Henry J. Taylor

The paper identifies genetic factors influencing iPSC growth rates, finding rare variants in WDR54 and a polygenic background explaining most variance.

This study examines how genetic and lifestyle factors together influence the risk of developing type 2 diabetes in the UK Biobank population.

This study uses Mendelian randomization to show that higher glycemic traits are inversely associated with thoracic aortic diameters and reduced risk of aneurysm and dissection.

This study investigates causal links between T2D genetic clusters and non-cardiovascular comorbidities, identifying potential drug repurposing opportunities.

The paper uses direct RNA nanopore sequencing to identify RNA modification changes in human pancreatic beta-cells after glucose stimulation, finding 1,697 differentially modified sites linked to type 2 diabetes genes.

This study identifies metabolic reaction fluxes that interact with CAD risk alleles, revealing their role as amplifiers or buffers in disease susceptibility.

This study integrates multi-omics data to identify genetic variants and molecular mechanisms associated with type 2 diabetes and highlights potential drug targets.

This study uses single-cell RNA sequencing to analyze gene expression changes in human pancreatic islets under different glucose conditions over 24 hours, identifying genes and modules associated with time, glucose exposure, and their interaction.

This study functionally interrogates 20 T2D-associated genes using isogenic hESC-derived β-like cells, identifying variants and genes linked to insulin production and lipotoxicity sensitivity.

This study identifies 1,289 genetic signals for type 2 diabetes in 2.5 million individuals, revealing distinct clusters linked to vascular complications and highlighting ancestry-specific genetic risk factors.

This paper identifies miRNAs associated with type 2 diabetes and glycemic traits through genetic analysis of miRNA expression in human pancreatic islets.

This study integrates single-cell gene expression and chromatin accessibility data from human pancreatic islets to identify T1D risk mechanisms involving multiple cell types and genetic variants.