Mark I. McCarthy

This paper identifies four genetic regions associated with both type 1 and type 2 diabetes, with three showing opposite effect directions and one showing concordant effects.

This paper identifies 56 new type 2 diabetes loci in 433,540 East Asian individuals through a meta-analysis of GWAS data.

This study identifies novel genetic loci associated with BMI in Indians through GWAS and explores their epigenetic and regulatory mechanisms.

The paper uses deep learning models to predict regulatory variants in pancreatic islets and refines T2D association signals by integrating epigenomic data with genetic fine-mapping.

This study evaluates multi-SNP transcriptome-wide association models for gene expression in human tissues and their ability to identify causal genes for metabolites.

This study develops a polygenic and phenotypic risk score for PCOS using EHR data, showing improved detection and identifying shared metabolic and endocrine comorbidities.

The paper shows that a loss-of-function variant in ZnT8 improves insulin secretion and protects against type 2 diabetes by enhancing glucose responsiveness and proinsulin conversion.

ELGH is a population genomics study of British-Bangladeshi and British-Pakistani people in east London, combining health records with genetic data to study disease and genetic influences.

The paper integrates genetic, genomic, and functional data to identify convergent biological pathways in type 2 diabetes, revealing enriched functional connectivity among causal genes.

This study investigates the association between genetic variants in PMAT and OCT1 transporters and metformin gastrointestinal intolerance in type 2 diabetes patients.

This study performs a large-scale genome-wide meta-analysis of PCOS cases and identifies genetic loci associated with PCOS and related traits, showing shared genetic architecture across different diagnostic criteria.

This study identifies 16 genome-wide significant loci associated with diabetic kidney disease, including a protective variant in the COL4A3 gene.

This study identifies a fetal genome-wide association signal near pro-inflammatory cytokine genes on 2q13 linked to gestational duration and preterm/postterm birth.

This study identifies rare variant associations with fat distribution and cardio-metabolic risk, implicating intracellular lipolysis genes in these traits.

The paper develops S-PrediXcan to compute gene expression associations from GWAS summary data and applies it to 44 GTEx tissues and 100+ phenotypes, finding tissue-specific effects and colocalized associations.

This paper introduces the Recall-by-Genotype study design to improve causal inference in genetic studies through genotype-directed deep-phenotyping.

The paper integrates chromatin accessibility and DNA methylation data from human pancreatic islets to refine regulatory mechanisms at Type 2 Diabetes susceptibility loci.

This study identifies maternal genetic variants associated with offspring birth weight using GWAS and SEM, showing independent effects from fetal genetics.

This study identifies genetic loci associated with early childhood growth phenotypes and links them to later adiposity traits, suggesting potential targets for obesity prevention.