Integrating Multi-Omics Data to Identify Novel Disease Genes and Single-Neucleotide Polymorphisms

Abstract-In the world, stroke ranks the second leading cause of death among people over 60 years of age. Stroke is widely regarded as a complex disease affected by genetic and environmental factors. Evidence from twin and family studies suggests that genetic factors may play an important role in its pathogenesis. Therefore, the study of genetic association of susceptibility genes is helpful to reveal the pathogenesis of these two diseases. GWAS has found a large number of stroke-related loci, but their mechanism is unknown. In order to explore the pathogenesis of SNPs at the molecular level, in this paper, we integrated 8 GWAS datasets with brain eQTL dataset to identify SNPs and genes which are related to four types of stroke (ischemic stroke, large artery stroke, cardioembolic stroke, small vessel stroke). 38 SNPs which can affect 14 genes expression are found to be associated with stroke. We found that genes expression are associated with ischemic stroke, 1 gene for large artery stroke, 6 genes for cardioembolic stroke and 8 genes for small vessel stroke. To explore the effects of environmental factors on stroke, we identified methylation susceptibility loci associated with stroke using mQTL. 31 of these 38 SNPs are at greater risk of methylation and can significant change gene expression levels. We explored the genetic pathogenesis from locus to gene, gene to gene expression and gene expression to phenotype.