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. 2023 Sep 1;146(9):3760-3769.
doi: 10.1093/brain/awad120.

Genetic variability in sporadic amyotrophic lateral sclerosis

Sien Hilde Van Daele  1   2   3   4 , Matthieu Moisse  1   2 , Joke J F A van Vugt  5 , Ramona A J Zwamborn  5 , Rick van der Spek  5 , Wouter van Rheenen  5 , Kristel Van Eijk  5 , Kevin Kenna  5 , Philippe Corcia  6   7 , Patrick Vourc'h  7 , Philippe Couratier  8 , Orla Hardiman  9 , Russell McLaughin  10 , Marc Gotkine  11 , Vivian Drory  12 , Nicola Ticozzi  13   14 , Vincenzo Silani  13   14 , Antonia Ratti  13   15 , Mamede de Carvalho  16 , Jesús S Mora Pardina  17 , Monica Povedano  18 , Peter M Andersen  19 , Markus Weber  20 , Nazli A Başak  21 , Chris Shaw  22 , Pamela J Shaw  23 , Karen E Morrison  24 , John E Landers  25 , Jonathan D Glass  26 , Michael A van Es  5 , Leonard H van den Berg  5 , Ammar Al-Chalabi  22 , Jan Veldink  5 , Philip Van Damme  1   2   3
Affiliations

Genetic variability in sporadic amyotrophic lateral sclerosis

Sien Hilde Van Daele et al. Brain. .

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.

Keywords: complex genetic disease; motor neuron disease; oligogenic inheritance.

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Conflict of interest statement

J.V. reports to have sponsored research agreements with Biogen and Astra Zeneca. A.A.-C reports consultancies or advisory boards for Amylyx, Apellis, Biogen, Brainstorm, Cytokinetics, GenieUs, GSK, Lilly, Mitsubishi Tanabe Pharma, Novartis, OrionPharma, Quralis, Sano, Sanofi and Wave Pharmaceuticals. P.V.D. has served in advisory boards for Biogen, CSL Behring, Alexion Pharmaceuticals, Ferrer, QurAlis, Cytokinetics, Argenx, UCB, Muna Therapeutics, Alector, Augustine Therapeutics, VectorY and Zambon.

Figures

Figure 1
Figure 1
Lolliplots showing pathogenic and likely pathogenic variants encountered in NEK1, SOD1, FUS, OPTN, TARDBP and TBK1 in cases and controls. Lolliplots showing the mutational spectra of the displayed genes in cases (n = 6013) and controls (n = 2411). For each gene, exons and untranslated regions are represented as grey bars, connected by introns shown as grey lines (reduced with a factor 1/100). Protein domains and motifs are shown as coloured bars. Each lollipop represents a pathogenic or likely pathogenic variant encountered in cases (top) or controls (bottom). The absolute number of cases and controls with the variant is reflected by the height of the lollipop. Known ALS-associated mutations (from ClinVar and the NMHP) are shown as red lines. AXH = ataxin-1/HBP1 domain; CCD1 = coiled-coil domain 1; NMHP = neuromuscular homepage; RRM = RNA recognition motif; ULD = ubiquitin-like domain; UTR = untranslated region.
Figure 2
Figure 2
Odds ratios and their 95% confidence intervals. Illustration of the odds ratios and their 95% confidence intervals for the 40 genes with pathogenic or likely pathogenic variants in. Odds ratios are calculated compared to gnomAD v3.
Figure 3
Figure 3
Waterfall plot: combinations of variants. A waterfall plot shows for all cases (left) and controls (right) which variants they carry: repeat expansions in C9orf72; pathogenic or likely pathogenic sequencing variants in NEK1, SOD1, FUS, OPTN, TARDBP, TBK1 or in one of the other ALS-associated genes; risk factors such as (intermediate) repeat expansions in ATXN1, ATXN2 and NIPA1 or the CC-genotype of the SNP rs12608932 in UNC13A. Brown = repeat expansions; grey = pathogenic (P) and likely pathogenic (LP) sequencing variants; purple = non-repeat expansion risk variants.
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