Qian Hanyu, Wu Chao, Yang Yupeng, Li Bo, Rosenzweig Anthony, Wang Meng
Stanley and Judith Frankel Institute for Heart and Brain Health, University of Michigan Medical Center, Ann Arbor, 48109, USA.
Gilbert S. Omenn Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA.
medRxiv. 2025 Jun 28:2025.06.27.25330418. doi: 10.1101/2025.06.27.25330418.
Different patterns of physical activity (PA), including sedentary behavior, have been linked to a wide range of health outcomes. However, the underlying molecular mechanisms-particularly the biological pathways connecting distinct aspects of PA to health outcomes-are incompletely understood. In this study, we investigated the associations between 14 PA features across four categories-captured using wearable accelerometer data-and plasma protein (PP) expression levels in 9,210 individuals from the UK Biobank. Our analysis identified 2,655 significantly associated PA feature-PP expression pairs, involving 613 unique proteins. These included broadly associated proteins such as ITGAV and MYOM3, which were linked to all PA feature categories, as well as proteins uniquely associated with specific activity features. Mediation analysis revealed 359 paths linking 10 PA features, 99 unique PPs, and seven incident health outcomes. Aggressive PA features, including both the proportion of moderate-to-vigorous physical activity (MVPA) time and the frequency of MVPA bouts, exhibited protective effects mediated through proteins to those risks for incident health outcomes. Proteins such as GDF15, PRSS8, and IGFBP4 mediated associations across multiple PA features. Additionally, genetic analyses identified 32 mediator proteins with putative causal effects on incident health outcomes, highlighting them as potential therapeutic targets. Together, these results implicate PP as key mediators of the health effects of PA, offering new mechanistic insights and uncovering potential targets for therapeutic intervention.
不同模式的身体活动（PA），包括久坐行为，已与广泛的健康结果相关联。然而，潜在的分子机制——特别是将PA的不同方面与健康结果联系起来的生物学途径——尚未完全被理解。在本研究中，我们调查了来自英国生物银行的9210名个体中，通过可穿戴加速度计数据获取的四类14种PA特征与血浆蛋白（PP）表达水平之间的关联。我们的分析确定了2655个显著相关的PA特征-PP表达对，涉及613种独特的蛋白质。这些包括广泛相关的蛋白质，如ITGAV和MYOM3，它们与所有PA特征类别相关联，以及与特定活动特征独特相关的蛋白质。中介分析揭示了连接10种PA特征、99种独特PP和7种健康结局的359条路径。积极的PA特征，包括中度至剧烈身体活动（MVPA）时间的比例和MVPA发作的频率，通过蛋白质对那些发生健康结局的风险表现出保护作用。诸如GDF15、PRSS8和IGFBP4等蛋白质介导了多种PA特征之间的关联。此外，遗传分析确定了32种对健康结局有假定因果效应的中介蛋白，突出了它们作为潜在治疗靶点的地位。总之，这些结果表明PP是PA健康效应的关键中介，提供了新的机制见解并揭示了治疗干预的潜在靶点。
