An Improved Genome-Wide Polygenic Score Model for Predicting the Risk of Type 2 Diabetes

Abstract

Polygenic risk score (PRS) has been shown to be predictive of disease risk such as type 2 diabetes (T2D). However, the existing studies on genetic prediction for T2D only had limited predictive power. To further improve the predictive capability of the PRS model in identifying individuals at high T2D risk, we proposed a new three-step filtering procedure, which aimed to include truly predictive single-nucleotide polymorphisms (SNPs) and avoid unpredictive ones into PRS model. First, we filtered SNPs according to the marginal association p-values (p≤ 5× 10−2) from large-scale genome-wide association studies. Second, we set linkage disequilibrium (LD) pruning thresholds (r2) as 0.2, 0.4, 0.6, and 0.8. Third, we set p-value thresholds as 5× 10−2, 5× 10−4, 5× 10−6, and 5× 10−8. Then, we constructed and tested multiple candidate PRS models obtained by the PRSice-2 software among 182,422 individuals in the UK Biobank (UKB) testing dataset. We validated the predictive capability of the optimal PRS model that was chosen from the testing process in identifying individuals at high T2D risk based on the UKB validation dataset (n = 274,029). The prediction accuracy of the PRS model evaluated by the adjusted area under the receiver operating characteristics curve (AUC) showed that our PRS model had good prediction performance [AUC = 0.795, 95% confidence interval (CI): (0.790, 0.800)]. Specifically, our PRS model identified 30, 12, and 7% of the population at greater than five-, six-, and seven-fold risk for T2D, respectively. After adjusting for sex, age, physical measurements, and clinical factors, the AUC increased to 0.901 [95% CI: (0.897, 0.904)]. Therefore, our PRS model could be useful for population-level preventive T2D screening.

Polygenic risk scores of endo-phenotypes identify the effect of genetic background in congenital heart disease

“…Interest in PRS to assess clinical risk for complex disorders has gained traction over the past several years, with PRSs having been developed for cancer risk, 70 , 71 , 72 CAD, 22 and diabetes. 22 , 73 One area that has had limited uptake of PRSs is a field that has a long history of genetic and genomic testing for rare congenital syndromes: clinical genetics. The classic population in medical genetics has been children with rare, phenotypically classifiable, genetic syndromes caused by single-gene mutations.…”

Body Mass Index and Birth Weight Improve Polygenic Risk Score for Type 2 Diabetes

“…Another study on CAD, T2D, atrial fibrillation, breast and prostate cancer found that PRS improved the prediction power of such predictors [ 36 ]. Similarly, augmenting PRS with additional information such as BMI, and lab results such as HDL and LDL measures improved prediction power for T2D [ 37 ]. Similarly, augmenting PRS by traditional measures for cardiovascular disease risk modestly enhanced its prediction power [ 38 ].…”

From biobanking to personalized prevention of obesity, diabetes and metabolic syndrome

“…При помощи ШГР оценивалось влияние генетической предрасположенности к ожирению на продолжительность жизни. Интересно, что высокие показатели ШГР ожирения имели значительное влия-ШГР СД [31]. Анализ генетических данных 274029 участников показал, что тщательный отбор ВНП позволяет разрабатывать шкалы риска, которые обладают достоверной прогностической цен ностью (площадь под кривой (AUC)=0,795; 95% ДИ: 0,790-0,800).…”