Integrative machine learning reveals telomere-associated gene modules reflecting neuronal dysregulation in Alzheimer's disease.

In GSE5281 hippocampus, RMA + age-adjusted limma identified 38 AD-associated telomere genes (FDR<0.05).

Ward clustering (silhouette) defined two modules, summarized as eigengenes (module PC1).

Robustness used 500-bootstrap stability; hub genes from the dominant module were interpreted with BRETIGEA and Reactome/GO enrichment.

With only two module features, models achieved ROC-AUC 0.722-0.780 internally and 0.689-0.695 externally.