Association of epigenetic age and everyday discrimination with longitudinal trajectories of chronic health conditions in older adults

Miriam Mutambudzi, Maria T Brown, Nai-Wei Chen
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Abstract

We investigated the strength of the association between baseline epigenetic age, everyday discrimination, and trajectories of chronic health conditions (CHCs) across 3 study waves, among adults 50 years of age and older. We used 2016-2020 data from the Health and Retirement Study (HRS). Data for the PhenoAge and DNAm GrimAge second-generation epigenetic clocks were from the 2016 HRS Venous Blood Study. CHC trajectories were constructed using latent class growth curve models. Multinomial logistic regression models assessed the strength of the association between accelerated epigenetic age, everyday discrimination, and the newly constructed CHC trajectories for participants with complete data (n=2,893). In the fully adjusted model, accelerated PhenoAge (RRR=2.53, 95%CI= 1.81,3.55) and DNAm GrimAge (RRR=2.79, 95%CI= 1.95,4.00) were associated with classification into the high CHC trajectory class. Racial disparities were evident, with increased risk of classification into the high trajectory class for Black (PhenoAge: RRR=1.69, 95%CI=1.07, 2.68) and reduced risk for Hispanic (PhenoAge: RRR=0.32, 95%CI=0.16,0.64; DNAm GrimAge: RRR=0.34,95%CI=0.17,0.68), relative to White participants. Everyday discrimination was associated with classification into the medium-high (RRR=1.28, 95%CI=1.00,1.64) and high (RRR=1.52, 95%CI=1.07,2.16) trajectory classes in models assessing DNAm GrimAge. More research is needed to better understand the longitudinal health outcomes of accelerated aging and adverse social exposures. Such research may provide insights into vulnerable adults who may need varied welfare supports earlier than the mandated chronological age for access to federal and state resources.
表观遗传年龄和日常歧视与老年人慢性健康状况纵向轨迹的关系
我们调查了 50 岁及以上成年人的基线表观遗传年龄、日常歧视和慢性健康状况(CHC)轨迹之间在 3 次研究波中的关联强度。我们使用了健康与退休研究(HRS)的 2016-2020 年数据。PhenoAge 和 DNAm GrimAge 第二代表观遗传时钟的数据来自 2016 年 HRS 静脉血研究。CHC轨迹采用潜类增长曲线模型构建。多叉逻辑回归模型评估了具有完整数据的参与者(n=2,893)的加速表观遗传年龄、日常辨别力和新构建的 CHC 轨迹之间的关联强度。在完全调整模型中,PhenoAge 加速(RRR=2.53,95%CI= 1.81,3.55)和 DNAm GrimAge(RRR=2.79,95%CI= 1.95,4.00)与高 CHC 轨迹分类相关。与白人参与者相比,黑人(PhenoAge:RRR=1.69, 95%CI=1.07,2.68)和西班牙裔(PhenoAge:RRR=0.32, 95%CI=0.16,0.64;DNAm GrimAge:RRR=0.34,95%CI=0.17,0.68)被归入高轨迹等级的风险增加,种族差异明显。在评估 DNAm GrimAge 的模型中,日常歧视与中高(RRR=1.28,95%CI=1.00,1.64)和高(RRR=1.52,95%CI=1.07,2.16)轨迹分类有关。要更好地了解加速衰老和不良社会暴露的纵向健康结果,还需要进行更多的研究。此类研究可能有助于深入了解弱势成人的情况,他们可能在规定的获取联邦和州资源的法定年龄之前就需要各种福利支持。
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