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Accelerated brain aging predicts impaired cognitive performance and greater disability in geriatric but not midlife adult depression

机译:加速脑老化预测老年人的认知性能和更大的残疾性障碍,但不是中期成年抑郁症

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Depression is associated with markers of accelerated aging, but it is unclear how this relationship changes across the lifespan. We examined whether a brain-based measure of accelerated aging differed between depressed and never-depressed subjects across the adult lifespan and whether it was related to cognitive performance and disability. We applied a machine-learning approach that estimated brain age from structural MRI data in two depressed cohorts, respectively 170 midlife adults and 154 older adults enrolled in studies with common entry criteria. Both cohorts completed broad cognitive batteries and the older subgroup completed a disability assessment. The machine-learning model estimated brain age from MRI data, which was compared to chronological age to determine the brain–age gap (BAG; estimated age-chronological age). BAG did not differ between midlife depressed and nondepressed adults. Older depressed adults exhibited significantly higher BAG than nondepressed elders (Wald χ2?=?8.84, p?=?0.0029), indicating a higher estimated brain age than chronological age. BAG was not associated with midlife cognitive performance. In the older cohort, higher BAG was associated with poorer episodic memory performance (Wald χ2?=?4.10, p?=?0.0430) and, in the older depressed group alone, slower processing speed (Wald χ2?=?4.43, p?=?0.0354). We also observed a statistical interaction where greater depressive symptom severity in context of higher BAG was associated with poorer executive function (Wald χ2?=?5.89, p?=?0.0152) and working memory performance (Wald χ2?=?4.47, p?=?0.0346). Increased BAG was associated with greater disability (Wald χ2?=?6.00, p?=?0.0143). Unlike midlife depression, geriatric depression exhibits accelerated brain aging, which in turn is associated with cognitive and functional deficits.
机译:抑郁症与加速老化的标志有关,但目前尚不清楚这种关系如何在寿命周围发生变化。我们检查了在成人寿命的抑郁和从未抑郁的受试者之间是否有基于脑的加速衰老,以及是否与认知性能和残疾有关。我们应用了一种机器学习方法,即在两个抑郁的队列中估计大脑年龄的脑电年龄,分别为170名中西生长的成人和154名年龄较大的成年人,共同参加了共同进入标准。两个队列都完成了广泛的认知电池,较旧的子组完成了残疾人评估。机器学习模型估计来自MRI数据的脑年龄,与年龄的年龄相比,确定脑年龄间隙(袋子;估计年龄 - 年龄年龄)。袋子在中年郁闷和伤记的成年人之间没有差异。较旧的抑郁症的成年人显着高于Nondebress _2?=β=?8.84,p?= 0.0029),表明估计的脑年龄高于年龄年龄。袋与中年认知性能无关。在较旧的队列中,更高的袋子与较较差的情节记忆性能(Waldχ2?=?4.10,p?= 0.0430),并且在较旧的凹陷群中单独,加工速度较慢(Waldχ2?=?4.43,P?4.43,P? = 0.0354)。我们还观察到统计学相互作用,较高袋子背景下的更大抑郁症状严重程度与较差的执行功能(Waldχ2?=?5.89,P?=?0.0152)和工作记忆性能(Waldχ2?=?4.47,P? =?0.0346)。增加的袋子与更大的残疾有关(Waldχ2?=?6.00,P?= 0.0143)。与中年抑郁症不同,老年抑郁症表现出加速的脑老化,这反过来与认知和功能赤字有关。

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