Genome-Wide Identification of the Genetic Basis of Amyotrophic Lateral Sclerosis

Abstract

Amyotrophic lateral sclerosis (ALS) is a complex disease centered on progressive death of motor neurons. Despite heritability estimates of 52%, GWAS studies have discovered only seven genome-wide significant hits. We developed a new machine learning approach called RefMap that integrates functional genomics with ALS genetics. Comprehensive transcriptomic and epigenetic profiling of iPSC-derived motor neurons enabled RefMap to identify 690 genes associated with ALS, the majority of which are novel. Extensive conservation, transcriptome and network analyses demonstrated the functional significance of these candidate genes in motor neurons and disease progression, and our genetic results support initiation of ALS neurotoxicity in the distal axon. KANK1 is enriched with coding and noncoding, common and rare ALS-associated variants. Reproducing patient KANK1 mutations in human neurons led to neurotoxicity with disruption of the distal axon. RefMap can be applied broadly to increase the discovery power in genetic association studies of human complex traits and diseases.