Integration of multiomic data identifies core-module of inherited-retinal diseases

Abstract

Human diseases with similar phenotypes can be interconnected through shared biological pathways, genes, or molecular mechanisms. Inherited retinal diseases (IRDs) cause photoreceptor dysfunction due to mutations in approximately 300 genes, affecting visual transduction, photoreceptor morphogenesis, and transcription factors, suggesting common pathobiological mechanisms. This study examined the functional relationship between known IRDs genes by integrating binding sites and gene expression data from the key photoreceptor transcription factors (TFs), Crx and Nrl. We show that the targets of these TFs were enriched in IRDs causal genes. Co-expression network analysis revealed that IRD-centric networks were disrupted when Crx and Nrl were knocked out. Finally, we identified a highly connected core module comprising 14 IRD and 39 target genes, of which 29 were dysregulated in the rod photoreceptors of the four IRD mouse models. These findings offer a network-based interpretation of IRDs, aiding in the identification of common mechanisms, prioritizing genes for novel disease gene identification, and informing the development of gene-agnostic therapies for IRDs.

Keywords: Bioinformatics; Disease network; Genetics; Genomics; WGCNA.