Integration of summary data from GWAS and eQTL studies predicts complex trait gene targets

Nature Genetics

Volumn 48, Issue 5, 2016, Pages 481-487

  Zhu, Zhihong ^a   Zhang, Futao ^a   Hu, Han ^b   Bakshi, Andrew ^a   Robinson, Matthew R ^a   Powell, Joseph E ^a   Montgomery, Grant W ^c   Goddard, Michael E ^d,e   Wray, Naomi R ^a   Visscher, Peter M ^a   Yang, Jian ^a  

^a UNIVERSITY OF QUEENSLAND   (Australia)

^b ZHEJIANG UNIVERSITY   (China)

^c QIMR BERGHOFER MEDICAL RESEARCH INSTITUTE   (Australia)

^d UNIVERSITY OF MELBOURNE   (Australia)

^e Biosciences Research Division Department of Environment and Primary Industries   (Australia)

Author keywords

[No Author keywords available]

Indexed keywords

PROTEIN; TRANSCRIPTOME;

ARTICLE; DNA METHYLATION; GENE EXPRESSION; GENE LOCUS; GENETIC ASSOCIATION; GENETIC TRAIT; GENETIC VARIABILITY; GENOME-WIDE ASSOCIATION STUDY; HUMAN; MENDELIAN RANDOMIZATION ANALYSIS; METABOLITE; PLEIOTROPY; PREDICTIVE VALUE; PRIORITY JOURNAL; QUANTITATIVE TRAIT LOCUS; RNA SEQUENCE; SEQUENCE ANALYSIS; SINGLE NUCLEOTIDE POLYMORPHISM; TISSUE SPECIFICITY; GENE EXPRESSION REGULATION; GENETIC LINKAGE; GENETIC PROCEDURES; GENETIC VARIATION; STATISTICAL ANALYSIS;

DATA INTERPRETATION, STATISTICAL; GENE EXPRESSION REGULATION; GENETIC LINKAGE; GENETIC PLEIOTROPY; GENETIC TECHNIQUES; GENETIC VARIATION; GENOME-WIDE ASSOCIATION STUDY; HUMANS; QUANTITATIVE TRAIT LOCI; TRANSCRIPTOME;

EID: 84961927084     PISSN: 10614036     EISSN: 15461718     Source Type: Journal    
DOI: 10.1038/ng.3538     Document Type: Article

References (50)

1. Welter D, et al. The NHGRI GWAS Catalog, a curated resource of SNP-Trait associations. Nucleic Acids Res. 42, D1001-D1006 (2014).
2. Smemo S, et al. Obesity-Associated variants within FTO form long-range functional connections with IRX3. Nature. 507, 371-375 (2014).
3. Claussnitzer M, et al. FTO obesity variant circuitry and adipocyte browning in humans. N. Engl. J. Med. 373, 895-907 (2015).
4. Golzio C, et al. KCTD13 is a major driver of mirrored neuroanatomical phenotypes of the 16p11.2 copy number variant. Nature. 485, 363-367 (2012).
5. Weiss L.A, et al. Association between microdeletion and microduplication at 16p11.2 and autism. N. Engl. J. Med. 358, 667-675 (2008).
6. McCarthy S.E, et al. Microduplications of 16p11.2 are associated with schizophrenia. Nat. Genet. 41, 1223-1227 (2009).
7. Jansen R.C, & Nap J.P. Genetical genomics: the added value from segregation. Trends Genet. 17, 388-391 (2001).
8. Katan M.B. Apolipoprotein E isoforms, serum cholesterol, and cancer. Lancet. 1, 507-508 (1986).
9. Smith G.D, & Ebrahim S. 'Mendelian randomization': can genetic epidemiology contribute to understanding environmental determinants of disease? Int. J. Epidemiol. 32, 1-22 (2003).
10. Freeman G, Cowling B.J, & Schooling C.M. Power and sample size calculations for Mendelian randomization studies using one genetic instrument. Int. J. Epidemiol. 42, 1157-1163 (2013).
11. Brion M.J, Shakhbazov K, & Visscher P.M. Calculating statistical power in Mendelian randomization studies. Int. J. Epidemiol. 42, 1497-1501 (2013).
12. Yang J, et al. Ubiquitous polygenicity of human complex traits: genome-wide analysis of 49 traits in Koreans. PLoS Genet. 9, e1003355 (2013).
13. Wood A.R, et al. Defining the role of common variation in the genomic and biological architecture of adult human height. Nat. Genet. 46, 1173-1186 (2014).
14. Locke A.E, et al. Genetic studies of body mass index yield new insights for obesity biology. Nature. 518, 197-206 (2015).
15. Shungin D, et al. New genetic loci link adipose and insulin biology to body fat distribution. Nature. 518, 187-196 (2015).
16. Okada Y, et al. Genetics of rheumatoid arthritis contributes to biology and drug discovery. Nature. 506, 376-381 (2014).
17. Schizophrenia Working Group of the Psychiatric Genomics Consortium. Biological insights from 108 schizophrenia-Associated genetic loci. Nature. 511, 421-427 (2014).
18. Westra H.J, et al. Systematic identification of trans eQTLs as putative drivers of known disease associations. Nat. Genet. 45, 1238-1243 (2013).
19. Patsopoulos N.A, et al. Fine-mapping the genetic association of the major histocompatibility complex in multiple sclerosis: HLA and non-HLA effects. PLoS Genet. 9, e1003926 (2013).
20. Plenge R.M, et al. TRAF1-C5 as a risk locus for rheumatoid arthritis-A genomewide study. N. Engl. J. Med. 357, 1199-1209 (2007).
21. Stahl E.A, et al. Genome-wide association study meta-Analysis identifies seven new rheumatoid arthritis risk loci. Nat. Genet. 42, 508-514 (2010).
22. Albers H.M, et al. The TRAF1/C5 region is a risk factor for polyarthritis in juvenile idiopathic arthritis. Ann. Rheum. Dis. 67, 1578-1580 (2008).
23. Xavier R.J, & Rioux J.D. Genome-wide association studies: a new window into immune-mediated diseases. Nat. Rev. Immunol. 8, 631-643 (2008).
24. Tsitsikov E.N, et al. TRAF1 is a negative regulator of TNF signaling. enhanced TNF signaling in TRAF1-deficient mice. Immunity. 15, 647-657 (2001).
25. Chung J.Y, Park Y.C, Ye H, & Wu H. All TRAFs are not created equal: common and distinct molecular mechanisms of TRAF-mediated signal transduction. J. Cell Sci. 115, 679-688 (2002).
26. Nica A.C, et al. The architecture of gene regulatory variation across multiple human tissues: the MuTHER study. PLoS Genet. 7, e1002003 (2011).
27. GTEx Consortium. The Genotype-Tissue Expression (GTEx) pilot analysis: multitissue gene regulation in humans. Science. 348, 648-660 (2015).
28. McKenzie M, Henders A.K, Caracella A, Wray N.R, & Powell J.E. Overlap of expression quantitative trait loci (eQTL) in human brain and blood. BMC Med. Genomics. 7, 31 (2014).
29. Finucane H.K, et al. Partitioning heritability by functional annotation using genome-wide association summary statistics. Nat. Genet. 47, 1228-1235 (2015).
30. Eaton W.W, et al. Association of schizophrenia and autoimmune diseases: linkage of Danish national registers. Am. J. Psychiatry. 163, 521-528 (2006).
31. Nemani K, Hosseini Ghomi R, McCormick B, & Fan X. Schizophrenia and the gut-brain axis. Prog. Neuropsychopharmacol. Biol. Psychiatry. 56, 155-160 (2015).
32. Ramasamy A, et al. Genetic variability in the regulation of gene expression in ten regions of the human brain. Nat. Neurosci. 17, 1418-1428 (2014).
33. Veyrieras J.B, et al. Exon-specific QTLs skew the inferred distribution of expression QTLs detected using gene expression array data. PLoS One 7, e30629 (2012).
34. Yang J, et al. Conditional and joint multiple-SNP analysis of GWAS summary statistics identifies additional variants influencing complex traits. Nat. Genet. 44, 369-375, S1-S3 (2012).
35. Lawlor D.A, Harbord R.M, Sterne J.A, Timpson N, & Davey Smith G. Mendelian randomization: using genes as instruments for making causal inferences in epidemiology. Stat. Med. 27, 1133-1163 (2008).
36. Giambartolomei C, et al. Bayesian test for colocalisation between pairs of genetic association studies using summary statistics. PLoS Genet. 10, e1004383 (2014).
37. Gamazon E.R, et al. A gene-based association method for mapping traits using reference transcriptome data. Nat. Genet. 47, 1091-1098 (2015).
38. Gusev A, et al. Integrative approaches for large-scale transcriptome-wide association studies. Nat. Genet. 48, 245-252 (2016).
39. Powell J.E, et al. The Brisbane Systems Genetics Study: genetical genomics meets complex trait genetics. PLoS One 7, e35430 (2012).
40. Davey Smith G, & Hemani G. Mendelian randomization: genetic anchors for causal inference in epidemiological studies. Hum. Mol. Genet. 23 R1, R89-R98 (2014).
41. Ference B.A, et al. Effect of long-Term exposure to lower low-density lipoprotein cholesterol beginning early in life on the risk of coronary heart disease: a Mendelian randomization analysis. J. Am. Coll. Cardiol. 60, 2631-2639 (2012).
42. Pierce B.L, & Burgess S. Efficient design for Mendelian randomization studies: subsample and 2-sample instrumental variable estimators. Am. J. Epidemiol. 178, 1177-1184 (2013).
43. Inoue A, & Solon G. Two-sample instrumental variables estimators. Rev. Econ. Stat. 92, 557-561 (2010).
44. Lynch M, & Walsh B. Genetics and Analysis of Quantitative Traits (Sinauer Associates, 1998).
45. International HapMap Consortium. The International HapMap Project. Nature. 426, 789-796 (2003).
46. Psaty B.M, et al. Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium: design of prospective meta-Analyses of genome-wide association studies from 5 cohorts. Circ. Cardiovasc. Genet. 2, 73-80 (2009).
47. Kuonen D. Saddlepoint approximations for distributions of quadratic forms in normal variables. Biometrika. 86, 929-935 (1999).
48. Davies R.B. Numerical inversion of a characteristic function. Biometrika. 60, 415-417 (1973).
49. 1000 Genomes Project Consortium. A map of human genome variation from population-scale sequencing. Nature. 467, 1061-1073 (2010).
50. Yang J, Lee S.H, Goddard M.E, & Visscher P.M. GCTA: a tool for genome-wide complex trait analysis. Am. J. Hum. Genet. 88, 76-82 (2011).