside Committee on Medical Research Ethics (05/S1401/89 Tayside Committee on Medical Research Ethics A). We are grateful to all the families who took part, the general practitioners and the Scottish School of Primary Care for their help in recruiting them, and the whole Generation Scotland team, which includes interviewers, computer and laboratory technicians, clerical workers, research scientists, volunteers, managers, receptionists, healthcare assistants and nurses. This work was supported by the University of Edinburgh Centre for Cognitive Ageing and Cognitive Epidemiology, part of the cross-council Lifelong Health and Wellbeing Initiative (MR/K026992/1); funding from the Biotechnology and Biological Sciences Research Council (BBSRC) and the Medical Research Council (MRC) is gratefully acknowledged. This report represents independent research funded in part by the National Institute for Health Research (NIHR) Biomedical Research Centre at South London and the Maudsley NHS Foundation Trust and King’s College London. W.D.H. is supported by a grant from Age UK (Disconnected Mind Project). A.M.M. and I.J.D. are supported by funding from a Wellcome Trust Strategic Award (104036/Z/14/Z).

Author information

M.L. drafted the manuscript with contributions from W.D.H. and I.J.D. G.D., D.C.L., R.E.M., M.J.A. and D.M.H. performed quality control of UK Biobank and/or Generation Scotland data. M.L., G.D., S.P.H. and M.S. analyzed the data. T.-K.C., C.F.-R., W.D.H. and S.E.H. performed or assisted with downstream analysis. C.R.G., C.M.L. and A.M.M. provided critical comments on the manuscript draft and analysis. M.L. and I.J.D. coordinated the work. All authors commented on and approved the manuscript.

Competing interests

I.J.D. was a participant in UK Biobank. The other authors declare no conflict of interest.

Correspondence to Michelle Luciano.

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Fig. 1
Fig. 2: Regional association plots for suggestive and significant signals in UK Biobank.