PROJECT SUMMARY Interactions between different biomolecules, including proteins, lipids and metabolites, give rise to higher cellular, tissue and organismal phenotypes and functions. Perturbation of these interaction networks is observed during aging and in age-related diseases and identification of these changes can help identify contributing mechanisms. This may be particularly valuable in case of complex diseases, such as late-onset Alzheimer’s Disease and Related Dementias (AD/ADRD), with multiple contributing factors over a life span. Biomolecule networks are affected not only by the overall abundance of individual components but also by their distribution between specific cell types and localization to intracellular compartments. Although snRNA-seq advances allow identification of cell-type specific gene expression patterns in many tissues including the brain, cell-type and organelle-specific proteomic, lipidomic and metabolomic assessments remain challenging. Additionally, integration of the various “omics” data and defining the influence of these changes on cellular, tissue and organismal function presents an ongoing challenge. This poses a limitation, as understanding of disease states requires consideration of interactions between different classes of biomolecules and associated pathways. To address these challenges, we propose to develop an analytical multi-omics pipeline to identify cell-type and organelle-specific functional relationships between different omics parameters and their effects on organellar, cellular, tissue and organismal function during brain aging and in age-related neurodegenerative disease. Consistent with their known contribution to brain aging and neurodegeneration, our initial focus will be on interactions between lipid and protein networks specifically in mitochondria. We will use transgenic reporter mice and optimize MS-based analytical approaches to determine cell-type (microglial and neuronal) specific changes in mitochondrial lipidome and proteome and their influence on mitochondrial function during brain aging (AIM 1). We will develop machine learning-based tools and workflows to allow integrated analysis of proteomic and lipidomic data to generate testable hypotheses about mechanisms contributing to aging and to identify potential novel intervention targets (AIM 2). Eventually the focus will be expanded to include other compartments (lysosomes and lipid droplets) relevant to brain aging and AD/ADRD (AIM 3). Once established, our multi-omics pipeline and tools will be made available to members of UMB, UMCP and other researchers interested in understanding brain aging, neurodegeneration and other age-related processes.