Mechanism-free repurposing of drugs for C9orf72-related ALS/FTD using large-scale genomic data

Abstract

Repeat expansions in the C9orf72 gene are the most common genetic cause of (ALS) and frontotemporal dementia (FTD). Like other genetic forms of neurodegeneration, pinpointing the precise mechanism(s) by which this mutation leads to neuronal death remains elusive, and this lack of knowledge hampers the development of therapy for C9orf72-related disease. We used an agnostic approach based on genomic data (n = 41,273 ALS and healthy samples, and n = 1,516 C9orf72 carriers) to overcome these bottlenecks. Our drug-repurposing screen, based on gene- and expression-pattern matching and information about the genetic variants influencing onset age among C9orf72 carriers, identified acamprosate, a γ-aminobutyric acid analog, as a potentially repurposable treatment for patients carrying C9orf72 repeat expansions. We validated its neuroprotective effect in cell models and showed comparable efficacy to riluzole, the current standard of care. Our work highlights the potential value of genomics in repurposing drugs in situations where the underlying pathomechanisms are inherently complex. VIDEO ABSTRACT.

Keywords: C9orf72; acamprosate; age at onset; amyotrophic lateral sclerosis; drug repurposing; frontotemporal dementia; translation.

Graphical abstract

Figure 1

Schematic illustration of the analytical workflow The genetic risk score for sporadic ALS was generated using large cohorts as the reference and training sets. This general ALS genetic risk score was then calculated for a sizable cohort of C9orf72 carriers. Follow-up analyses included pathway analysis and the identification of individual loci with a major contribution to the age at onset. Using the information obtained from these genetic analyses, we performed drug repurposing based on gene-gene-pattern matching and expression-pattern matching to identify drugs that may delay symptom onset among C9orf72 carriers. In vitro drug validation confirmed the neuroprotective effect of the drug nominated by this approach.

Figure 2

Genetic variants influencing symptom onset age among ALS/FTD patients carrying the C9orf72 repeat expansion The ideograms show the 161 ALS genetic risk loci making up the general ALS polygenic risk score. Labels with red text denote the 16 SNPs making up decile 10. The nearest genes to the variants are displayed. The colors of the circles correspond to the gene type: dark blue, RNA gene; light blue, protein-coding gene; red, pseudogene; black, intergenic. The numbers at the top indicate the chromosome. Interg, intergenic. See also Table S1.

Figure 3

The ALS genetic risk score significantly influences onset age in C9orf72 carriers (A and B) The regression lines show the association of the ALS genetic risk scores and age at onset in (A) the test dataset (n = 817 ALS/FTD C9orf72 carriers, p = 0.024, β = −0.765, 95% CI = −1.429 to −0.101) and (B) the replication dataset (n = 699, p = 0.026, β = −0.799, 95% CI = −1.499 to −0.099). The shadow areas represent the 90% confidence interval of the regression model. (C) The forest plot shows the results of the meta-analysis of the test and replication datasets (p = 1.5 × 10⁻³, β = −0.781, 95% CI = −1.263 to −0.299). See also Figures S1 and S2 and Table S2.

Figure 4

Contribution of individual SNPs to age at symptom onset among C9orf72 patients (A) The forest plot shows the effect size of each decile obtained by ranking the 161 individual SNPs based on their effect on age at onset in C9orf72 patients. (B) The regression lines show the association between the ALS genetic risk scores and age at onset in 817 ALS/FTD C9orf72 carriers based on the 16 SNPs of decile 10 (n = 817 ALS/FTD C9orf72 carriers, p = 8.97 × 10⁻¹¹, β = −2.17, 95% CI = −2.81 to −1.52). The shadow area represents the 90% confidence interval of the regression model. (C) Sankey diagram showing the functional enrichment of decile 10 genes, based on Gene Ontology terms. Only gene lists that contain between 5 and 500 genes were selected for the analysis. The significant threshold was an false discovery rate (FDR)-corrected p < 0.05. See also Figures S3–S5 and Tables S3, S4, and S7.

Figure 5

Repurposing drugs to delay onset among C9orf72 carriers The figure shows the results obtained from our drug-repositioning pipeline. (A) Enriched terms derived from the GREP software package, which is based on the Anatomical Therapeutic Chemical classification. Blue indicates the significant “other nervous system drugs” category. Some of the drugs within this category are shown (see Table S6 for a complete list). (B) Lollipop plots depict drug enrichment analysis for different categories, such as disease indication, gene target, and mechanism of action. Information was obtained from the Drugmonizome database, and the x axis depicts the enrichment corrected p value, which uses Bonferroni correction for the disease indication and the gene target plots and FDR for the mechanism of action. (C) Drug perturbation data were obtained from the LINCS database. The graphs show the CMap scores for the selected drugs across cell types. CMap scores are determined using a bidirectional weighted Kolmogorov-Smirnov enrichment statistic test, which compares gene expression changes in the disease and drug signatures to quantify the extent to which the drug effectively reversed (flipped) the gene expression signature associated with the disease. Lower scores indicate a more substantial potential for therapeutic effectiveness. An average CMap (diamond shape) was calculated using the normalized connectivity score to evaluate the overall effect of each drug across the tested cell lines. Drugs with a reversal potential were selected if (1) they depicted a negative average CMap and (2) they showed a negative or neutral (measured as 0) CMap score for each cell line (circle shape). A375, ASC, FIBRNPC, HCC515, HT29, NEU, A549, NPC, HA1E, PC3, MCF7, PHH, SKB, and VCAP refer to the cell line types available in the LINCS database (see STAR Methods for details). (D) The Venn diagram shows the drugs that fulfilled these criteria in the motor cortex and cerebellum. Of these, acamprosate was selected for additional in vitro validation. See also Figures S5 and S6.

Figure 6

Acamprosate is neuroprotective in iPSC-derived motor neurons from C9orf72 patients (A) Schematic representation of the experiments to validate the effect of acamprosate. (B) The bar graph depicts the percentage of cells showing cleaved caspase-3 (caspase-3⁺ cells) after acamprosate treatment. Minor dots represent biological replicates, averaging from three technical replicates each. In contrast, the bordered dots represent the mean effect in iPSC-derived motor neurons from two healthy donors, two C9orf72 ALS patients, and one isogenic line. Data are mean ± SD. Comparisons within the control and the ALS-C9orf72 groups were performed using a two-way ANOVA, with a Tukey’s post hoc test (n = 2). Only p < 0.05 and comparisons with the vehicle group are displayed in the graph. (C) Representative images of the motor neurons showing cleaved caspase-3 staining (green), MAP2 staining (red), and DAPI (blue). Scale bar, 50 μm. All molecular phenotypes were confirmed in a minimum of 3 technical replicates, and at least 25 fields were randomly selected and scanned per well of a 96-well plate in triplicate. (D) Acamprosate effective doses (10 and 30 μM) were confirmed in additional iPSC-derived motor neurons, totaling cells from four healthy donors, five C9orf72 ALS patients, and two isogenic lines. Each point represents the mean effect per cell line. Data are mean ± SD. Comparisons within the control, the ALS-C9orf72, and the ISO-C9orf72 groups were performed using a two-way ANOVA, with Tukey’s post hoc test (control, n = 4; ALS-C9orf72, n = 5; ISO-C9orf72, n = 2). p < 0.05 are annotated. (E) The graph shows the percentage of cleaved caspase-3⁺ motor neurons derived from C9orf72 patients treated with riluzole (10 μM) and riluzole plus acamprosate (10 and 30 μM). Dots represent the mean effect of each line. Data are mean ± SD. Comparisons were performed using a one-way ANOVA with Tukey’s post hoc test (n = 5). p < 0.05 are annotated as follows: ∗p < 0.05; ∗∗p < 0.01; ∗∗∗p < 0.001; ∗∗∗∗p < 0.001, ∗∗∗∗∗p < 0.0001. See also Figures S6–S9 and Table S10.