A hallmark of amyloid disorders, such as Alzheimer's disease, is aggregation of secreted proteins. However it is largely unclear how the hundreds of secretory pathway proteins contribute to amyloid formation. We developed a systems biology framework that integrates expression data with protein-protein interaction networks to successfully estimate a tissue's fitness for producing specific secreted proteins. Using this framework, we analyzed the fitness of the secretory pathway of various brain regions and cell types for synthesizing the Alzheimer's disease-associated amyloid-precursor protein (APP). While none of the key amyloidogenic pathway components were differentially expressed in AD brain, we found the deposition of Aβ is associated with repressed expression of the secretory pathway components proximal to APP. Concurrently, we detected systemic up-regulation of the secretory pathway components proximal to β- and γ-secretases in AD brains. Our analyses suggest that perturbations from 3 high confidence AD risk genes cascade through the secretory machinery support network for APP and into the endocytosis pathway. Thus, we present a model where amyloidogenesis is associated with dysregulation of dozens of secretory pathway components supporting APP, which could yield novel therapeutic targets for the treatment of AD.

中文翻译：

---

分泌途径的失调将阿尔茨海默氏病的遗传学联系到聚集体的形成

淀粉样变性疾病（例如阿尔茨海默氏病）的标志是分泌蛋白的聚集。然而，目前尚不清楚数百种分泌途径蛋白如何促进淀粉样蛋白的形成。我们开发了一个系统生物学框架，该框架将表达数据与蛋白质-蛋白质相互作用网络相集成，以成功地估计组织产生特定分泌蛋白质的适应性。使用此框架，我们分析了各种大脑区域和细胞类型的分泌途径的适应性，以合成与阿尔茨海默氏病相关的淀粉样前体蛋白（APP）。尽管AD脑中没有关键的淀粉样蛋白生成途径成分差异表达，但我们发现Aβ的沉积与APP旁分泌途径成分的表达受抑制有关。同时，我们在AD脑中检测到β-和γ-分泌酶附近的分泌途径成分的系统上调。我们的分析表明，来自3个高置信度AD风险基因的扰动通过APP的分泌机制支持网络级联并进入胞吞途径。因此，我们提出了一个模型，其中淀粉样蛋白生成与支持APP的数十种分泌途径组分的失调有关，这可能产生用于治疗AD的新型治疗靶标。