Alzheimer's disease (AD) and Alzheimer's disease-related dementias (ADRD) are responsible for considerable morbidity and mortality, and are expected to pose an increasing burden because the US population is aging. Technological advances in magnetic resonance imaging (MRI) and analytic algorithms facilitate increasingly precise measurement and characterization of structural and functional brain changes that may be early indicators of pathologic processes leading to AD/ADRD. Early detection of these changes is critical during preclinical stages before the pathologic change has advanced to an irreversible state, as this is a period when treatment may be most effective. Type 2 diabetes mellitus (T2DM) appears to accelerate the trajectory of brain aging. As Type 1 diabetes mellitus (T1DM) patients live longer, they might be at increased risk for AD/ADRD but little is known about the impact of T1DM on accelerated brain aging and ADRD. We are responding to NOT-AG-18-039 to seek an administrative supplement to DP3114812 -(Effects of Biomedical Risk Factors on Neuro-cognition Using MRI) to leverage the long term follow-up of the Diabetes Control & Complications Trial (DCCT)/Epidemiology of Diabetes Interventions and Complications Study (EDIC) Cohort to investigate associations with AD-related changes on brain MRI. The participants have been studied for over 35 years, with detailed longitudinal biomedical and cognitive data gathered from baseline and are entering the age of increased risk for AD/ADRD. Our project addresses action item 1.C.1 of the National Alzheimer's Project Act 2018 update: identify imaging and biomarkers to monitor disease progression. Enhanced neuroimaging methods for early diagnosis can serve as foundations for designing and following subjects in clinical trials and selecting patients at greatest risk for therapeutic interventions. The primary goal of this supplement is to evaluate the presence of AD-like patterns of brain atrophy in the DCCT/EDIC population. We plan to construct robust imaging markers of clinical and preclinical AD, as well as to systematically characterize the heterogeneity of brain aging and its associations with various risk factors by leveraging multiple advances since the original proposal including a large NIA-funded study led by our group that pools together data from approximately 20,000 individuals, called iSTAGING. These new advances will permit us to develop a new focus on ADRD, addressing our Specific Aims: 1) Harmonize the EDIC MRI datasets with a large brain aging and AD consortium (iSTAGING), using state of the art statistical imaging analytics methods, as well as an enriched set of healthy control individuals scanned in the same sites and by the same protocol. 2) Evaluate the presence of patterns of brain atrophy that have been established in MCI and AD, and to relate those patterns to biomedical predictors and cognitive decline in EDIC. This plan builds upon the currently funded project to now include explicit ADRD research objectives. Our study will help determine whether T1DM is associated with pre-clinical brain imaging patterns of AD.
The Diabetes Control & Complications Trial/Epidemiology of Diabetes Interventions & Complications (DCCT/EDIC) study affords an unparalleled opportunity to use blood sugar control and other information gathered over a 30 year period from early in the course of illness, among this well-characterized group of patients, to examine important and unresolved questions about the frequency and causes of these problems using magnetic resonance imaging (MRI) techniques. In this supplement we now apply machine learning techniques and evaluate whether Type 1 diabetes leads to premature brain aging and patterns of brain alterations previously associated with Alzheimer's disease. This is consistent with The National Plan for Alzheimer Disease (AD) and Alzheimer's Disease Related Dementias (ADRD) to develop neuroimaging methods for early diagnosis and assessment of biomedical risk factors for AD and ADRD as important goals.
