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Amyotrophic lateral sclerosis (ALS) is a complex disease that leads to motor neuron death. Despite heritability estimates of 52%, genome-wide association studies (GWASs) have discovered relatively few loci. We developed a machine learning approach called RefMap, which integrates functional genomics with GWAS summary statistics for gene discovery. With transcriptomic and epigenetic profiling of motor neurons derived from induced pluripotent stem cells (iPSCs), RefMap identified 690 ALS-associated genes that represent a 5-fold increase in recovered heritability. Extensive conservation, transcriptome, network, and rare variant analyses demonstrated the functional significance of candidate genes in healthy and diseased motor neurons and brain tissues. Genetic convergence between common and rare variation highlighted KANK1 as a new ALS gene. Reproducing KANK1 patient mutations in human neurons led to neurotoxicity and demonstrated that TDP-43 mislocalization, a hallmark pathology of ALS, is downstream of axonal dysfunction. RefMap can be readily applied to other complex diseases.

Original publication

DOI

10.1016/j.neuron.2021.12.019

Type

Journal article

Journal

Neuron

Publication Date

16/03/2022

Volume

110

Pages

992 - 1008.e11

Keywords

ALS, TDP-43 mislocalization, axonal dysfunction, epigenetics, gene discovery, genetics, iPSC, machine learning, motor neurons, multiomics, Adaptor Proteins, Signal Transducing, Amyotrophic Lateral Sclerosis, Cell Death, Cytoskeletal Proteins, Genome-Wide Association Study, Humans, Induced Pluripotent Stem Cells, Motor Neurons