Alzheimer’s disease (AD) is the leading cause of aging-related cognitive decline, affecting more than 5 million Americans over 65 years old, and the number of patients is expected to climb to 13 million as baby boomers age. Our ability to learn and remember declines with age due to progressive changes in synaptic connectivity and function. Synaptic abnormalities also commonly precede neuronal loss during early stages of Alzheimer’s disease (AD) and other neurodegenerative disorders. However, we are only beginning to understand the full spectrum of these abnormalities, their contributions to cognitive decline, and the underlying mechanisms. This challenge is largely attributed to the complexity of the brain and etiologies of aging and neurodegeneration. Hallmarks of advanced Alzheimer’s disease (AD) include accumulations of extracellular amyloid peptides and intracellular hyperphosphorylated tau protein as well as chronic neuroinflammation. While genes for familial AD have been identified, which shed substantial light on the etiology of the disease, the mechanisms behind sporadic onset AD still remain a mystery. While studies of transcriptional dynamics in the brain have been transformative, transcriptional dynamics do not correlate well with protein dynamics because protein synthesis, turnover and subcellular localization are more tightly regulated spatially and temporally than transcription. Studies have suggested that proteostasis declines with age, impairing cells from managing the inevitable misfolding of proteins. Our team will study protein dynamics in animal models based on bio-orthogonal non-canonical amino acid (BONCAT) protein labeling. These methods allow us to measure dynamics in protein synthesis and degradation in specific brain cell types relevant to AD. These measurements will provide new information about the disruption of normal cellular processes. The overreaching goal of our collaborative proposal is to bridge critical gaps in knowledge by leveraging the state-of-the-art methods for bio-orthogonal non-canonical amino acid tagging (BONCAT) and quantitative mass spectrometry (MS) to identify brain cell-type contributions to synaptic and neuronal decline associated with AD.