Integrating polygenic risk scores in the prediction of gestational diabetes risk in China

Abstract

BackgroundPolygenic risk scores (PRS) serve as valuable tools for connecting initial genetic discoveries with clinical applications in disease risk estimation. However, limited studies have explored the association between PRS and gestational diabetes mellitus (GDM), particularly in predicting GDM risk among Chinese populations.AimTo evaluate the relationship between PRS and GDM and explore the predictive capability of PRS for GDM risk in a Chinese population.MethodsA prospective cohort study was conducted, which included 283 GDM and 2,258 non-GDM cases based on demographic information on pregnancies. GDM was diagnosed using the oral glucose tolerance test (OGTT) at 24–28 weeks. The strength of the association between PRS and GDM odds was assessed employing odds ratios (ORs) with 95% confidence intervals (CIs) derived from logistic regression. Receiver operating characteristic curves, net reclassification improvement (NRI), and integrated discrimination improvement (IDI) were employed to evaluate the improvement in prediction achieved by the new model.ResultsWomen who developed GDM exhibited significantly higher PRS compared to control individuals (OR = 2.01, 95% CI = 1.33–3.07). The PRS value remained positively associated with fasting plasma glucose (FPG), 1-hour post-glucose load (1-h OGTT), and 2-hour post-glucose load (2-h OGTT) (all p < 0.05). The incorporation of PRS led to a statistically significant improvement in the area under the curve (0.71, 95% CI: 0.66–0.75, p = 0.024) and improved discrimination and classification (IDI: 0.007, 95% CI: 0.003–0.012, p < 0.001; NRI: 0.258, 95% CI: 0.135–0.382, p < 0.001).ConclusionsThis study highlights the increased odds of GDM associated with higher PRS values and modest improvements in predictive capability for GDM.