title: Joint GWAS Analysis: Comparing similar GWAS at different genomic resolutions identifies novel pathway associations with six complex diseases.
abstract: 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.
authors.affiliation: Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA ; Harvard Medical School, Boston, MA, USA.
authors.forename: Michael J
authors.initials: MJ
authors.lastname: McGeachie
authors.affiliation: Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA.
authors.forename: George L
authors.initials: GL
authors.lastname: Clemmer
authors.affiliation: Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA ; Harvard Medical School, Boston, MA, USA.
authors.forename: Jessica
authors.initials: J
authors.lastname: Lasky-Su
authors.affiliation: Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA ; Harvard Medical School, Boston, MA, USA.
authors.forename: Amber
authors.initials: A
authors.lastname: Dahlin
authors.affiliation: Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA ; Harvard Medical School, Boston, MA, USA.
authors.forename: Benjamin A
authors.initials: BA
authors.lastname: Raby
authors.affiliation: Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA ; Harvard Medical School, Boston, MA, USA.
authors.forename: Scott T
authors.initials: ST
authors.lastname: Weiss
keywords: GWAS; Meta-analysis; Pathway enrichment; Pleiotropy; Systems genetics
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