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.
•Machine learning method identifies risk genes by integrating GWASs and epigenetic data•Discovered ALS risk genes lead to a 5-fold increase in recovered heritability•Genetic and experimental support for initiation of ALS pathogenesis in the distal axon•Convergent genetic and experimental data establish KANK1 as a new ALS gene
Zhang et al. develop a new machine learning method that integrates epigenetic profiling with GWAS summary statistics for gene discovery. Application to ALS identifies 690 risk genes with 5-fold increase in recovered heritability. Leading candidate KANK1 is reproduced in human neurons leading to TDP-43 mislocalization, a hallmark pathology of ALS.
Abstract
With the advent of gene therapies for amyotrophic lateral sclerosis (ALS), there is a surge in gene testing for this disease. Although there is ample experience with gene testing for ...C9orf72, SOD1, FUS and TARDBP in familial ALS, large studies exploring genetic variation in all ALS-associated genes in sporadic ALS (sALS) are still scarce. Gene testing in a diagnostic setting is challenging, given the complex genetic architecture of sALS, for which there are genetic variants with large and small effect sizes. Guidelines for the interpretation of genetic variants in gene panels and for counselling of patients are lacking.
We aimed to provide a thorough characterization of genetic variability in ALS genes by applying the American College of Medical Genetics and Genomics (ACMG) criteria on whole genome sequencing data from a large cohort of 6013 sporadic ALS patients and 2411 matched controls from Project MinE.
We studied genetic variation in 90 ALS-associated genes and applied customized ACMG-criteria to identify pathogenic and likely pathogenic variants. Variants of unknown significance were collected as well. In addition, we determined the length of repeat expansions in C9orf72, ATXN1, ATXN2 and NIPA1 using the ExpansionHunter tool.
We found C9orf72 repeat expansions in 5.21% of sALS patients. In 50 ALS-associated genes, we did not identify any pathogenic or likely pathogenic variants. In 5.89%, a pathogenic or likely pathogenic variant was found, most commonly in SOD1, TARDBP, FUS, NEK1, OPTN or TBK1. Significantly more cases carried at least one pathogenic or likely pathogenic variant compared to controls (odds ratio 1.75; P-value 1.64 × 10−5). Isolated risk factors in ATXN1, ATXN2, NIPA1 and/or UNC13A were detected in 17.33% of cases. In 71.83%, we did not find any genetic clues. A combination of variants was found in 2.88%.
This study provides an inventory of pathogenic and likely pathogenic genetic variation in a large cohort of sALS patients. Overall, we identified pathogenic and likely pathogenic variants in 11.13% of ALS patients in 38 known ALS genes. In line with the oligogenic hypothesis, we found significantly more combinations of variants in cases compared to controls. Many variants of unknown significance may contribute to ALS risk, but diagnostic algorithms to reliably identify and weigh them are lacking. This work can serve as a resource for counselling and for the assembly of gene panels for ALS. Further characterization of the genetic architecture of sALS is necessary given the growing interest in gene testing in ALS.
The development of gene therapies for amyotrophic lateral sclerosis (ALS) has led to increased interest in genetic testing, including for patients with the sporadic form of the disease. Van Daele et al. characterize variability in ALS-associated genes, and search for likely pathogenic variants, in more than 6000 patients with sporadic ALS.
Objective
The role of the survival of motor neuron (SMN) gene in amyotrophic lateral sclerosis (ALS) is unclear, with several conflicting reports. A decisive result on this topic is needed, given ...that treatment options are available now for SMN deficiency.
Methods
In this largest multicenter case control study to evaluate the effect of SMN1 and SMN2 copy numbers in ALS, we used whole genome sequencing data from Project MinE data freeze 2. SMN copy numbers of 6,375 patients with ALS and 2,412 controls were called from whole genome sequencing data, and the reliability of the calls was tested with multiplex ligation‐dependent probe amplification data.
Results
The copy number distribution of SMN1 and SMN2 between cases and controls did not show any statistical differences (binomial multivariate logistic regression SMN1 p = 0.54 and SMN2 p = 0.49). In addition, the copy number of SMN did not associate with patient survival (Royston‐Parmar; SMN1 p = 0.78 and SMN2 p = 0.23) or age at onset (Royston‐Parmar; SMN1 p = 0.75 and SMN2 p = 0.63).
Interpretation
In our well‐powered study, there was no association of SMN1 or SMN2 copy numbers with the risk of ALS or ALS disease severity. This suggests that changing SMN protein levels in the physiological range may not modify ALS disease course. This is an important finding in the light of emerging therapies targeted at SMN deficiencies. ANN NEUROL 2021;89:686–697
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