Defining lipid droplet homeostasis in Alzheimer's disease and aging with high molecular specificity using mass spectrometry imaging and isomer resolved lipidomics

SUMMARY Loss of healthspan - declining health and function as we age – impacts nearly every living organism and is a pronounced feature of Alzheimer’s disease and related dementias (ADRD), affecting nearly 6 million people in the United States. Lipids are poorly understood central components of aging, having roles in healthy aging and diseases of aging. The gap in lipid knowledge begins with a missing definition of ‘normal’ and extends to a lack of understanding surrounding lipid fluctuations throughout life. Lipid homeostasis is an important component of the healthy brain and both aging and multiple diseases are associated with alterations in lipid populations and lipid droplet (LD) volume and count. Dysregulated lipid homeostasis is linked to inflammation, diabetes, forms of liver failure, Gaucher disease, Parkinson’s disease, ADRD, and untold more pathologies. The failure to understand lipids in health and disease can be explained by a lack of adequate tools to study lipids. With the wide adoption of mass spectrometry tools, we recently entered the lipidomic era in which lipids can be characterized in fine structural detail across a range of lipid classes with spatial sensitivity and relative or absolute quantity. Spatial lipidomics using multimodal mass spectrometry imaging (MSI) produces regio-, cell-, and organelle-specific lipid maps and reveals changes in tissue sections even when traditional, extracted lipidomic studies fail to show changes. While progress has been made in spatial mapping of brain lipids in aging and AD, these studies were limited by scope (lacking total lipid coverage, spatial resolution, and structural specificity). Here, we will use leading edge high specificity and resolution spatial lipidomics to describe the most thorough spatial lipid survey of aging brains possible, to date, using a combinatorial approach. We will produce characteristic lipid fingerprints based on age, sex, disease state, and brain region. These lipid fingerprints will be supported with phenotypic data and spatial transcriptomic data. These end result will be an important resource for the aging and lipid research communities and will lead to new, translational therapeutic approaches.