Christopher N. Foley

The paper shows that imputing DNA methylation loci from epigenome-wide data provides stronger associations with smoking and age than directly measured CpGs.

This study identifies gene-environment interactions affecting plasma proteins in UK Biobank, discovering 683 vQTLs and over 1,400 GEIs across 571 proteins.

isGWAS enables fast and scalable genetic association analysis using cohort-level summary data, achieving speeds up to 1500 times faster than existing methods.

This study combines sequencing and genotyping data from two biobanks to identify 975 protein-coding variant associations across 744 disease endpoints, enhancing understanding of genetic disease mechanisms and drug targets.

This study identifies 388 genetic associations with regional brain sulcal morphology using UK Biobank data, highlighting gene expression and eQTL patterns and providing a 3D visualization resource.

This paper introduces HyPrColoc, a Bayesian algorithm for multi-trait colocalization using GWAS summary statistics, identifying 43 regions where coronary heart disease colocalizes with other traits.

MR-Clust clusters genetic variants with similar causal estimates in Mendelian randomization to identify distinct causal mechanisms.

This study investigates shared mechanisms between coronary heart disease and depression using UK Biobank data, finding that environmental factors and specific biomarkers like IL-6, CRP, and triglycerides are likely causal for depression.

This paper introduces a robust MR method that identifies groups of genetic variants with similar causal effects, showing it outperforms existing methods in accuracy and speed for HDL-cholesterol and CHD analysis.

This paper introduces a heterogeneity-penalized model averaging method for Mendelian randomization that improves efficiency and Type 1 error control when multiple valid instruments are present.