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2014 ; 2
(ä): 202-211
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Joint GWAS Analysis: Comparing similar GWAS at different genomic resolutions
identifies novel pathway associations with six complex diseases
#MMPMID25838990
McGeachie MJ
; Clemmer GL
; Lasky-Su J
; Dahlin A
; Raby BA
; Weiss ST
Genom Data
2014[Dec]; 2
(ä): 202-211
PMID25838990
show ga
We show here that combining two existing genome wide association studies (GWAS)
yields additional biologically relevant information, beyond that obtained by
either GWAS separately. We propose Joint GWAS Analysis, a method that compares a
pair of GWAS for similarity among the top SNP associations, top genes identified,
gene functional clusters, and top biological pathways. We show that Joint GWAS
Analysis identifies additional enriched biological pathways that would be missed
by traditional Single-GWAS analysis. Furthermore, we examine the similarities of
six complex genetic disorders at the SNP-level, gene-level, gene-cluster-level,
and pathway-level. We make concrete hypotheses regarding novel pathway
associations for several complex disorders considered, based on the results of
Joint GWAS Analysis. Together, these results demonstrate that common complex
disorders share substantially more genomic architecture than has been previously
realized and that the meta-analysis of GWAS needs not be limited to GWAS of the
same phenotype to be informative.