Alzheimer’s disease (AD) is an incurable age-related progressive neurodegenerative disorder. Currently, molecular mechanisms underlying memory loss and cognitive defects caused by AD remain elusive. Systematic characterization of the central nervous system (CNS) is essential to understanding neurodegenerative disorders. However, detailed analysis of neuronal networks remains extremely challenging due to the enormous complexity of the human brain, which is comprised of nearly a hundred billion neurons that interconnect to form an exceedingly intricate and delicate neuronal circuitry. While current MS-based proteomics approaches have enabled global profiling of proteomes and posttranslational modifications in human brains, our understanding of the dynamic and functional organization and regulation of neuronal networks associated with AD remains very limited. Therefore, there is an urgent need to define the molecular networks associated with AD to advance our understanding of its pathobiology. Protein-protein interactions (PPIs) are fundamental to the formation of protein complexes and crucial for orchestrating a diverse array of pathways in regulating cellular activities. Aberrant PPIs have been associated with AD and other neurodegenerative disorders, however, molecular alterations in protein complexes and network pathways specific to AD development have not been well explored. Therefore, systems-wide profiling of interaction landscapes of protein complexes in healthy and diseased states is crucial for a deeper understanding of neurobiology and neuropathology, and ultimately the discovery of novel interaction-based diagnostics and therapeutics. In this supplement, we propose to employ cross-linking mass spectrometry (XL-MS) technologies to dissect protein interaction landscapes in brain tissues of AD models and patient samples to allow us to unravel neuronal networks with PPI identities and contact sites for the first time. The molecular details determined by our novel XL-MS technology will undoubtedly provide unique insights that cannot be easily revealed by other approaches. The results will allow us to define protein modules and networks associated with AD and thus uncover new molecular details underlying the pathophysiological mechanisms of AD.