Yun Jae-Seung, Jung Sang-Hyuk, Shivakumar Manu, Xiao Brenda, Khera Amit V, Park Woong-Yang, Won Hong-Hee, Kim Dokyoon
Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States.
Division of Endocrinology and Metabolism, Department of Internal Medicine, St. Vincent's Hospital, College of Medicine, The Catholic University of Korea, Seoul, South Korea.
Front Cardiovasc Med. 2022 Aug 17;9:919374. doi: 10.3389/fcvm.2022.919374. eCollection 2022.
Previous studies primarily targeted the ability of polygenic risk scores (PRSs) to predict a specific disease, and only a few studies have investigated the association between genetic risk scores and cardiovascular (CV) mortality. We assessed PRSs for coronary artery disease (CAD) and type 2 diabetes (T2DM) as the predictive factors for CV mortality, independent of traditional risk factors, and further investigated the additive effect between lifestyle behavior and PRS on CV mortality.
We used genetic and phenotypic data from UK Biobank participants aged 40-69 years at baseline, collected with standardized procedures. Genome-wide PRSs were constructed using >6 million genetic variants. Cox proportional hazard models were used to analyze the relationship between PRS and CV mortality with stratification by age, sex, disease status, and lifestyle behavior.
Of 377,909 UK Biobank participants having European ancestry, 3,210 (0.8%) died due to CV disease during a median follow-up of 8.9 years. CV mortality risk was significantly associated with CAD PRS [low vs. very high genetic risk groups, CAD PRS hazard ratio (HR) 2.61 (2.02-3.36)] and T2DM PRS [HR 2.08 (1.58-2.73)], respectively. These relationships remained significant even after an adjustment for a comprehensive range of demographic and clinical factors. In the very high genetic risk group, adherence to an unfavorable lifestyle was further associated with a substantially increased risk of CV mortality [favorable vs. unfavorable lifestyle with very high genetic risk for CAD PRS, HR 8.31 (5.12-13.49); T2DM PRS, HR 5.84 (3.39-10.04)]. Across all genetic risk groups, 32.1% of CV mortality was attributable to lifestyle behavior [population attributable fraction (PAF) 32.1% (95% CI 28.8-35.3%)] and 14.1% was attributable to smoking [PAF 14.1% (95% CI 12.4-15.7%)]. There was no evidence of significant interaction between PRSs and age, sex, or lifestyle behavior in predicting the risk of CV mortality.
PRSs for CAD or T2DM and lifestyle behaviors are the independent predictive factors for future CV mortality in the white, middle-aged population. PRS-based risk assessment could be useful to identify the individuals who need intensive behavioral or therapeutic interventions to reduce the risk of CV mortality.
以往研究主要关注多基因风险评分（PRSs）预测特定疾病的能力，仅有少数研究调查了遗传风险评分与心血管（CV）死亡率之间的关联。我们评估了冠状动脉疾病（CAD）和2型糖尿病（T2DM）的PRSs作为CV死亡率的预测因素，独立于传统风险因素，并进一步研究了生活方式行为与PRS对CV死亡率的相加效应。
我们使用了英国生物银行中基线年龄为40 - 69岁参与者的遗传和表型数据，这些数据通过标准化程序收集。使用超过600万个遗传变异构建全基因组PRSs。采用Cox比例风险模型分析PRS与CV死亡率之间的关系，并按年龄、性别、疾病状态和生活方式行为进行分层。
在377,909名具有欧洲血统的英国生物银行参与者中，在中位随访8.9年期间，有3210人（0.8%）死于心血管疾病。CV死亡率风险分别与CAD PRS [低遗传风险组与极高遗传风险组，CAD PRS风险比（HR）2.61（2.02 - 3.36）]和T2DM PRS [HR 2.08（1.58 - 2.73）]显著相关。即使在对一系列全面的人口统计学和临床因素进行调整后，这些关系仍然显著。在极高遗传风险组中，坚持不良生活方式与CV死亡率风险大幅增加进一步相关[CAD PRS极高遗传风险下，有利生活方式与不利生活方式相比，HR 8.31（5.12 - 13.49）；T2DM PRS，HR 5.84（3.39 - 10.04）]。在所有遗传风险组中，32.1%的CV死亡率可归因于生活方式行为[人群归因分数（PAF）32.1%（95%CI 28.8 - 35.3%）]，14.1%可归因于吸烟[PAF 14.1%（95%CI 12.4 - 15.7%）]。在预测CV死亡率风险方面，没有证据表明PRS与年龄、性别或生活方式行为之间存在显著相互作用。
CAD或T2DM的PRSs以及生活方式行为是白人中年人群未来CV死亡率的独立预测因素。基于PRS的风险评估可能有助于识别那些需要强化行为或治疗干预以降低CV死亡率风险的个体。
