Abstract

Postmenopausal women are at increased risk of developing coronary artery disease (CAD). Metabolomic approaches aim at discovering more helpful biomarkers of CAD to reduce the disease burden in the future. Here, we intend to find potential blood biomarkers, amino acids, and acylcarnitines in postmenopausal women with different severity of CAD by using high-throughput methods. This cross-sectional study was performed on postmenopausal women ( n = 183) who underwent coronary CT scans. Coronary artery calcium scoring (CACS) was assessed to detect plaque burden and degree of coronary artery obstruction. The participants were divided into three groups based on the score as follows (i) "low CACS" ( n = 96); a score of 0 to 10, (ii) "medium CACS" ( n = 35); a score between 11 and 100 and (iii) "high CACS" ( n = 52); a score greater than 100. Metabolites, including amino acids and acylcarnitines, were quantified using a targeted mass spectrometry method in serum samples. The association between metabolites and disease status was evaluated using univariate and multivariate regression analyses with adjustment for confounding factors. Factor analysis was used to deal with multiple comparisons. Metabolites, including proline, glutamic acid, and phenylalanine, were significantly lower in the high CACS group than the low CACS one. Also, a lower level of lysine and phenylalanine in high CACS compared with medium one was observed. Concerning acylcarnitines, it was found that C4 and C8:1 significantly were higher in women with high CACS. The logistic regression analysis revealed that the circulating levels of these metabolites (except C4) were associated with the presence of coronary artery calcification independently of age, body mass index, and time of menopause. Also, the amino acids were associated independently of medication and diabetes. The present study indicated that circulating levels of amino acids and acylcarnitines profile in postmenopausal women are partly associated with the severity of CAD in these participants.

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