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Genome-wide association analyses identify new risk variants and the genetic architecture of amyotrophic lateral sclerosis


To elucidate the genetic architecture of amyotrophic lateral sclerosis (ALS) and find associated loci, we assembled a custom imputation reference panel from whole-genome-sequenced patients with ALS and matched controls (n = 1,861). Through imputation and mixed-model association analysis in 12,577 cases and 23,475 controls, combined with 2,579 cases and 2,767 controls in an independent replication cohort, we fine-mapped a new risk locus on chromosome 21 and identified C21orf2 as a gene associated with ALS risk. In addition, we identified MOBP and SCFD1 as new associated risk loci. We established evidence of ALS being a complex genetic trait with a polygenic architecture. Furthermore, we estimated the SNP-based heritability at 8.5%, with a distinct and important role for low-frequency variants (frequency 1–10%). This study motivates the interrogation of larger samples with full genome coverage to identify rare causal variants that underpin ALS risk.

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Figure 1: Comparison of imputation accuracy.
Figure 2: Meta-analysis and LMM associations.
Figure 3: Partitioned heritability.

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The work of the contributing groups was supported by various grants from governmental and charitable bodies. Details are provided in the Supplementary Note.

Author information

Authors and Affiliations




A.V., N.T., K.L., B.R., K.V., M.R.-G., B.K., J.Z., L.L., L.D.G., S.M., F.S., V.M., M.d.C., S. Pinto, J.S.M., R.R.-G., M.P., S. Chandran, S. Colville, R.S., K.E.M., P.J.S., J.H., R.W.O., A. Pittman, K.S., P.F., A. Malaspina, S.T., S. Petri, S. Abdulla, C.D., M.S., T. Meyer, R.A.O., K.A.S., M.W.-P., C.L.-H., V.M.V.D., J.Q.T., L.E., L. McCluskey, A.N.B., Y.P., T. Meitinger, P.L., M.R.-B., C.R.A., C. Maurel, G. Bensimon, B.L., A.B., C.A.M.P., S.S.-D., A.D., N.W.W., L.T., W.L., A.F., M.R., S. Cichon, M.M.N., P.A., C. Tzourio, J.-F.D., A.G.U., F.R., K.E., A.H., C. Curtis, H.M.B., A.J.v.d.K., M.d.V., A.G., M.W., C.E.S., B.N.S., O.P., C. Cereda, R.D.B., G.P.C., S.D'A., C.B., G.S., L. Mazzini, V.P., C.G., C. Tiloca, A.R., A. Calvo, C. Moglia, M.B., S. Arcuti, R.C., C.Z., C.L., S. Penco, N.R., A. Padovani, M.F., B.M., R.J.S., PARALS Registry, SLALOM Group, SLAP Registry, FALS Sequencing Consortium, SLAGEN Consortium, NNIPPS Study Group, I.B., G.A.N., D.B.R., R.P., M.C.K., J.G., O.W.W., T.R., B.S., I.K., C.A.H., P.N.L., F.C., A. Chìo, E.B., E.P., R.T., G.L., J.P., A.C.L., J.H.W., W.R., P.V.D., L.F., T.P., R.H.B., J.D.G., J.E.L., O. Hardiman, P.M.A., P.C., P.V., V.S., M.A.v.E., A.A.-C., L.H.v.d.B. and J.H.V. were involved in phenotyping, sample collection and management. W.v.R., A.S., A.M.D., R.L.M., F.P.D., R.A.A.v.d.S., P.T.C.v.D., G.H.P.T., M.K., A.M.B., W.S., A.R.J., K.P.K., I.F., A.V., N.T., R.D.S., W.J.B., A.V., K.V., M.R.-G., B.K., L.L., S. Abdulla, K.S., E.P., F.P.D., J.M., C. Curtis, G. Breen, A.A.-C. and J.H.V. prepared DNA and performed SNP array hybridizations. W.v.R., S.L.P., K.P.K., K.L., A.M.D., P.T.C.v.D., G.H.P.T., K.R.v.E., P.I.W.d.B. and J.H.V. were involved in the next-generation sequencing analyses. W.v.R., K.R.v.E., A. Menelaou, P.I.W.d.B., A.A.-C. and J.H.V. performed the imputation. W.v.R., A.S., F.P.D., R.L.M., S.L.P., S.d.J., I.F., N.T., W.S., A.R.J., K.P.K., K.R.v.E., K.S., H.M.B., P.I.W.d.B., M.A.v.E., C.M.L., G. Breen, A.A.-C., L.H.v.d.B. and J.H.V. performed GWAS analyses. W.v.R., A.M.D., R.A.A.v.d.S., R.L.M., C.R.A., M.K., A.M.B., R.D.S., E.P.M., J.A.F., C. Tunca, H.H., K.Z., P.C., P.V. and J.H.V. performed the replication analyses. W.v.R., A.S., R.L.M., M.R.R., J.Y., N.R.W., P.M.V., C.M.L., A.A.-C. and J.H.V. performed polygenic risk scoring and heritability analyses. S.d.J., U.V., L.F., T.H.P., W.v.R., O. Harschnitz, G. Breen, R.J.P. and J.H.V. performed biological pathway analyses. U.V., L.F., W.v.R. and J.H.V. performed eQTL analyses. W.v.R., A.S., A.A.-C., L.H.v.d.B. and J.H.V. prepared the manuscript with contributions from all authors. A.A.-C., L.H.v.d.B. and J.H.V. directed the study.

Corresponding authors

Correspondence to Ammar Al-Chalabi or Jan H Veldink.

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Competing interests

The authors declare no competing financial interests.

Additional information

A list of members appears in the Supplementary Note.

A list of members appears in the Supplementary Note.

A list of members appears in the Supplementary Note.

A list of members appears in the Supplementary Note.

A list of members appears in the Supplementary Note.

A list of members appears in the Supplementary Note.

Integrated supplementary information

Supplementary Figure 1 Coverage distribution for reference panel.

(a) Average coverage for all non-reference bases for all samples in the custom reference panel. An average coverage of 43.7 reads per base was achieved. (b) Percentage of non-reference bases covered by at least 5 (blue), 10 (yellow) or 20 (red) reads. Histograms include all individuals, before quality control.

Source data

Supplementary Figure 2 Comparison between meta-analysis and linear mixed-model results.

Regressing the –log10 (P values) derived from the linear mixed model on the meta-analysis P values yielded a slope below the diagonal (β = 0.86), implying no overall inflation of the test statistic. Strongly associated SNPs, however, deviated from the regression line representing the increased power of a linear mixed model in comparison to a meta-analysis for association testing.

Supplementary Figure 3 Quantile–quantile plots.

(a,b) Meta-analysis (a) and linear mixed model (b). For presentation purposes, P values <5 × 10−8 are plotted at 5 × 10−8.

Supplementary Figure 4 Replication results.

Forest plot for the inverse-variance-weighted, fixed-effect meta-analysis of the discovery phase and replication cohorts. OR, odds ratio; CI, confidence interval.

Supplementary Figure 5 Fine-mapping of the C21orf2 locus.

(a) Associations for all SNPs analyzed in the GWAS in the C21orf2 locus where only rs75087725 reaches genome-wide significance. (b) LD as defined by |D′| (absolute D-prime value) for all variants obtained from whole-genome sequencing data of the custom reference panel. Possible causal variants for driving factors of the GWAS association were considered when they met the following criteria: (i) risk allele frequency difference between cases and controls exceeding 0.4% (risk allele frequency difference for rs75087725 = 0.8%), (ii) rs75087725 as the best genotyped GWAS tag for the variant and (iii) minor allele with a risk-increasing effect on ALS. (c) No such variant was in LD with rs75087725. (d) LD defined by R2 is very sparse. (e) C21orf2 is the only gene in this locus with an increased burden of rare nonsynonymous variants in the sequencing data of our custom reference panel, indicating that C21orf2 is indeed the ALS risk gene.

Source data

Supplementary Figure 6 C21orf2 rare variant burden.

Summary of the rare (MAF < 0.05) nonsynonymous and loss-of-function mutations in the canonical transcript of C21orf2. Conditioning on the SNP found to be associated in the GWAS (rs75087725, p.V58L; gray), there was an increased burden of nonsynonymous and loss-of-function mutations among ALS cases (PT5 = 9.2 × 10−5, PT1 = 0.01). Odds ratios (calculated by counting alleles in cases and controls per stratum, unadjusted for principal components, combined in a Cochran–Mantel–Haenszel test) are 1.63 and 1.48 for T5 and T1 burden, respectively. The two loss-of-function mutations observed in cases are colored red.

Supplementary Figure 7 cis-eQTL regional plots for six genome-wide-significant loci.

Highlighted are cis-eQTLs acquired from several resources (genes in green) and brain cis-eQTLs (genes in black). Stranded RNA-seq data for one fetal brain (3,000-bp sliding window) are shown on a separate track. For the MOBP region, there was an eQTL effect for MOBP (P = 7.12 × 10−18), but the effect SNP, rs1707953, did not show any association with ALS in our GWAS (P = 0.74). Further details of highlighted brain cis-eQTLs and non-brain cis-eQTLs are given in Supplementary Table 10 and the Supplementary Data Set. eQTL annotation and LD data are shown only for SNPs present in the 1000 Genomes Project p1v3 CEU population.

Source data

Supplementary Figure 8 Polygenic risk scores.

(a) Polygenic risk score analyses where nine cohorts were used as targets. Best predictions were made when including the six genome-wide-significant SNPs from the C9orf72 and UNC13A loci only. (b) Polygenic risk score analyses excluding all variants on chromosome 9. Increased polygenic risk score predictions were made when including more variants by lowering the P-value threshold. Note that the overall prediction accuracy is lower than when SNPs on chromosome 9 were included.

Source data

Supplementary Figure 9 Partitioned heritability excluding candidate loci.

(a) SNPs in the C9orf72 locus (within 1 Mb of rs3849943 and r2 >0.2) were excluded from heritability estimates. (b) SNPs within 1 Mb of the top associated SNP and r2 >0.2 for all loci exceeding genome-wide significance were excluded for heritability estimates. In both instances, most heritability was explained by low-frequency variants (MAF < 0.1).

Source data

Supplementary Figure 10 DEPICT biological pathway analysis.

The top ten terms from Gene Ontology, KEGG and Reactome pathways that are most enriched for genes tagged by SNPs in the GWAS are displayed. Different thresholds of significance were used to select SNPs for the DEPICT analyses. The lengths of the bars correspond to the nominal significance levels, the black line indicates the P-value threshold of 0.05 and color corresponds to FDR, determined by 200 permutations. When all SNPs with a P value <1 × 10−4 in the linear mixed-model analysis were included, it identifies the Gene Ontology category SNAP receptor (SNARE) activity as the only significantly enriched term after correction for multiple testing.

Supplementary Figure 11 Population outlier removal.

(a) Example of stratum sNL2 projected onto the first two principal components calculated on HapMap 3 individuals. Individuals of non-European ancestry (±10 s.d. from the HapMap CEU mean on PC1–PC4) were removed. (b) Subsequent removal of samples deviating by more than 4 s.d. from the stratum mean eigenvalues on PC1 and PC2 (HapMap 3). (c,d) Individuals remaining after removing population outliers resulting in a homogenous European sample where the Scandinavian individuals (mainly Finnish), as expected, depart from the other strata.

Source data

Supplementary Figure 12 Population structure of the custom reference panel.

Individuals projected onto the first two principal components calculated on HapMap 3 individuals. NL, Netherlands; Ir, Ireland; It, Italy; No, Norway; Sp, Spain; Sw, Sweden; US, United States.

Source data

Supplementary Figure 13 C21orf2 rare variant analysis quality control.

Quantile–quantile plots for the single-SNV regression of chromosome 21 including the first ten principal components as covariates are displayed on the left. Principal-components plots for each stratum are shown on the right. Population stratification was successfully corrected for, resulting in well-behaved burden tests without evidence for overall inflation of the test statistic.

Source data

Supplementary Figure 14 Genetic relationship matrix distribution.

(a) Diagonal values of the SNP-based GRM. (b) Distribution of the off-diagonal values representing the relatedness between samples. Pairs of individuals whose relatedness exceeded 0.05 were excluded from the heritability estimations. GRM, genetic relationship matrix.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–14, Supplementary Tables 1–20 and Supplementary Note. (PDF 4545 kb)

Supplementary Data Set: Brain cis-eQTLs.

Overlap with previously identified brain cis-eQTLs for all SNPs in the genome-wide-significant loci. (XLSX 88 kb)

Source data

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van Rheenen, W., Shatunov, A., Dekker, A. et al. Genome-wide association analyses identify new risk variants and the genetic architecture of amyotrophic lateral sclerosis. Nat Genet 48, 1043–1048 (2016).

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