Prognostic significance of metabolomic biomarkers in patients with diabetes mellitus and coronary artery disease.


Journal

Cardiovascular diabetology
ISSN: 1475-2840
Titre abrégé: Cardiovasc Diabetol
Pays: England
ID NLM: 101147637

Informations de publication

Date de publication:
07 05 2022
Historique:
received: 05 03 2022
accepted: 06 04 2022
entrez: 7 5 2022
pubmed: 8 5 2022
medline: 11 5 2022
Statut: epublish

Résumé

Diabetes mellitus (DM) and coronary artery disease (CAD) constitute inter-related clinical entities. Biomarker profiling emerges as a promising tool for the early diagnosis and risk stratification of either DM or CAD. However, studies assessing the predictive capacity of novel metabolomics biomarkers in coexistent CAD and DM are scarce. This post-hoc analysis of the CorLipid trial (NCT04580173) included 316 patients with CAD and comorbid DM who underwent emergency or elective coronary angiography due to acute or chronic coronary syndrome. Cox regression analyses were performed to identify metabolomic predictors of the primary outcome, which was defined as the composite of major adverse cardiovascular or cerebrovascular events (MACCE: cardiovascular death, myocardial infarction, stroke, major bleeding), repeat unplanned revascularizations and cardiovascular hospitalizations. Linear regression analyses were also performed to detect significant predictors of CAD complexity, as assessed by the SYNTAX score. After a median 2-year follow up period (IQR = 0.7 years), the primary outcome occurred in 69 (21.8%) of patients. Acylcarnitine ratio C4/C18:2, apolipoprotein (apo) B, history of heart failure (HF), age > 65 years and presence of acute coronary syndrome were independent predictors of the primary outcome in diabetic patients with CAD (aHR = 1.89 [1.09, 3.29]; 1.02 [1.01, 1.04]; 1.28 [1.01, 1.41]; 1.04 [1.01, 1.05]; and 1.12 [1.05-1.21], respectively). Higher levels of ceramide ratio C24:1/C24:0, acylcarnitine ratio C4/C18:2, age > 65 and peripheral artery disease were independent predictors of higher CAD complexity (adjusted β = 7.36 [5.74, 20.47]; 3.02 [0.09 to 6.06]; 3.02 [0.09, 6.06], respectively), while higher levels of apoA1 were independent predictors of lower complexity (adjusted β= - 0.65 [- 1.31, - 0.02]). In patients with comorbid DM and CAD, novel metabolomic biomarkers and metabolomics-based prediction models could be recruited to predict clinical outcomes and assess the complexity of CAD, thereby enabling the integration of personalized medicine into routine clinical practice. These associations should be interpreted taking into account the observational nature of this study, and thus, larger trials are needed to confirm its results and validate them in different and larger diabetic populations.

Sections du résumé

BACKGROUND
Diabetes mellitus (DM) and coronary artery disease (CAD) constitute inter-related clinical entities. Biomarker profiling emerges as a promising tool for the early diagnosis and risk stratification of either DM or CAD. However, studies assessing the predictive capacity of novel metabolomics biomarkers in coexistent CAD and DM are scarce.
METHODS
This post-hoc analysis of the CorLipid trial (NCT04580173) included 316 patients with CAD and comorbid DM who underwent emergency or elective coronary angiography due to acute or chronic coronary syndrome. Cox regression analyses were performed to identify metabolomic predictors of the primary outcome, which was defined as the composite of major adverse cardiovascular or cerebrovascular events (MACCE: cardiovascular death, myocardial infarction, stroke, major bleeding), repeat unplanned revascularizations and cardiovascular hospitalizations. Linear regression analyses were also performed to detect significant predictors of CAD complexity, as assessed by the SYNTAX score.
RESULTS
After a median 2-year follow up period (IQR = 0.7 years), the primary outcome occurred in 69 (21.8%) of patients. Acylcarnitine ratio C4/C18:2, apolipoprotein (apo) B, history of heart failure (HF), age > 65 years and presence of acute coronary syndrome were independent predictors of the primary outcome in diabetic patients with CAD (aHR = 1.89 [1.09, 3.29]; 1.02 [1.01, 1.04]; 1.28 [1.01, 1.41]; 1.04 [1.01, 1.05]; and 1.12 [1.05-1.21], respectively). Higher levels of ceramide ratio C24:1/C24:0, acylcarnitine ratio C4/C18:2, age > 65 and peripheral artery disease were independent predictors of higher CAD complexity (adjusted β = 7.36 [5.74, 20.47]; 3.02 [0.09 to 6.06]; 3.02 [0.09, 6.06], respectively), while higher levels of apoA1 were independent predictors of lower complexity (adjusted β= - 0.65 [- 1.31, - 0.02]).
CONCLUSIONS
In patients with comorbid DM and CAD, novel metabolomic biomarkers and metabolomics-based prediction models could be recruited to predict clinical outcomes and assess the complexity of CAD, thereby enabling the integration of personalized medicine into routine clinical practice. These associations should be interpreted taking into account the observational nature of this study, and thus, larger trials are needed to confirm its results and validate them in different and larger diabetic populations.

Identifiants

pubmed: 35525960
doi: 10.1186/s12933-022-01494-9
pii: 10.1186/s12933-022-01494-9
pmc: PMC9077877
doi:

Substances chimiques

Biomarkers 0

Banques de données

ClinicalTrials.gov
['NCT04580173']

Types de publication

Clinical Trial Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

70

Informations de copyright

© 2022. The Author(s).

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Auteurs

Efstratios Karagiannidis (E)

First Department of Cardiology, AHEPA University Hospital, Aristotle University of Thessaloniki, St. Kiriakidi 1, 54636, Thessaloniki, Greece. stratoskarag@gmail.com.

Dimitrios V Moysidis (DV)

First Department of Cardiology, AHEPA University Hospital, Aristotle University of Thessaloniki, St. Kiriakidi 1, 54636, Thessaloniki, Greece.

Andreas S Papazoglou (AS)

First Department of Cardiology, AHEPA University Hospital, Aristotle University of Thessaloniki, St. Kiriakidi 1, 54636, Thessaloniki, Greece.

Eleftherios Panteris (E)

Laboratory of Forensic Medicine and Toxicology, School of Medicine, Aristotle University of Thessaloniki, 54124, Thessaloniki, Greece.
Biomic_Auth, Bioanalysis and Omics Lab, Centre for Interdisciplinary Research of Aristotle, University of Thessaloniki, Innovation Area of Thessaloniki, 57001, Thermi, Greece.

Olga Deda (O)

Laboratory of Forensic Medicine and Toxicology, School of Medicine, Aristotle University of Thessaloniki, 54124, Thessaloniki, Greece.
Biomic_Auth, Bioanalysis and Omics Lab, Centre for Interdisciplinary Research of Aristotle, University of Thessaloniki, Innovation Area of Thessaloniki, 57001, Thermi, Greece.

Nikolaos Stalikas (N)

First Department of Cardiology, AHEPA University Hospital, Aristotle University of Thessaloniki, St. Kiriakidi 1, 54636, Thessaloniki, Greece.

Georgios Sofidis (G)

First Department of Cardiology, AHEPA University Hospital, Aristotle University of Thessaloniki, St. Kiriakidi 1, 54636, Thessaloniki, Greece.

Anastasios Kartas (A)

First Department of Cardiology, AHEPA University Hospital, Aristotle University of Thessaloniki, St. Kiriakidi 1, 54636, Thessaloniki, Greece.

Alexandra Bekiaridou (A)

First Department of Cardiology, AHEPA University Hospital, Aristotle University of Thessaloniki, St. Kiriakidi 1, 54636, Thessaloniki, Greece.

George Giannakoulas (G)

First Department of Cardiology, AHEPA University Hospital, Aristotle University of Thessaloniki, St. Kiriakidi 1, 54636, Thessaloniki, Greece.

Helen Gika (H)

Laboratory of Forensic Medicine and Toxicology, School of Medicine, Aristotle University of Thessaloniki, 54124, Thessaloniki, Greece.
Biomic_Auth, Bioanalysis and Omics Lab, Centre for Interdisciplinary Research of Aristotle, University of Thessaloniki, Innovation Area of Thessaloniki, 57001, Thermi, Greece.

George Theodoridis (G)

Biomic_Auth, Bioanalysis and Omics Lab, Centre for Interdisciplinary Research of Aristotle, University of Thessaloniki, Innovation Area of Thessaloniki, 57001, Thermi, Greece.
Laboratory of Analytical Chemistry, Department of Chemistry, Aristotle University of Thessaloniki, Thessaloniki, Greece.

Georgios Sianos (G)

First Department of Cardiology, AHEPA University Hospital, Aristotle University of Thessaloniki, St. Kiriakidi 1, 54636, Thessaloniki, Greece. gsianos@auth.gr.

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