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A Phenome-wide Association and Mendelian Randomization Study for Alzheimer’s Disease: A Prospective Cohort Study of 502,493 Participants From the UK Biobank

孟德尔随机化 生命银行 现象 痴呆 医学 疾病 队列 内嗅皮质 内科学 生物信息学 生物 海马体 遗传学 基因型 表型 基因 遗传变异
作者
Shi-Dong Chen,Wei Zhang,Yuzhu Li,Yang Liu,Yuyuan Huang,Yue‐Ting Deng,Bang‐Sheng Wu,John Suckling,Edmund T. Rolls,Jianfeng Feng,Wei Cheng,Qiang Dong,Jin‐Tai Yu
出处
期刊:Biological Psychiatry [Elsevier BV]
卷期号:93 (9): 790-801 被引量:15
标识
DOI:10.1016/j.biopsych.2022.08.002
摘要

Background Considerable uncertainty remains regarding associations of multiple risk factors with Alzheimer’s disease (AD). We aimed to systematically screen and validate a wide range of potential risk factors for AD. Methods Among 502,493 participants from the UK Biobank, baseline data were extracted for 4171 factors spanning 10 different categories. Phenome-wide association analyses and time-to-event analyses were conducted to identify factors associated with both polygenic risk scores for AD and AD diagnosis at follow-up. We performed two-sample Mendelian randomization analysis to further assess their potential causal relationships with AD and imaging association analysis to discover underlying mechanisms. Results We identified 39 factors significantly associated with both AD polygenic risk scores and risk of incident AD, where higher levels of education, body size, basal metabolic rate, fat-free mass, computer use, and cognitive functions were associated with a decreased risk of developing AD, and selective food intake and more outdoor exposures were associated with an increased risk of developing AD. The identified factors were also associated with AD-related brain structures, including the hippocampus, entorhinal cortex, and inferior/middle temporal cortex, and 21 of these factors were further supported by Mendelian randomization evidence. Conclusions To our knowledge, this is the first study to comprehensively and rigorously assess the effects of wide-ranging risk factors on AD. Strong evidence was found for fat-free body mass, basal metabolic rate, computer use, selective food intake, and outdoor exposures as new risk factors for AD. Integration of genetic, clinical, and neuroimaging information may help prioritize risk factors and prevention targets for AD.
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