Laboratory of Epidemiology and Population Sciences, National Institute on Aging, NIA/NIH/IRP, Baltimore, MD 21224, USA.
VA National Center on Homelessness Among Veterans, U.S. Department of Veterans Affairs, Washington, DC 20420, USA.
Aging (Albany NY). 2024 May 27;16(10):8446-8471. doi: 10.18632/aging.205868.
We investigated relations of depressive symptoms, antidepressant use, and epigenetic age acceleration with all-cause mortality risk among postmenopausal women. Data were analyzed from ≤1,900 participants in the Women's Health Initiative study testing four-way decomposition models. After a median 20.4y follow-up, 1,161 deaths occurred. Approximately 11% had elevated depressive symptoms (EDS), 7% were taking antidepressant medication at baseline (ANTIDEP), while 16.5% fell into either category (EDS_ANTIDEP). Baseline ANTIDEP, longitudinal transition into ANTIDEP and accelerated epigenetic aging directly predicted increased mortality risk. GrimAge DNA methylation age acceleration (AgeAccelGrim) partially mediated total effects of baseline ANTIDEP and EDS_ANTIDEP on all-cause mortality risk in socio-demographic factors-adjusted models (Pure Indirect Effect >0, < 0.05; Total Effect >0, < 0.05). Thus, higher AgeAccelGrim partially explained the relationship between antidepressant use and increased all-cause mortality risk, though only prior to controlling for lifestyle and health-related factors. Antidepressant use and epigenetic age acceleration independently predicted increased all-cause mortality risk. Further studies are needed in varying populations.
我们研究了绝经后妇女的抑郁症状、抗抑郁药物使用和表观遗传年龄加速与全因死亡率风险之间的关系。数据分析来自于 Women's Health Initiative 研究中的≤1900 名参与者,该研究测试了四向分解模型。在中位数为 20.4 年的随访后,发生了 1161 例死亡。大约 11%的人有较高的抑郁症状(EDS),7%的人在基线时服用抗抑郁药物(ANTIDEP),而 16.5%的人属于这两个类别(EDS_ANTIDEP)。基线 ANTIDEP、纵向过渡到 ANTIDEP 和加速的表观遗传老化直接预测了死亡率风险的增加。在社会人口因素调整模型中,GrimAge DNA 甲基化年龄加速(AgeAccelGrim)部分介导了基线 ANTIDEP 和 EDS_ANTIDEP 对全因死亡率风险的总效应(纯间接效应>0,<0.05;总效应>0,<0.05)。因此,较高的 AgeAccelGrim 部分解释了抗抑郁药物使用与全因死亡率风险增加之间的关系,但仅在未控制生活方式和与健康相关的因素之前。抗抑郁药物使用和表观遗传年龄加速独立预测了全因死亡率风险的增加。需要在不同人群中进一步研究。