# Effects of metabolic phenotype on functional connectivity in aging and Alzheimer’s Disease

> **NIH NIH F30** · UNIVERSITY OF KANSAS MEDICAL CENTER · 2024 · $53,974

## Abstract

Summary/Abstract
Alzheimer’s Disease (AD), the most common cause of dementia, affects over 6.2 million Americans and 50
million individuals worldwide. Ten to fifteen years prior to the onset of cognitive symptoms, AD pathology
begins to appear in the brain. While the primary pathology associated with AD include amyloid beta and
hyperphosphorylated tau, the pathogenesis of AD remains elusive. Other changes in the AD brain include
derangements in cerebral glucose metabolism. Recent epidemiological studies have highlighted an association
between AD and systemic metabolic impairment (i.e. diabetes). This indicates a major role of altered
metabolism in AD, and warrants examination of how metabolic risk may contribute to brain health and
dementia risk. Biomarker studies of brain structure and function offer potential opportunities for early detection
of AD, and for improving our understanding of factors relating to disease risk. Functional connectivity, a
measure of correlated neural activity in two brain regions can be measured by resting-state functional
magnetic resonance imaging (rsfMRI). This functional neuroimaging approach has emerged as a potential
biomarker for AD diagnosis and disease monitoring. Importantly, metabolic risk has previously been
associated with altered functional connectivity. However, data regarding early forms of metabolic risk, like
prediabetes, is lacking. Additionally, functional connectivity studies often suffer from limited sample size and a
lack of diversity. We intend to analyze the existing rsfMRI data of individuals recruited into the Health and
Aging Brain Among Latino Elders (HABLE) Study, a diverse cohort of approximately 2,000 individuals. In our
first aim, we will characterize the effect of metabolic risk (prediabetes or Type 2 Diabetes status assessed by
blood glucose, diagnosis, or medication use) on functional connectivity in cognitively healthy individuals. As
part of this aim, we will also examine the role of APOE4, a foremost genetic risk factor of AD that is closely
related to cerebrovascular dysfunction. In our second aim, we will examine functional networks across the AD
diagnostic spectrum, and examine to what degree metabolic risk mediates changes in these networks. We will
then assess the relationship between cardiometabolic risk score and functional connectivity across the entire
cohort.

## Key facts

- **NIH application ID:** 10910115
- **Project number:** 5F30AG076278-03
- **Recipient organization:** UNIVERSITY OF KANSAS MEDICAL CENTER
- **Principal Investigator:** Zachary Douglass Green
- **Activity code:** F30 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $53,974
- **Award type:** 5
- **Project period:** 2022-09-19 → 2027-02-18

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10910115

## Citation

> US National Institutes of Health, RePORTER application 10910115, Effects of metabolic phenotype on functional connectivity in aging and Alzheimer’s Disease (5F30AG076278-03). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10910115. Licensed CC0.

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