Polygenic Risk Score Improves Cataract Prediction in East Asian Population

doi:10.3390/biomedicines10081920

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Please use this identifier to cite or link to this item: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/123296

Title:	Polygenic Risk Score Improves Cataract Prediction in East Asian Population
Authors:	Hsu, Chih-Chien;Chuang, Hao-Kai;Hsiao, Yu-Jer;Teng, Yuan-Chi;Chiang, Pin-Hsuan;Wang, Yu-Jun;Lin, Ting-Yi;Tsai, Ping-Hsing;Weng, Chang-Chi;Lin, Tai-Chi;Hwang, De-Kuang;Hsieh, Ai-Ru
Keywords:	cataract;genome-wide association studies;polygenic risk score;Asian population;biobank;retrospective study
Date:	2022-08-08
Issue Date:	2023-04-28 17:33:43 (UTC+8)
Publisher:	MDPI AG
Abstract:	Cataracts, characterized by crystalline lens opacities in human eyes, is the leading cause of blindness globally. Due to its multifactorial complexity, the molecular mechanisms remain poorly understood. Larger cohorts of genome-wide association studies (GWAS) are needed to investigate cataracts’ genetic basis. In this study, a GWAS was performed on the largest Han population to date, analyzing a total of 7079 patients and 13,256 controls from the Taiwan Biobank (TWB) 2.0 cohort. Two cataract-associated SNPs with an adjustment of p < 1 × 10−7 in the older groups and nine SNPs with an adjustment of p < 1 × 10−6 in the younger group were identified. Except for the reported AGMO in animal models, most variations, including rs74774546 in GJA1 and rs237885 in OXTR, were not identified before this study. Furthermore, a polygenic risk score (PRS) was created for the young and old populations to identify high-risk cataract individuals, with areas under the receiver operating curve (AUROCs) of 0.829 and 0.785, respectively, after covariate adjustments. Younger individuals had 17.45 times the risk while older people had 10.97 times the risk when comparing individuals in the highest and lowest PRS quantiles. Validation analysis on an independent TWB1.0 cohort revealed AUROCs of 0.744 and 0.659.
Relation:	Biomedicines 10(8), 1920
DOI:	10.3390/biomedicines10081920
Appears in Collections:	[Graduate Institute & Department of Statistics] Journal Article

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