# Associations Between the Dietary Inflammatory Index and MRI Measures of Brain Volume, Markers of Cerebral Small Vessel Disease and PET Imaging Biomarkers of Alzheimer's Disease (beta amyloid and tau)

> **NIH NIH R03** · UNIVERSITY OF TEXAS HLTH SCIENCE CENTER · 2021 · $77,292

## Abstract

In the context of a lack of effective treatment for dementia currently, the way forward is the rigorous investigation
of modifiable preventive factors such as diet that impact brain aging. Diet plays a pivotal role in the regulation of
chronic inflammation, one of the causal pathways leading to dementia. The Dietary Inflammatory index (DII) is a
universally applicable tool on diets across the world and is designed to investigate the inflammatory potential of
diet on multiple health outcomes ranging from blood concentrations of inflammatory cytokines to chronic
diseases. This is the first study to investigate the DII in relation to brain volume measures, markers of cerebral
small vessel disease, and biomarkers of AD.
We aim to investigate (1a) the longitudinal relationships between the Dietary Inflammatory Index (DII) and
structural magnetic resonance imaging (MRI) markers of brain aging (i.e. total brain volume, hippocampal
volume, lateral ventricular volume, and total grey matter volume) among participants (n=2,500) in the Offspring
cohort and the Omni 1 cohort of the Framingham Heart Study (FHS); (1b) the longitudinal and cross-sectional
relationships between the DII and markers of cerebral small vessel disease (i.e. white matter hyperintensities,
silent brain infarcts, cerebral microbleeds (CMB) and peak width of skeletonized mean diffusivity (PSMD) in this
cohort; (1c) mediation effect by plasma inflammatory markers if significant associations are found in aim 1a and
aim 1b. Secondly, we will investigate (2) the cross-sectional relationships between the DII and positron-emission
tomography (PET)-imaging biomarkers of Alzheimer’s disease dementia (AD), including beta-amyloid PET
(specifically, fronto-lateral-retrosplenial) and Tau PET (specifically, entorhinal cortex and inferotemporal cortex)
among participants in the Offspring Cohort of the FHS (n=60). Sample for aim 1 will include FHS Offspring (who
attended exam 7 and either exam 5 or 6) and Omni 1 (who attended exam 1 and 2) participants who filled out
the Food Frequency Questionnaire (FFQ) for the creation of an averaged DII, who underwent brain MRI
(Offspring: exams 7,8 and 9; Omni 1: exams 2 and 3) and have data on covariates. Sample for aim 2 will include
FHS Offspring participants (who attended exam 7 and at least exam 5 or 6) who filled out the FFQ, underwent
beta-amyloid and Tau PET scans at exam 9, and have data on covariates. We will relate the DII to changes of
structural MRI markers of brain aging as well as markers of cerebral small vessel disease using multivariable
linear regression and logistic regression models. When significant associations are found, we will perform
mediation analyses to investigate the role of plasma inflammatory markers. In addition, we will relate the DII to
PET-imaging biomarkers of AD using multivariable linear regression models. We will adjust for age at MRI/PET
Exam, age squared at MRI/PET Exam, sex, education, Apolipoprotein e4, ethnicity, body ma...

## Key facts

- **NIH application ID:** 10176351
- **Project number:** 5R03AG067062-02
- **Recipient organization:** UNIVERSITY OF TEXAS HLTH SCIENCE CENTER
- **Principal Investigator:** Debora Melo van Lent
- **Activity code:** R03 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $77,292
- **Award type:** 5
- **Project period:** 2020-06-15 → 2024-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10176351

## Citation

> US National Institutes of Health, RePORTER application 10176351, Associations Between the Dietary Inflammatory Index and MRI Measures of Brain Volume, Markers of Cerebral Small Vessel Disease and PET Imaging Biomarkers of Alzheimer's Disease (beta amyloid and tau) (5R03AG067062-02). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10176351. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*