Molecular subtyping of Alzheimer's disease using balanced integrative multi‐omics, deep learning, and multi‐scale network models

The proposed multi-omics integration methodology provides a robust framework for patient stratification and disease subtyping in AD. By integrating transcriptomics, proteomics, and metabolomics data with the multi-scale AD atlas network, we identify patient groups with shared disease-relevant clinical parameters, advancing our understanding of the molecular heterogeneity and respective subtype-specific manifestations of Alzheimer's disease.