Marzuki Aleya A, Wong Kean Yung, Chan Jee Kei, Na Sze Yie, Thanaraju Arjun, Phon-Amnuaisuk Paveen, Vafa Samira, Yap Jie, Lim Wei Gene, Yip Wei Zern, Arokiaraj Annette Shamala, Shee Dexter, Lee Louisa Gee Ling, Chia Yook Chin, Jenkins Michael, Schaefer Alexandre
Department of Psychiatry and Psychotherapy, Medical School and University Hospital, Eberhard Karls University of Tübingen, Tübingen, Germany.
German Center for Mental Health (DZPG), Tübingen, Germany.
NPJ Aging. 2024 Oct 31;10(1):50. doi: 10.1038/s41514-024-00171-3.
Aging is associated with declines in cognition and brain structural integrity. However, there is equivocality over (1) the specificity of affected domains in different people, (2) the location of associated patterns of brain structural deterioration, and (3) the sociodemographic factors contributing to 'unhealthy' cognition. We aimed to identify cognitive profiles displayed by older adults and determine brain and sociodemographic features potentially shaping these profiles. A sample of Southeast-Asian older adults (N = 386) participated in a multi-session study comprising cognitive testing, neuroimaging, and a structured interview. We used computational models to extract latent mechanisms underlying cognitive flexibility and response inhibition. Data-driven methods were used to construct cognitive profiles based on standard performance measures and model parameters. We also investigated grey matter volume and machine-learning derived 'brain-ages'. A profile associated with poor set-shifting and rigid focusing was associated with widespread grey matter reduction in cognitive control regions. A slow responding profile was associated with advanced brain-age. Both profiles were correlated with poor socioeconomic standing and cognitive reserve. We found that the impact of sociodemographic factors on cognitive profiles was partially mediated by total grey and white matter, and dorsolateral prefrontal and cerebellar volumes. This study furthers understanding of how distinct aging profiles of cognitive impairment uniquely correspond to specific vs. global brain deterioration and the significance of socioeconomic factors in informing cognitive performance in older age.
衰老与认知能力下降和脑结构完整性受损有关。然而,关于以下几个方面仍存在不确定性:(1)不同人群中受影响领域的特异性;(2)脑结构退化相关模式的位置;(3)导致“不健康”认知的社会人口学因素。我们旨在确定老年人所表现出的认知特征,并确定可能塑造这些特征的脑和社会人口学特征。一组东南亚老年人(N = 386)参与了一项多阶段研究,该研究包括认知测试、神经影像学检查和结构化访谈。我们使用计算模型来提取认知灵活性和反应抑制背后的潜在机制。基于标准性能指标和模型参数,采用数据驱动方法构建认知特征。我们还研究了灰质体积和机器学习得出的“脑龄”。一种与不良的集合转换和僵化聚焦相关的特征与认知控制区域广泛的灰质减少有关。一种反应缓慢的特征与脑龄提前有关。这两种特征都与社会经济地位低下和认知储备不足相关。我们发现,社会人口学因素对认知特征的影响部分由总灰质和白质以及背外侧前额叶和小脑体积介导。这项研究进一步加深了我们对认知障碍的不同衰老特征如何独特地对应于特定的与整体的脑退化,以及社会经济因素在影响老年人认知表现方面的重要性的理解。