Multi-trait Polygenic Probability Risk Score Enhances Glaucoma Prediction Across Ancestries.

Xiaoyi Raymond Gao
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Abstract

Primary open-angle glaucoma (POAG) remains the leading cause of irreversible blindness worldwide, with early detection crucial for preventing vision loss. However, current risk assessment methods have limited predictive power. Here, we present a multi-trait polygenic probability risk score (PPRS) approach that integrates multiple glaucoma-related traits and leverages functional genomic annotations to enhance POAG prediction across diverse ancestries. We constructed PRSs for POAG, intraocular pressure (IOP), vertical cup-to-disc ratio (VCDR), and retinal nerve fiber layer (RNFL) thickness using extensive genomic coverage (>7 million variants) and 96 functional annotations through the SBayesRC method. Validation in the UK Biobank (n=324,713, European ancestry) and Mexican American Glaucoma Genetic Study (MAGGS, n=4,549, Latino ancestry) demonstrated significant improvements in predictive accuracy over conventional approaches. Our multi-trait PPRS achieved area under the curve (AUC) values of 0.814 in Europeans and 0.801 in Latinos, compared to AUC ≤0.79 for single-trait models. We identified ancestry-specific differences in genetic contributions, with IOP demonstrating the strongest association in Europeans (OR=1.63, P = 5.37 × 10 -89 ), while VCDR was predominant in Latinos (OR=1.64, P = 2.04 × 10 - 11 ). The model achieved remarkable risk stratification, with the highest PPRS decile showing 80.2-fold and 51.1-fold increased POAG risk in Europeans and Latinos, respectively, compared to the lowest decile. Importantly, the top PPRS quintile captured 65.9% and 62.2% of POAG cases in Europeans and Latinos, substantially improving upon previous approaches. Our findings demonstrate that integrating multiple disease-relevant traits and functional annotations significantly enhances polygenic prediction of POAG across diverse populations, with significant implications for targeted screening, early intervention, and reduction of disease burden.

多性状多基因概率风险评分增强青光眼预测。
原发性开角型青光眼(POAG)仍然是世界范围内不可逆失明的主要原因,早期发现对于预防视力丧失至关重要。然而,现有的风险评估方法预测能力有限。在这里,我们提出了一种多性状多基因概率风险评分(PPRS)方法,该方法整合了多个青光眼相关性状,并利用功能基因组注释来增强不同祖先的POAG预测。我们通过SBayesRC方法构建了POAG,眼压(IOP),垂直杯盘比(VCDR)和视网膜神经纤维层(RNFL)厚度的prs,使用广泛的基因组覆盖(bb70万个变体)和96个功能注释。在英国生物银行(n=324,713,欧洲血统)和墨西哥裔美国人青光眼遗传研究(MAGGS, n=4,549,拉丁裔血统)的验证表明,与传统方法相比,预测准确性有显著提高。我们的多性状PPRS在欧洲人和拉丁美洲人的曲线下面积(AUC)分别为0.814和0.801,而单性状模型的AUC≤0.79。我们确定了遗传贡献的谱系特异性差异,IOP在欧洲人中表现出最强的相关性(OR=1.63, P = 5.37 × 10 -89),而VCDR在拉丁美洲人中表现出优势(OR=1.64, P = 2.04 × 10 - 11)。该模型实现了显著的风险分层,与最低十分位数相比,最高PPRS十分位数的欧洲人和拉丁美洲人的POAG风险分别增加了80.2倍和51.1倍。重要的是,在欧洲和拉丁美洲,前五分之一的PPRS患者分别获得了65.9%和62.2%的POAG病例,大大改善了以前的方法。我们的研究结果表明,整合多种疾病相关特征和功能注释可显著增强POAG在不同人群中的多基因预测,对靶向筛查、早期干预和减轻疾病负担具有重要意义。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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