Sjögren Marketa, Almgren Peter, Melander Olle
Department of Clinical Sciences Malmö, Lund University, Sweden.
Int J Cardiol Heart Vasc. 2019 Jul 16;24:100391. doi: 10.1016/j.ijcha.2019.100391. eCollection 2019 Sep.
Coronary artery disease (CAD) is a leading cause of death worldwide and increasing cost for society. Genome wide association studies (GWAS) have identified common variants associated with CAD. Combining single nucleotide polymorphisms (SNPs) into a genetic risk score (GRS) can estimate an individual's genetic burden.
To investigate whether GRS for CAD can predict hospitalization and mortality.
23,594 individuals without CAD at baseline and with full data for all covariates from the population based prospective study Malmö diet and cancer study were investigated. The association between hospitalizations was calculated by negative binomial regression and risk of mortality was calculated by Cox proportional hazards regression. The GRS was constructed from 50 SNPs.
The study population was divided into quintiles according to the value of GRS. During the mean follow-up time of 17.8 years, 17,254 individuals were hospitalized at least once. Individuals in the highest quintile of GRS were hospitalized 10% more often than individuals in the lowest quintile (IRR: 1.10 [95% CI 1.04-1.16], = 0.001), mainly for cardiovascular reasons (IRR: 1.31 [95% CI 1.20-1.43], = 5.17 × 10). These individuals had highly increased risk of CVD mortality (HR: 1.44 [1.25-1.66], = 6.56 × 10) but not the risk of mortality due to other causes.
Our results suggest that genetic predisposition for CAD can predict hospitalization burden and mortality, especially due to cardiovascular causes, independently of traditional risk factors. As the risk conferred by the GRS is partially modifiable, our results may help to reduce societal costs, individual suffering and prolong life.
冠状动脉疾病(CAD)是全球主要的死亡原因,且社会成本不断增加。全基因组关联研究(GWAS)已确定了与CAD相关的常见变异。将单核苷酸多态性(SNP)组合成遗传风险评分(GRS)可以估计个体的遗传负担。
研究CAD的GRS是否能预测住院率和死亡率。
对基于人群的前瞻性研究——马尔默饮食与癌症研究中23594名基线时无CAD且所有协变量数据完整的个体进行了调查。通过负二项回归计算住院之间的关联,并通过Cox比例风险回归计算死亡风险。GRS由50个SNP构建。
根据GRS值将研究人群分为五分位数。在平均17.8年的随访期内,17254人至少住院一次。GRS最高五分位数的个体住院频率比最低五分位数的个体高10%(发病率比:1.10[95%置信区间1.04 - 1.16],P = 0.001),主要是心血管原因(发病率比:1.31[95%置信区间1.20 - 1.43],P = 5.17×10⁻⁵)。这些个体心血管疾病死亡风险大幅增加(风险比:1.44[1.25 - 1.66],P = 6.56×10⁻⁵),但其他原因导致的死亡风险未增加。
我们的结果表明,CAD的遗传易感性可以独立于传统风险因素预测住院负担和死亡率,尤其是心血管原因导致的。由于GRS赋予的风险部分是可改变的,我们的结果可能有助于降低社会成本、减少个体痛苦并延长寿命。