Genomic Context Differs Between Human Dilated Cardiomyopathy and Hypertrophic Cardiomyopathy

Figures

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  Figure 1. Principal component analysis (PCA) of echocardiographic data separates hypertrophic cardiomyopathy (HCM) and dilated cardiomyopathy (DCM) and is predicted by the number of nonsynonymous single‐nucleotide variants (nsSNVs) in cardiomyopathy genes. A, PCA of echocardiography data shows that echocardiographic principal component 1 (Echo PC1) summarizes the difference in echocardiography data between HCM (red) and DCM (black). B, Regression of Echo PC1 against the number of cardiomyopathy gene nsSNVs/person was significant and effectively separated HCM and DCM, as seen by the solid gray line (n=82). To account for genetic ancestry, linear regression was repeated in the absence of African ancestry (n=70) subjects (dashed gray line) or Hispanic ancestry (n=73) subjects (dot‐dash gray line) or using only the European ancestry (dotted gray line; n=58) subjects. *P=0.024, **P=0.005, ***P=0.002, † P=0.069.

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  Figure 2. Dilated cardiomyopathy (DCM) probability is increased with cardiomyopathy gene nonsynonymous single‐nucleotide variant (nsSNV) number compared with hypertrophic cardiomyopathy (HCM). Multivariate generalized linear models demonstrate that the probability of DCM is increased with the total number of cardiomyopathy gene nsSNVs per person in this cohort (left panel). The red and black dots represent individual participants and their number of nsSNVs in cardiomyopathy genes. The analysis on the left considered all nsSNVs in cardiomyopathy genes, including rare and high‐frequency variants. The right‐hand panel shows the same analysis when considering only high‐frequency cardiomyopathy gene nsSNVs, where the same trend was evident (allele frequency, 0.25–0.50 variants included). DCM is black, and HCM is red. P values after adjustment for platform prevalence imbalance are shown (see Table S5). Number on x axis indicates the number of nsSNVs per subject.

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  Figure 3. The number of cardiomyopathy gene nonsynonymous single‐nucleotide variants (nsSNVs) per person associates with reduced cardiac function and increased left ventricular (LV) diameter. LV ejection fraction (LVEF) (A) and left ventricular internal diameter end diastole (LVIDd), normalized to body surface area (BSA) (B), were regressed against the total number of cardiomyopathy gene nsSNVs per person. Cardiomyopathy gene nsSNV number significantly correlated with reduced LVEF and increased LVIDd in subjects with dilated cardiomyopathy (DCM), and this correlation was not seen for subjects with hypertrophic cardiomyopathy (HCM) (*LVEF DCM P=0.01; HCM P=0.78; **LVIDd/BSA DCM P=0.02; HCM P=0.34); gray shading represents 95% CIs (see Table S6 for values). A randomly selected group of genes with comparable variant numbers was chosen from the low‐expression heart genes and similarly tested. This process was repeated 1000 times with different groups of genes. LVEF (C) and LVIDd/BSA (D) were regressed against low‐expression heart genes, and the regression lines did not reveal any significant association with LV measures. Dashed lines represent 95% CIs (see Table S8 for values).

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  Figure 4. Resampling identifies genes with deviant cumulative missense allele frequencies that may modify dilated cardiomyopathy (DCM) or hypertrophic cardiomyopathy (HCM). The bootstrap method (5000 resampling with replacement tests) was used to identify excess nonsynonymous single‐nucleotide variant burden in DCM compared with HCM (Delta) in either cardiomyopathy genes (A) or high‐expression heart genes (B). When conducting this analysis on cardiomyopathy genes, MYH7 and BAG3 were identified as having increased cumulative variation in HCM. MYH7 was expected to appear in this analysis because MYH7 mutations were enriched in the HCM cohort, and thus serve as an internal control for this approach. From known cardiomyopathy genes, BAG3 was identified as being enriched in HCM over DCM, and LMNA variation was enriched in DCM over HCM. This bootstrap method was applied across all high expressed cardiac genes and identified potential novel modifiers of HCM and DCM.