Neuroinflammation and Alzheimer's Disease Imaging Biomarkers in Midlife Obesity

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Summary/Abstract: High body fat at midlife, as evidenced by overweight or obese body mass index (BMI), is increasingly understood as a risk factor for Alzheimer’s disease. However, the underlying processes and mechanisms that may underlie this risk remains unknown. With this R01 proposal, we request funding to create a new cohort of cognitively normal 120 midlife individuals, age 40-60 years. We propose to characterize their overweight or obese status using metabolic tests including, an oral glucose tolerance test, fasting plasma insulin, fasting plasma glucose, and hemoglobin A1c measurements. This testing will generate categories of metabolically abnormal overweight or obese (MAOO), metabolically normal overweight or obese, and metabolically normal lean persons. We will evaluate differences between these groups on neuroimaging with the newer classification of Alzheimer’s biomarkers with amyloid (A), tau (T), and neurodegeneration (N), or ATN. Neurodegeneration will be assessed by atrophy on brain MRI as reflected by regional volumes on FreeSurfer. We will also evaluate MR neuroimaging markers for neuroinflammation using a newer method called diffusion basis spectrum imaging (DBSI), developed at the Mallinckrodt Institute of Radiology at Washington University in St. Louis in collaboration with The Charles F. and Joanne Knight Alzheimer’s Disease Research Center (Knight ADRC). Recruitment of participants for this study will be done in conjunction with both the Knight ADRC and the Washington University Center for Human Nutrition. In Aim 1, we hypothesize increased atrophy in MAOO compared to metabolically normal overweight, obese, and lean participants particularly in regions important for AD pathology such as the hippocampus and subregions. With Aim 2, we hypothesize a higher burden of white matter neuroinflammation on DBSI in MAOO compared to other metabolic, overweight or obese and lean groups. In Aim 3, we hypothesize increased amyloid and tau on brain PET in MAOO versus other groups. Related sub-aims will examine sex differences in atrophy and neuroinflammation. We will also investigate sex differences in amyloid and tau deposition across the overweight/obese and lean groups. This approach is not only of interest given the known sex differences in obesity and AD risk but is also recognized by the NIA as important in understanding trends of risk in AD. We will also examine the anatomical distribution of abnormally high body fat by acquiring separate body torso MRI scans at the time of brain MRI scan. This will allow for separate quantification of visceral, abdominal subcutaneous, and liver fat volumes that we will separately relate to the imaging markers in Aims 1-3. By understanding how metabolic abnormalities with, and anatomical distribution of, high body fat relate to brain imaging metrics of ATN and neuroinflammation, we will contribute key understanding to how obesity increases Alzheimer’s risk. These results will have public health implications and inform future studies of interventions to reduce risk for Alzheimer’s by identifying important metrics to utilize for optimization of metabolic and related brain health in overweight and obese persons.