The Proteome-Wide Association Study (PWAS) is a protein-based genetic association approach designed to complement traditional variant-based methods like GWAS. PWAS operates in two stages: first, machine learning models predict the impact of genetic variants on protein-coding genes, generating effect scores. These scores are then aggregated into a gene-damaging score for each individual. This score is then used in case-control statistical tests to significantly link to specific phenotypes. PWAS Hub (v1.2) is a user-friendly platform that facilitates the exploration of gene-disease associations using clinical and genetic data from the UK Biobank (UKB), encompassing 500k individuals. PWAS Hub reports on 819 diseases and phenotypes determined by PheCode and ICD-10 clinical codes, each with a minimum of 400 affected individuals. PWAS-derived gene associations were reported for 72% of the tested phenotypes. The PWAS Hub also analyzes gene associations separately for males and females, considering sex-specific genetic effects, inheritance patterns (dominant and recessive), and gene pleiotropy. We illustrated the utility of the PWAS Hub for primary (essential) hypertension (I10), type 2 diabetes mellitus (E11), and specified haematuria (R31) that showed sex-dependent genetic signals. The PWAS Hub, available at pwas.huji.ac.il, is a valuable resource for studying genetic contributions to common diseases and sex-specific effects.

中文翻译：

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PWAS 中心：探索复杂疾病与性别依赖的基于基因的关联


蛋白质组范围关联研究 （PWAS） 是一种基于蛋白质的遗传关联方法，旨在补充 GWAS 等传统的基于变异的方法。PWAS 分两个阶段运行：首先，机器学习模型预测遗传变异对蛋白质编码基因的影响，生成效果评分。然后将这些分数汇总成每个人的基因损伤分数。然后将该分数用于病例对照统计测试，以显着链接到特定表型。PWAS Hub （v1.2） 是一个用户友好的平台，它使用来自英国生物样本库 （UKB） 的临床和遗传数据促进探索基因与疾病的关联，包括 500k 个体。PWAS Hub 报告了由 PheCode 和 ICD-10 临床代码确定的 819 种疾病和表型，每种疾病和表型至少有 400 名受影响的个体。据报道，72% 的测试表型存在 PWAS 衍生的基因关联。PWAS Hub 还分别分析男性和女性的基因关联，考虑性别特异性遗传效应、遗传模式（显性和隐性）和基因多效性。我们说明了 PWAS Hub 对显示性别依赖性遗传信号的原发性（原发性）高血压 （I10） 、2 型糖尿病 （E11） 和特定血尿 （R31） 的效用。pwas.huji.ac.il 提供的 PWAS Hub 是研究遗传对常见疾病和性别特异性影响的贡献的宝贵资源。