Brian Gordon, Ph.D.
Project Overview:
The number of adults age 65 and older is expected to increase to nearly 1 billion by 2030. With this dramatic increase in elderly individuals, there is a rising concern over the implications of a corresponding increase in the number of individuals suffering from dementia. The objective of this project was to examine the influence that obesity and diabetes have on Alzheimer’s disease (AD) risk and pathology. Epidemiological studies suggest that both obesity and diabetes increase the risk of developing dementia. It is unclear if these two conditions act directly on AD pathology, or rather represent comorbid pathology that act in parallel to AD to increase dementia risk. Studying and unraveling this distinction is critical in understanding in what ways obesity and diabetes impact AD.
Progress Report
Using longitudinal cognitive and neuroimaging data from the Knight Alzheimer’s Disease Research Center we examined the influence that obesity and diabetes had on cognition and AD biomarkers. We quantified obesity using body mass index (BMI) and diabetes using self-reported medication and glycated hemoglobin (HbA1c). Our primary cognitive outcome was whether individuals would ever develop dementia as measured using the clinical dementia rating (CDR). We used the neuroimaging technique positron emission tomography (PET) to measure levels of beta-amyloid (Aβ), the primary pathological protein associated with AD pathogenesis. In addition to these primary measures, we examined interactions with the apolipoprotein genotype (APOE) as well as baseline age group (mid-life or late-life).
We found there was no relationship between mid-life or late-life BMI at risk of developing dementia. In the subset with HbA1c we found no relationship between insulin resistance and risk of developing dementia. When examining Aβ levels we found a negative association, such that greater levels of BMI, and also greater insulin resistance, was associated with lower levels of beta-amyloid pathology measured with PET. We found that there were no interactions with APOE genotype (presence or absence of e4 allele). We did find significant interactions with baseline age group, with the significant effect of BMI only being present in late-life. This work suggests that if BMI and diabetes increase the risk for dementia the effect is subtle and not detectable in our current cohorts. Although we found a significant relationship between health measures and levels of Aβ, the direction of the relationship was such that worse health profiles were associated with less pathology. This result is consistent with two other recent publications examining the link between AD, obesity, and diabetes, but contrary to expectations from the animal literature.
Our current analyses have been a first step towards focusing on such health-related factors such as obesity and diabetes in the context of AD. We recognize that the available measures in our cohort are only rough approximations of the true measures we would like to get. Rather than looking at BMI, central adiposity or body composition from a DEXA scan would be a better measure. We need to get fasting HbA1c and lipid panels as a routine measure on all ADRC participants, not just a subsample. Ideally, we would even get an oral glucose tolerance test on participants.
To pursue these aims we currently are preparing two R01s. One R01 we are collaborating on is primarily looking at the effects diabetes and obesity has on white matter integrity in the brain. This study will specifically recruit individuals with diabetes and is proposing to get DEXA and OGTT data on its participants in addition to MRI imaging. A second R01 in the works would provide funds to add additional measures to the ADRC cohort. This proposal would add dietary surveys, blood tests (HbA1c), body composition measures of central adiposity, DEXA, a five minute walk test, and a peak exercise test for aerobic capacity (VO2). Getting this data would enrich the ADRC cohort and make it possible to ask more in-depth questions. The data funded by the LLF grant will serve as preliminary data in this R01 submission.
