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Prediction of Alzheimer's disease using multi-variants from a Chinese genome-wide association study

Authors :
Longfei Jia
Fangyu Li
Cuibai Wei
Min Zhu
Qiumin Qu
Wei Qin
Yi Tang
Luxi Shen
Yanjiang Wang
Lu Shen
Honglei Li
Dantao Peng
Lan Tan
Benyan Luo
Qihao Guo
Muni Tang
Yifeng Du
Jiewen Zhang
Junjian Zhang
Jihui Lyu
Ying Li
Aihong Zhou
Fen Wang
Changbiao Chu
Haiqing Song
Liyong Wu
Xiumei Zuo
Yue Han
Junhua Liang
Qi Wang
Hongmei Jin
Wei Wang
Yang Lü
Fang Li
Yuying Zhou
Wei Zhang
Zhengluan Liao
Qiongqiong Qiu
Yan Li
Chaojun Kong
Haishan Jiao
Jie Lu
Jianping Jia
Source :
Brain
Publication Year :
2020
Publisher :
Oxford University Press (OUP), 2020.

Abstract

Previous genome-wide association studies have identified dozens of susceptibility loci for sporadic Alzheimer’s disease, but few of these loci have been validated in longitudinal cohorts. Establishing predictive models of Alzheimer’s disease based on these novel variants is clinically important for verifying whether they have pathological functions and provide a useful tool for screening of disease risk. In the current study, we performed a two-stage genome-wide association study of 3913 patients with Alzheimer’s disease and 7593 controls and identified four novel variants (rs3777215, rs6859823, rs234434, and rs2255835; Pcombined = 3.07 × 10−19, 2.49 × 10−23, 1.35 × 10−67, and 4.81 × 10−9, respectively) as well as nine variants in the apolipoprotein E region with genome-wide significance (P<br />Jia et al. identify novel Alzheimer’s disease-related variants in a two-stage genome-wide association study in a Chinese population, and use the variants to build 11 predictive models. Validation of the models in a separate longitudinal cohort confirms that they can predict Alzheimer's disease risk.

Details

ISSN :
14602156 and 00068950
Volume :
144
Database :
OpenAIRE
Journal :
Brain
Accession number :
edsair.doi.dedup.....1fddde0e921c19e9bfcbda6004d95a7d
Full Text :
https://doi.org/10.1093/brain/awaa364