Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, Houston, TX 77030, USA.
Center for Precision Health, School of Biomedical Informatics, Houston, TX 77030, USA.
Hum Mol Genet. 2022 Sep 29;31(19):3341-3354. doi: 10.1093/hmg/ddac124.
Genome-wide association studies (GWAS) have identified more than 75 genetic variants associated with Alzheimer's disease (ad). However, how these variants function and impact protein expression in brain regions remain elusive. Large-scale proteomic datasets of ad postmortem brain tissues have become available recently. In this study, we used these datasets to investigate brain region-specific molecular pathways underlying ad pathogenesis and explore their potential drug targets. We applied our new network-based tool, Edge-Weighted Dense Module Search of GWAS (EW_dmGWAS), to integrate ad GWAS statistics of 472 868 individuals with proteomic profiles from two brain regions from two large-scale ad cohorts [parahippocampal gyrus (PHG), sample size n = 190; dorsolateral prefrontal cortex (DLPFC), n = 192]. The resulting network modules were evaluated using a scale-free network index, followed by a cross-region consistency evaluation. Our EW_dmGWAS analyses prioritized 52 top module genes (TMGs) specific in PHG and 58 TMGs in DLPFC, of which four genes (CLU, PICALM, PRRC2A and NDUFS3) overlapped. Those four genes were significantly associated with ad (GWAS gene-level false discovery rate < 0.05). To explore the impact of these genetic components on TMGs, we further examined their differentially co-expressed genes at the proteomic level and compared them with investigational drug targets. We pinpointed three potential drug target genes, APP, SNCA and VCAM1, specifically in PHG. Gene set enrichment analyses of TMGs in PHG and DLPFC revealed region-specific biological processes, tissue-cell type signatures and enriched drug signatures, suggesting potential region-specific drug repurposing targets for ad.
全基因组关联研究（GWAS）已经确定了 75 种以上与阿尔茨海默病（AD）相关的遗传变异。然而，这些变异如何在大脑区域发挥作用并影响蛋白质表达仍然难以捉摸。最近，AD 死后脑组织的大型蛋白质组数据集已经可用。在这项研究中，我们使用这些数据集来研究 AD 发病机制背后的大脑区域特异性分子途径，并探索其潜在的药物靶点。我们应用了我们新的基于网络的工具，即 GWAS 的边缘加权密集模块搜索（EW_dmGWAS），将 472868 名个体的 AD GWAS 统计数据与来自两个大型 AD 队列的两个大脑区域的蛋白质组谱[海马旁回（PHG），样本量 n=190；背外侧前额叶皮层（DLPFC），n=192]进行整合。使用无标度网络指数评估所得网络模块，然后进行跨区域一致性评估。我们的 EW_dmGWAS 分析优先考虑了 52 个在 PHG 中特异性的顶级模块基因（TMG）和 58 个在 DLPFC 中的 TMG，其中 4 个基因（CLU、PICALM、PRRC2A 和 NDUFS3）重叠。这四个基因与 AD 显著相关（GWAS 基因水平假发现率<0.05）。为了探索这些遗传成分对 TMG 的影响，我们进一步在蛋白质组水平上检查了它们差异共表达的基因，并将其与研究药物靶点进行了比较。我们在 PHG 中确定了三个潜在的药物靶点基因，即 APP、SNCA 和 VCAM1。PHG 和 DLPFC 的 TMG 基因集富集分析揭示了区域特异性的生物学过程、组织-细胞类型特征和丰富的药物特征，这表明 AD 可能存在区域特异性药物再利用靶点。
