孟德尔随机化
全基因组关联研究
2019年冠状病毒病(COVID-19)
生物
遗传学
优势比
置信区间
单核苷酸多态性
遗传关联
医学
统计
肿瘤科
基因型
内科学
数学
疾病
基因
传染病(医学专业)
遗传变异
作者
Danqi Huang,Siqi Lin,Junting He,Qi Wang,Yiqiang Zhan
摘要
Several traditional observational studies suggested an association between COVID-19 and leukocyte telomere length (LTL), a biomarker for biological age. However, whether there was a causal association between them remained unclear. We aimed to investigate whether genetically predicted COVID-19 is related to the risk of LTL, and vice versa. We performed bidirectional Mendelian randomization (MR) study using summary statistics from the genome-wide association studies of critically ill COVID-19 (n = 1 388 342) and LTL (n = 472 174) of European ancestry. The random-effects inverse-variance weighted estimation method was applied as the primary method with several other estimators as complementary methods. Using six single-nucleotide polymorphisms (SNPs) of genome-wide significance as instrumental variables for critically ill COVID-19, we did not find a significant association of COVID-19 on LTL (β = 0.0075, 95% confidence interval [CI]: -0.018 to 0.021, p = 0.733). Likewise, using 97 SNPs of genome-wide significance as instrumental variables for LTL, we did not find a significant association of LTL on COVID-19 (odds ratio = 1.00, 95% CI: 0.79-1.28, p = 0.973). Comparable results were obtained using MR-Egger regression, weighted median, and weighted mode approaches. We did not find evidence to support a causal association between COVID-19 and LTL in either direction.
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