title: A network-based approach to prioritize results from genome-wide association studies.
abstract: Genome-wide association studies (GWAS) are a valuable approach to understanding the genetic basis of complex traits. One of the challenges of GWAS is the translation of genetic association results into biological hypotheses suitable for further investigation in the laboratory. To address this challenge, we introduce Network Interface Miner for Multigenic Interactions (NIMMI), a network-based method that combines GWAS data with human protein-protein interaction data (PPI). NIMMI builds biological networks weighted by connectivity, which is estimated by use of a modification of the Google PageRank algorithm. These weights are then combined with genetic association p-values derived from GWAS, producing what we call 'trait prioritized sub-networks.' As a proof of principle, NIMMI was tested on three GWAS datasets previously analyzed for height, a classical polygenic trait. Despite differences in sample size and ancestry, NIMMI captured 95% of the known height associated genes within the top 20% of ranked sub-networks, far better than what could be achieved by a single-locus approach. The top 2% of NIMMI height-prioritized sub-networks were significantly enriched for genes involved in transcription, signal transduction, transport, and gene expression, as well as nucleic acid, phosphate, protein, and zinc metabolism. All of these sub-networks were ranked near the top across all three height GWAS datasets we tested. We also tested NIMMI on a categorical phenotype, Crohn's disease. NIMMI prioritized sub-networks involved in B- and T-cell receptor, chemokine, interleukin, and other pathways consistent with the known autoimmune nature of Crohn's disease. NIMMI is a simple, user-friendly, open-source software tool that efficiently combines genetic association data with biological networks, translating GWAS findings into biological hypotheses.
authors.affiliation: Mood and Anxiety Section, Human Genetics Branch, National Institute of Mental Health, National Institutes of Health, Department of Health and Human Services, Bethesda, Maryland, United States of America. akulan@mail.nih.gov
authors.forename: Nirmala
authors.initials: N
authors.lastname: Akula
authors.forename: Ancha
authors.initials: A
authors.lastname: Baranova
authors.forename: Donald
authors.initials: D
authors.lastname: Seto
authors.forename: Jeffrey
authors.initials: J
authors.lastname: Solka
authors.forename: Michael A
authors.initials: MA
authors.lastname: Nalls
authors.forename: Andrew
authors.initials: A
authors.lastname: Singleton
authors.forename: Luigi
authors.initials: L
authors.lastname: Ferrucci
authors.forename: Toshiko
authors.initials: T
authors.lastname: Tanaka
authors.forename: Stefania
authors.initials: S
authors.lastname: Bandinelli
authors.forename: Yoon Shin
authors.initials: YS
authors.lastname: Cho
authors.forename: Young Jin
authors.initials: YJ
authors.lastname: Kim
authors.forename: Jong-Young
authors.initials: JY
authors.lastname: Lee
authors.forename: Bok-Ghee
authors.initials: BG
authors.lastname: Han
authors.forename: Francis J
authors.initials: FJ
authors.lastname: McMahon
mesh_terms: D018925:Chemokines / Q000378:metabolism; D003424:Crohn Disease / Q000378:metabolism; D055106:Genome-Wide Association Study / Q000379:methods*; D006801:Humans; D007378:Interleukins / Q000378:metabolism; D011485:Protein Binding; D011948:Receptors, Antigen, T-Cell / Q000378:metabolism
chemical_list: D018925:Chemokines; D007378:Interleukins; D011948:Receptors, Antigen, T-Cell