Matthews, G., Deary, I. J. & Whiteman, M. C. Personality Traits (Cambridge University Press, Cambridge, UK, 2009).
Vukasovic, T. & Bratko, D. Heritability of personality: a meta-analysis of behavior genetic studies. Psychol. Bull. 141, 769–785 (2015).
Smith, D. J. et al. Genome-wide analysis of over 106 000 individuals identifies 9 neuroticism-associated loci. Mol. Psychiatry 21, 749–757 (2016).
Okbay, A. et al. Genetic variants associated with subjective well-being, depressive symptoms, and neuroticism identified through genome-wide analyses. Nat. Genet. 48, 624–633 (2016).
Power, R. A. & Pluess, M. Heritability estimates of the Big Five personality traits based on common genetic variants. Transl. Psychiatry 5, e604 (2015).
Vinkhuyzen, A. A. et al. Common SNPs explain some of the variation in the personality dimensions of neuroticism and extraversion. Transl. Psychiatry 2, e102 (2012).
Kubzansky, L. D., Martin, L. T. & Buka, S. L. Early manifestations of personality and adult health: a life course perspective. Health. Psychol. 28, 364–372 (2009).
Strickhouser, J. E., Zell, E. & Krizan, Z. Does personality predict health and well-being? A metasynthesis. Health. Psychol. 36, 797–810 (2017).
Cuijpers, P. et al. Economic costs of neuroticism: a population-based study. Arch. Gen. Psychiatry 67, 1086–1093 (2010).
Few, L. R. et al. Genetic variation in personality traits explains genetic overlap between borderline personality features and substance use disorders. Addiction 109, 2118–2127 (2014).
Kendler, K. S., Gatz, M., Gardner, C. O. & Pedersen, N. L. Personality and major depression: a Swedish longitudinal, population-based twin study. Arch. Gen. Psychiatry 63, 1113–1120 (2006).
Wray, N. R. & Sullivan, P. F. Genome-wide association analyses identify 44 risk variants and refine the genetic architecture of major depression. Preprint at bioRxiv https://doi.org/10.1101/167577 (2017).
Sudlow, C. et al. UK Biobank: an open access resource for identifying the causes of a wide range of complex diseases of middle and old age. PLoS Med. 12, e1001779 (2015).
Bycroft, C. et al. Genome-wide genetic data on ~500,000 UK Biobank participants. Preprint at bioRxiv https://doi.org/10.1101/166298 (2017).
Eysenck, S. B., Eysenck, H. J. & Barrett, P. A revised version of the psychoticism scale. Pers. Individ. Dif. 6, 21–29 (1985).
McCarthy, S. et al. A reference panel of 64,976 haplotypes for genotype imputation. Nat. Genet. 48, 1279–1283 (2016).
Bulik-Sullivan, B. K. et al. LD Score regression distinguishes confounding from polygenicity in genome-wide association studies. Nat. Genet. 47, 291–295 (2015).
Cross-Disorder Group of the Psychiatric Genomics Consortium. Identification of risk loci with shared effects on five major psychiatric disorders: a genome-wide analysis. Lancet 381, 1371–1379 (2013).
Sekar, A. et al. Schizophrenia risk from complex variation of complement component 4. Nature 530, 177–183 (2016).
Hegyi, H. GABBR1 has a HERV-W LTR in its regulatory region—a possible implication for schizophrenia. Biol. Direct 8, 5 (2013).
Wei, J. & Hemmings, G. P. TNXB locus may be a candidate gene predisposing to schizophrenia. Am. J. Med. Genet. B Neuropsychiatr. Genet. 125B, 43–49 (2004).
Lo, M.-T. et al. Genome-wide analyses for personality traits identify six genomic loci and show correlations with psychiatric disorders. Nat. Genet. 49, 152–156 (2017).
de Moor, M. H. et al. Meta-analysis of genome-wide association studies for neuroticism, and the polygenic association with major depressive disorder. JAMA Psychiatry 72, 642–650 (2015).
Hu, Y. et al. GWAS of 89,283 individuals identifies genetic variants associated with self-reporting of being a morning person. Nat. Commun. 7, 10448 (2016).
Duggan, K. A., Friedman, H. S., McDevitt, E. A. & Mednick, S. C. Personality and healthy sleep: the importance of conscientiousness and neuroticism. PLoS One 9, e90628 (2014).
Mi, H., Muruganujan, A. & Thomas, P. D. PANTHER in 2013: modeling the evolution of gene function, and other gene attributes, in the context of phylogenetic trees. Nucleic Acids Res. 41, D377–D386 (2013).
Sulser, F. The role of CREB and other transcription factors in the pharmacotherapy and etiology of depression. Ann. Med. 34, 348–356 (2002).
Wang, H. et al. Forkhead box O transcription factors as possible mediators in the development of major depression. Neuropharmacology 99, 527–537 (2015).
Malan-Müller, S., Hemmings, S. M. J. & Seedat, S. Big effects of small RNAs: a review of microRNAs in anxiety. Mol. Neurobiol. 47, 726–739 (2013).
Dwivedi, Y. Emerging role of microRNAs in major depressive disorder: diagnosis and therapeutic implications. Dialogues Clin. Neurosci. 16, 43–61 (2014).
Ambrosini, A. et al. Possible involvement of the CACNA1E gene in migraine: a search for single nucleotide polymorphism in different clinical phenotypes. Headache 57, 1136–1144 (2017).
Schraa-Tam, C. K. L. et al. fMRI activities in the emotional cerebellum: a preference for negative stimuli and goal-directed behavior. Cerebellum 11, 233–245 (2012).
Schutter, D. J. L. G., Koolschijn, P. C. M. P., Peper, J. S. & Crone, E. A. The cerebellum link to neuroticism: a volumetric MRI association study in healthy volunteers. PLoS One 7, e37252 (2012).
Grinberg, M. et al. Mitochondrial carrier homolog 2 is a target of tBID in cells signaled to die by tumor necrosis factor α. Mol. Cell. Biol. 25, 4579–4590 (2005).
Locke, A. E. et al. Genetic studies of body mass index yield new insights for obesity biology. Nature 518, 197–206 (2015).
de Leeuw, C. A., Mooij, J. M., Heskes, T. & Posthuma, D. MAGMA: generalized gene-set analysis of GWAS data. PLoS Comput. Biol. 11, e1004219 (2015).
Lucassen, P. J., Oomen, C. A., Schouten, M., Encinas, J. M. & Fitzsimons, C. P. in Adult Neurogenesis in the Hippocampus (ed. Canales, J. J.) 177–206 (Academic Press, San Diego, CA, 2016).
Schoenfeld, T. J. & Cameron, H. A. Adult neurogenesis and mental illness. Neuropsychopharmacology 40, 113–128 (2015).
Wray, N. R. et al. Anxiety and comorbid measures associated with PLXNA2. Arch. Gen. Psychiatry 64, 318–326 (2007).
Redies, C., Hertel, N. & Hübner, C. A. Cadherins and neuropsychiatric disorders. Brain Res. 1470, 130–144 (2012).
Chang, H. et al. The protocadherin 17 gene affects cognition, personality, amygdala structure and function, synapse development and risk of major mood disorders. Mol. Psychiatry http://dx.doi.org/10.1038/mp.2016.231 (2017).
DeYoung, C. G., Cicchetti, D. & Rogosch, F. A. Moderation of the association between childhood maltreatment and neuroticism by the corticotropin-releasing hormone receptor 1 gene. J. Child Psychol. Psychiatry 52, 898–906 (2011).
Binder, E. B. & Nemeroff, C. B. The CRF system, stress, depression and anxiety—insights from human genetic studies. Mol. Psychiatry 15, 574–588 (2010).
Bulik-Sullivan, B. et al. An atlas of genetic correlations across human diseases and traits. Nat. Genet. 47, 1236–1241 (2015).
Smith, B. H. et al. Cohort profile: Generation Scotland: Scottish Family Health Study (GS:SFHS). The study, its participants and their potential for genetic research on health and illness. Int. J. Epidemiol. 42, 689–700 (2013).
Burton, R. The Anatomy of Melancholy (eds. Faulkner, T. C., Kiessling, N. K. & Blair, R. L.) (Oxford University Press, Oxford, UK, 1989).
Chang, C. C. et al. Second-generation PLINK: rising to the challenge of larger and richer datasets. Gigascience 4, 7 (2015).
Willer, C. J., Li, Y. & Abecasis, G. R. METAL: fast and efficient meta-analysis of genomewide association scans. Bioinformatics 26, 2190–2191 (2010).
Boyle, A. P. et al. Annotation of functional variation in personal genomes using RegulomeDB. Genome Res. 22, 1790–1797 (2012).
Mi, H. et al. PANTHER version 11: expanded annotation data from Gene Ontology and Reactome pathways, and data analysis tool enhancements. Nucleic Acids Res. 45 (D1), D183–D189 (2017).
Gene Ontology Consortium. Expansion of the Gene Ontology knowledgebase and resources. Nucleic Acids Res. 45 (D1), D331–D338 (2017).
Hemani, G. et al. MR-Base: a platform for systematic causal inference across the phenome using billions of genetic associations. Preprint at bioRxiv https://doi.org/10.1101/078972 (2016).
Tobacco and Genetics Consortium. Genome-wide meta-analyses identify multiple loci associated with smoking behavior. Nat. Genet. 42, 441–447 (2010).
Rietveld, C. A. et al. GWAS of 126,559 individuals identifies genetic variants associated with educational attainment. Science 340, 1467–1471 (2013).
Euesden, J., Lewis, C. M. & O’Reilly, P. F. PRSice: polygenic risk score software. Bioinformatics 31, 1466–1468 (2015).
Benjamini, Y. & Hochberg, Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J. R. Stat. Soc. B 57, 289–300 (1995).