Polygenic scores for longitudinal prediction of incident type 2 diabetes in an ancestrally and medically diverse primary care physician network: a patient cohort study
Ravi Mandla, Philip Schroeder, Bianca Porneala, Jose C. Florez, James B. Meigs, Josep M. Mercader, Aaron Leong
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引用次数: 0
Abstract
The clinical utility of genetic information for type 2 diabetes (T2D) prediction with polygenic scores (PGS) in ancestrally diverse, real-world US healthcare systems is unclear, especially for those at low clinical phenotypic risk for T2D. We tested the association of PGS with T2D incidence in patients followed within a primary care practice network over 16 years in four hypothetical scenarios that varied by clinical data availability (N = 14,712): (1) age and sex; (2) age, sex, body mass index (BMI), systolic blood pressure, and family history of T2D; (3) all variables in (2) and random glucose; and (4) all variables in (3), HDL, total cholesterol, and triglycerides, combined in a clinical risk score (CRS). To determine whether genetic effects differed by baseline clinical risk, we tested for interaction with the CRS. PGS was associated with incident T2D in all models. Adjusting for age and sex only, the Hazard Ratio (HR) per PGS standard deviation (SD) was 1.76 (95% CI 1.68, 1.84) and the HR of top 5% of PGS vs interquartile range (IQR) was 2.80 (2.39, 3.28). Adjusting for the CRS, the HR per SD was 1.48 (1.40, 1.57) and HR of the top 5% of PGS vs IQR was 2.09 (1.72, 2.55). Genetic effects differed by baseline clinical risk ((PGS-CRS interaction p = 0.05; CRS below the median: HR 1.60 (1.43, 1.79); CRS above the median: HR 1.45 (1.35, 1.55)). Genetic information can help identify high-risk patients even among those perceived to be low risk in a clinical evaluation.
期刊介绍:
Genome Medicine is an open access journal that publishes outstanding research applying genetics, genomics, and multi-omics to understand, diagnose, and treat disease. Bridging basic science and clinical research, it covers areas such as cancer genomics, immuno-oncology, immunogenomics, infectious disease, microbiome, neurogenomics, systems medicine, clinical genomics, gene therapies, precision medicine, and clinical trials. The journal publishes original research, methods, software, and reviews to serve authors and promote broad interest and importance in the field.