An integrative transcriptome-wide analysis of amyotrophic lateral sclerosis for the identification of potential genetic markers and drug candidates

Abstract

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative neuromuscular disease. Although genome-wide association studies (GWAS) have successfully identified many variants signifi-cantly associated with ALS, it is still difficult to characterize the underlying biological mechanisms inducing ALS. In this study, we performed a transcriptome-wide association study (TWAS) to identify disease-specific genes in ALS. Using the largest ALS GWAS summary statistic (n = 80,610), we identified seven novel genes using 19 tissue reference panels. We conducted a conditional analysis to verify the genes’ independence and to confirm that they are driven by genetically regulated expres-sions. Furthermore, we performed a TWAS-based enrichment analysis to highlight the association of important biological pathways, one in each of the four tissue reference panels. Finally, utilizing a connectivity map, a database of human cell expression profiles cultured with bioactive small molecules, we discovered functional associations between genes and drugs to identify 15 bioactive small molecules as potential drug candidates for ALS. We believe that, by integrating the largest ALS GWAS summary statistic with gene expression to identify new risk loci and causal genes, our study provides strong candidates for molecular basis experiments in ALS.