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基因预测的端粒长度及其与阿尔茨海默病的关系。

Genetically Predicted Telomere Length and Its Relationship With Alzheimer's Disease.

作者信息

Yu Guangping, Lu Leihong, Ma Zaihong, Wu Shouhai

机构信息

Wuqing Center for Disease Control and Prevention, Tianjin, China.

Linyi People's Hospital, Linyi, China.

出版信息

Front Genet. 2021 Feb 19;12:595864. doi: 10.3389/fgene.2021.595864. eCollection 2021.

DOI:10.3389/fgene.2021.595864
PMID:33679878
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7934420/
Abstract

Are shorter telomeres causal risk factors for Alzheimer's disease (AD)? This study aimed to examine if shorter telomeres were causally associated with a higher risk of AD using Mendelian randomization (MR) analysis. Two-sample MR methods were applied to the summary effect sizes and standard errors from a genome-wide association study for AD. Twenty single nucleotide polymorphisms of genome-wide significance were selected as instrumental variables for leukocyte telomere length. The main analyses were performed primarily using the random-effects inverse-variance weighted method and complemented with the other three methods: weighted median approaches, MR-Egger regression, and weighted mode approach. The intercept of MR-Egger regression was used to assess horizontal pleiotropy. We found that longer telomeres were associated with lower risks of AD (odds ratio = 0.79, 95% confidence interval: 0.67, 0.93, = 0.004). Comparable results were obtained using weighted median approaches, MR-Egger regression, and weighted mode approaches. The intercept of the MR-Egger regression was close to zero. This may show that there was not suggestive of horizontal pleiotropy. Our findings provided additional evidence regarding the putative causal association between shorter telomere length and the higher risk of AD.

摘要

较短的端粒是阿尔茨海默病(AD)的因果风险因素吗?本研究旨在使用孟德尔随机化(MR)分析来检验较短的端粒是否与AD的较高风险存在因果关联。将双样本MR方法应用于AD全基因组关联研究的汇总效应大小和标准误差。选择20个具有全基因组显著性的单核苷酸多态性作为白细胞端粒长度的工具变量。主要分析主要使用随机效应逆方差加权法进行,并辅以其他三种方法:加权中位数法、MR-Egger回归法和加权模式法。MR-Egger回归的截距用于评估水平多效性。我们发现较长的端粒与较低的AD风险相关(优势比=0.79,95%置信区间:0.67,0.93,P=0.004)。使用加权中位数法、MR-Egger回归法和加权模式法获得了类似的结果。MR-Egger回归的截距接近零。这可能表明没有提示水平多效性。我们的研究结果为较短的端粒长度与较高的AD风险之间的假定因果关联提供了更多证据。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4601/7934420/702a6597789d/fgene-12-595864-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4601/7934420/932438b66bb4/fgene-12-595864-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4601/7934420/f3abb69d170b/fgene-12-595864-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4601/7934420/702a6597789d/fgene-12-595864-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4601/7934420/932438b66bb4/fgene-12-595864-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4601/7934420/f3abb69d170b/fgene-12-595864-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4601/7934420/702a6597789d/fgene-12-595864-g003.jpg

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