Metabolomics Profile and 10-Year Atherosclerotic Cardiovascular Disease (Ascvd) Risk Score Publisher



Dehghanbanadaki H¹ ; Dodangeh S¹ ; Parhizkarroudsari P² ; Hosseinkhani S³ ; Khashayar P⁴ ; Noorchenarboo M⁵ ; Rezaei N⁶ ; Dilmaghanimarand A⁶ ; Yoosefi M⁶ ; Arjmand B⁷ ; Khalagi K^{8, 9} ; Najjar N¹⁰ ; Kakaei A⁹ ; Bandarian F¹⁰ Show All Authors Show Affiliations
Source: Frontiers in Cardiovascular Medicine Published:2023

Abstract

Background: The intermediate metabolites associated with the development of atherosclerotic cardiovascular disease (ASCVD) remain largely unknown. Thus, we conducted a large panel of metabolomics profiling to identify the new candidate metabolites that were associated with 10-year ASCVD risk. Methods: Thirty acylcarnitines and twenty amino acids were measured in the fasting plasma of 1,102 randomly selected individuals using a targeted FIA-MS/MS approach. The 10-year ASCVD risk score was calculated based on 2013 ACC/AHA guidelines. Accordingly, the subjects were stratified into four groups: low-risk (n = 620), borderline-risk (n = 110), intermediate-risk (n = 225), and high-risk (n = 147). 10 factors comprising collinear metabolites were extracted from principal component analysis. Results: C4DC, C8:1, C16OH, citrulline, histidine, alanine, threonine, glycine, glutamine, tryptophan, phenylalanine, glutamic acid, arginine, and aspartic acid were significantly associated with the 10-year ASCVD risk score (p-values ≤ 0.044). The high-risk group had higher odds of factor 1 (12 long-chain acylcarnitines, OR = 1.103), factor 2 (5 medium-chain acylcarnitines, OR = 1.063), factor 3 (methionine, leucine, valine, tryptophan, tyrosine, phenylalanine, OR = 1.074), factor 5 (6 short-chain acylcarnitines, OR = 1.205), factor 6 (5 short-chain acylcarnitines, OR = 1.229), factor 7 (alanine, proline, OR = 1.343), factor 8 (C18:2OH, glutamic acid, aspartic acid, OR = 1.188), and factor 10 (ornithine, citrulline, OR = 1.570) compared to the low-risk ones; the odds of factor 9 (glycine, serine, threonine, OR = 0.741), however, were lower in the high-risk group. “D-glutamine and D-glutamate metabolism”, “phenylalanine, tyrosine, and tryptophan biosynthesis”, and “valine, leucine, and isoleucine biosynthesis” were metabolic pathways having the highest association with borderline/intermediate/high ASCVD events, respectively. Conclusions: Abundant metabolites were found to be associated with ASCVD events in this study. Utilization of this metabolic panel could be a promising strategy for early detection and prevention of ASCVD events. 2023 Dehghanbanadaki, Dodangeh, Parhizkar Roudsari, Hosseinkhani, Khashayar, Noorchenarboo, Rezaei, Dilmaghani-Marand, Yoosefi, Arjmand, Khalagi, Najjar, Kakaei, Bandarian, Aghaei Meybodi, Larijani and Razi.