Title

Metabolomic patterns in heart failure patients vary across demographic and clinical factors

Document Type

Conference Proceeding

Publication Date

8-2015

Publication Title

J Card Fail

Abstract

Background: Measurement of small molecules of intermediary metabolism (‘metabolites’) is an emerging method for characterizing a host of diverse disease states. Heart Failure (HF) is of particular interest since there is evidence that energetic derangements contribute to progression and certain metabolites have correlated with prognosis. Systematic description of metabolite patterns in large numbers of HF patients has not been described.

Methods: We analyzed plasma samples from 400 patients with chronic HF. All participants met Framingham criteria for HF and had a previous echocardiogram. Data on demographics, comorbid conditions, functional status (6 minute walk distance [6MWD]), and quality of life (Kansas City Cardiomyopathy Questionnaire [KCCQ]) were collected. A blood sample was obtained and aliquoted plasma stored at -70 OC. Eighty-six amino acids (AA), organic acids (OA) and acylcarnitines (AC) were quantified using targeted metabolomic profiling. Analytes with coefficient of variation

Results: The cohort was 50% African American, 50% female, 67% HFrEF, and had an average age of 70. There were significant differences in metabolite abundance by each characteristic examined, including race and gender. A strong pattern emerged for citric acid cycle intermediates and HF phenotype; one or more of these intermediates showed significant association with HF type, NYHA class, and 6MWD. Also of note was an increased abundance of short branched-chain AC among diabetics, which was not accompanied by the expected increase in corresponding branched-chain AA. Each of these associations persisted after adjustment for renal function.

Conclusion: There are significant differences in plasma metabolomic profiles among HF patients. Metabolites vary by demographics and diabetes status, and citric acid cycle intermediates may be associated with disease severity/prognosis. Analysis in larger data sets is warranted.

Volume

21

Issue

8 Suppl

First Page

S88

Last Page

S89

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