Full spectrum of clonal haematopoiesis-driver mutations in chronic heart failure and their associations with mortality

Abstract

Aims: Somatic mutations in haematopoietic stem cells can lead to the clonal expansion of mutated blood cells, known as clonal haematopoiesis (CH). Mutations in the most prevalent driver genes DNMT3A and TET2 with a variant allele frequency (VAF) ≥ 2% have been associated with atherosclerosis and chronic heart failure of ischemic origin (CHF). However, the effects of mutations in other driver genes for CH with low VAF (<2%) on CHF are still unknown.

Methods and results: Therefore, we analysed mononuclear bone marrow and blood cells from 399 CHF patients by deep error-corrected targeted sequencing of 56 genes and associated mutations with the long-term mortality in these patients (3.95 years median follow-up). We detected 1113 mutations with a VAF ≥ 0.5% in 347 of 399 patients, and only 13% had no detectable CH. Despite a high prevalence of mutations in the most frequently mutated genes DNMT3A (165 patients) and TET2 (107 patients), mutations in CBL, CEBPA, EZH2, GNB1, PHF6, SMC1A, and SRSF2 were associated with increased death compared with the average death rate of all patients. To avoid confounding effects, we excluded patients with DNMT3A-related, TET2-related, and other clonal haematopoiesis of indeterminate potential (CHIP)-related mutations with a VAF ≥ 2% for further analyses. Kaplan-Meier survival analyses revealed a significantly higher mortality in patients with mutations in either of the seven genes (53 patients), combined as the CH-risk gene set for CHF. Baseline patient characteristics showed no significant differences in any parameter including patient age, confounding diseases, severity of CHF, or blood cell parameters except for a reduced number of platelets in patients with mutations in the risk gene set in comparison with patients without. However, carrying a mutation in any of the risk genes remained significant after multivariate cox regression analysis (hazard ratio, 3.1; 95% confidence interval, 1.8-5.4; P < 0.001), whereas platelet numbers did not.

Conclusions: Somatic mutations with low VAF in a distinct set of genes, namely, in CBL, CEBPA, EZH2, GNB1, PHF6, SMC1A, and SRSF2, are significantly associated with mortality in CHF, independently of the most prevalent CHIP-mutations in DNMT3A and TET2. Mutations in these genes are prevalent in young CHF patients and comprise an independent risk factor for the outcome of CHF, potentially providing a novel tool for risk assessment in CHF.

Keywords: Age; Blood cell mutations; Clonal haematopoiesis; Heart failure.

Figure 1

Prevalence of clonal haematopoiesis (CH) according to age and number of mutations in chronic heart failure (CHF) patients. (A) Prevalence of CH mutations with variant allele frequency (VAF) ≥ 0.5% in CHF patients. The number of patients analysed per group is given. Significance was tested with Spearman correlation. (B) Number of CH‐associated mutations with VAF ≥ 0.5% in the 56 analysed genes. Because some CHF patients carried more than 1 mutation, the total number of identified mutations per gene exceeds the number of patients with CH. The list of individual mutations (n = 1113) can be found in Table S1. (C) Number of CHF patients carrying different number of CH‐associated mutations with VAF ≥ 0.5%. (D) Number of CH‐associated mutations with VAF ≥ 0.5% increases significantly per age group. Tukey box plot indicates the median, first and third quartiles. Correlation was tested with a two‐tailed Spearman's correlation.

Figure 2

Association between mutated genes and incidence of death. Bubble chart showing the association between clonal haematopoiesis mutations in the indicated genes with variant allele frequency ≥ 0.5% and death. The bubble size represents the number of mutated patients per gene. The absolute numbers of mutated patients are given next to the genes. The two lines denote average death rate in total cohort (dotted) and in patients without any mutation (solid).

Figure 3

Forest plot and Kaplan–Meier survival analyses of individual mutated genes. (A) Forest plot of the indicated genes showing the association between CH mutations with variant allele frequency ≥ 0.5% and death. The patients without any mutation in any gene were used for comparison. The horizontal lines denote 95% confidence intervals. For each gene, the hazard ratio is indicated by the diamant. The hazard ratio (HR), the 95% confidence interval (CI) and the P value are indicated to the right of the forest plot. (B–H) Kaplan–Meier curves of survival, defined as the time between sample collection and death or last follow‐up. Survival curves are stratified according to the mutations with variant allele frequency ≥ 0.5% in the indicated genes in CHF patients. The control group is defined as the patients without a mutation in the gene set (CBL, CEBPA, EZH2, GNB1, PHF6, SMC1A, and SRSF2). Patients with mutations with a VAF ≥ 2% were excluded from the analyses. Statistical significance was tested with Log Rank (Mantel–Cox).

Figure 4

Kaplan–Meier survival analyses of chronic heart failure (CHF) patients with a mutation in the risk gene set. Kaplan–Meier curves of survival, defined as the time between sample collection and death or last follow‐up. Patients with mutations with a VAF ≥ 2% were excluded. Statistical significance was tested with Log Rank (Mantel–Cox). (A) Survival curves are stratified according to the mutations with VAF ≥ 0.5% in genes of the gene set (CBL, CEBPA, EZH2, GNB1, PHF6, SMC1A, and SRSF2) in CHF patients. (B) Survival curves are stratified according to the number of driver mutations with VAF ≥ 0.5% in genes of the gene set per CHF patient. Non‐gene set mutation, patients with mutations in any other gene; No mutation, patients without any mutation.