Department of Medical Research, Taipei Veterans General Hospital, Taipei, Taiwan.
College of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan.
Transl Vis Sci Technol. 2024 May 1;13(5):13. doi: 10.1167/tvst.13.5.13.
The purpose of this study was to conduct a large-scale genome-wide association study (GWAS) and construct a polygenic risk score (PRS) for risk stratification in patients with dry eye disease (DED) using the Taiwan Biobank (TWB) databases.
This retrospective case-control study involved 40,112 subjects of Han Chinese ancestry, sourced from the publicly available TWB. Cases were patients with DED (n = 14,185), and controls were individuals without DED (n = 25,927). The patients with DED were further divided into 8072 young (<60 years old) and 6113 old participants (≥60 years old). Using PLINK (version 1.9) software, quality control was carried out, followed by logistic regression analysis with adjustments for sex, age, body mass index, depression, and manic episodes as covariates. We also built PRS prediction models using the standard clumping and thresholding method and evaluated their performance (area under the curve [AUC]) through five-fold cross-validation.
Eleven independent risk loci were identified for these patients with DED at the genome-wide significance levels, including DNAJB6, MAML3, LINC02267, DCHS1, SIRPB3P, HULC, MUC16, GAS2L3, and ZFPM2. Among these, MUC16 encodes mucin family protein. The PRS model incorporated 932 and 740 genetic loci for young and old populations, respectively. A higher PRS score indicated a greater DED risk, with the top 5% of PRS individuals having a 10-fold higher risk. After integrating these covariates into the PRS model, the area under the receiver operating curve (AUROC) increased from 0.509 and 0.537 to 0.600 and 0.648 for young and old populations, respectively, demonstrating the genetic-environmental interaction.
Our study prompts potential candidates for the mechanism of DED and paves the way for more personalized medication in the future.
Our study identified genes related to DED and constructed a PRS model to improve DED prediction.
本研究旨在利用台湾生物银行（TWB）数据库进行大规模全基因组关联研究（GWAS），并构建多基因风险评分（PRS）以对干眼病（DED）患者进行风险分层。
这是一项回顾性病例对照研究，共纳入 40112 名汉族血统的受试者，数据来源于公开的 TWB。病例为 DED 患者（n=14185），对照为无 DED 个体（n=25927）。DED 患者进一步分为 8072 名年龄<60 岁的年轻患者和 6113 名年龄≥60 岁的老年患者。使用 PLINK（版本 1.9）软件进行质量控制，然后进行逻辑回归分析，并调整性别、年龄、体重指数、抑郁和躁狂发作作为协变量。我们还使用标准聚类和阈值方法构建了 PRS 预测模型，并通过五折交叉验证评估了它们的性能（曲线下面积[AUC]）。
在全基因组显著水平上，共鉴定出 11 个与这些 DED 患者相关的独立风险位点，包括 DNAJB6、MAML3、LINC02267、DCHS1、SIRPB3P、HULC、MUC16、GAS2L3 和 ZFPM2。其中，MUC16 编码黏蛋白家族蛋白。PRS 模型分别纳入了年轻和老年人群的 932 个和 740 个遗传位点。较高的 PRS 评分表明 DED 风险增加，PRS 评分最高的 5%个体的风险增加了 10 倍。将这些协变量纳入 PRS 模型后，年轻和老年人群的受体操作曲线（AUROC）下面积分别从 0.509 和 0.537 增加到 0.600 和 0.648，表明遗传-环境相互作用。
我们的研究提示了 DED 发病机制的潜在候选基因，并为未来更个性化的药物治疗铺平了道路。
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