Genetically predicted body fat mass and distribution with diabetic kidney disease: A two-sample Mendelian randomization study - Wang, Min; Li, Xin; Mei, Hang; Huang, Zhao-Hui; Liu, Yue; Zhu, Yong-Hong; Ma, Tian-Kui; Fan, Qiu-Ling (Frontiers in Genetics, 2022)
The aim of this study was to apply a Mendelian randomization (MR) design to investigate the potential causal associations between body mass index (BMI) and body fat mass (trunk fat mass and waist circumference (WC)) , and diabetic kidney disease (DKD). A two-sample MR study was conducted to obtain exposure and outcome data from previously published studies. The instrumental variables for BMI, trunk fat mass and WC were selected from genome-wide association study summary datasets based on summary-level statistics. The random-effects inverse-variance weighted (IVW) method was used for the main analyses, and the weighted median and MR-Egger approaches were complementary. Three MR methods suggested that genetically-predicted BMI, trunk fat mass, and WC were positively associated all with DKD. Using IVW, we found evidence of causal relationships between BMI [odds ratio (OR) =1.99; 95% confidence interval (CI), 1.47-2.69; p= 7.89×10-6], trunk fat mass [OR=1.80; 95%CI, 1.28-2.53; p=6.84×10-4], WC [OR= 2.48; 95%CI, 1.40-4.42; p=1.93×10-3] and DKD. MR-Egger and weighted median regression also showed directionally similar estimates. Both funnel plots and MR-Egger intercepts showed no directional pleiotropic effects involving the above variables and DKD. Our MR analysis supportsed the causal effect of BMI, trunk fat mass and WC on DKD. Individuals can substantially reduce their DKD risk by reducing of body fat mass and modifying thier body fat distribution.