Significant resources on age-related neurodegeneration are directed toward animal research in the assumption that results will inform our understanding of parallel processes in human. Yet, no reliable method exists to accurately translate cerebral blood flow or metabolic data from animal to human. For lack of rigorous mathematical methods for associating cerebral metabolic parameters between species, correlation of valuable data from mouse to human remains guesswork. There is a need for a predictive computational framework that quantifies cerebral blood flow and metabolism in normal and diseased brain states. Our long term goal is that mechanistic models of animal data that are precisely scaled to human brain metabolism will enable rational development of therapies that will ameliorate the effects of aging, especially Alzheimer?s and dementia. The objective is to identify structural and functional modifications in the micro-angioarchitecture that cause age- related decline in brain health. The central hypothesis is that structural and functional changes to the cerebral microcirculation are major physical factors in reduced perfusion, loss of vascular reserve, and diminished oxygen extraction, eventually leading to age-induced cognitive decline. The central hypothesis will be tested by pursuing three specific aims:
Aim 1) Characterize the effect of aging and Alzheimer?s disease on brain metabolic function in mouse. We will validate a mechanistic model of cerebral circulation in mouse to determine the effect of structural changes on perfusion and oxygen extraction in the aged rodent brain.
Aim 2) Create in-silico models of cerebral blood flow and metabolism in the human brain predictive of normative and unhealthy aging. We will create an anatomically detailed mechanistic model of cerebral circulation in human to predict the effect of structural changes on perfusion and oxygen extraction. The model will enable prospective simulation of age-related changes that are expected to occur in the human angioarchitecture based on scaled observations in mouse.
Aim 3) Quantify age-related changes in cerebral blood flow and metabolism in human brain to refine and validate in silico mechanistic modeling. To validate the mechanistic translation from mouse to human, we will measure age-related metabolic functions in cohorts of aged and Alzheimer patients. We will identify imaging biomarkers for morphometric changes in imaging data that correlate with cognitive decline. The research is significant because it will establish a novel scientific method to form quantifiable conclusions about the human brain from experiments in mouse. It will identify biomarkers visible in noninvasive diagnostic imaging in humans that signal age-related deterioration before symptoms develop. The computational framework for relating data acquired in animal models to human will enable interpretation without guesswork and dramatically boost the relevance and utility of animal data for human medicine.
The project will quantify both healthy and deteriorated cerebral metabolic function in order to precisely correlate biological conditions with age and Alzheimer-related decline. As the main thrust, a computational framework, fully validated by advanced imaging at the cellular level, will be created for translating research data acquired in animal models to human. This computational platform will remove the guesswork from the interpretation of findings obtained in mouse as they relate to aging in humans, ultimately leading to the ability to accurately monitor, diagnose, and treat metabolic disorders causing decline.
