Mendelian Randomization Analysis
Mendelian randomization uses genetic variants — naturally assigned at conception — as instrumental variables to infer causal relationships between modifiable exposures and health outcomes.
Unlike observational studies, MR is inherently robust to confounding because genotypes are not influenced by lifestyle, environment, or disease. This makes it the gold standard for causal inference in epidemiology.
- Two-sample MR using large-scale GWAS summary statistics
- Sensitivity analyses: MR-Egger, weighted median, PRESSO, CAUSE
- Multivariable MR for mediation and network analysis
- Steiger filtering to detect and remove weak instruments
- Phenome-wide MR for comprehensive effect profiling
MR Pipeline Overview
Instrument Selection
Extract genome-wide significant SNPs (p<5×10⁻⁸) for the exposure; apply LD clumping (r²<0.001)
Effect Extraction
Harmonise alleles between exposure and outcome GWAS; handle palindromic SNPs carefully
Causal Estimation
IVW primary estimate; Egger, WM, WM, and PRESSO as sensitivity methods
Pleiotropy Diagnostics
Funnel plots, leave-one-out, Egger intercept, heterogeneity statistics
Reporting & Interpretation
Publication-ready figures, effect tables, and narrative summary of causal evidence
