Item-level analyses reveal genetic heterogeneity in neuroticism

Nature Communications

Volumn 9, Issue 1, 2018, Pages

  Nagel, Mats ^a   Watanabe, Kyoko ^b   Stringer, Sven ^b   Posthuma, Danielle ^a,b   Van Der Sluis, Sophie ^a,b  

^a Amsterdam University Medical Center   (Netherlands)

^b VU UNIVERSITY AMSTERDAM   (Netherlands)

Author keywords

[No Author keywords available]

Indexed keywords

CLUSTER ANALYSIS; GENETIC ANALYSIS; GENOMICS; HETEROGENEITY; META-ANALYSIS; SYMPTOM;

AFFECT; ARTICLE; GENETIC ANALYSIS; GENETIC CORRELATION; GENETIC DIFFERENCE; GENETIC HETEROGENEITY; GENOME-WIDE ASSOCIATION STUDY; HUMAN; NEUROSIS; PATIENT WORRY; PHENOTYPE; GENETIC PREDISPOSITION; META ANALYSIS (TOPIC); MOLECULAR GENETICS;

GENETIC HETEROGENEITY; GENETIC PREDISPOSITION TO DISEASE; GENOME-WIDE ASSOCIATION STUDY; HUMANS; META-ANALYSIS AS TOPIC; MOLECULAR SEQUENCE ANNOTATION; NEUROTICISM; PHENOTYPE;

EID: 85042877381     PISSN: None     EISSN: 20411723     Source Type: Journal    
DOI: 10.1038/s41467-018-03242-8     Document Type: Article

References (59)

1. Hyde, C. L. et al. Identification of 15 genetic loci associated with risk of major depression in individuals of European descent. Nat. Genet. 48, 1031-1036 (2016).
2. Sniekers, S. et al. Genome-wide association meta-analysis of 78,308 individuals identifies new loci and genes influencing human intelligence. Nat. Genet. 49, 1107-1112 (2017).
3. Okbay, A. et al. Genetic variants associated with subjective well-being, depressive symptoms, and neuroticism identified through genome-wide analyses. Nat. Genet. 48, 624-636 (2016).
4. Smith, D. J. et al. Genome-wide analysis of over 106 000 individuals identifies 9 neuroticism-associated loci. Mol. Psychiatry 21, 1-9 (2016).
5. Polderman, T. J. C. et al. Meta-analysis of the heritability of human traits based on fifty years of twin studies. Nat. Genet. 47, 702-709 (2015).
6. American Psychiatric Association (ed.) Diagnostic and Statistical Manual of Mental Disorders 5th edn (American Psychiatric Association Publishing, 2013).
7. Lux, V. &Kendler, K. S. Deconstructing major depression: a validation study of the DSM-IV symptomatic criteria. Psychological Medicine 40, 1679-1690 (2010).
8. Fried, E. I. &Nesse, R. M. Depression sum-scores don't add up: why analyzing specific depression symptoms is essential. BMC Med. 13, 72 (2015).
9. Hawi, Z. et al. The molecular genetic architecture of attention deficit hyperactivity disorder. Mol. Psychiatry 20, 289-297 (2015).
10. van der Sluis, S., Verhage, M., Posthuma, D. &Dolan, C. V. Phenotypic complexity, measurement bias, and poor phenotypic resolution contribute to the missing heritability problem in genetic association studies. PLoS One 5, e13929 (2010).
11. Eysenck, B. G., Eysenck, H. J. &Barrett, P. A revised version of the psychoticism scale. Pers. Individ. Dif. 6, 21-29 (1985).
12. Middeldorp, C. M., Cath, D. C., van den Berg, M., Beem, A. L., van Dyck, R. &Boomsma, D. I. In Biology of Personality and Individual Differences (ed. Canli, T.) Ch. 12 (Guilford Press, New York, 2006).
13. Hettema, J. M., Neale, M. C., Myers, J. M., Prescott, C. A. &Kendler, K. S. A population-based twin study of the relationship between neuroticism and internalizing disorders. Am. J. Psychiatry 163, 857-864 (2006).
14. Kendler, K. S., Gatz, M., Gardner, C. O., Pedersen, N. L. &Virginia, V. Personality and major depression: A Swedish longitudinal, population-based twin study. Arch. Gen. Psychiatry 63, 1113-1120 (2006).
15. 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).
16. Bulik-Sullivan, B. K. et al. An atlas of genetic correlations across human diseases and traits. Nat. Genet. 47, 1-9 (2015).
17. Bulik-Sullivan, B. K. et al. LD Score regression distinguishes confounding from polygenicity in genome-wide association studies. Nat. Genet. 47, 291-295 (2015).
18. Tian, C. et al. Analysis and application of European genetic substructure using 300 K SNP information. PLoS Genet. 4, (2008).
19. Nagel, M. et al. GWAS Meta-analysis of neuroticism (N = 449,484) identifies novel genetic loci and pathways. Preprint at bioRxiv https://www.biorxiv.org/ content/early/2017/09/05/184820 (2017).
20. Watanabe, K., Taskesen, E., Bochoven, A. van &Posthuma, D. FUMA: Functional mapping and annotation of genetic associations. Nat. Commun. 8, 1826 (2017).
21. Lo, M. et al. Genome-wide analyses for personality traits identify six genomic loci and show correlations with psychiatric disorders. Nat. Genet. 49, 152-156 (2016).
22. Genetics of Personality Consortium. Meta-analysis of genome-wide association studies for neuroticism, and the polygenic association with major depressive disorder. JAMA Psychiatry 72, 642-650 (2015).
23. de Leeuw, C. A., Mooij, J. M., Heskes, T. &Posthuma, D. MAGMA: Generalized gene-set analysis of GWAS data. PLoS Comput. Biol. 11, 1-19 (2015).
24. Subramanian, A. et al. Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles. Proc. Natl. Acad. Sci. USA 102, 15545-15550 (2005).
25. GTEx Consortium. The Genotype-Tissue Expression (GTEx) pilot analysis: multitissue gene regulation in humans. Science 348, 648-660 (2015).
26. Mor, N. et al. Evaluating the invariance of the factor structure of the EPQ-R-N among adolescents. J. Pers. Assess. 90, 66-75 (2008).
27. Ostergaard, S. D., Jensen, S. O. W. &Bech, P. The heterogeneity of the depressive syndrome: When numbers get serious. Acta Psychiatr. Scand. 124, 495-496 (2011).
28. Kendler, K. S., Aggen, S. H. &Neale, M. C. Evidence for multiple genetic factors underlying DSM-IV criteria for major depression. JAMA Psychiatry 70, 599-607 (2013).
29. Wechsler, D., Coalson, D. L. &Raiford, S. E. WAIS-III: Wechsler adult intelligence scale (Psychological Corporation, San Antonio, Texas, 1997).
30. Wechsler, D. Wechsler adult intelligence scale-Fourth Edition (WAIS-IV). San Antonio, TX NCS Pearson 22, 498 (2008).
31. Petrill, S. A., Saudino, K. S., Wilkerson, B. &Plomin, R. Genetic and environmental molarity and modularity of cognitive functioning in 2-year-old twins. Intelligence 29, 31-43 (2001).
32. Price, T. S. et al. Genetic and environmental covariation between verbal and nonverbal cognitive development in infancy. Child Dev. 71, 948-959 (2000).
33. Posthuma, D., De Geus, E. J. C. &Boomsma, D. I. Perceptual speed and IQ are associated through common genetic factors. Behav. Genet. 31, 593-602 (2001).
34. Rijsdijk, F. V., Vernon, P. A. &Boomsma, D. I. Application of hierarchical genetic models to raven and WAIS subtests: A Dutch twin study. Behav. Genet. 32, 199-210 (2002).
35. Plomin, R. &Spinath, F. Genetics and general cognitive ability. Nature 402, C25-C29 (1999).
36. Auton, A. et al. A global reference for human genetic variation. Nature 526, 68-74 (2015).
37. Chang, C. C. et al. Second-generation PLINK: rising to the challenge of larger and richer datasets. Gigascience 4, 1 (2015).
38. Purcell, S. et al. PLINK: a tool set for whole-genome association and population-based linkage analyses. Am. J. Hum. Genet. 81, 559-575 (2007).
39. Abraham, G. &Inouye, M. Fast principal component analysis of large-scale genome-wide data. PLoS One 9, 1-5 (2014).
40. McCarthy, M. I. M. I. et al. Genome-wide association studies for complex traits: consensus, uncertainty and challenges. Nat. Rev. Genet. 9, 356-369 (2008).
41. Willer, C. J., Li, Y., Abecasis, G. R. &Overall, P. METAL: fast and efficient meta-analysis of genomewide association scans. Bioinformatics 26, 2190-2191 (2010).
42. Franke, B. et al. Genetic influences on schizophrenia and subcortical brain volumes: large-scale proof-of-concept and roadmap for future studies. Nat. Neurosci. 19, 420-431 (2016).
43. Boyle, A. P. et al. Annotation of functional variation in personal genomes using RegulomeDB. Genome Res. 22, 1790-1797 (2012).
44. Ernst, J. &Kellis, M. ChromHMM: automating chromatin-state discovery and characterization. Nat. Methods 9, 215-216 (2012).
45. Roadmap Epigenomics Consortium et al. Integrative analysis of 111 reference human epigenomes. Nature 518, (2015).
46. Schmitt, A. D. et al. A compendium of chromatin contact maps reveals spatially active regions in the human genome. Cell Rep. 17, 2042-2059 (2016).
47. Astle, W. J. et al. The allelic landscape of human blood cell trait variation and links to common complex disease. Cell 167, 1415-1429.e19 (2016).
48. Do, C. B. et al. Web-based genome-wide association study identifies two novel loci and a substantial genetic component for Parkinson's disease. PLoS Genet. 7, e1002141 (2011).
49. Savage, J. E. et al. GWAS meta-analysis (N = 279,930) identifies new genes and functional links to intelligence. Preprint at bioRxiv http://biorxiv.org/ content/early/2017/09/06/184853.1 (2017).
50. Nalls, Ma et al. Large-scale meta-analysis of genome-wide association data identifies six new risk loci for Parkinson's disease. Nat. Genet 56, 1-7 (2014).
51. Jun, G. et al. A novel Alzheimer disease locus located near the gene encoding tau protein. Mol. Psychiatry 21, 108-117 (2016).
52. Li, Q. S., Tian, C., Seabrook, G. R., Drevets, W. C. &Narayan, V. A. Analysis of 23 and Me antidepressant efficacy survey data: implication of circadian rhythm and neuroplasticity in bupropion response. Transl. Psychiatry 6, e889 (2016).
53. Graff, M. et al. Genome-wide physical activity interactions in adiposity-A meta-analysis of 200,452 adults. PLoS Genet. 13, 1-26 (2017).
54. Justice, A. E. et al. Genome-wide meta-analysis of 241,258 adults accounting for smoking behaviour identifies novel loci for obesity traits. Nat. Commun. 8, 14977 (2017).
55. de Lange, K. M. et al. Genome-wide association study implicates immune activation of multiple integrin genes in inflammatory bowel disease. Nat. Genet. 49, 256-261 (2017).
56. Suhre, K. et al. Connecting genetic risk to disease end points through the human blood plasma proteome. Nat. Commun. 8, 14357 (2017).
57. Okbay, A. et al. Genome-wide association study identifies 74 loci associated with educational attainment. Nature 533, 539-542 (2016).
58. The Autism Spectrum Disorders Working Group of The Psychiatric Genomics Consortium. Meta-analysis of GWAS of over 16,000 individuals with autism spectrum disorder highlights a novel locus at 10q24.32 and a significant overlap with schizophrenia. Mol. Autism 8, 21 (2017).
59. Ripke, S. et al. Biological insights from 108 schizophrenia-associated genetic loci. Nature 511, 421-427 (2014).