# Application of a novel dietary pattern predictive of trimethylamine N-oxide production to examine associations with metabolomic profiles, the gut microbiome, and vascular health

> **NIH NIH F31** · STATE UNIVERSITY OF NEW YORK AT BUFFALO · 2024 · $31,380

## Abstract

ABSTRACT/PROJECT SUMMARY
Good vascular health is important for the prevention of atherosclerotic cardiovascular disease (CVD), a highly
prevalent disease in the US, with post-menopausal women at an especially high risk. Dietary intake is a major
driver of vascular health, and diet can affect vascular health in part through actions involving the gut microbiome.
Specifically, choline can be converted to trimethylamine, a precursor to trimethylamine N-oxide (TMAO) which
is a metabolite shown to have atherosclerotic effects. This reaction is dependent on bacteria in the gut
microbiome. Studies of this metabolic pathway have examined individual foods rich in choline (i.e., red meat,
fish, and eggs), however, the effect of an overall dietary pattern on this pathway has been understudied. We
have created a novel dietary pattern predictive of biomarkers of TMAO production (the TMAO dietary pattern)
within an ancillary study sample of the Women’s Health Initiative (WHI) Observational Study, a prospective
cohort study of post-menopausal women. Applying the TMAO dietary pattern to examine how it is associated
with the intermediates of the pathway of TMAO production and a measure of vascular health is critical to gain a
more complete understanding of the influence of overall dietary intake on this metabolic process. Examining an
individual’s vasculature typically requires invasive procedures, however, measuring the retinal vessel caliber is
a noninvasive way to assess an individual’s vascular health at the microvascular level. The purpose of this
proposal is to examine how adherence to the TMAO dietary pattern is associated with 1) a broad array of
circulating plasma metabolite concentrations, 2) the composition and diversity of the gut microbiome, and 3)
retinal vessel caliber measured several years after dietary assessment using data from separate ancillary study
samples of the WHI. We hypothesize that higher adherence to the TMAO dietary pattern will be associated with
less favorable (e.g., pro-atherogenic) metabolomic profiles, gut microbiome composition, and retinal vessel
caliber measures compared to lower adherence. Data are already collected and available on metabolomic
profiles (>300 metabolites) of plasma samples measured using liquid chromatography-mass spectrometry
methods and on the gut microbiome composition assessed using 16S ribosomal RNA (rRNA) sequencing of
DNA extracted from stool samples, with habitual dietary intake assessed at the same time points. Additionally,
digital color photographs have already been graded for retinal vessel caliber. We expect findings from this
research to provide implications for future interventions targeting the diet and gut microbiome for vascular-related
disease prevention. Ultimately, based on our findings, dietary guidelines for the prevention of atherosclerotic
CVD may be enhanced. This study will facilitate my proposed training plan by allowing me to gain a deeper
understanding of the underlying metaboli...

## Key facts

- **NIH application ID:** 10898570
- **Project number:** 5F31HL168805-02
- **Recipient organization:** STATE UNIVERSITY OF NEW YORK AT BUFFALO
- **Principal Investigator:** Kaelyn Burns
- **Activity code:** F31 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $31,380
- **Award type:** 5
- **Project period:** 2023-07-01 → 2025-06-06

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10898570

## Citation

> US National Institutes of Health, RePORTER application 10898570, Application of a novel dietary pattern predictive of trimethylamine N-oxide production to examine associations with metabolomic profiles, the gut microbiome, and vascular health (5F31HL168805-02). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10898570. Licensed CC0.

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