Identification of circulating risk biomarkers for cognitive decline in a large community-based population in Chongqing China.
Обработка статьи · этапы, ошибки и управление
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Kang Yu, Feng Zijuan, Zhang Qian, Liu Mingjing, Li Yanhua, Yang Huan, Zheng Lingling, Cheng Chunjiang, Zhou Weitao, Lou Dandan, Li Xiaoyong, Chen Liangping, Feng Yi, Duan Xiaoling, Duan Jianzhong, Yu Mengjiao, Yang Shou, Liu Yuhang, Wang Xin, Deng Bo, Liu Chenghui, Yao Xiuqing, Zhu Chi, Liang Chunrong, Zeng Xiaolong, Ren Sisi, Li Qunying, Zhong Yin, Yan Yong, Meng Huaqing, Zhong Zhaohui, Zhang Yong, Kang Jun, Luan Xiaoqian, Pan Sipei, Wu Yili, Li Tingyu, Song Weihong, Zhang Yun
Аннотация
METHODS: A total of 26,554 residents aged 50 years and older were recruited. Multinomial logistic regression models were applied to assess the risk factors of cognition levels. Propensity score matching and linear mixed effects models were used to evaluate the relationship between key risk factors and the circulating biomarkers.
RESULTS: Shared and distinct risk factors for MCI and dementia were identified. Age, lower education, medical history of stroke, hypertension, and epilepsy influenced mild cognitive impairment (MCI) progression to dementia. Correlations between key risk factors and circulating neurofilament light chain (NfL), glial fibrillary acidic protein (GFAP), amyloid β protein (Aβ)40, and Aβ42/Aβ40 ratio suggest underlying mechanisms contributing to cognitive impairment.
DISCUSSION: The common and distinct risk factors across cognitive decline stages emphasize the need for tailored interventions. The correlations with blood biomarkers provide insights into potential management targets.
HIGHLIGHTS: From a large community-based cohort study on the residents in Chongqing, we have identified that mild cognitive impairment (MCI) and dementia share several common risk factors, including age, female gender, rural living, lower education levels, and a medical history of stroke. However, each condition also has its own unique risk factors. Several factors contribute to the progression of MCI into dementia including age, education levels, occupation, and a medical history of hypertension and epilepsy. We discover the correlations between the risk factors for dementia and blood biomarkers that indicate the presence of axonal damage, glial activation, and Aβ pathology.