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Causal Effects of Genetically Predicted Cardiovascular Risk Factors on Chronic Kidney Disease: A Two-Sample Mendelian Randomization Study

Authors :
Hui-Min Liu
Qin Hu
Qiang Zhang
Guan-Yue Su
Hong-Mei Xiao
Bo-Yang Li
Wen-Di Shen
Xiang Qiu
Wan-Qiang Lv
Hong-Wen Deng
Source :
Frontiers in Genetics, Vol 10 (2019)
Publication Year :
2019
Publisher :
Frontiers Media S.A., 2019.

Abstract

Observational studies have demonstrated that cardiovascular risk factors are associated with chronic kidney disease (CKD). However, these observational associations are potentially influenced by the residual confounding, including some unmeasured lifestyle factors and interaction risk factors. Two-sample mendelian randomization analysis was conducted in this study to evaluate whether genetically predicted cardiovascular risk factors have a causal effect on the risk of CKD. We selected genetic variants associated with cardiovascular risk factors and extracted the corresponding effect sizes from the largest GWAS summary-level dataset of CKD. Cardiovascular risk factors contain high density lipoprotein (HDL) cholesterol, low density lipoprotein (LDL) cholesterol, total cholesterol (TC), triglyceride (TG), glycated hemoglobin (HbA1c), fasting glucose, systolic blood pressure (SBP) and diastolic blood pressure (DBP). A Bonferroni corrected threshold of P = 0.006 was considered as significant, and 0.006 < P < 0.05 was considered suggestive of evidence for a potential association. Genetically predicted DBP was significantly associated with CKD [odds ratio (OR) was 1.35 (95% confidence interval (CI) (1.10, 1.65); P = 0.004)]. There was suggestive evidence for potential associations between genetically predicted higher HDL cholesterol [OR: 0.88, 95%CI (0.80, 0.98), P = 0.025] and lower adds of CKD, and between higher SBP [OR: 1.36, 95%CI (1.07, 1.73), P = 0.013] and higher adds of CKD. However, genetically predicted LDL cholesterol, TC, TG, HbA1c, and fasting glucose did not show any causal association with CKD.

Details

Language :
English
ISSN :
16648021
Volume :
10
Database :
Directory of Open Access Journals
Journal :
Frontiers in Genetics
Publication Type :
Academic Journal
Accession number :
edsdoj.497af7254a8f4d1f87071876a3484e30
Document Type :
article
Full Text :
https://doi.org/10.3389/fgene.2019.00415