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Published on: January 28, 2020
Metabolic profiles predict adverse events after coronary artery bypass grafting
Asad A Shah1, Damian M Craig, Jacqueline K Sebek
1Division of Thoracic and Cardiovascular Surgery, Department of Surgery, Duke University Medical Center, Durham, NC 27710, USA.
Insights
Metabolic profiles predict adverse events after coronary artery bypass grafting (CABG). Specific metabolite factors, including short-chain dicarboxylacylcarnitines and ketone-related metabolites, offer novel biomarkers for improved risk stratification in CABG patients.
Area of Science:
- Cardiovascular Medicine
- Metabolomics
- Biomarker Discovery
Background:
- Clinical models for predicting outcomes after coronary artery bypass grafting (CABG) are insufficient.
- Novel molecular technologies offer potential for identifying biomarkers to enhance risk stratification.
- Metabolic profiling presents a promising avenue for improving patient risk assessment.
Purpose of the Study:
- To investigate whether pre-operative metabolic profiles can predict adverse events in patients undergoing CABG.
- To identify specific metabolic signatures associated with poor outcomes post-CABG.
- To explore the potential of metabolic biomarkers for augmenting existing risk stratification tools.
Main Methods:
- Analysis of 478 patients from the CATHGEN biorepository who underwent CABG.
- Targeted mass spectrometry profiling of 69 metabolites in pre-operative plasma samples.
- Principal components analysis and Cox proportional hazards regression to assess metabolite factors and adverse outcomes.
Main Results:
- During a mean follow-up of 4.3 years, 26.4% of patients experienced an adverse event.
- Three metabolite factors—short-chain dicarboxylacylcarnitines, ketone-related metabolites, and short-chain acylcarnitines—were significantly associated with adverse outcomes.
- These factors remained independently predictive of adverse events after multivariate adjustment.
Conclusions:
- Pre-operative metabolic profiles are independently associated with adverse outcomes following CABG.
- These metabolic profiles may serve as novel biomarkers for risk stratification in CABG patients.
- The findings may elucidate novel biochemical pathways contributing to adverse outcomes after CABG.
Objective:
Clinical models incompletely predict the outcomes after coronary artery bypass grafting. Novel molecular technologies can identify biomarkers to improve risk stratification. We examined whether metabolic profiles can predict adverse events in patients undergoing coronary artery bypass grafting.
Methods:
The study population comprised 478 subjects from the CATHGEN biorepository of patients referred for cardiac catheterization who underwent coronary artery bypass grafting after enrollment. Targeted mass spectrometry-based profiling of 69 metabolites was performed in frozen, fasting plasma samples collected before surgery. Principal components analysis and Cox proportional hazards regression modeling were used to assess the relation between the metabolite factor levels and a composite outcome of postcoronary artery bypass grafting myocardial infarction, the need for percutaneous coronary intervention, repeat coronary artery bypass grafting, and death.
Results:
During a mean follow-up period of 4.3 ± 2.4 years, 126 subjects (26.4%) experienced an adverse event. Three principal components analysis-derived factors were significantly associated with an adverse outcome on univariate analysis: short-chain dicarboxylacylcarnitines (factor 2, P = .001); ketone-related metabolites (factor 5, P = .02); and short-chain acylcarnitines (factor 6, P = .004). These 3 factors remained independently predictive of an adverse outcome after multivariate adjustment: factor 2 (adjusted hazard ratio, 1.23; 95% confidence interval, 1.10-1.38; P < .001), factor 5 (odds ratio, 1.17; 95% confidence interval, 1.01-1.37; P = .04), and factor 6 (odds ratio, 1.14; 95% confidence interval, 1.02-1.27; P = .03).
Conclusions:
Metabolic profiles are independently associated with adverse outcomes after coronary artery bypass grafting. These profiles might represent novel biomarkers of risk that can augment existing tools for risk stratification of coronary artery bypass grafting patients and might elucidate novel biochemical pathways that mediate risk.
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