Highlights
Prediction of progression to type 1 diabetes with dynamic biomarkers and risk scores
From the abstract: "Identifying biomarkers of functional ß-cell loss is an important step in the risk stratification of type 1 diabetes. Genetic risk scores (GRS), generated by profiling an array of single nucleotide polymorphisms, are a widely used type 1 diabetes risk-prediction tool. Type 1 diabetes screening studies have relied on a combination of biochemical (autoantibody) and GRS screening methodologies for identifying individuals at high-risk of type 1 diabetes. "
Equitable implementation of a precision digital health program for glucose management in individuals with newly diagnosed type 1 diabetes
From the abstract: " Few young people with type 1 diabetes (T1D) meet glucose targets. Continuous glucose monitoring improves glycemia, but access is not equitable. We prospectively assessed the impact of a systematic and equitable digital-health-team-based care program implementing tighter glucose targets (HbA1c?<?7%), early technology use (continuous glucose monitoring starts <1?month after diagnosis) and remote patient monitoring on glycemia in young people with newly diagnosed T1D enrolled in the Teamwork, Targets, Technology, and Tight Control (4T Study)."
Polygenic scores for longitudinal prediction of incident type 2 diabetes in an ancestrally and medically diverse primary care physician network: a patient cohort study
From the article: "Genetic information, if available, could improve T2D prediction among patients lacking measured clinical risk factors. Genome-wide association studies (GWAS) have identified hundreds of unique loci associated with T2D, the results of which can be used to calculate polygenic scores (PGS) that model genetic risk independently of established clinical risk factors including family history. Previous work has evaluated how PGS can be used within healthcare systems, but analyses have been largely cross-sectional in biobanks of mostly European ancestry, limiting the generalizability of results to a more ancestrally and medically diverse US healthcare system. "
Multi-ancestry polygenic mechanisms of type 2 diabetes
K Smith et al, Nature Medicine, March 6, 2024
From the abstract: "Type 2 diabetes (T2D) is a multifactorial disease with substantial genetic risk, for which the underlying biological mechanisms are not fully understood. In this study, we identified multi-ancestry T2D genetic clusters by analyzing genetic data from diverse populations in 37 published T2D genome-wide association studies representing more than 1.4 million individuals. We implemented soft clustering with 650 T2D-associated genetic variants and 110 T2D-related traits, capturing known and novel T2D clusters with distinct cardiometabolic trait associations across two independent biobanks. "
