Abstract
Recent advances in multi-omics and spatial proteomics are reshaping our understanding of Alzheimer's disease. Guo et al.(1) applied integrative multi-omics to stratify mild cognitive impairment into biologically distinct subtypes with divergent progression trajectories: one metabolically impaired and slow-progressing, the other immune-activated and rapidly declining. Current techniques such as STC-DESI, LCM-MS, and machine learning enhance regional proteomic resolution, supporting biomarker discovery and spatially targeted interventions. This work exemplifies a broader shift toward precision medicine and a systems-level molecular framework in neurodegenerative disease research.