Metabolomics Technologies for Defining Diet Influences on Brain Metabolome and in Alzheimer’s Disease

Abstract

AbstractBackgroundDiet and our gut microbiota influence brain function. This is also true in Alzheimer’s disease. Technologies are emerging to inventory the complexity of the gut microbiome produced chemicals and also the complexity of chemicals released in the body from types of food we ingest. Many of these chemicals can cross blood brain barrier and can impact brain function.MethodIn this presentation, we will describe new technologies that enable us to understand the true diversity and complexities of the small molecules that can be detected using an MS/MS‐based untargeted metabolomics platform. Strategies, such as MASST, FoodMASST, and reference data‐driven metabolomics that enable an empirical readout of diet effects on metabolic profiles of AD patients will be discussed (Figure 1a).ResultThese new computational strategies provide a direct roadmap to relate diet, and diet ingredients, to clinical phenotypes such as empirical readout of variability of diet composition (Figure 1b), and how machine learning strategies, such as regression analysis, are employed to understand how the diet readouts relate to microbiome composition, cognition, and memory function from analysis of Alzheimer’s cohorts (Figure 1c). We will describe the influences of diet on brain metabolome in AD patients and links to imaging changes.ConclusionWe have developed a new metabolomics approach that can provide an empirical, and even retrospective, diet readout form clinical samples of AD patients. We illustrate how diet components relate to clinical symptoms in AD.