Functionally altered biological mechanisms arising from disease-Associated polymorphisms, remain difficult to characterise 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 modelling 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 (FDRo0.05). These prioritised SNP pairs with overlapping messenger RNA targets or similar functional annotations were more likely to be associated with the same disease than unrelated pathologies (OR412). We additionally confirmed synergistic and antagonistic genetic interactions for a subset of prioritised 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 Po10-4). Using ENCODE data sets, we further statistically validated that the biological mechanisms shared within prioritised 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.
ASJC Scopus subject areas
- Molecular Biology