Mendelian randomization in cardiometabolic disease: challenges in evaluating causality

Area of Science:

• Genetics
• Epidemiology
• Biostatistics

Background:

• Mendelian randomization (MR) is a powerful method for causal inference using genetic variants.
• Interpreting MR findings can be challenging due to complex genetic-exposure relationships.

Purpose of the Study:

• To review challenges in interpreting Mendelian randomization analyses.
• To elaborate on molecular features and causal associations in complex MR scenarios.

Main Methods:

• Review of existing Mendelian randomization studies.
• Analysis of genetic variants associated with various exposures and outcomes.
• Discussion of pleiotropy, multiple traits, and time-dependent exposures.

Main Results:

• Identified challenges in MR interpretation including pleiotropic variants and complex exposure relationships.
• Discussed specific examples such as branched-chain amino acids, C-reactive protein, HDL cholesterol, IL-6, alcohol metabolism, and lipid profiles.
• Provided molecular explanations for likely causal associations.

Conclusions:

• Addressing complexities in MR analyses is crucial for reliable causal inference.
• Understanding molecular mechanisms enhances the evaluation of MR findings.