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基于中国汉族人群的心力衰竭多变量预后模型。

Multivariable prognostic model for heart failure in Chinese Han population-based setting.

机构信息

Division of Cardiology, Department of Internal Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, PR China.

Hubei Key Laboratory of Genetics and Molecular Mechanism of Cardiologic Disorders, Huazhong University of Science and Technology, Wuhan, PR China.

出版信息

ESC Heart Fail. 2022 Aug;9(4):2388-2398. doi: 10.1002/ehf2.13932. Epub 2022 Apr 22.

Abstract

AIMS

The prognosis of heart failure (HF) depends on genetic predisposition, and recent studies have shown that impaired autophagy is involved in HF. This study was aimed to construct a prognostic model combining polygenetic background based on the autophagy pathway and other traditional risk factors (TRF) of HF prognosis.

METHODS AND RESULTS

Via re-analysing the transcriptomic data of 50 failing and 14 non-failing donors, differentially expressed autophagy-related genes (ARGs) were chosen for further comparison and analysis with whole exome sequencing and follow-up data of 1000 HF patients. By searching from reported articles, prognosis-related polymorphisms were identified. ARGs and prognosis-related polymorphisms were used to develop genetic risk score (GRS) and genetic risk factor (GRF), respectively. We compared the predictive power of five models [Model 1, GRS; Model 2, composite of TRF and N-terminal B-type natriuretic peptide (NT-proBNP); Model 3, composite of TRF, NT-proBNP, and GRS; Model 4, composite of TRF, NT-proBNP, and GRF; and Model 5, composite of TRF, NT-proBNP, GRF, and GRS] by applying receiver operating characteristic curves. Twenty-four prognosis-related polymorphisms were used to construct GRF and 11 variants among 48 differentially expressed ARGs associated with clinical outcomes of HF patients were applied for GRS. GRS was strongly associated with cardiac mortality of HF patients, independent of TRF and GRF (95% confidence interval 1.273-1.739, P = 5.78 × 10 ). Comparing with patients with lowest GRS tertile, those with highest tertile had higher risks of developing worse clinical outcomes (hazard ratio = 1.866; 95% confidence interval 1.352-2.575, P = 1.47 × 10 ). The discrimination power of the model including GRS, TRF, GRF, and NT-proBNP is most considerable (area under curve = 0.777), especially in men, patients over 60, patients with hypertension, patients without diabetes or hyperlipidaemia.

CONCLUSIONS

The model combining autophagy-related GRS, TRF, GRF, and NT-proBNP performs well in distinguishing between worse-prognosis and better-prognosis HF patients, leading a promising strategy for HF treatment and HF prevention.

摘要

目的

心力衰竭(HF)的预后取决于遗传易感性,最近的研究表明,自噬受损与 HF 有关。本研究旨在构建一个基于自噬途径和 HF 预后其他传统危险因素(TRF)的多基因背景的预后模型。

方法和结果

通过重新分析 50 名衰竭供体和 14 名非衰竭供体的转录组数据,选择差异表达的自噬相关基因(ARGs)进行进一步比较,并与 1000 名 HF 患者的全外显子测序和随访数据进行分析。通过检索文献,确定了与预后相关的多态性。分别使用 ARGs 和与预后相关的多态性来构建遗传风险评分(GRS)和遗传风险因素(GRF)。我们通过应用受试者工作特征曲线比较了五个模型[模型 1,GRS;模型 2,TRF 和 N 末端 B 型利钠肽(NT-proBNP)的组合;模型 3,TRF、NT-proBNP 和 GRS 的组合;模型 4,TRF、NT-proBNP 和 GRF 的组合;和模型 5,TRF、NT-proBNP、GRF 和 GRS 的组合]的预测能力。使用 24 个与预后相关的多态性构建 GRF,使用与 HF 患者临床结局相关的 48 个差异表达 ARGs 中的 11 个变体构建 GRS。GRS 与 HF 患者的心脏死亡率密切相关,独立于 TRF 和 GRF(95%置信区间 1.273-1.739,P=5.78×10)。与最低 GRS 三分位组的患者相比,最高三分位组发生更差临床结局的风险更高(风险比=1.866;95%置信区间 1.352-2.575,P=1.47×10)。包含 GRS、TRF、GRF 和 NT-proBNP 的模型的区分能力最强(曲线下面积=0.777),尤其是在男性、60 岁以上患者、高血压患者、无糖尿病或高脂血症患者中。

结论

结合自噬相关 GRS、TRF、GRF 和 NT-proBNP 的模型在区分预后较差和预后较好的 HF 患者方面表现良好,为 HF 治疗和 HF 预防提供了一种有前途的策略。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1290/9288793/a683dbe401d8/EHF2-9-2388-g001.jpg

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