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. 2012 Apr;143(4):873-8.
doi: 10.1016/j.jtcvs.2011.09.070. Epub 2012 Feb 4.

Metabolic profiles predict adverse events after coronary artery bypass grafting

Asad A Shah  1 , Damian M Craig, Jacqueline K Sebek, Carol Haynes, Robert C Stevens, Michael J Muehlbauer, Christopher B Granger, Elizabeth R Hauser, L Kristin Newby, Christopher B Newgard, William E Kraus, G Chad Hughes, Svati H Shah
Affiliations

Metabolic profiles predict adverse events after coronary artery bypass grafting

Asad A Shah et al. J Thorac Cardiovasc Surg. 2012 Apr.

Abstract

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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Figures

Figure 1
Figure 1. Kaplan-Meier curve for the relationship between factor 2 levels and adverse events
Displayed is an adjusted Kaplan-Meier curve of the relationship between tertiles of metabolite factor 2 and event-free survival after CABG, adjusted for all variables retained in the final multivariable model, demonstrating a linear relationship between factor 2 levels and decreased event-free survival.
Figure 2
Figure 2. Kaplan-Meier curve for the relationship between factor 5 levels and adverse events
Displayed is an adjusted Kaplan-Meier curve of the relationship between tertiles of metabolite factor 5 and event-free survival after CABG, adjusted for all variables retained in the final multivariable model, demonstrating a linear relationship between factor 5 levels and decreased event-free survival.
Figure 3
Figure 3. Kaplan-Meier curve for the relationship between factor 6 levels and adverse events
Displayed is an adjusted Kaplan-Meier curve of the relationship between tertiles of metabolite factor 6 and event-free survival after CABG, adjusted for all variables retained in the final multivariable model, demonstrating a linear relationship between factor 6 levels and decreased event-free survival.
See this image and copyright information in PMC

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