Abstract Body (Do not enter title and authors here): Introduction
Epicardial adipose tissue (EAT) is a metabolically active tissue associated with cardiometabolic disease. EAT likely has local paracrine inflammatory and atherogenic effects on coronary vessels, but the metabolic underpinnings related to systemic metabolic pathways has not been evaluated.

Hypothesis
We hypothesized that metabolic markers of lipid and fatty acid oxidation will be positively associated with volume of EAT.

Methods
In a biomarker substudy of the Prospective Multicenter Imaging Study for Evaluation of Chest Pain (PROMISE) clinical trial which randomized participants to computed tomography angiography (CTA) vs. stress testing, we analyzed 1542 participants randomized to the CTA arm with available plasma at baseline. CTA phenotyping of EAT volume indexed to body surface area (cm³/m²) was determined using a validated deep-learning algorithm. Comprehensive metabolomic profiling was performed on plasma samples using mass spectrometry. Principal components analysis (PCA) was used for dimensionality reduction of 571 named metabolites. Linear regression tested the association of metabolomic factors with EAT. Univariate models were adjusted for multiple comparisons and multivariate models were adjusted for age, race and ethnicity, sex, diabetes, BMI, LDL-C, HDL-C and metabolic syndrome.

Results
Of 82 PCA-derived metabolomic factors, 16 were associated with EAT in univariate models and nine were associated with EAT in multivariate models (p=0.001-0.046); 116 individual metabolites heavily loaded within these factors were significantly associated with EAT volume in multivariate models (Figure 1). This included three linoleic acid derivatives, six cholesterol esters, and glycine that were inversely associated with EAT volume (p<0.04) and 106 metabolites positively associated with EAT volume including di- and triacylcerols, glycerophospholipids, fatty acyls and dimethylguanidino valeric acid (p<0.05).

Conclusions
Leveraging a large clinical trial of CTA to study metabolomics of EAT, we have identified circulating lipid species associated with EAT independent of BMI and conventional lipids. These findings highlight biomarkers of systemic metabolic dysregulation as risk modifiers and therapeutic targets in cardiometabolic disease prevention and treatment.