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• W3010580919 endingPage "1703" @default.
• W3010580919 startingPage "1703" @default.
• W3010580919 abstract "Recent studies have led to considerable advances in the identification of genetic variants associated with type 1 and type 2 diabetes. An approach for converting genetic data into a predictive measure of disease susceptibility is to add the risk effects of loci into a polygenic risk score. In order to summarize the recent findings, we conducted a systematic review of studies comparing the accuracy of polygenic risk scores developed during the last two decades. We selected 15 risk scores from three databases (Scopus, Web of Science and PubMed) enrolled in this systematic review. We identified three polygenic risk scores that discriminate between type 1 diabetes patients and healthy people, one that discriminate between type 1 and type 2 diabetes, two that discriminate between type 1 and monogenic diabetes and nine polygenic risk scores that discriminate between type 2 diabetes patients and healthy people. Prediction accuracy of polygenic risk scores was assessed by comparing the area under the curve. The actual benefits, potential obstacles and possible solutions for the implementation of polygenic risk scores in clinical practice were also discussed. Develop strategies to establish the clinical validity of polygenic risk scores by creating a framework for the interpretation of findings and their translation into actual evidence, are the way to demonstrate their utility in medical practice." @default.
• W3010580919 created "2020-03-13" @default.
• W3010580919 creator A5008745221 @default.
• W3010580919 creator A5010519754 @default.
• W3010580919 creator A5052856867 @default.
• W3010580919 creator A5083598039 @default.
• W3010580919 date "2020-03-02" @default.
• W3010580919 modified "2023-10-10" @default.
• W3010580919 title "Systematic Review of Polygenic Risk Scores for Type 1 and Type 2 Diabetes" @default.
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