Feng Li, Ye Zhenyao, Du Zewen, Pan Yezhi, Canida Travis, Ke Hongjie, Liu Song, Chen Shuo, Hong L Elliot, Kochunov Peter, Chen Jie, Lei David K Y, Shenassa Edmond, Ma Tianzhou
Department of Nutrition and Food Science, College of Agriculture & Natural Resources, University of Maryland, College Park, MD, United States.
Department of Epidemiology and Biostatistics, School of Public Health, University of Maryland, College Park, MD, United States.
Am J Epidemiol. 2024 Oct 11. doi: 10.1093/aje/kwae396.
White matter (WM) brain age, a neuroimaging-derived biomarker indicating WM microstructural changes, helps predict dementia and neurodegenerative disorder risks. The cumulative effect of chronic stress on WM brain aging remains unknown. In this study, we assessed cumulative stress using a multi-system composite allostatic load (AL) index based on inflammatory, anthropometric, respiratory, lipidemia, and glucose metabolism measures, and investigated its association with WM brain age gap (BAG), computed from diffusion tensor imaging data using a machine learning model, among 22 951 European ancestries aged 40 to 69 (51.40% women) from UK Biobank. Linear regression, Mendelian randomization, along with inverse probability weighting and doubly robust methods, were used to evaluate the impact of AL on WM BAG adjusting for age, sex, socioeconomic, and lifestyle behaviors. We found increasing one AL score unit significantly increased WM BAG by 0.29 years in association analysis and by 0.33 years in Mendelian analysis. The age- and sex-stratified analysis showed consistent results among participants 45-54 and 55-64 years old, with no significant sex difference. This study demonstrated that higher chronic stress was significantly associated with accelerated brain aging, highlighting the importance of stress management in reducing dementia and neurodegenerative disease risks.
脑白质（WM）脑龄是一种通过神经影像学得出的生物标志物，可指示WM微观结构变化，有助于预测痴呆症和神经退行性疾病风险。慢性应激对WM脑老化的累积影响尚不清楚。在本研究中，我们使用基于炎症、人体测量、呼吸、血脂和葡萄糖代谢指标的多系统综合应激负荷（AL）指数评估累积应激，并在英国生物银行中22951名年龄在40至69岁之间（女性占51.40%）的欧洲血统人群中，研究其与使用机器学习模型从扩散张量成像数据计算得出的WM脑龄差距（BAG）之间的关联。我们使用线性回归、孟德尔随机化以及逆概率加权和双重稳健方法，在调整年龄、性别、社会经济和生活方式行为的情况下，评估AL对WM BAG的影响。我们发现，在关联分析中，AL评分每增加一个单位，WM BAG显著增加0.29岁，在孟德尔分析中增加0.33岁。年龄和性别分层分析显示，45 - 54岁和55 - 64岁参与者的结果一致，且无显著性别差异。本研究表明，更高的慢性应激与加速脑老化显著相关，凸显了压力管理在降低痴呆症和神经退行性疾病风险方面的重要性。
