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Coronary artery disease (CAD) and atherosclerosis pose significant global health challenges, with intricate molecular changes influencing disease progression. Hypercholesterolemia (HC), hypertension (HT), and diabetes are key contributors to CAD development. Metabolomics, with its comprehensive analysis of metabolites, offers a unique perspective on cardiovascular diseases. This study leveraged metabolomics profiling to investigate the progression of CAD, focusing on the interplay of hypercholesterolemia, hypertension, and diabetes. We performed a metabolomic analysis on 221 participants from four different groups: (I) healthy individuals, (II) individuals with hypercholesterolemia (HC), (III) individuals with both HC and hypertension (HT) or diabetes, and (IV) patients with self-reported coronary artery disease (CAD). Utilizing data from the Qatar Biobank, we combined clinical information, metabolomic profiling, and statistical analyses to identify key metabolites associated with CAD risk. Our data identified distinct metabolite profiles across the study groups, indicating changes in carbohydrate and lipid metabolism linked to CAD risk. Specifically, levels of mannitol/sorbitol, mannose, glucose, and ribitol increased, while pregnenediol sulfate, oleoylcarnitine, and quinolinate decreased with higher CAD risk. These findings suggest a significant role of sugar, steroid, and fatty acid metabolism in CAD progression and point to the need for further research on the correlation between quinolinate levels and CAD risk, potentially guiding targeted treatments for atherosclerosis. This study provides novel insights into the metabolomic changes associated with CAD progression, emphasizing the potential of metabolites as predictive biomarkers.
Anlar et al. (Wed,) studied this question.