Systemic study of pathogenic pathways and interrelationships underlying genes associated with Alzheimer's disease (AD) facilitates the identification of new targets for effective treatments. Recently available large-scale multiomics datasets provide opportunities to use computational approaches for such studies. Here, we devised a novel disease gene identification (digID) computational framework that consists of a semi-supervised deep learning classifier to predict AD-associated genes and a protein–protein interaction (PPI) network-based analysis to prioritize the importance of these predicted genes in AD. digID predicted 1,529 AD-associated genes and revealed potentially new AD molecular mechanisms and therapeutic targets including GNAI1 and GNB1, two G-protein subunits that regulate cell signaling, and KNG1, an upstream modulator of CDC42 small G-protein signaling and mediator of inflammation and candidate coregulator of amyloid precursor protein (APP). Analysis of mRNA expression validated their dysregulation in AD brains but further revealed the significant spatial patterns in different brain regions as well as among different subregions of the frontal cortex and hippocampi. Super-resolution STochastic Optical Reconstruction Microscopy (STORM) further demonstrated their subcellular colocalization and molecular interactions with APP in a transgenic mouse model of both sexes with AD-like mutations. These studies support the predictions made by digID while highlighting the importance of concurrent biological validation of computationally identified gene clusters as potential new AD therapeutic targets.

对阿尔茨海默病 （AD） 相关基因的致病途径和相互关系的系统研究有助于确定有效治疗的新靶点。最近可用的大规模多组学数据集为使用计算方法进行此类研究提供了机会。在这里，我们设计了一种新的疾病基因鉴定 （digID） 计算框架，该框架包括一个半监督深度学习分类器，用于预测 AD 相关基因，以及一个基于蛋白质-蛋白质相互作用 （PPI） 网络的分析，以优先考虑这些预测基因在 AD 中的重要性。digID 预测了 1,529 个 AD 相关基因，并揭示了潜在的新 AD 分子机制和治疗靶点，包括 GNAI1 和 GNB1， 两个调节细胞信号传导的 G 蛋白亚基，以及 KNG1，CDC42 小 G 蛋白信号传导的上游调节剂和炎症介质，淀粉样蛋白前体蛋白 （APP） 的候选共调节因子。mRNA 表达分析验证了它们在 AD 大脑中的失调，但进一步揭示了不同大脑区域以及额叶皮层和海马的不同亚区域之间的显着空间模式。超分辨率随机光学重建显微镜 （STORM） 在具有 AD 样突变的两性转基因小鼠模型中进一步证明了它们与 APP 的亚细胞共定位和分子相互作用。这些研究支持 digID 的预测，同时强调了对计算确定的基因簇作为潜在的新 AD 治疗靶点进行同步生物学验证的重要性。