Multiple Single Nucleotide Polymorphism Testing Improves the Prediction of Diabetic Retinopathy Risk with Type 2 Diabetes Mellitus

Author:

Hsiao Yu-Ting,Shen Feng-Chih,Weng Shao-WenORCID,Wang Pei-WenORCID,Chen Yung-Jen,Lee Jong-JerORCID

Abstract

Diabetic retinopathy (DR) is one of the most frequent causes of irreversible blindness, thus prevention and early detection of DR is crucial. The purpose of this study is to identify genetic determinants of DR in individuals with type 2 diabetic mellitus (T2DM). A total of 551 T2DM patients (254 with DR, 297 without DR) were included in this cross-sectional research. Thirteen T2DM-related single nucleotide polymorphisms (SNPs) were utilized for constructing genetic risk prediction model. With logistic regression analysis, genetic variations of the FTO (rs8050136) and PSMD6 (rs831571) polymorphisms were independently associated with a higher risk of DR. The area under the curve (AUC) calculated on known nongenetic risk variables was 0.704. Based on the five SNPs with the highest odds ratio (OR), the combined nongenetic and genetic prediction model improved the AUC to 0.722. The discriminative accuracy of our 5-SNP combined risk prediction model increased in patients who had more severe microalbuminuria (AUC = 0.731) or poor glycemic control (AUC = 0.746). In conclusion, we found a novel association for increased risk of DR at two T2DM-associated genetic loci, FTO (rs8050136) and PSMD6 (rs831571). Our predictive risk model presents new insights in DR development, which may assist in enabling timely intervention in reducing blindness in diabetic patients.

Funder

Chang Gung Memorial Hospital

Publisher

MDPI AG

Subject

Medicine (miscellaneous)

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. The role of m6A and m6Am RNA modifications in the pathogenesis of diabetes mellitus;Frontiers in Endocrinology;2023-07-07

2. Deep Transfer Learning Methods for the Prediction of Diabetic Eye Disease: An Experimental Analysis;2023 3rd International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE);2023-05-12

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