Large-scale, case-control genome-wide association studies (GWASs) have revealed genetic variations associated with diverse neurological and psychiatric disorders. Recent advances in neuroimaging and genomic databases of large healthy and diseased cohorts have empowered studies to characterize effects of the discovered genetic factors on brain structure and function, implicating neural pathways and genetic mechanisms in the underlying biology. However, the unprecedented scale and complexity of the imaging and genomic data requires new advanced biomedical data science tools to manage, process and analyze the data. In this work, we introduce Neuroimaging PheWAS (phenome-wide association study): a web-based system for searching over a wide variety of brain-wide imaging phenotypes to discover true system-level gene-brain relationships using a unified genotype-to-phenotype strategy. This design features a user-friendly graphical user interface (GUI) for anonymous data uploading, study definition and management, and interactive result visualizations as well as a cloud-based computational infrastructure and multiple state-of-art methods for statistical association analysis and multiple comparison correction. We demonstrated the potential of Neuroimaging PheWAS with a case study analyzing the influences of the apolipoprotein E (APOE) gene on various brain morphological properties across the brain in the Alzheimer’s Disease Neuroimaging Initiative (ADNI) cohort. Benchmark tests were performed to evaluate the system’s performance using data from UK Biobank. The Neuroimaging PheWAS system is freely available. It simplifies the execution of PheWAS on neuroimaging data and provides an opportunity for imaging genetics studies to elucidate routes at play for specific genetic variants on diseases in the context of detailed imaging phenotypic data.

大规模病例对照全基因组关联研究 (GWAS) 揭示了与多种神经和精神疾病相关的遗传变异。大型健康和患病队列的神经影像学和基因组数据库的最新进展使研究能够表征已发现的遗传因素对大脑结构和功能的影响，并在基础生物学中暗示神经通路和遗传机制。然而，成像和基因组数据前所未有的规模和复杂性需要新的先进生物医学数据科学工具来管理、处理和分析数据。在这项工作中，我们介绍了神经影像学 PheWAS（全现象关联研究）：一个基于网络的系统，用于搜索各种全脑成像表型，以使用统一的基因型到表型策略发现真正的系统级基因-大脑关系。该设计具有用户友好的图形用户界面 (GUI)，用于匿名数据上传、研究定义和管理以及交互式结果可视化，以及基于云的计算基础设施和多种最先进的统计关联分析方法和多种比较修正。我们通过案例研究展示了神经影像学 PheWAS 的潜力，该案例研究分析了载脂蛋白 E (APOE) 基因对阿尔茨海默病神经影像学倡议 (ADNI) 队列中各种大脑形态学特性的影响。使用来自 UK Biobank 的数据进行基准测试以评估系统的性能。Neuroimaging PheWAS 系统是免费提供的。它简化了 PheWAS 在神经影像数据上的执行，并为影像遗传学研究提供了一个机会，以在详细的影像表型数据的背景下阐明疾病特定遗传变异的作用途径。