BMI as a Modifiable Risk Factor for Type 2 Diabetes: Refining and Understanding Causal Estimates Using Mendelian...

Area of Science:

• Genetics and Epidemiology
• Metabolic Disease Research

Background:

• Understanding the causal relationship between body mass index (BMI) and type 2 diabetes is crucial for public health.
• Genetic variants associated with BMI offer opportunities to explore causality using Mendelian randomization (MR).

Purpose of the Study:

• To resolve the true causal effect of BMI on type 2 diabetes using advanced MR methods.
• To assess the impact of pleiotropic genetic variants on causal estimates and evaluate new analytical approaches.

Main Methods:

• A two-sample Mendelian randomization (MR) approach was employed using 96 genetic variants.
• Three analysis methods were utilized, including MR-Egger and weighted median, to address potential bias from invalid instrumental variables.
• The influence of pleiotropy was examined, particularly focusing on the TCF7L2(rs7903146) variant.

Main Results:

• An odds ratio for type 2 diabetes per unit increase in BMI (kg/m²) was estimated between 1.19 and 1.38.
• The most stable estimate, using all instruments with a weighted median approach, was 1.26 (95% CI 1.17, 1.34).
• Removal of the pleiotropic variant TCF7L2(rs7903146) led to convergence of causal effect estimates, demonstrating the impact of pleiotropy.

Conclusions:

• BMI has a significant causal effect on the risk of type 2 diabetes.
• Pleiotropic genetic variants can introduce bias in causal effect estimates.
• Advanced analytical methods, such as weighted median and MR-Egger, are valuable for mitigating bias in MR studies.