State-of-the-art rare variant association testing methods aggregate the contribution of rare variants in biologically relevant genomic regions to boost statistical power. However, testing single genes separately does not consider the complex interaction landscape of genes, nor the downstream effects of non-synonymous variants on protein structure and function. Here we present the NETwork Propagation-based Assessment of Genetic Events (NETPAGE), an integrative approach aimed at investigating the biological pathways through which rare variation results in complex disease phenotypes. We applied NETPAGE to sporadic, late-onset Alzheimer’s disease (AD), using whole-genome sequencing from the AD Neuroimaging Initiative (ADNI) cohort, as well as whole-exome sequencing from the AD Sequencing Project (ADSP). NETPAGE is based on network propagation, a framework that models information flow on a graph and simulates the percolation of genetic variation through tissue-specific gene interaction networks. The result of network propagation is a set of smoothed gene scores that can be tested for association with disease status through sparse regression. The application of NETPAGE to AD enabled the identification of a set of connected genes whose smoothed variation profile was robustly associated to case-control status, based on gene interactions in the hippocampus. Additionally, smoothed scores significantly correlated with risk of conversion to AD in Mild Cognitive Impairment (MCI) subjects. Lastly, we investigated tissue-specific transcriptional dysregulation of the core genes in two independent RNA-seq datasets, as well as significant enrichments in terms of gene sets with known connections to AD. We present a framework that enables enhanced genetic association testing for a wide range of traits, diseases, and sample sizes.

最先进的罕见变异关联测试方法汇总了生物相关基因组区域中罕见变异的贡献，以提高统计能力。然而，单独测试单个基因没有考虑基因的复杂相互作用，也没有考虑非同义变异对蛋白质结构和功能的下游影响。在这里，我们介绍了基于网络传播的遗传事件评估 (NETPAGE)，这是一种综合方法，旨在研究罕见变异导致复杂疾病表型的生物学途径。我们使用来自 AD Neuroimaging Initiative (ADNI) 队列的全基因组测序以及来自 AD Sequencing Project (ADSP) 的全外显子组测序，将 NETPAGE 应用于散发性、迟发性阿尔茨海默病 (AD)。NETPAGE基于网络传播，一种在图上模拟信息流并通过组织特异性基因相互作用网络模拟遗传变异渗透的框架。网络传播的结果是一组平滑的基因评分，可以通过稀疏回归测试与疾病状态的关联。基于海马体中的基因相互作用，NETPAGE 在 AD 中的应用能够识别一组连接的基因，这些基因的平滑变异特征与病例对照状态密切相关。此外，平滑的分数与轻度认知障碍 (MCI) 受试者转换为 AD 的风险显着相关。最后，我们研究了两个独立的 RNA-seq 数据集中核心基因的组织特异性转录失调，以及已知与 AD 相关的基因集的显着富集。我们提出了一个框架，可以对各种性状、疾病和样本量进行增强的遗传关联测试。