Title: Integrative genomics analyses unveil downstream biological effectors of disease-specific polymorphisms buried in intergenic regions.
Authors: Li, Haiquan; Achour, Ikbel; Bastarache, Lisa; Berghout, Joanne; Gardeux, Vincent; Li, Jianrong; Lee, Younghee; Pesce, Lorenzo; Yang, Xinan; Ramos, Kenneth S; Foster, Ian; Denny, Joshua C; Moore, Jason H; Lussier, Yves A
Published In NPJ Genom Med, (2016)
Abstract: Functionally altered biological mechanisms arising from disease-associated polymorphisms, remain difficult to characterize when those variants are intergenic, or, fall between genes. We sought to identify shared downstream mechanisms by which inter- and intragenic single nucleotide polymorphisms (SNPs) contribute to a specific physiopathology. Using computational modeling of 2 million pairs of disease-associated SNPs drawn from genome wide association studies (GWAS), integrated with expression Quantitative Trait Loci (eQTL) and Gene Ontology functional annotations, we predicted 3,870 inter-intra and inter-intra SNP pairs with convergent biological mechanisms (FDR<0.05). These prioritized SNP pairs with overlapping mRNA targets or similar functional annotations were more likely to be associated with the same disease than unrelated pathologies (OR>12). We additionally confirmed synergistic and antagonistic genetic interactions for a subset of prioritized SNP pairs in independent studies of Alzheimer's disease (entropy p=0.046), bladder cancer (entropy p=0.039), and rheumatoid arthritis (PheWAS case-control p<10-4). Using ENCODE datasets, we further statistically validated that the biological mechanisms shared within prioritized SNP pairs are frequently governed by matching transcription factor binding sites and long-range chromatin interactions. These results provide a "roadmap" of disease mechanisms emerging from GWAS and further identify candidate therapeutic targets among downstream effectors of intergenic SNPs.
PubMed ID: 27482468
MeSH Terms: No MeSH terms associated with this publication