Causal relationship between blood lipids and diabetic kidney disease：a Mendelian randomization study

Abstract

ObjectiveTo explore the causal relationship between blood lipids and diabetic kidney disease （DKD） by a Mendelian randomization （MR） analysis using the summary data of large-scale population genome-wide association studies （GWAS）.MethodsUsing inverse variance weighting method （IVW）， weighted median method and MR-Egger regression method， the causal relationship of triglyceride （TG）， total cholesterol （TC）， high density lipoprotein （HDL）， and low density lipoprotein （LDL） with DKD was analyzed by MR， and evaluated by odds ratio （OR） and 95% confidence interval （CI）. Sensitivity analysis was performed to verify the reliability of the results. Cochran Q test was used to test heterogeneity， and MR-Egger-intercept test was used to test whether there was horizontal pleiotropic effect. Steiger test was used to test directionality， and leave-one-out analysis was used to determine whether there was potential single nucleotide polymorphism.ResultsThe IVW method was used as the main analysis method. The analysis results showed that the genetic prediction of TG （OR=1.428， 95%CI： 1.150-1.774， P=0.001） and TC （OR=0.683， 95%CI： 0.486-0.960， P=0.028） had a causal relationship with DKD. HDL （OR=0.879， 95%CI： 0.707-1.092， P=0.244） and LDL （OR=0.911， 95%CI： 0.698-1.191， P=0.496） had no evidence to prove their causal relationship with DKD.ConclusionTG and TC may play a role in the pathogenesis of DKD， but there is no evidence that HDL and LDL play a role in the pathogenesis of DKD.

Keywords

• plasma lipid
• diabetic kidney disease
• mendelian randomization
• causal inference