Department of Bioengineering, Gebze Technical University, 41400, Gebze, Kocaeli, Turkey.
Mol Neurobiol. 2024 Apr;61(4):2120-2135. doi: 10.1007/s12035-023-03690-4. Epub 2023 Oct 19.
Alzheimer's disease (AD) is a highly heterogenous neurodegenerative disease, and several omic-based datasets were generated in the last decade from the patients with the disease. However, the vast majority of studies evaluate these datasets in bulk by considering all the patients as a single group, which obscures the molecular differences resulting from the heterogeneous nature of the disease. In this study, we adopted a personalized approach and analyzed the transcriptome data from 403 patients individually by mapping the data on a human protein-protein interaction network. Patient-specific subnetworks were discovered and analyzed in terms of the genes in the subnetworks, enriched functional terms, and known AD genes. We identified several affected pathways that could not be captured by the bulk comparison. We also showed that our personalized findings point to patterns of alterations consistent with the recently suggested AD subtypes.
阿尔茨海默病（AD）是一种高度异质性的神经退行性疾病，在过去十年中，已经从患者身上生成了多个基于组学的数据集。然而，绝大多数研究都是通过将所有患者视为一个单一的组来整体评估这些数据集，这掩盖了由于疾病的异质性而导致的分子差异。在这项研究中，我们采用了个性化的方法，通过将数据映射到人类蛋白质-蛋白质相互作用网络上来单独分析 403 名患者的转录组数据。我们根据子网络中的基因、富集的功能术语和已知的 AD 基因来发现和分析患者特异性的子网络。我们确定了几个受影响的途径，这些途径不能通过批量比较来捕捉。我们还表明，我们的个性化发现指向与最近提出的 AD 亚型一致的改变模式。
