(P13-018-24) Identification of Fecal Biomarkers of High-Fat Diet in Peri–And Postmenopausal Women: A Cross-Sectional Study

Sunday, June 30, 2024

11:45 AM – 12:45 PM CT

Location: Poster Board 407

Presenting Author(s)

MD

Manije Darooghegi Mofrad, MSc (she/her/hers)

Graduate Assistant
University of Connecticut
Storrs, Connecticut, United States

Co-Author(s)

AL

Ali Lotfi

University of Connecticut, United States
Briana M. Nosal, B.S. (she/her/hers)

Graduate Student
University of Connecticut
Willington, Connecticut, United States
Staci Thornton, Ph.D

Postdoctoral Fellow
University of Connecticut
Storrs, Connecticut, United States
AM

Alexey V. Melnik

University of Connecticut, United States
AA

Alexander Aksenov

University of Connecticut, United States
EC

Elaine Choung-Hee Lee

University of Connecticut
Ock K. Chun, PhD, MPH

Associate Professor
University of Connecticut
Storrs, Connecticut, United States

Disclosure(s):

Manije Darooghegi Mofrad, MSc: No relevant financial relationship(s) with ineligible companies to disclose.

Briana M. Nosal, B.S.: No relevant financial relationship(s) with ineligible companies to disclose.

Objectives: This study performed untargeted metabolomics on stool samples of peri-and postmenopausal women to identify fecal biomarkers related to the high fat diet (HFD).

Methods: This cross-sectional study analyzed baseline data from a clinical trial on blackcurrant supplementation for bone health in 27 peri- and early postmenopausal women aged 45-60. Fecal metabolites were measured by liquid chromatography-mass spectrometry (LC-MS/MS). Principal Component Analysis (PCA), Partial Least Squares-Discriminant Analysis (PLS-DA) and Orthogonal Projections to Latent Structures Discriminant Analysis (OPLS-DA) were performed with MetaboAnalyst (version 6) to find group separation. The cross-validation of PLS-DA model was conducted using the 10-fold cross validation method. The study utilized Variable Importance in Projection (VIP) scores to identify key metabolites contributing to group discrimination.

Results: 1769 features were significantly different between fecal samples from low/medium and high fat diet groups (P < 0.05). Principal component 1 (PC1) showed 11.5 % of the variance and component 2 (PC2) demonstrated 8.5% of the variance, and PLS-DA and OPLS-DA improved the separation of groups. The validation of the PLS-DA model showed R2 of 0.99 and Q2 of 0.58 after using a maximum of 5 components. 100 top metabolites were selected based on VIP scores, and of these 10 were assigned annotated compounds and suspects. Suspects originate from unannotated spectra that are linked to an annotated spectrum in a molecular network. These metabolites were related to poly unsaturated fatty acid (PUFA), trans fatty acid, monoterpene alcohol, sesquiterpene lactone, sesquiterpenoids, and benzodioxoles families. The VIP score for the 10 metabolites were between 2.69 and 3.45.

Conclusions: Our study identified some fecal biomarkers that reflect adherence to HFD in peri- and early postmenopausal women. To be utilized as an objective tool for predicting HFD, these findings need further validation in large-scale observational and experimental studies.

Funding Sources: This research was funded by the USDA NIFA Seed Grant to Dr. Ock K. Chun. The supporting sources had no such involvement or restrictions regarding publication.