Decoding the glycoproteome of Alzheimer's disease by network-based glycoproteomics

Alzheimer's disease (AD) is the most common neurodegenerative disorder with no effective means of prevention or treatment, highlighting the need for novel biomarkers and therapeutic targets to improve AD diagnosis and treatment. Protein glycosylation plays critical roles in controlling brain function, but current knowledge of human brain glycoproteome and its alterations in AD is limited. To address the gap in knowledge, we established a network-based glycoproteomics approach that integrates intact glycopeptide-based quantitative glycoproteomics with network biology for large-scale, site-specific analysis of human brain glycoproteome and its changes in AD. We used this approach to analyze human brain tissue samples from neuropathologically confirmed AD cases and their age-matched controls and identified over 10,000 human brain N-glycoforms from nearly 1200 glycoproteins with 164 glycan compositions across more than 2500 in vivo N-glycosylation sites. Data-driven network analyses reveal previously unknown co-regulation relationships among different glycan modifications in human brain and highlights an involvement of glycan-specific elevations in oligomannosylation and paucimannosylation and reductions in sialylation and N-glycan branching in AD pathophysiology. Furthermore, network analyses show that human brain glycoproteome is organized into 21 modules of co-regulated protein glycoforms, 7 of which are associated with AD clinical phenotype, amyloid-b accumulation, and tau pathology. This study uncovers a number of dysregulated glycosylation-affected processes in AD, including altered cell adhesion, matrisome dysfunction, neuroinflammation, synaptic dysfunction, signaling dysregulation, endocytic trafficking alteration, and lysosomal dysfunction. Our findings provide mechanistic insights into AD pathogenesis and pave the way forward for developing glycosylation-based therapies and biomarkers to combat this devastating disease.