Fast set-based association analysis using summary data from GWAS identifies novel gene loci for human complex traits

Scientific Reports

Volumn 6, Issue , 2016, Pages

  Bakshi, Andrew ^a,b   Zhu, Zhihong ^a   Vinkhuyzen, Anna A E ^a   Hill, W David ^c   McRae, Allan F ^a   Visscher, Peter M ^a   Yang, Jian ^a  

^a UNIVERSITY OF QUEENSLAND   (Australia)

^b UNIVERSITY OF MELBOURNE   (Australia)

^c UNIVERSITY OF EDINBURGH   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

BODY HEIGHT; BODY MASS; COMPUTER SIMULATION; FACTUAL DATABASE; FEMALE; GENE LINKAGE DISEQUILIBRIUM; GENETICS; GENOME-WIDE ASSOCIATION STUDY; HUMAN; MALE; PROCEDURES; QUANTITATIVE TRAIT; SCHIZOPHRENIA; SINGLE NUCLEOTIDE POLYMORPHISM; STATISTICAL ANALYSIS;

BODY HEIGHT; BODY MASS INDEX; COMPUTER SIMULATION; DATA INTERPRETATION, STATISTICAL; DATABASES, FACTUAL; FEMALE; GENOME-WIDE ASSOCIATION STUDY; HUMANS; LINKAGE DISEQUILIBRIUM; MALE; POLYMORPHISM, SINGLE NUCLEOTIDE; QUANTITATIVE TRAIT, HERITABLE; SCHIZOPHRENIA;

EID: 84986881457     PISSN: None     EISSN: 20452322     Source Type: Journal    
DOI: 10.1038/srep32894     Document Type: Article

References (27)

1. Visscher, P. M., Brown, M. A., McCarthy, M. I. & Yang, J. Five years of GWAS discovery. Am. J. Hum. Genet. 90, 7-24 (2012).
2. Yang, J. et al. Genome partitioning of genetic variation for complex traits using common SNPs. Nat. Genet. 43, 519-525 (2011).
3. Schork, A. J. et al. All SNPs are not created equal: genome-wide association studies reveal a consistent pattern of enrichment among functionally annotated SNPs. PLoS Genet 9, e1003449 (2013).
4. 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 (2012).
5. 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).
6. 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).
7. Liu, J. Z. et al. A versatile gene-based test for genome-wide association studies. Am. J. Hum. Genet. 87, 139-145 (2010).
8. The International HapMap Consortium. A second generation human haplotype map of over 3.1 million SNPs. Nature 449, 851-861 (2007).
9. The 1000 Genomes Project Consortium. A map of human genome variation from population-scale sequencing. Nature 467, 1061-1073 (2010).
10. Li, M. X., Gui, H. S., Kwan, J. S. & Sham, P. C. GATES: a rapid and powerful gene-based association test using extended Simes procedure. Am J Hum Genet 88, 283-293 (2011).
11. Kwak, I. Y. & Pan, W. Adaptive gene- and pathway-trait association testing with GWAS summary statistics. Bioinformatics 32, 1178-1184 (2016).
12. Lamparter, D., Marbach, D., Rueedi, R., Kutalik, Z. & Bergmann, S. Fast and Rigorous Computation of Gene and Pathway Scores from SNP-Based Summary Statistics. PLoS Comput Biol 12, e1004714 (2016).
13. Li, M. X., Kwan, J. S. & Sham, P. C. HYST: a hybrid set-based test for genome-wide association studies, with application to proteinprotein interaction-based association analysis. Am J Hum Genet 91, 478-488 (2012).
14. Moskvina, V. et al. Permutation-based approaches do not adequately allow for linkage disequilibrium in gene-wide multi-locus association analysis. Eur J Hum Genet 20, 890-896 (2012).
15. Gusev, A. et al. Partitioning heritability of regulatory and cell-type-specific variants across 11 common diseases. Am. J. Hum. Genet. 95, 535-552 (2014).
16. Locke, A. E. et al. Genetic studies of body mass index yield new insights for obesity biology. Nature 518, 197-206 (2015).
17. Schizophrenia Working Group of the Psychiatric Genomics, C. Biological insights from 108 schizophrenia-associated genetic loci. Nature 511, 421-427 (2014).
18. Hamdan, F. F. et al. De novo mutations in FOXP1 in cases with intellectual disability, autism, and language impairment. Am J Hum Genet 87, 671-678 (2010).
19. Chien, W. H. et al. Increased gene expression of FOXP1 in patients with autism spectrum disorders. Mol Autism 4, 23 (2013).
20. Bacon, C. et al. Brain-specific Foxp1 deletion impairs neuronal development and causes autistic-like behaviour. Mol Psychiatry 20, 632-639 (2015).
21. Yang, J. et al. Genetic variance estimation with imputed variants finds negligible missing heritability for human height and body mass index. Nat. Genet. 47, 1114-1120 (2015).
22. Davies, R. B. Numerical Inversion of a Characteristic Function. Biometrika 60, 415-417 (1973).
23. Kuonen, D. Saddlepoint approximations for distributions of quadratic forms in normal variables. Biometrika 86, 929-935 (1999).
24. 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).
25. The UK10K Consortium. The UK10K project identifies rare variants in health and disease. Nature 526, 82-90 (2015).
26. Howie, B., Fuchsberger, C., Stephens, M., Marchini, J. & Abecasis, G. R. Fast and accurate genotype imputation in genome-wide association studies through pre-phasing. Nat. Genet. 44, 955-959 (2012).
27. 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).