Retinal Lipidomics Associations as Candidate Biomarkers for Cardiovascular Health

TL;DR

This study explores how specific blood lipid subclasses relate to retinal microvascular features, proposing retinal imaging as a non-invasive biomarker for systemic metabolic health, with novel integration of deep learning-derived traits.

Contribution

It is the first to combine deep learning retinal trait analysis with lipidomics in a healthy cohort, revealing associations independent of disease or treatment effects.

Findings

Free fatty acids linked to vessel twistiness

Cholesteryl esters correlated with vessel widths

DAG and TAG negatively associated with vessel complexity

Abstract

Retinal microvascular imaging is increasingly recognised as a non invasive method for evaluating systemic vascular and metabolic health. However, the association between lipidomics and retinal vasculature remains inadequate. This study investigates the relationships between serum lipid subclasses, free fatty acids (FA), diacylglycerols (DAG), triacylglycerols (TAG), and cholesteryl esters (CE), and retinal microvascular characteristics in a large population-based cohort. Using Spearman correlation analysis, we examined the interconnection between lipid subclasses and ten retinal microvascular traits, applying the Benjamini-Hochberg false discovery rate (BH-FDR) to adjust for statistical significance. Results indicated that FA were linked to retinal vessel twistiness, while CE correlated with the average widths of arteries and veins. Conversely, DAG and TAG showed negative correlations with the width and complexity of arterioles and venules. These findings suggest that retinal vascular architecture reflects distinct circulating lipid profiles, supporting its role as a non-invasive marker of systemic metabolic health. This study is the first to integrate deep learning (DL)derived retinal traits with lipidomic subclasses in a healthy cohort, thereby providing insights into microvascular structural changes independent of disease status or treatment effects.