Pan-cancer analysis demonstrates that integrating polygenic risk scores with modifiable risk factors improves risk prediction.
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ABSTRACT:
SUBMITTER: Kachuri L
PROVIDER: S-EPMC7695829 | biostudies-literature | 2020 Nov
REPOSITORIES: biostudies-literature
Publications
Pan-cancer analysis demonstrates that integrating polygenic risk scores with modifiable risk factors improves risk prediction.
Kachuri Linda L Graff Rebecca E RE Smith-Byrne Karl K Meyers Travis J TJ Rashkin Sara R SR Ziv Elad E Witte John S JS Johansson Mattias M
Nature communications 20201127 1
Cancer risk is determined by a complex interplay of environmental and heritable factors. Polygenic risk scores (PRS) provide a personalized genetic susceptibility profile that may be leveraged for disease prediction. Using data from the UK Biobank (413,753 individuals; 22,755 incident cancer cases), we quantify the added predictive value of integrating cancer-specific PRS with family history and modifiable risk factors for 16 cancers. We show that incorporating PRS measurably improves prediction ...[more]
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Project description: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.
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