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Amino acid profiling to predict prognosis in patients with heart failure: an expert review

Heart failure is a complex disease with a poor prognosis. A number of widely used prognostic tools have limitations, so efforts to identify novel predictive markers and measures are important. As a metabolomics tool, amino acid profiling has shown promise in predicting heart failure prognosis; howev...

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Autores principales: Hiraiwa, Hiroaki, Okumura, Takahiro, Murohara, Toyoaki
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9871678/
https://www.ncbi.nlm.nih.gov/pubmed/36300549
http://dx.doi.org/10.1002/ehf2.14222
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author Hiraiwa, Hiroaki
Okumura, Takahiro
Murohara, Toyoaki
author_facet Hiraiwa, Hiroaki
Okumura, Takahiro
Murohara, Toyoaki
author_sort Hiraiwa, Hiroaki
collection PubMed
description Heart failure is a complex disease with a poor prognosis. A number of widely used prognostic tools have limitations, so efforts to identify novel predictive markers and measures are important. As a metabolomics tool, amino acid profiling has shown promise in predicting heart failure prognosis; however, the evidence has not yet been sufficiently evaluated. We describe the utilization of amino acids in the healthy heart and in heart failure before reviewing the literature on amino acid profiling for prognostic prediction. We expertly interpret the findings and provide suggestions for future research to advance the understanding of the prognostic potential of amino acid profiling in heart failure. Our analysis revealed correlations between amino acid biomarkers and traditional prognostic factors, the additional prognostic value of amino acid biomarkers over traditional prognostic factors, and the successful use of amino acid biomarkers to distinguish heart failure aetiology. Although certain amino acid biomarkers have demonstrated additional prognostic value over traditional measures, such as New York Heart Association functional class, these measures are deeply rooted in clinical practice; thus, amino acid biomarkers may be best placed as additional prognostic tools to improve current risk stratification rather than as surrogate tools. Once the metabolic profiles of different heart failure aetiologies have been clearly delineated, the amino acid biomarkers with the most value in prognostic prediction should be determined. Amino acid profiling could be useful to evaluate the pathophysiology and metabolic status of different heart failure cohorts, distinguish heart failure aetiologies, and improve risk stratification and prognostic prediction.
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spelling pubmed-98716782023-01-25 Amino acid profiling to predict prognosis in patients with heart failure: an expert review Hiraiwa, Hiroaki Okumura, Takahiro Murohara, Toyoaki ESC Heart Fail Reviews Heart failure is a complex disease with a poor prognosis. A number of widely used prognostic tools have limitations, so efforts to identify novel predictive markers and measures are important. As a metabolomics tool, amino acid profiling has shown promise in predicting heart failure prognosis; however, the evidence has not yet been sufficiently evaluated. We describe the utilization of amino acids in the healthy heart and in heart failure before reviewing the literature on amino acid profiling for prognostic prediction. We expertly interpret the findings and provide suggestions for future research to advance the understanding of the prognostic potential of amino acid profiling in heart failure. Our analysis revealed correlations between amino acid biomarkers and traditional prognostic factors, the additional prognostic value of amino acid biomarkers over traditional prognostic factors, and the successful use of amino acid biomarkers to distinguish heart failure aetiology. Although certain amino acid biomarkers have demonstrated additional prognostic value over traditional measures, such as New York Heart Association functional class, these measures are deeply rooted in clinical practice; thus, amino acid biomarkers may be best placed as additional prognostic tools to improve current risk stratification rather than as surrogate tools. Once the metabolic profiles of different heart failure aetiologies have been clearly delineated, the amino acid biomarkers with the most value in prognostic prediction should be determined. Amino acid profiling could be useful to evaluate the pathophysiology and metabolic status of different heart failure cohorts, distinguish heart failure aetiologies, and improve risk stratification and prognostic prediction. John Wiley and Sons Inc. 2022-10-27 /pmc/articles/PMC9871678/ /pubmed/36300549 http://dx.doi.org/10.1002/ehf2.14222 Text en © 2022 The Authors. ESC Heart Failure published by John Wiley & Sons Ltd on behalf of European Society of Cardiology. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ (https://creativecommons.org/licenses/by-nc-nd/4.0/) License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.
spellingShingle Reviews
Hiraiwa, Hiroaki
Okumura, Takahiro
Murohara, Toyoaki
Amino acid profiling to predict prognosis in patients with heart failure: an expert review
title Amino acid profiling to predict prognosis in patients with heart failure: an expert review
title_full Amino acid profiling to predict prognosis in patients with heart failure: an expert review
title_fullStr Amino acid profiling to predict prognosis in patients with heart failure: an expert review
title_full_unstemmed Amino acid profiling to predict prognosis in patients with heart failure: an expert review
title_short Amino acid profiling to predict prognosis in patients with heart failure: an expert review
title_sort amino acid profiling to predict prognosis in patients with heart failure: an expert review
topic Reviews
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9871678/
https://www.ncbi.nlm.nih.gov/pubmed/36300549
http://dx.doi.org/10.1002/ehf2.14222
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