Systematic Review of Polygenic Risk Scores for Type 1 and Type 2 Diabetes

International Journal of Molecular Sciences
Felipe Padilla-MartínezAdam Kretowski

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...Continue Reading

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Citations

Jan 20, 2021·Journal of Medical Ethics·Sarah Munday, Julian Savulescu
Mar 7, 2021·Journal of Personalized Medicine·Deborah TraversiStefania Boccia
Jul 3, 2021·Journal of Personalized Medicine·Avigail MoldovanMichal Linial
Aug 28, 2021·Seminars in Cell & Developmental Biology·Tayaza FadasonWilliam Schierding
Nov 10, 2021·Current Sports Medicine Reports·Anthony J GriswoldThomas M Best

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Methods Mentioned

BETA
genotyping

Software Mentioned

Scopus

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