Abstract
Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease with a lifetime risk of one in 350 people and an unmet need for disease-modifying therapies. We conducted a cross-ancestry genome-wide association study (GWAS) including 29,612 patients with ALS and 122,656 controls, which identified 15 risk loci. When combined with 8,953 individuals with whole-genome sequencing (6,538 patients, 2,415 controls) and a large cortex-derived expression quantitative trait locus (eQTL) dataset (MetaBrain), analyses revealed locus-specific genetic architectures in which we prioritized genes either through rare variants, short tandem repeats or regulatory effects. ALS-associated risk loci were shared with multiple traits within the neurodegenerative spectrum but with distinct enrichment patterns across brain regions and cell types. Of the environmental and lifestyle risk factors obtained from the literature, Mendelian randomization analyses indicated a causal role for high cholesterol levels. The combination of all ALS-associated signals reveals a role for perturbations in vesicle-mediated transport and autophagy and provides evidence for cell-autonomous disease initiation in glutamatergic neurons.
Highlights
Further information on research design is available in the Nature Research Reporting Summary linked to this article
J. et al Gene discovery and polygenic prediction from a genome-wide association study of educational attainment in 1.1 million individuals
Summary
Cross-ancestry meta-analysis reveals 15 risk loci for ALS. To generate the largest GWAS of ALS to date, we merged individual-level genotype data from 117 cohorts into six strata matched by genotyping platform. This was the most likely causal mechanism for rs75087725 (CFAP410, formerly C21orf[2], p.V58L; Supplementary Fig. 15), as the GWAS variant is a missense variant; no evidence for other mechanisms including repeat expansions or eQTL or mQTL effects was observed within this locus, and CFAP410 itself is known to directly interact with NEK1, another ALS gene[6,28] These three loci illustrate the power of large-scale GWASs combined with large imputation panels to directly identify low-frequency causal variants that confer disease risk. To find tissues and cell types for which gene expression profiles were enriched for genes within ALS-risk loci, we first combined gene-based association statistics
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