Ralf Tambets

This study performs a large-scale GWAS on 249 metabolic traits in 619,372 individuals, identifying 88,604 associations and using MR to explore causal links between metabolites and diseases.

The paper explores challenges in Mendelian randomisation with proxy exposures, demonstrating how variant effects on downstream metabolites can infer causal roles in biological processes.

The paper benchmarks methods for prioritizing GWAS target genes using eQTLs and finds that assigning pQTLs to closest protein-coding genes outperforms colocalisation methods.

The paper visualises molecular QTLs to better understand genetic effects on gene expression and identifies causal genes at GWAS loci.