AI Article Synopsis
- Alzheimer’s disease is complex and varies significantly among patients, making it hard to study with traditional methods that lump everyone together.
- The study used a personalized approach to analyze transcriptome data from 403 individual AD patients and mapped this data onto a human protein-protein interaction network.
- This individualized analysis revealed specific patient subnetworks and affected pathways that might align with new subtypes of Alzheimer’s, highlighting the importance of considering individual molecular differences in research.
Article Abstract
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.
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| http://dx.doi.org/10.1007/s12035-023-03690-4 | DOI Listing |
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