Zhao Xuhao, Xu Xiaolin, Yan Yifan, Lipnicki Darren M, Pang Ting, Crawford John D, Chen Christopher, Cheng Ching-Yu, Venketasubramanian Narayanaswamy, Chong Eddie, Blay Sergio Luis, Lima-Costa Maria Fernanda, Castro-Costa Erico, Lipton Richard B, Katz Mindy J, Ritchie Karen, Scarmeas Nikolaos, Yannakoulia Mary, Kosmidis Mary H, Gureje Oye, Ojagbemi Akin, Bello Toyin, Hendrie Hugh C, Gao Sujuan, Guerra Ricardo Oliveira, Auais Mohammad, Gomez José Fernando, Rolandi Elena, Davin Annalisa, Rossi Michele, Riedel-Heller Steffi G, Löbner Margit, Roehr Susanne, Ganguli Mary, Jacobsen Erin P, Chang Chung-Chou H, Aiello Allison E, Ho Roger, Sanchez-Juan Pascual, Valentí-Soler Meritxell, Ser Teodoro Del, Lobo Antonio, De-la-Cámara Concepción, Lobo Elena, Sachdev Perminder S, Xu Xin
School of Public Health, The Second Affiliated Hospital of School of Medicine, Zhejiang University, Hangzhou, China.
School of Public Health, Faculty of Medicine, The University of Queensland, Brisbane, Australia.
Lancet Reg Health West Pac. 2024 Sep 12;51:101198. doi: 10.1016/j.lanwpc.2024.101198. eCollection 2024 Oct.
Cardiometabolic multimorbidity (CMM) and depression are often co-occurring in older adults and associated with neurodegenerative outcomes. The present study aimed to estimate the independent and joint associations of CMM and depression on cognitive function in multi-regional cohorts, and to validate the generalizability of the findings in additional settings, including clinical.
Data harmonization was performed across 14 longitudinal cohort studies within the Cohort Studies of Memory in an International Consortium (COSMIC) group, spanning North America, South America, Europe, Africa, Asia, and Australia. Three external validation studies with distinct settings were employed for generalization. Participants were eligible for inclusion if they had data for CMM and were free of dementia at baseline. Baseline CMM was defined as: 1) CMM 5, ≥2 among hypertension, hyperlipidemia, diabetes, stroke, and heart disease and 2) CMM 3 (aligned with previous studies), ≥2 among diabetes, stroke, and heart disease. Baseline depression was primarily characterized by binary classification of depressive symptom measurements, employing the Geriatric Depression Scale and the Center for Epidemiological Studies-Depression scale. Global cognition was standardized as z-scores through harmonizing multiple cognitive measures. Longitudinal cognition was calculated as changes in global cognitive z-scores. A pooled individual participant data (IPD) analysis was utilized to estimate the independent and joint associations of CMM and depression on cognitive outcomes in COSMIC studies, both cross-sectionally and longitudinally. Repeated analyses were performed in three external validation studies.
Of the 32,931 older adults in the 14 COSMIC cohorts, we included 30,382 participants with complete data on baseline CMM, depression, and cognitive assessments for cross-sectional analyses. Among them, 22,599 who had at least 1 follow-up cognitive assessment were included in the longitudinal analyses. The three external studies for validation had 1964 participants from 3 multi-ethnic Asian older adult cohorts in different settings (community-based, memory clinic, and post-stroke study). In COSMIC studies, each of CMM and depression was independently associated with cross-sectional and longitudinal cognitive function, without significant interactions between them (s > 0.05). Participants with both CMM and depression had lower cross-sectional cognitive performance (e.g. β = -0.207, 95% CI = (-0.255, -0.159) for CMM5 (+)/depression (+)) and a faster rate of cognitive decline (e.g. β = -0.040, 95% CI = (-0.047, -0.034) for CMM5 (+)/depression (+)), compared with those without either condition. These associations remained consistent after additional adjustment for APOE genotype and were robust in two-step random-effects IPD analyses. The findings regarding the joint association of CMM and depression on cognitive function were reproduced in the three external validation studies.
Our findings highlighted the importance of investigating age-related co-morbidities in a multi-dimensional perspective. Targeting both cardiometabolic and psychological conditions to prevent cognitive decline could enhance effectiveness.
Natural Science Foundation of China and National Institute on Aging/National Institutes of Health.
心脏代谢性共病(CMM)和抑郁症在老年人中常常同时出现,并与神经退行性病变相关。本研究旨在评估多地区队列中CMM和抑郁症对认知功能的独立及联合关联,并在包括临床环境在内的其他场景中验证研究结果的普遍性。
在国际财团记忆队列研究(COSMIC)组内的14项纵向队列研究中进行数据整合,该组研究覆盖北美、南美、欧洲、非洲、亚洲和澳大利亚。采用三项具有不同场景的外部验证研究进行普遍性验证。如果参与者有CMM数据且基线时无痴呆,则符合纳入条件。基线CMM定义为:1)CMM 5,即高血压、高脂血症、糖尿病、中风和心脏病中至少2种;2)CMM 3(与先前研究一致),即糖尿病、中风和心脏病中至少2种。基线抑郁症主要通过抑郁症状测量的二元分类来表征,采用老年抑郁量表和流行病学研究中心抑郁量表。通过整合多种认知测量指标,将整体认知标准化为z分数。纵向认知通过整体认知z分数的变化来计算。在COSMIC研究中,采用汇总个体参与者数据(IPD)分析来评估CMM和抑郁症对认知结局的独立及联合关联,包括横断面和纵向分析。在三项外部验证研究中进行重复分析。
在14个COSMIC队列的32931名老年人中,我们纳入了30382名具有基线CMM、抑郁症和认知评估完整数据的参与者进行横断面分析。其中,22599名至少有1次随访认知评估的参与者被纳入纵向分析。三项外部验证研究中有来自3个不同场景(社区、记忆门诊和中风后研究)的多民族亚洲老年人群体的1964名参与者。在COSMIC研究中,CMM和抑郁症各自均与横断面和纵向认知功能独立相关,它们之间无显著交互作用(P>0.05)。与无CMM和抑郁症的参与者相比,同时患有CMM和抑郁症的参与者横断面认知表现更低(例如,CMM5(+)/抑郁症(+)时β=-0.207,95%CI=(-0.255,-0.159)),认知衰退速度更快(例如,CMM5(+)/抑郁症(+)时β=-0.040,95%CI=(-0.047,-0.034))。在对APOE基因型进行额外调整后,这些关联仍然一致,并且在两步随机效应IPD分析中具有稳健性。CMM和抑郁症对认知功能的联合关联在三项外部验证研究中得到了重现。
我们的研究结果强调了从多维度视角研究与年龄相关的共病的重要性。针对心脏代谢和心理状况以预防认知衰退可能会提高有效性。
中国国家自然科学基金以及美国国立衰老研究所/美国国立卫生研究院。