Publications by authors named "R E Holman"
Genomics can provide insight into the etiology of type 2 diabetes and its comorbidities, but assigning functionality to non-coding variants remains challenging. Polygenic scores, which aggregate variant effects, can uncover mechanisms when paired with molecular data. Here, we test polygenic scores for type 2 diabetes and cardiometabolic comorbidities for associations with 2,922 circulating proteins in the UK Biobank.
View Article and Find Full Text PDFBackground: Data to support individualised choice of optimal glucose-lowering therapy are scarce for people with type 2 diabetes. We aimed to establish whether routinely available clinical features can be used to predict the relative glycaemic effectiveness of five glucose-lowering drug classes.
Methods: We developed and validated a five-drug class model to predict the relative glycaemic effectiveness, in terms of absolute 12-month glycated haemoglobin (HbA), for initiating dipeptidyl peptidase-4 inhibitors, glucagon-like peptide-1 receptor agonists, sodium-glucose co-transporter-2 inhibitors, sulfonylureas, and thiazolidinediones.
Objective: To evaluate the association of four bone metabolism biomarkers (osteoprotegerin, osteopontin, sclerostin, and osteocalcin) with cardiovascular events in people with type 2 diabetes (T2D).
Research Design And Methods: The Exenatide Study of Cardiovascular Event Lowering (EXSCEL) was a randomized clinical trial evaluating the cardiovascular (CV) safety and efficacy of once-weekly exenatide for patients with T2D. Candidate biomarker data were selected from proteomic profiling performed at baseline and 12 months after randomization samples by SomaScan assay in 5,473 trial participants.