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老年认知衰退在多大程度上是由与年龄相关的神经病理学引起的?

To what degree is late life cognitive decline driven by age-related neuropathologies?

机构信息

Rush University Medical Center, Rush Alzheimer's Disease Center, Chicago, IL 60612, USA.

Department of Psychiatry and Behavioral Sciences, Rush University Medical Center, Chicago, IL 60612, USA.

出版信息

Brain. 2021 Aug 17;144(7):2166-2175. doi: 10.1093/brain/awab092.

DOI:10.1093/brain/awab092
PMID:33742668
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8370442/
Abstract

The ageing brain is vulnerable to a wide array of neuropathologies. Prior work estimated that the three most studied of these, Alzheimer's disease, infarcts, and Lewy bodies, account for ∼40% of the variation in late life cognitive decline. However, that estimate did not incorporate many other diseases that are now recognized as potent drivers of cognitive decline [e.g. limbic predominant age-related TDP-43 encephalopathy (LATE-NC), hippocampal sclerosis, other cerebrovascular conditions]. We examined the degree to which person-specific cognitive decline in old age is driven by a wide array of neuropathologies. Deceased participants (n = 1164) from two longitudinal clinical-pathological studies, the Rush Memory and Aging Project and Religious Orders Study, completed up to 24 annual evaluations including 17 cognitive performance tests and underwent brain autopsy. Neuropathological examinations provided 11 pathological indices, including markers of Alzheimer's disease, non- Alzheimer's disease neurodegenerative diseases (i.e. LATE-NC, hippocampal sclerosis, Lewy bodies), and cerebrovascular conditions (i.e. macroscopic infarcts, microinfarcts, cerebral amyloid angiopathy, atherosclerosis, and arteriolosclerosis). Mixed effects models examined the linear relation of pathological indices with global cognitive decline, and random change point models examined the relation of the pathological indices with the onset of terminal decline and rates of preterminal and terminal decline. Cognition declined an average of about 0.10 unit per year (estimate = -0.101, SE = 0.003, P < 0.001) with considerable heterogeneity in rates of decline (variance estimate for the person-specific slope of decline was 0.0094, P < 0.001). When considered separately, 10 of 11 pathological indices were associated with faster decline and accounted for between 2% and 34% of the variation in decline, respectively. When considered simultaneously, the 11 pathological indices together accounted for 43% of the variation in decline; Alzheimer's disease-related indices accounted for 30-36% of the variation, non-Alzheimer's disease neurodegenerative indices 4-10%, and cerebrovascular indices 3-8%. Finally, the 11 pathological indices combined accounted for less than a third of the variation in the onset of terminal decline (28%) and rates of preterminal (32%) and terminal decline (19%). Although age-related neuropathologies account for a large proportion of the variation in late life cognitive decline, considerable variation remains unexplained even after considering a wide array of neuropathologies. These findings highlight the complexity of cognitive ageing and have important implications for the ongoing effort to develop effective therapeutics and identify novel treatment targets.

摘要

衰老的大脑容易受到多种神经病理学的影响。先前的研究估计,在这些最受研究的三种中,阿尔茨海默病、梗死和路易体,占晚年认知能力下降的约 40%。然而,该估计并未纳入许多其他现在被认为是认知能力下降的主要驱动因素的疾病[例如,边缘为主的与年龄相关的 TDP-43 脑病(LATE-NC)、海马硬化症、其他脑血管疾病]。我们研究了个体衰老过程中的认知能力下降在多大程度上是由广泛的神经病理学引起的。来自两项纵向临床病理学研究的已故参与者(n=1164),即拉什记忆和衰老项目和宗教秩序研究,完成了多达 24 项年度评估,包括 17 项认知表现测试,并进行了大脑尸检。神经病理学检查提供了 11 种病理指标,包括阿尔茨海默病标志物、非阿尔茨海默病神经退行性疾病(即 LATE-NC、海马硬化症、路易体)和脑血管疾病(即大梗死、微梗死、脑淀粉样血管病、动脉粥样硬化和小动脉硬化)。混合效应模型检查了病理指标与整体认知能力下降的线性关系,随机变化点模型检查了病理指标与终末期下降的关系以及前终末期和终末期下降的关系。认知能力平均每年下降约 0.10 个单位(估计值=-0.101,SE=0.003,P<0.001),下降率存在很大差异(个体斜率的方差估计值为 0.0094,P<0.001)。当单独考虑时,11 种病理指标中有 10 种与更快的下降相关,分别占下降幅度的 2%至 34%。当同时考虑时,这 11 种病理指标共同解释了下降幅度的 43%;与阿尔茨海默病相关的指标占 30-36%,非阿尔茨海默病神经退行性疾病指标占 4-10%,脑血管疾病指标占 3-8%。最后,11 种病理指标合计仅占终末期下降(28%)和前终末期(32%)和终末期(19%)的变化的三分之一以下。尽管与年龄相关的神经病理学占晚年认知能力下降的很大一部分,但即使考虑到广泛的神经病理学,仍有相当大的一部分无法解释。这些发现强调了认知老化的复杂性,并对正在进行的开发有效疗法和识别新治疗靶点的努力具有重要意义。

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