Program on Healthy Aging and Late Life Brain Disorders, Columbia University College of Physicians and Surgeons, New York State Psychiatric Institute.
Department of Biostatistics, Mailman School of Public Health, Columbia University College of Physicians and Surgeons, New York State Psychiatric Institute.
J Gerontol A Biol Sci Med Sci. 2018 Sep 11;73(10):1370-1376. doi: 10.1093/gerona/glx162.
The pathophysiology of late-life depression (LLD) is complex and heterogeneous, with age-related processes implicated in its pathogenesis. This study examined the cross-sectional and longitudinal association between depressive symptoms and a baseline multibiomarker algorithm of biological age (BA) that aggregates indicators of inflammatory, metabolic, cardiovascular, lung, liver, and kidney functioning.
Data were analyzed from 2,776 men and women from the prospective observational Health Aging and Body Composition Study, who had both evaluable chronological age (CA) and BA. Depressive symptoms were assessed using the Center for Epidemiologic Studies Depression (CES-D) scale.
A covariate-adjusted regression model showed that BA (B = 0.03, p = .0471) but not CA (B = -0.01, p = .7185) is associated with baseline CES-D scores. The mean baseline BA for individuals with a CES-D ≥ 10 was 1.28 years greater than in those with a CES-D < 10. Comparatively, there is only a 0.05-year difference in mean CA between the two depression groups. A covariate-adjusted longitudinal model found that baseline BA predicts CES-D score at follow-up (B = 0.04, p = .0058), whereas CA does not (B = 0.03, p = .4125). Additionally, an older BA significantly predicted a CES-D ≥ 10 (B = 0.02, p = .032) over a 10-year period.
A multibiomarker index of an older adult's BA outperformed their CA in predicting subsequent increased and clinically significant depressive symptoms. This result supports the evolving view of LLD as a brain disorder resulting from deleterious age-associated changes across numerous physiological systems.
老年期抑郁症（LLD）的病理生理学复杂且具有异质性，与年龄相关的过程与发病机制有关。本研究考察了抑郁症状与基线多生物标志物算法生物年龄（BA）之间的横断面和纵向关联，该算法聚合了炎症、代谢、心血管、肺、肝和肾功能的指标。
对前瞻性观察性健康衰老和身体成分研究中的 2776 名男性和女性进行了数据分析，他们的年龄（CA）和 BA 均可以评估。使用流行病学研究中心抑郁量表（CES-D）评估抑郁症状。
调整协变量的回归模型显示，BA（B=0.03，p=0.0471）而不是 CA（B=-0.01，p=0.7185）与基线 CES-D 评分相关。CES-D≥10 的个体的平均基线 BA 比 CES-D<10 的个体大 1.28 岁。相比之下，两组抑郁患者的平均 CA 仅相差 0.05 岁。调整协变量的纵向模型发现，基线 BA 可预测随访时的 CES-D 评分（B=0.04，p=0.0058），而 CA 则不能（B=0.03，p=0.4125）。此外，BA 较老显著预测了 10 年内 CES-D≥10（B=0.02，p=0.032）的情况。
生物标志物指数 BA 预测老年患者随后出现抑郁症状增加和临床显著抑郁症状的能力优于 CA。这一结果支持了 LLD 作为一种大脑疾病的观点，这种疾病是由多个生理系统中与年龄相关的有害变化引起的。
