Abstract P3021: Inflammatory Metabolomic Profiles are Associated with Increased Cardiovascular Disease Risk in Women

K Kevin Sanchez (Brigham and Women's Hospital, Boston, Massachusetts, United States) J Jie Hu (School of Biomedical Sciences and Engineering) O Oana Zeleznik (Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, United States) R Raji Balasubramanian D Dong Hoon Lee J Jun Li F Fred Tabung (The Ohio State University, Columbus, Ohio, United States) A A Eliassen (Harvard University, BOSTON, Massachusetts, United States) K Kathryn Rexrode (BRIGHAM AND WOMENS HOSPITAL, Boston, Massachusetts, United States)

Abstract

Background: Cardiovascular disease (CVD) is the leading cause of death worldwide; ischemic stroke (IS) and coronary heart disease (CHD) are the two leading causes of CVD. The burden of CVD is particularly pronounced in women, who have a 20% higher lifetime risk of stroke than men and have worse outcomes for CHD and IS. Inflammation is a risk factor for CVD, yet the mechanisms through which chronic inflammation increases this risk remain uncertain. Methods: Metabolomic data from 11 case-control studies in the Nurses’ Health Study (NHS) focusing on chronic inflammatory disease outcomes were used. In this cohort, 1,734 women also had data on inflammatory biomarkers (i.e., hs-CRP, IL6, TNFaR2, adiponectin). A composite inflammatory score was created based on these four biomarkers, and elastic net regression was used to identify metabolites associated with the inflammatory score. A metabolomic signature index of inflammation (i-MSI) was subsequently calculated as the sum of retained metabolites with weights equal to their regression coefficients. In an independent NHS IS case-control study ( n = 405 cases and 405 controls), conditional logistic regression was used to determine the odds ratios (OR) for the i-MSI and IS risk, controlling for standard CVD risk factors. Additionally, the association between the i-MSI and CHD risk was assessed in a case-control dataset from the Women’s Health Initiative (WHI; n = 793 cases and 795 controls). Results: The i-MSI comprised 92 metabolites in the NHS and 87 overlapping metabolites in the WHI, showing enrichment in branched-chain amino acid biosynthesis and degradation pathways. Moreover, weighted coexpression network analysis revealed distinct pro- and anti-inflammatory metabolite clusters, identifying diacylglycerides in the pro-inflammatory cluster and cholesteryl esters in the anti-inflammatory cluster. Every standard deviation (SD) increase in the i-MSI was associated with an OR for IS of 1.31 (95% CI: 1.06 – 1.62), and women in the highest i-MSI quartile had an OR of 1.96 (95% CI: 1.12 – 3.42). These findings were consistent in the CHD case-control cohort from the WHI, where the OR for CHD was 1.27 (95% CI: 1.07 – 1.51) per SD of the i-MSI. Conclusions: These data identify an association between metabolites linked with inflammation and CVD risk. These findings may aid in identifying novel metabolic targets that can be utilized to develop therapies for mitigating IS and CHD risk in women.

Article Details

Journal Circulation
Volume / Issue Vol. 151, Issue Suppl_1
Published March 11, 2025
ISSN 0009-7322
Publisher Lippincott Williams & Wilkins

Journal Info

Circulation

Lippincott Williams & Wilkins

ISSN: 0009-7322 Health Sciences

Authors (9)

K

Kevin Sanchez

Brigham and Women's Hospital, Boston, Massachusetts, United States

J

Jie Hu

School of Biomedical Sciences and Engineering

O

Oana Zeleznik

Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, United States

R

Raji Balasubramanian

D

Dong Hoon Lee

J

Jun Li

F

Fred Tabung

The Ohio State University, Columbus, Ohio, United States

A

A Eliassen

Harvard University, BOSTON, Massachusetts, United States

K

Kathryn Rexrode

BRIGHAM AND WOMENS HOSPITAL, Boston, Massachusetts, United States