轻度认知障碍,阿尔茨海默病 z-bio 2025-02-12 234

　　Diagram of Revealing Risk Factors and Mechanisms of Cognitive Decline through Community Population Cohort Research

　　With the support of National Natural Science Foundation of China projects (approval numbers: 81161120498, 82293642, 82230403), Professor Song Weihong from Wenzhou Medical University/Oujiang Laboratory, Professor Li Tingyu from Chongqing Medical University, and Researcher Zhang Yun from Nanjing Gulou Hospital have made progress in the research on risk factors for the transformation of mild cognitive impairment (MCI) to Alzheimer's disease (AD). The research findings, titled "Identification of circulating risk biomarkers for cognitive decline in a large community based population in Chongqing," were published online on December 23, 2024 in the journal Alzheimer's&Dementia. The link to the paper is: https://alz-journals.onlinelibrary.wiley.com/doi/10.1002/alz.14443 .

　　The aging population has led to a significant increase in the incidence of chronic diseases related to aging. China has the largest elderly population in the world, with 300 million people aged 60 and above. The number of dementia patients, mainly AD, is as high as 15 million, which brings huge disease and economic burden to patients, families, and society. MCI is considered a precursor to the onset of AD. Accurately identifying risk markers for MCI to AD conversion can contribute to the study of AD mechanisms, early diagnosis, and precise intervention.

　　This study used a multi-stage stratified clustering sampling method, including 26554 residents from urban and rural areas in 6 districts and counties of Chongqing, covering diverse backgrounds such as age and ethnicity. Through lifestyle survey, clinical evaluation and blood biomarker detection, age, gender, education level, occupation, body mass index, diabetes, hypertension, stroke and other comorbidity were found as risk factors for cognitive decline, and the differences of these risk factors between urban and rural populations and between different genders were revealed. In addition, the research system analyzed the shared risk factors and unique characteristics among different degrees of cognitive decline, and found that aging, low education level, stroke, hypertension, and epilepsy history are important factors that promote the transformation of MCI to dementia. The study also found that there is an interaction between significantly elevated biomarkers in the blood of AD patients and major risk factors. Specifically, age is significantly positively correlated with the ratio of beta amyloid A β 42/A β 40, glial fibrillary acidic protein and neurofilament light chain levels in the blood of AD patients, and body mass index, type 2 diabetes history are significantly positively correlated with the levels of NfL and A β 40 in the blood of patients with AD.

　　This study reveals the risk factors of cognitive decline at different stages and their correlation with AD pathology, and systematically explores the potential mechanisms of these risk factors in the occurrence and development of AD. The research results provide a new perspective for a deeper understanding of the mechanism of risk factors in cognitive decline, and offer potential new targets and theoretical basis for the early diagnosis and prevention of AD.