Abstract
SummaryThe molecular correlates of Alzheimer’s disease (AD) are increasingly being defined by multi-omics. However, findings from different data types are often difficult to reconcile. Here, we apply a data-driven multi-omics framework integrating seven omics layers from up to 1,358 aged human brain samples from the Religious Orders Study and Rush Memory and Aging Project. We demonstrate sprawling cross-omics biological factors relating to AD phenotypes. The strongest AD-associated factor (factor 8) is characterized by elevated immune activity at the epigenetic level, decreased heat shock gene expression in the transcriptome, and disrupted energy metabolism and cytoskeletal dynamics in the proteome. Unsupervised clustering reveals 11 molecular subtypes, including three AD-associated clusters displaying distinct molecular signatures and phenotypic characteristics. Our findings provide a comprehensive map of molecular mechanisms underlying AD heterogeneity, highlighting neuroinflammatory processes and yielding potential biomarkers and therapeutic targets for precision medicine approaches.
| Original language | English |
|---|---|
| Article number | 117235 |
| Journal | Cell Reports |
| Volume | 45 |
| Issue number | 4 |
| DOIs | |
| State | Published - 28 Apr 2026 |
| Externally published | Yes |
Keywords
- Alzheimer’s disease
- MOFA
- biomarkers
- molecular subtypes
- multi-omics integration
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