Context: Type 2 diabetes and obesity often coexist, so it is difficult to judge whether diabetes or obesity induce certain types of hyperlipidemia due to mutual confounds and reverse causation. We used Mendelian randomization analyses to explore the causal relationships of diabetes and adiposity with lipid profiles. Design, Setting, and Main Outcome Measures: From 23 sites in East China, 9798 participants were enrolled during 2014 to 2016. We calculated two weighted genetic risk scores as instrumental variables for type 2 diabetes and body mass index (BMI). These scores were used to measure the causal relationships of diabetes and BMI with lipid profiles that included total cholesterol, high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and triglycerides (TGs). Results: The causal regression coefficients (βIV) of genetically determined diabetes for the total cholesterol, LDL-C, and log10TG were 0.130 [95% confidence interval (CI): 0.020, 0.240; P = 0.014], 0.125 (96% CI: 0.041, 0.209; P = 0.001), and 0.019 (95% CI: -0.001, 0.039; P = 0.055), respectively. The βIV for HDL-C was -0.008 (95% CI: -0.032. 0.016), which was not significant (P = 0.699). The causal regression coefficients of a genetically determined 10 kg/m2 increase in BMI for HDL-C and log10TG were -0.409 (96% CI: -0.698, -0.120; P = 0.004) and 0.227 (95% CI: 0.039, 0.415; P = 0.026), respectively. The βIVs for TGs and LDL-C were not significant. Conclusions: This study has provided evidence for the biologically plausible causal effects of diabetes and adiposity by BMI on different elements of the lipid profile using Mendelian randomization analyses.
Context:Type 2 diabetes and obesity often coexist, so it is difficult to judge whether diabetes or obesity induce certain types of hyperlipidemia due to mutual confounds and reverse causation. We used Mendelian randomization analyses to explore the causal relationships of diabetes and adiposity with lipid profiles. Design, Setting, and Main Outcome Measures: From 23 sites in East China, 9798 participants were enrolled during 2014 to 2016. We calculated two weighted genetic risk scores as instrumental variables for type 2 diabetes and body mass index (BMI). These scores were used to measure the causal relationships of diabetes and BMI with lipid profiles that included total cholesterol, high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and triglycerides (TGs). Results: The causal regression coefficients (βIV) of genetically determined diabetes for the total cholesterol, LDL-C, and log10TG were 0.130 [95% confidence interval (CI): 0.020, 0.240; P = 0.014], 0.125 (96% CI: 0.041, 0.209; P = 0.001), and 0.019 (95% CI: -0.001, 0.039; P = 0.055), respectively. The βIV for HDL-C was -0.008 (95% CI: -0.032. 0.016), which was not significant (P = 0.699). The causal regression coefficients of a genetically determined 10 kg/m2 increase in BMI for HDL-C and log10TG were -0.409 (96% CI: -0.698, -0.120; P = 0.004) and 0.227 (95% CI: 0.039, 0.415; P = 0.026), respectively. The βIVs for TGs and LDL-C were not significant. Conclusions: This study has provided evidence for the biologically plausible causal effects of diabetes and adiposity by BMI on different elements of the lipid profile using Mendelian randomization analyses.
Authors: Amy R Bentley; Guanjie Chen; Ayo P Doumatey; Daniel Shriner; Karlijn A C Meeks; Mateus H Gouveia; Kenneth Ekoru; Jie Zhou; Adebowale Adeyemo; Charles N Rotimi Journal: Hum Mol Genet Date: 2021-11-01 Impact factor: 5.121