Non-lipid metabolomic biomarkers are associated with adverse cardiac remodelling and cardiovascular outcomes
Authors: Sanghvi M M , Young W J , Chadalavada S , Petersen S E , Aung N , Munroe P B 
Published: October 2024

Background

Metabolomics is the detailed profiling of circulating metabolites including carbohydrates, lipids, amino and fatty acids, and ketones, all of which are substrates used in energy metabolism by cardiomyocytes.

Purpose

The role of cholesterol fractions with cardiovascular risk is well-established. This novel study examines the association between non-lipid circulating metabolites and markers of cardiac remodelling as assessed by cardiovascular magnetic resonance (CMR) imaging. Metabolites associated with adverse remodelling were taken forward to examine their impact on incident cardiovascular disease (CVD); ischaemic heart disease (IHD) and heart failure (HF).

Methods

This study used data from the UK Biobank. After exclusions (prevalent IHD, HF; outliers), there were a maximum of 34,727 individuals for CMR analyses and 262,536 individuals for incident CVD analysis.

For CMR analyses, outcome variables were LV end-diastolic volume (EDV), LV mass, LV mass:volume ratio (MVR), LV global longitudinal strain (GLS) and native T1. Separate regression models were built for each of the 40 scaled metabolite biomarkers. Each model incorporated one metabolite at a time with additional covariates: age, sex, ethnicity, systolic blood pressure, cholesterol medication use, type 2 diabetes, dietary intake, smoking status, fasting time, and time between recruitment and CMR examination. A Bonferroni-corrected significance threshold of 2.4x10-4 was used.

To account for correlation between metabolites, Lasso regression with 10 fold cross-validation to identify the most important predictors was performed for LV MVR, LV GLS and native T1 whereby all metabolites and above covariates were included in the model. Metabolite predictors of adverse remodelling were included in an adjusted logistic regression model with incident CVD as an outcome.

Results

Metabolites demonstrating significant (p &lt; 2.4x10-4) associations with CMR parameters are presented in Fig 1. For higher LV MVR and more positive LV GLS, the metabolites with the largest effect were monounsaturated fatty acids and glycoprotein acetyls. Higher omega-6:omega-3 ratio was associated with higher T1 values.

The Lasso model identified 8 important predictors for adverse cardiac remodelling. Of these, two were routine biomarkers (creatinine, glucose). Of the remainder, monounsaturated fatty acids, glycoprotein acetyls and apolipoprotein B:apolipoprotein A1 ratio were significantly associated with increased risk of incident CVD (Fig 2).

Current evidence regarding monounsaturated fatty acids in CVD is mixed. Glycoprotein acetyls are implicated in vascular inflammation. Apolipoproteins are thought to be a potential therapeutic target for CVD risk reduction.

Conclusion

This study demonstrates a role of non-lipid metabolites on subclinical CVD as assessed by adverse remodelling with CMR as well as associations with incident CVD. We highlight potential novel biomarkers for identification of CVD.Metabolite association with LV MVR/GLSMetabolite association with incident CVD