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慢性心力衰竭中克隆性造血驱动基因突变的全谱及其与死亡率的关联。

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

作者信息

Kiefer Katharina C, Cremer Sebastian, Pardali Evangelia, Assmus Birgit, Abou-El-Ardat Khalil, Kirschbaum Klara, Dorsheimer Lena, Rasper Tina, Berkowitsch Alexander, Serve Hubert, Dimmeler Stefanie, Zeiher Andreas M, Rieger Michael A

机构信息

Department of Medicine, Hematology/Oncology, Goethe University Hospital, Frankfurt, Germany.

Department of Medicine, Cardiology, Goethe University Hospital, Frankfurt, Germany.

出版信息

ESC Heart Fail. 2021 Jun;8(3):1873-1884. doi: 10.1002/ehf2.13297. Epub 2021 Mar 28.

DOI:10.1002/ehf2.13297
PMID:33779075
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8120376/
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.

摘要

目的

造血干细胞中的体细胞突变可导致突变血细胞的克隆性扩增,即克隆性造血(CH)。变异等位基因频率(VAF)≥2%的最常见驱动基因DNMT3A和TET2中的突变与动脉粥样硬化和缺血性起源的慢性心力衰竭(CHF)相关。然而,其他低VAF(<2%)的CH驱动基因中的突变对CHF的影响仍不清楚。

方法与结果

因此,我们通过对56个基因进行深度纠错靶向测序,分析了399例CHF患者的单核骨髓和血细胞,并将这些患者(中位随访3.95年)的突变与长期死亡率相关联。我们在399例患者中的347例中检测到1113个VAF≥0.5%的突变,只有13%的患者未检测到CH。尽管最常突变的基因DNMT3A(165例患者)和TET2(107例患者)中突变的发生率很高,但与所有患者的平均死亡率相比,CBL、CEBPA、EZH2、GNB1、PHF6、SMC1A和SRSF2中的突变与死亡增加相关。为避免混杂效应,我们排除了VAF≥2%的与DNMT3A相关、TET2相关和其他不确定潜能的克隆性造血(CHIP)相关突变的患者,以进行进一步分析。Kaplan-Meier生存分析显示,这七个基因(53例患者)中任一基因发生突变的患者死亡率显著更高,这七个基因共同作为CHF的CH风险基因集。基线患者特征显示,除风险基因集发生突变的患者血小板数量减少外,包括患者年龄、混杂疾病、CHF严重程度或血细胞参数在内的任何参数均无显著差异。然而,在多变量cox回归分析后,任何一个风险基因中的突变仍然具有显著性(风险比,3.1;95%置信区间,1.8 - 5.4;P < 0.001),而血小板数量则不然。

结论

一组特定基因(即CBL、CEBPA、EZH2、GNB1、PHF6、SMC1A和SRSF2)中低VAF的体细胞突变与CHF患者的死亡率显著相关,独立于DNMT3A和TET2中最常见的CHIP突变。这些基因中的突变在年轻CHF患者中很普遍,是CHF预后的独立危险因素,可能为CHF的风险评估提供一种新工具。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a5eb/8120376/bef25c4e1caf/EHF2-8-1873-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a5eb/8120376/96e923be9087/EHF2-8-1873-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a5eb/8120376/6ad0cf75cb74/EHF2-8-1873-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a5eb/8120376/218069e1e79a/EHF2-8-1873-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a5eb/8120376/bef25c4e1caf/EHF2-8-1873-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a5eb/8120376/96e923be9087/EHF2-8-1873-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a5eb/8120376/6ad0cf75cb74/EHF2-8-1873-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a5eb/8120376/218069e1e79a/EHF2-8-1873-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a5eb/8120376/bef25c4e1caf/EHF2-8-1873-g002.jpg

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