Jimmy David Bell

This paper uses machine learning to impute MRI-derived organ volumes and applies bias-corrected GWAS to identify genetic loci associated with these traits across 450,000 individuals.

The paper identifies shared genetic regulation across mRNA, proteins, and metabolites in blood, revealing networks and mediators of GWAS variants.

This study identifies genetic variants associated with glycaemic response to GLP-1 receptor agonists using observational and trial data, finding variants in GLP-1R and ARRB1 linked to HbA1c reduction.

The paper uses deep learning to quantify abdominal organ traits from MRI scans and identifies genetic associations with organ health parameters.

This study develops machine learning models to predict liver fat content using multi-omic and clinical data from NAFLD patients, achieving higher accuracy than existing tools.

This study identifies 46 novel genetic loci associated with alcohol consumption and suggests shared genetic mechanisms with neuropsychiatric disorders using GWAS and functional analyses.