Open AccessGenetic risk scores to predict the prognosis of chronic heart failure patients in Chinese Han
Author(s) -
Li Shiyang,
Sun Yang,
Hu Senlin,
Hu Dong,
Li Chenze,
Xiao Lei,
Chen Yanghui,
Li Huihui,
Cui Guanglin,
Wang Dao Wen
Publication year - 2020
Publication title -
journal of cellular and molecular medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.44
H-Index - 130
eISSN - 1582-4934
pISSN - 1582-1838
DOI - 10.1111/jcmm.14722
Subject(s) - medicine , single nucleotide polymorphism , heart failure , proportional hazards model , cohort , framingham risk score , cohort study , oncology , bioinformatics , genotype , genetics , gene , biology , disease
Chronic heart failure (CHF) has poor prognosis and polygenic heritability, and the genetic risk score (GRS) to predict CHF outcome has not yet been researched comprehensively. In this study, we sought to establish GRS to predict the outcomes of CHF. We re‐analysed the proteomics data of failing human heart and combined them to filter the data of high‐throughput sequencing in 1000 Chinese CHF cohort. Cox hazards models were used based on single nucleotide polymorphisms (SNPs) to estimate the association of GRS with the prognosis of CHF, and to analyse the difference between individual SNPs and tertiles of genetic risk. In the cohort study, GRS encompassing eight SNPs harboured in seven genes were significantly associated with the prognosis of CHF ( P = 2.19 × 10 −10 after adjustment). GRS was used in stratifying individuals into significantly different CHF risk, with those in the top tertiles of GRS distribution having HR of 3.68 (95% CI: 2.40‐5.65 P = 2.47 × 10 −10 ) compared with those in the bottom. We developed GRS and demonstrated its association with first event of heart failure endpoint. GRS might be used to stratify individuals for CHF prognostic risk and to predict the outcomes of genomic screening as a complement to conventional risk and NT‐proBNP.