Boston University Department of Medicine Boston MA.
Department of Public Health and Community Medicine Tufts University School of Medicine Boston MA.
J Am Heart Assoc. 2021 Jan 5;10(1):e018020. doi: 10.1161/JAHA.120.018020. Epub 2020 Dec 29.
Background Proteomic biomarkers related to cardiovascular disease risk factors may offer insights into the pathogenesis of cardiovascular disease. We investigated whether modifiable lifestyle risk factors for cardiovascular disease are associated with distinctive proteomic signatures. Methods and Results We analyzed 1305 circulating plasma proteomic biomarkers (assayed using the SomaLogic platform) in 897 FHS (Framingham Heart Study) Generation 3 participants (mean age 46±8 years; 56% women; discovery sample) and 1121 FOS (Framingham Offspring Study) participants (mean age 52 years; 54% women; validation sample). Participants were free of hypertension, diabetes mellitus, and clinical cardiovascular disease. We used linear mixed effects models (adjusting for age, sex, body mass index, and family structure) to relate levels of each inverse-log transformed protein to 3 lifestyle factors (ie, smoking, alcohol consumption, and physical activity). A Bonferroni-adjusted value indicated statistical significance (based on number of proteins and traits tested, <4.2×10 in the discovery sample; <6.85×10 in the validation sample). We observed statistically significant associations of 60 proteins with smoking (37/40 top proteins validated in FOS), 30 proteins with alcohol consumption (23/30 proteins validated), and 5 proteins with physical activity (2/3 proteins associated with the physical activity index validated). We assessed the associations of protein concentrations with previously identified genetic variants (protein quantitative trait loci) linked to lifestyle-related disease traits in the genome-wide-association study catalogue. The protein quantitative trait loci were associated with coronary artery disease, inflammation, and age-related mortality. Conclusions Our cross-sectional study from a community-based sample elucidated distinctive sets of proteins associated with 3 key lifestyle factors.
背景:与心血管疾病危险因素相关的蛋白质组生物标志物可能为心血管疾病的发病机制提供深入了解。我们研究了可改变的心血管疾病生活方式危险因素是否与独特的蛋白质组特征相关。
方法和结果:我们分析了 897 名 FHS(弗雷明汉心脏研究)第 3 代参与者(平均年龄 46±8 岁;56%为女性;发现样本)和 1121 名 FOS(弗雷明汉后代研究)参与者(平均年龄 52 岁;54%为女性;验证样本)的 1305 个循环血浆蛋白质组生物标志物(使用 SomaLogic 平台检测)。参与者无高血压、糖尿病和临床心血管疾病。我们使用线性混合效应模型(调整年龄、性别、体重指数和家庭结构)将每个逆对数转化蛋白的水平与 3 种生活方式因素(即吸烟、饮酒和体力活动)相关联。Bonferroni 调整后的 值表明统计学意义(基于蛋白质和测试的特征数量,在发现样本中<4.2×10;在验证样本中<6.85×10)。我们观察到 60 种蛋白质与吸烟(在 FOS 中验证的 37/40 种蛋白质中的 37 种为顶级蛋白质)、30 种蛋白质与饮酒(30 种蛋白质中的 23 种被验证)和 5 种蛋白质与体力活动(与体力活动指数相关的 3 种蛋白质中的 2 种被验证)之间存在统计学显著关联。我们评估了蛋白质浓度与全基因组关联研究目录中与生活方式相关疾病特征相关的遗传变异(蛋白质数量性状基因座)的关联。蛋白质数量性状基因座与冠状动脉疾病、炎症和与年龄相关的死亡率相关。
结论:我们从基于社区的样本进行的横断面研究阐明了与 3 个关键生活方式因素相关的独特蛋白质组。
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