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Untargeted Metabolomics Profiling Reveals Perturbations in Arginine-NO Metabolism in Middle Eastern Patients with Coronary Heart Disease

journal contribution
submitted on 2024-04-16, 06:31 and posted on 2024-04-16, 06:32 authored by Ehsan Ullah, Ayman El-Menyar, Khalid Kunji, Reem Elsousy, Haira R. B. Mokhtar, Eiman Ahmad, Maryam Al-Nesf, Alka Beotra, Mohammed Al-Maadheed, Vidya Mohamed-Ali, Mohamad Saad, Jassim Al Suwaidi

Coronary heart disease (CHD) is a major cause of death in Middle Eastern (ME) populations, with current studies of the metabolic fingerprints of CHD lacking in diversity. Identification of specific biomarkers to uncover potential mechanisms for developing predictive models and targeted therapies for CHD is urgently needed for the least-studied ME populations. A case-control study was carried out in a cohort of 1001 CHD patients and 2999 controls. Untargeted metabolomics was used, generating 1159 metabolites. Univariate and pathway enrichment analyses were performed to understand functional changes in CHD. A metabolite risk score (MRS) was developed to assess the predictive performance of CHD using multivariate analysis and machine learning. A total of 511 metabolites were significantly different between the CHD patients and the controls (FDR p < 0.05). The enriched pathways (FDR p < 10−300) included D-arginine and D-ornithine metabolism, glycolysis, oxidation and degradation of branched chain fatty acids, and sphingolipid metabolism. MRS showed good discriminative power between the CHD cases and the controls (AUC = 0.99). In this first study in the Middle East, known and novel circulating metabolites and metabolic pathways associated with CHD were identified. A small panel of metabolites can efficiently discriminate CHD cases and controls and therefore can be used as a diagnostic/predictive tool.

Other Information

Published in: Metabolites
License: https://creativecommons.org/licenses/by/4.0/
See article on publisher's website: https://dx.doi.org/10.3390/metabo12060517

History

Language

  • English

Publisher

MDPI

Publication Year

  • 2022

License statement

This Item is licensed under the Creative Commons Attribution 4.0 International License.

Institution affiliated with

  • Hamad Bin Khalifa University
  • Qatar Computing Research Institute - HBKU
  • Hamad Medical Corporation
  • Heart Hospital - HMC
  • Hamad General Hospital - HMC
  • Weill Cornell Medical College in Qatar (-2015)
  • Anti-Doping Laboratory Qatar - QA-DC

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