Genetic contributions to two special factors of neuroticism are associated with affluence, higher intelligence, better health, and longer life

Molecular Psychiatry

Volumn 25, Issue 11, 2020, Pages 3034-3052

  Hill, W David ^a,b   Weiss, Alexander ^a,b   Liewald, David C ^a   Davies, Gail ^a   Porteous, David J ^a   Hayward, Caroline ^a   McIntosh, Andrew M ^a   Gale, Catharine R ^a,b,c   Deary, Ian J ^a,b  

^a UNIVERSITY OF EDINBURGH   (United Kingdom)

^b UNIVERSITY OF EDINBURGH   (United Kingdom)

^c UNIVERSITY OF SOUTHAMPTON   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

ADULT; AGED; ANXIETY; ARTICLE; CORONARY ARTERY DISEASE; GENETIC ASSOCIATION; GENETIC RISK; GENETICS; HEALTH CARE; HUMAN; INTELLIGENCE; LONGEVITY; NEUROSIS; PRIORITY JOURNAL; RATING SCALE; SELF CONCEPT; SOCIAL STATUS; TENSION; VULNERABLE POPULATION; EMOTION; FEMALE; HEALTH; MALE; MIDDLE AGED;

ADULT; AGED; ANXIETY; ECONOMIC STATUS; EMOTIONS; FEMALE; HEALTH; HUMANS; INTELLIGENCE; LONGEVITY; MALE; MIDDLE AGED; NEUROTICISM;

EID: 85063005069     PISSN: 13594184     EISSN: 14765578     Source Type: Journal    
DOI: 10.1038/s41380-019-0387-3     Document Type: Article

References (75)

1. Goldberg LR. The structure of phenotypic personality traits. Am Psychol. 1993;48:26.
2. Wray NR, Birley AJ, Sullivan PF, Visscher PM, Martin NG. Genetic and phenotypic stability of measures of neuroticism over 22 years. Twin Res Human Genet. 2007;10:695–702.
3. Kendler KS, Myers J. The genetic and environmental relationship between major depression and the five-factor model of personality. Psychol Med. 2010;40:801–6.
4. Distel MA, Trull TJ, Willemsen G, Vink JM, Derom CA, Lynskey M, et al. The five-factor model of personality and borderline personality disorder: a genetic analysis of comorbidity. Biol Psychiatry. 2009;66:1131–8.
5. Van OsJ, Jones PB. Neuroticism as a risk factor for schizophrenia. Psychol Med. 2001;31:1129–34.
6. Gale CR, Čukić I, Batty GD, McIntosh AM, Weiss A, Deary IJ. When is higher neuroticism protective against death? Findings from UK Biobank. Psychol Sci. 2017;28:1345–57.
7. Cuijpers P, Smit F, Penninx BW, de Graaf R, ten Have M, Beekman AT. Economic costs of neuroticism: a population-based study. Arch Gen Psychiatry. 2010;67:1086–93.
8. Wood AR, Esko T, Yang J, Vedantam S, Pers TH, Gustafsson S, et al. Defining the role of common variation in the genomic and biological architecture of adult human height. Nat Genet. 2014;46:1173–86.
9. Hill W, Marioni R, Maghzian O, Ritchie S, Hagenaars S, McIntosh A et al. A combined analysis of genetically correlated traits identifies 187 loci and a role for neurogenesis and myelination in intelligence. Mol Psychiatry. 2019;24:169–81.
10. Hill WD, Arslan RC, Xia C, Luciano M, Amador C, Navarro P, et al. Genomic analysis of family data reveals additional genetic effects on intelligence and personality. Mol Psychiatry. 2018;23:2347–62.
11. Vukasović T, Bratko D. Heritability of personality: a meta-analysis of behavior genetic studies. Psychol Bull. 2015;141:769.
12. Smith DJ, Escott-Price V, Davies G, Bailey ME, Colodro-Conde L, Ward J et al. Genome-wide analysis of over 106 000 individuals identifies 9 neuroticism-associated loci. Mol Psychiatry. 2016;21:749–57.
13. Xia C, Amador C, Huffman J, Trochet H, Campbell A, Porteous D, et al. Pedigree-and SNP-associated genetics and recent environment are the major contributors to anthropometric and cardiometabolic trait variation. PLoS Genet. 2016;12:e1005804.
14. Gale C, Hagenaars SP, Davies G, Hill WD, Liewald DC, Cullen B, et al. Pleiotropy between neuroticism and physical and mental health: findings from 108 038 men and women in UK Biobank. Transl Psychiatry. 2016;6:e791.
15. Luciano M, Hagenaars SP, Davies G, Hill WD, Clarke T-K, Shirali M, et al. Association analysis in over 329,000 individuals identifies 116 independent variants influencing neuroticism. Nat Genet. 2018;50:6–11.
16. Lo M-T, Hinds DA, Tung JY, Franz C, Fan C-C, Wang Y et al. Genome-wide analyses for personality traits identify six genomic loci and show correlations with psychiatric disorders. Nat Genet. 2017;49:152–6.
17. Nagel M, Jansen PR, Stringer S, Watanabe K, de Leeuw CA, Bryois J, et al. Meta-analysis of genome-wide association studies for neuroticism in 449,484 individuals identifies novel genetic loci and pathways. Nat Genet. 2018;50:920–7.
18. Smeland OB, Wang Y, Lo M-T, Li W, Frei O, Witoelar A, et al. Identification of genetic loci shared between schizophrenia and the Big Five personality traits. Sci Rep. 2017;7:2222.
19. Nagel M, Watanabe K, Stringer S, Posthuma D, Sluis S. Item-level analyses reveal genetic heterogeneity in neuroticism. Nat Commun. 2018;9:905.
20. Wiernik BM, Wilmot MP, Kostal JW. How data analysis can dominate interpretations of dominant general factors. Ind Organ Psychol. 2015;8:438–45.
21. Eysenck SB, Eysenck HJ, Barrett P. A revised version of the psychoticism scale. Pers Individ Dif. 1985;6:21–9.
22. Jennrich RI, Bentler PM. Exploratory bi-factor analysis: the oblique case. Psychometrika. 2012;77:442–54.
23. Jennrich RI, Bentler PM. Exploratory bi-factor analysis. Psychometrika. 2011;76:537–49.
24. Sudlow C, Gallacher J, Allen N, Beral V, Burton P, Danesh J, 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. 2015;12:e1001779.
25. Bycroft C, Freeman C, Petkova D, Band G, Elliott LT, Sharp K et al. The UK Biobank resource with deep phenotyping and genomic data. Nature 2018;562:203–9.
26. Wain LV, Shrine N, Artigas MS, Erzurumluoglu AM, Noyvert B, Bossini-Castillo L, et al. Genome-wide association analyses for lung function and chronic obstructive pulmonary disease identify new loci and potential druggable targets. Nat Genet. 2017;49:416–25.
27. Winkler TW, Day FR, Croteau-Chonka DC, Wood AR, Locke AE, Mägi R, et al. Quality control and conduct of genome-wide association meta-analyses. Nat Protoc. 2014;9:1192.
28. Haplotype Reference C. A reference panel of 64,976 haplotypes for genotype imputation. Nat Genet. 2016;48:1279–83.
29. Genome Project C. An integrated map of genetic variation from 1,092 human genomes. Nature. 2012;491:56.
30. Manichaikul A, Mychaleckyj JC, Rich SS, Daly K, Sale M, Chen W-M. Robust relationship inference in genome-wide association studies. Bioinformatics. 2010;26:2867–73.
31. Yang J, Lee SH, Goddard ME, Visscher PM. GCTA: a tool for genome-wide complex trait analysis. Am J Human Genet. 2011;88:7.
32. Yang J, Lee SH, Goddard ME, Visscher PM. GCTA: a tool for genome-wide complex trait analysis. Am J Hum Genet. 2011;88:76–82.
33. Muthén LK, Muthén BO. Mplus User’s Guide. 8th edn., Muthén & Muthén, Los Angeles, 1998–2017.
34. Browne MW. An overview of analytic rotation in exploratory factor analysis. Multivar Behav Res. 2001;36:111–50.
35. Costa Jr PT, McCrae RR. Domains and facets: hierarchical personality assessment using the Revised NEO Personality Inventory. J Pers Assess. 1995;64:21–50.
36. Weiss A, Gale CR, Čukić I, Batty GD, McIntosh AM, Deary IJ. Conditioning on a Collider May or May Not Explain the Relationship Between Lower Neuroticism and Premature Mortality in the Study by Gale et al. (2017): A Reply to Richardson, Davey Smith, and Munafó (2019). Psychological Science 2019: 1–6. 10.1177/0956797619833325
37. Smith BH, Campbell A, Linksted P, Fitzpatrick B, Jackson C, Kerr SM, 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. 2013;42:689–700.
38. Smith BH, Campbell H, Blackwood D, Connell J, Connor M, Deary IJ, et al. Generation Scotland: the Scottish Family Health Study; a new resource for researching genes and heritability. BMC Med Genet. 2006;7:74.
39. Bulik-Sullivan BK, Loh P-R, Finucane HK, Ripke S, Yang J, Patterson N, et al. LD Score regression distinguishes confounding from polygenicity in genome-wide association studies. Nat Genet. 2015;47:291–5.
40. Bulik-Sullivan B, Finucane HK, Anttila V, Gusev A, Day FR, Loh P-R, et al. An atlas of genetic correlations across human diseases and traits. Nat Genet. 2015;47:1236–41.
41. Benjamini Y, Hochberg Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J R Stat Soc Ser B (Methodol). 1995;57:289–300.
42. 1000 Genomes Project Consortium. A map of human genome variation from population-scale sequencing. Nature. 2012;467:1061–73.
43. Wang K, Li M, Hakonarson H. ANNOVAR: functional annotation of genetic variants from high-throughput sequencing data. Nucleic Acids Res. 2010;38:e164–e164.
44. Kircher M, Witten DM, Jain P, O'roak BJ, Cooper GM, Shendure J. A general framework for estimating the relative pathogenicity of human genetic variants. Nat Genet. 2014;46:310.
45. Boyle AP, Hong EL, Hariharan M, Cheng Y, Schaub MA, Kasowski M, et al. Annotation of functional variation in personal genomes using RegulomeDB. Genome Res. 2012;22:1790–7.
46. Ernst J, Kellis M. ChromHMM: automating chromatin-state discovery and characterization. Nat Methods. 2012;9:215.
47. Kundaje A, Meuleman W, Ernst J, Bilenky M, Yen A, Heravi-Moussavi A, et al. Integrative analysis of 111 reference human epigenomes. Nature. 2015;518:317–30.
48. Zhu Z, Zhang F, Hu H, Bakshi A, Robinson MR, Powell JE, et al. Integration of summary data from GWAS and eQTL studies predicts complex trait gene targets. Nat Genet. 2016;48:481–7.
49. Schmitt AD, Hu M, Jung I, Xu Z, Qiu Y, Tan CL, et al. A compendium of chromatin contact maps reveals spatially active regions in the human genome. Cell Rep. 2016;17:2042–59.
50. de Leeuw CA, Mooij JM, Heskes T, Posthuma D. MAGMA: Generalized Gene-Set Analysis of GWAS. Data PLoS Comp Biol. 2015;11:4.
51. Ashburner M, Ball CA, Blake JA, Botstein D, Butler H, Cherry JM, et al. Gene Ontology: tool for the unification of biology. Nat Genet. 2000;25:4.
52. Fabregat A, Sidiropoulos K, Garapati P, Gillespie M, Hausmann K, Haw R, et al. The reactome pathway knowledgebase. Nucleic Acids Res. 2015;44(D1):D481–D487.
53. Subramanian A, Tamayo P, Mootha VK, Mukherjee S, Ebert BL, Gillette MA, et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc Natl Acad Sci USA. 2005;102:15545–50.
54. The GTEx Consortium. The Genotype-Tissue Expression (GTEx) pilot analysis: multitissue gene regulation in humans. Science. 2015;348:648–60.
55. Miller JA, Ding S-L, Sunkin SM, Smith KA, Ng L, Szafer A, et al. Transcriptional landscape of the prenatal human brain. Nature. 2014;508:199.
56. Euesden J, Lewis CM, O’Reilly PF. PRSice: polygenic risk score software. Bioinformatics. 2015;31:1466–8.
57. Lorenzo-Seva U, ten Berge JMF. Tucker's congruence coefficient as a meaningful index of factor similarity. Methodology. 2006;2:57–64.
58. Gorsuch RL. Factor analysis. Lawrence Erlbaum Associates, New Jersey, 2013.
59. Watanabe K, Taskesen E, van Bochoven A, Posthuma D. Functional mapping and annotation of genetic associations with FUMA. Nat Commun. 2017:8.
60. Fried EI, Nesse RM. Depression sum-scores don’t add up: why analyzing specific depression symptoms is essential. BMC Med. 2015;13:72.
61. Maurano MT, Humbert R, Rynes E, Thurman RE, Haugen E, Wang H et al. Systematic Localization of Common Disease-Associated Variation in Regulatory DNA. Science 2012;337:1190–5.
62. Schizophrenia Working Group of the Psychiatric Genomics C, Ripke S, Neale BM, Corvin A, JTR Walters, Farh K-H, et al. Biological insights from 108 schizophrenia-associated genetic loci. Nature. 2014;511:421.
63. Sanchez-Juan P, Bishop MT, Kovacs GG, Calero M, Aulchenko YS, Ladogana A, et al. A genome wide association study links glutamate receptor pathway to sporadic Creutzfeldt-Jakob disease risk. PLoS ONE. 2015;10:e0123654.
64. Beraldo FH, Arantes CP, Santos TG, Machado CF, Roffe M, Hajj GN, et al. Metabotropic glutamate receptors transduce signals for neurite outgrowth after binding of the prion protein to laminin γ1 chain. FASEB J. 2011;25:265–79.
65. Um JiW, Kaufman Adam C, Kostylev M, Heiss Jacqueline K, Stagi M, Takahashi H, et al. Metabotropic glutamate receptor 5 is a coreceptor for alzheimer Aβ oligomer bound to cellular prion protein. Neuron. 2013;79:887–902.
66. Ernst A, Alkass K, Bernard S, Salehpour M, Perl S, Tisdale J, et al. Neurogenesis in the striatum of the adult human brain. Cell. 2014;156:1072–83.
67. Clelland CD, Choi M, Romberg C, Clemenson GD, Fragniere A, Tyers P, et al. A functional role for adult hippocampal neurogenesis in spatial pattern separation. Science. 2009;325:210–3.
68. Sahay A, Scobie KN, Hill AS, O'Carroll CM, Kheirbek MA, Burghardt NS, et al. Increasing adult hippocampal neurogenesis is sufficient to improve pattern separation. Nature. 2011;472:466.
69. Dupret D, Revest J-M, Koehl M, Ichas F, De Giorgi F, Costet P, et al. Spatial relational memory requires hippocampal adult neurogenesis. PLoS ONE. 2008;3:e1959.
70. Garthe A, Behr J, Kempermann G. Adult-generated hippocampal neurons allow the flexible use of spatially precise learning strategies. PLoS ONE. 2009;4:e5464.
71. Swan AA, Clutton JE, Chary PK, Cook SG, Liu GG, Drew MR. Characterization of the role of adult neurogenesis in touch-screen discrimination learning. Hippocampus. 2014;24:1581–91.
72. Burghardt NS, Park EH, Hen R, Fenton AA. Adult-born hippocampal neurons promote cognitive flexibility in mice. Hippocampus. 2012;22:1795–808.
73. Hill WD, Harris SE, Deary IJ. What genome-wide association studies reveal about the association between intelligence and mental health. Curr Opin Psychol. 2019;27:25–30.
74. Catterall WA. Voltage-gated calcium channels. Cold Spring Harb Perspect Biol. 2011;3:a003947.
75. Hill WD, Hagenaars SP, Marioni RE, Harris SE, Liewald DC, Davies G, et al. Molecular genetic contributions to social deprivation and household income in UK Biobank. Curr Biol. 2016;26:3083–9.