PWAS (proteome-wide association study) is an innovative genetic association approach that complements widely used methods like GWAS (genome-wide association study). The PWAS approach involves consecutive phases. Initially, machine learning modeling and probabilistic considerations quantify the impact of genetic variants on protein-coding genes’ biochemical functions. Secondly, for each individual, aggregating the variants per gene determines a gene-damaging score. Finally, standard statistical tests are activated in the case-control setting to yield statistically significant genes per phenotype. The PWAS Hub offers a user-friendly interface for an in-depth exploration of gene–disease associations from the UK Biobank (UKB). Results from PWAS cover 99 common diseases and conditions, each with over 10,000 diagnosed individuals per phenotype. Users can explore genes associated with these diseases, with separate analyses conducted for males and females. For each phenotype, the analyses account for sex-based genetic effects, inheritance modes (dominant and recessive), and the pleiotropic nature of associated genes. The PWAS Hub showcases its usefulness for asthma by navigating through proteomic-genetic analyses. Inspecting PWAS asthma-listed genes (a total of 27) provide insights into the underlying cellular and molecular mechanisms. Comparison of PWAS-statistically significant genes for common diseases to the Open Targets benchmark shows partial but significant overlap in gene associations for most phenotypes. Graphical tools facilitate comparing genetic effects between PWAS and coding GWAS results, aiding in understanding the sex-specific genetic impact on common diseases. This adaptable platform is attractive to clinicians, researchers, and individuals interested in delving into gene–disease associations and sex-specific genetic effects.

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用于探索常见复杂疾病的基于基因的关联的 PWAS 中心


PWAS（全蛋白质组关联研究）是一种创新的遗传关联方法，是对 GWAS（全基因组关联研究）等广泛使用的方法的补充。PWAS 方法涉及连续阶段。最初，机器学习建模和概率考虑量化了遗传变异对蛋白质编码基因生化功能的影响。其次，对于每个个体，汇总每个基因的变异决定了基因损伤评分。最后，在病例对照设置中激活标准统计检验，以产生每个表型具有统计学意义的基因。PWAS Hub 提供了一个用户友好的界面，用于深入探索来自英国生物样本库 （UKB） 的基因-疾病关联。PWAS 的结果涵盖 99 种常见疾病和病症，每种病症和病症每种表型有超过 10,000 个诊断个体。用户可以探索与这些疾病相关的基因，并对男性和女性进行单独分析。对于每种表型，分析考虑了基于性别的遗传效应、遗传模式（显性和隐性）以及相关基因的多效性。PWAS Hub 通过浏览蛋白质组学遗传学分析来展示其对哮喘的有用性。检查 PWAS 哮喘列出的基因（总共 27 个）可以深入了解潜在的细胞和分子机制。将常见疾病的 PWAS 具有统计学意义的基因与 Open Targets 基准进行比较，显示大多数表型的基因关联部分但显着重叠。图形工具有助于比较 PWAS 之间的遗传效应和编码 GWAS 结果，有助于了解性别特异性遗传对常见疾病的影响。 这个适应性强的平台对临床医生、研究人员和有兴趣深入研究基因-疾病关联和性别特异性遗传效应的个人很有吸引力。