Large-scale genome-wide association analyses identify novel genetic loci and mechanisms in hypertrophic cardiomyopathy

Abstract

Hypertrophic cardiomyopathy (HCM) is an important cause of morbidity and mortality with both monogenic and polygenic components. Here, we report results from a large genome-wide association study and multitrait analysis including 5,900 HCM cases, 68,359 controls and 36,083 UK Biobank participants with cardiac magnetic resonance imaging. We identified 70 loci (50 novel) associated with HCM and 62 loci (20 novel) associated with relevant left ventricular traits. Among the prioritized genes in the HCM loci, we identify a novel HCM disease gene, SVIL, which encodes the actin-binding protein supervillin, showing that rare truncating SVIL variants confer a roughly tenfold increased risk of HCM. Mendelian randomization analyses support a causal role of increased left ventricular contractility in both obstructive and nonobstructive forms of HCM, suggesting common disease mechanisms and anticipating shared response to therapy. Taken together, these findings increase our understanding of the genetic basis of HCM, with potential implications for disease management.

Fig. 1. Study flowchart.

Flowchart of meta-analysis of seven case–control HCM GWAS datasets, GWAS of LV traits and downstream analyses. Created using BioRender.com.

Fig. 2. Genetic correlation of LV traits and HCM and use of MTAG to empower locus discovery.

Pairwise genetic correlation between LV traits shown in heatmap as absolute values (|rg_LV|) ranging from 0 (white) to 1 (red). LV traits are sorted into three clusters based on |rg_LV| along the x and y axes using Euclidean distance and complete hierarchical clustering: LV contractility (blue), volume (bluish green) and mass (orange) (see dendrogram on top). The table in the middle shows the individual LV trait h²_SNP and genetic correlation with HCM (rg_HCM), with corresponding s.e. The trait with the strongest correlation (based on rg_HCM) in each of the three clusters was carried forward for MTAG to empower locus discovery in HCM. MTAG resulted in an increase in N_eff, based on number of cases and controls and increase in mean χ² statistic from 21,725 to 28,106, with an estimated maxFDR of 0.027. Since strain^circ and strain^long are negative values where increasingly negative values reflect increased contractility, we show −strain^circ and −strain^long to facilitate interpretation of rg_HCM sign. Full rg_LV and rg_HCM results are shown in Supplementary Table 7.

Fig. 3. Circular Manhattan plot of HCM summary statistics from MTAG analysis.

Previously published loci are identified in black (n = 20), novel loci discovered by single-trait all-comer GWAS meta-analysis are identified in blue (n = 13) and other novel loci from MTAG are identified in green (n = 35). Two other loci reaching GWAS significance threshold in the single-trait HCM GWAS meta-analysis but not reaching significance in MTAG are not shown (mapped to TRDN/HEY2 and CHPF; Table 1). P values are not corrected for multiple testing and correspond to the HCM MTAG including the fixed-effects meta-analysis of seven HCM case–control GWAS and three LV traits (Fig. 2). Significant variants with P < 5 × 10⁻⁸ are shown as black triangles. Results with P < 1 × 10⁻¹⁵ are assigned P = 1 × 10⁻¹⁵. Locus naming was performed primarily by OpenTargets gene prioritization considering FUMA and previous gene association with Mendelian HCM. See Supplementary Table 8 for loci details.

Fig. 4. HCM locus-to-gene mapping, prioritization and rare LoF association testing identifies SVIL as a new HCM disease gene.

a, HCM locus-to-gene mapping and prioritization based on cardiac expression. Locus-to-gene mapping was done using the OpenTargets V2G pipeline (release of 12 October 2022) for all 68 lead variants at the HCM MTAG loci and using FUMA for the HCM MTAG summary statistics (see Methods for detailed parameters). Of 164 genes mapped using both FUMA and OpenTargets (top 3 genes per locus), 26 were prioritized because of either high specificity of LV expression using the bulk RNA-seq data of the GTEx project release v.8 and/or high expression in cardiomyocytes using snRNA-seq data. See Methods and Supplementary Tables 12 and 13 for details. b, Rare (MAF < 10⁻⁴) LoF variant association analyses with HCM versus controls performed for all 26 genes using sequencing data in up to 2,502 unrelated HCM cases and 486,217 controls from four datasets followed by IVW meta-analysis. Association of rare synonymous (SYN) variants was also performed as a negative control. Results shown restricted to two genes (ALPK3 and SVIL) reaching the Bonferroni-corrected threshold of P < 0.0019 (0.05/26) in the IVW meta-analysis. Filled circles and error bars represent the OR and their 95% CI, respectively, from the meta-analysis for LoF (blue) and SYN (red). P values shown are not corrected for multiple testing. Full results appear in Supplementary Table 16. c, Schematic of the rare LoF SVIL variants in HCM cases (top) and controls (bottom) along the linear structure of SVIL, showing the Gelsolin-like and headpiece (HP) domains. The coordinates reflect the codon numbers, and the colored bars are the exons. Detailed variant annotation appears in Supplementary Table 19. Panel a was created using BioRender.com.

Fig. 5. MR analysis of LV contractility and blood pressure on risk of oHCM and nHCM.

In both panels, filled circles represent the OR per s.d. increase inferred from the IVW two-sample MR. Error bars represent the 95% CI of the OR. a, MR suggests causal association of LV contractility (exposure) with HCM, oHCM and nHCM (outcomes), where increased contractility increases disease risk. Genetic instruments for LV contractility were selected from the present GWAS of LVEF and LV strain in the radial (strain_rad), longitudinal (strain_long) and circumferential (strain_circ) directions in 36,083 participants of the UKB without cardiomyopathy and with available CMR. To facilitate interpretation of effect directions, OR for strain_circ and strain_long reflect those of increased contractility (more negative strain_circ and strain_long values). The outcome HCM GWAS included 5,900 HCM cases versus 68,359 controls. Of those, 964 cases and 27,163 controls were included in the oHCM GWAS and 2,491 cases and 27,109 were included in the nHCM GWAS. Note a logarithmic scale in the x axis. b, MR suggests causal associations of SBP and DBP with HCM, nHCM and oHCM. Genetic instruments for SBP, DBP and PP (SBP − DBP) were selected from a published GWAS including up to 801,644 people. See Supplementary Table 21 for full MR results.