Section of Orthopedics Department of Surgical Sciences Uppsala University Uppsala Sweden.
Department of Medical Sciences Uppsala University Uppsala Sweden.
J Am Heart Assoc. 2019 Jun 4;8(11):e011860. doi: 10.1161/JAHA.118.011860. Epub 2019 Jun 1.
Background Mechanisms related to the influence of diet on the development of cardiovascular disease are not entirely understood, and protein biomarkers may help to understand these pathways. Studies of biomarkers identified with multiplex proteomic methods and dietary patterns are largely lacking. Methods and Results Dietary patterns were generated through principal component analysis in 2 population-based Swedish cohorts, the EpiHealth (EpiHealth study; n=20 817 men and women) and the SMCC (Swedish Mammography Cohort Clinical [n=4650 women]). A set of 184 protein cardiovascular disease biomarkers were measured with 2 high-throughput, multiplex immunoassays. Discovery and replication multivariable linear regression analyses were used to investigate the associations between the principal component analysis-generated dietary patterns and the cardiovascular disease-associated protein biomarkers, first in the EpiHealth (n=2240) and then in the Swedish Mammography Cohort Clinical. Four main dietary patterns were identified in the EpiHealth, and 3 patterns were identified in the Swedish Mammography Cohort Clinical. The healthy and the Western/traditional patterns were found in both cohorts. In the EpiHealth, 57 protein biomarkers were associated with 3 of the dietary patterns, and 41 of these associations were replicated in the Swedish Mammography Cohort Clinical, with effect estimates ranging from 0.057 to 0.083 (P-value range, 5.0×10-1.4×10) for each SD increase in the relative protein concentration. Independent associations were established between dietary patterns and the 21 protein biomarkers. Two proteins, myeloperoxidase and resistin, were associated with both the healthy and the light meal pattern but in opposite directions. Conclusions We have discovered and replicated independent associations between dietary patterns and 21 biomarkers linked to cardiovascular disease, which have a role in the pathways related to inflammation, endothelial and immune function, cell adhesion, and metabolism.
尽管人们对饮食影响心血管疾病发展的机制了解还不全面,但蛋白质生物标志物可能有助于理解这些途径。利用多元蛋白质组学方法和饮食模式来研究生物标志物的相关研究还很少。
通过对两个基于人群的瑞典队列(EpiHealth 研究[EpiHealth 研究;n=20817 名男性和女性]和 SMCC[瑞典乳腺 X 线摄影队列临床研究[n=4650 名女性])中的数据进行主成分分析,生成饮食模式。使用两种高通量、多重免疫测定法测量了一组 184 种与心血管疾病相关的蛋白质生物标志物。首先在 EpiHealth(n=2240)中,然后在瑞典乳腺 X 线摄影队列临床研究中,采用多元线性回归分析发现和复制了主成分分析生成的饮食模式与心血管疾病相关的蛋白质生物标志物之间的关联。在 EpiHealth 中发现了 4 种主要的饮食模式,在瑞典乳腺 X 线摄影队列临床研究中发现了 3 种饮食模式。健康饮食模式和西方/传统饮食模式在两个队列中都有发现。在 EpiHealth 中,有 57 种蛋白质生物标志物与 3 种饮食模式相关,其中 41 种关联在瑞典乳腺 X 线摄影队列临床研究中得到了复制,每种蛋白质浓度相对标准差增加 1 个单位,效应估计值范围为 0.057 至 0.083(P 值范围为 5.0×10-1.4×10-4)。饮食模式与 21 种蛋白质生物标志物之间存在独立的关联。两种蛋白质,髓过氧化物酶和抵抗素,与健康饮食模式和轻食模式都有关联,但方向相反。
我们已经发现并复制了饮食模式与 21 种与心血管疾病相关的生物标志物之间的独立关联,这些标志物在与炎症、内皮和免疫功能、细胞黏附以及代谢相关的途径中发挥作用。