Germline disease-causing variants are generally more spatially clustered in protein 3-dimensional structures than benign variants. Motivated by this tendency, we develop a fast and powerful protein-structure-based scan (PSCAN) approach for evaluating gene-level associations with complex disease and detecting signal variants. We validate PSCAN’s performance on synthetic data and two real data sets for lipid traits and Alzheimer’s disease. Our results demonstrate that PSCAN performs competitively with existing gene-level tests while increasing power and identifying more specific signal variant sets. Furthermore, PSCAN enables generation of hypotheses about the molecular basis for the associations in the context of protein structures and functional domains.

中文翻译：

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PSCAN：蛋白质结构引导的空间扫描测试改善复杂疾病基因发现和信号变异检测


与良性变异相比，种系致病变异通常在蛋白质 3 维结构中在空间上更加聚集。受这种趋势的推动，我们开发了一种快速而强大的基于蛋白质结构的扫描（PSCAN）方法，用于评估基因水平与复杂疾病的关联并检测信号变异。我们验证了 PSCAN 在合成数据和脂质特征和阿尔茨海默氏病的两个真实数据集上的性能。我们的结果表明，PSCAN 与现有基因水平测试相比具有竞争力，同时提高了功效并识别更具体的信号变异集。此外，PSCAN 能够生成有关蛋白质结构和功能域背景下关联的分子基础的假设。