Glucose Variability as a Digital Biomarker for Preclinical AD Risk in Prediabetes.

NIH RePORTER · NIH · R21 · $224,466 · view on reporter.nih.gov ↗

Abstract

PROJECT ABSTRACT Reliable diagnostic digital tools are needed for the early detection of cognitive dysfunction and stratification of early Alzheimer’s Dementia (AD) risk among older adults at risk for Type 2 diabetes (T2DM). T2DM is a well- known accelerator of cognitive decline and AD risk: T2DM is linked to dysfunction in episodic memory and executive functions, and proffers a 2- to 4-fold increased risk for AD. The prediabetes stage may be key to understanding this accelerated aging as it could provide an optimal window into the initial pathophysiological changes that trigger cognitive dysfunction and AD. However, uncertainty surrounds the role of hyperglycemia in the prediabetic stage, perhaps because only assessing peaks in glucose sporadically using single time-point measurements like hemoglobin A1c (HbA1c) and fasting glucose leaves key aspects of dysglycemia unexamined. These limitations open the possibility that more precise measurement of dysglycemia will yield a more definitive understanding of the mechanisms by which T2DM pathophysiology modifies cognitive function and AD risk, which are presently unknown. We will be the first to leverage cutting-edge Continuous Glucose Monitoring (CGM) technology to investigate the precise associations between dysglycemia, cognitive function, and key AD biomarkers in older adults with at risk for T2DM. CGM allows for the precise assessment of fluctuations in glucose levels to show individualized patterns of hyper- and hypoglycemia over days- a major component of dysglycemia not reflected in fasting glucose or HbA1c. Because CGM technology has almost exclusively been used by people with a T2DM diagnosis, examining those at risk for T2DM is innovative. Our established multidisciplinary research team, with expertise in behavioral medicine, endocrinology, geriatrics, neuropsychology, and neurology, and numerous years of collaborative clinical research experience, is well- positioned to examine among 40 older adults at risk for T2DM (a) the association of glycemic fluctuations with cognitive dysfunction in episodic memory and executive functions, key domains that show decrements both early in the AD trajectory, and in prediabetes, and (b) explore, for the first time, the association of glycemic fluctuations with well-established biomarkers of early AD risk. These plasma-based AD biomarkers of tau phosphorylation and amyloid burden are cost-effective, require minimally invasive blood draws, and minute amounts of brain-specific proteins in blood for use with ultrasensitive immunoassays. By leveraging precise, scalable technology to assess early glycemic fluctuations, and sensitive screening tools for early AD risk, this innovative proposal stands to make both scientific and technological advances in aging and AD risk research. Support for our hypotheses would introduce cost-effective, user-friendly CGM technology as a novel, sensitive, digital biomarker for the early detection of cognitive dysfunction and s...

Key facts

NIH application ID
10910153
Project number
5R21AG077647-02
Recipient
UNIVERSITY OF MARYLAND BALTIMORE COUNTY
Principal Investigator
Tasneem Khambaty
Activity code
R21
Funding institute
NIH
Fiscal year
2024
Award amount
$224,466
Award type
5
Project period
2023-09-01 → 2026-05-31