Cargando…

The value of serum metabolomics analysis in predicting the response to cardiac resynchronization therapy

OBJECTIVE: To construct a prediction model based on metabolic profiling for predicting the response to cardiac resynchronization therapy (CRT). METHODS: Peripheral venous (PV) and coronary sinus (CS) blood samples were collected from 25 patients with heart failure (HF) at the time of CRT implantatio...

Descripción completa

Detalles Bibliográficos
Autores principales: Zhu, Meng-Ruo, Fulati, Zibire, Liu, Yang, Wang, Wen-Shuo, Wu, Qian, Su, Yan-Gang, Chen, Hai-Yan, Shu, Xian-Hong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Science Press 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6689524/
https://www.ncbi.nlm.nih.gov/pubmed/31447892
http://dx.doi.org/10.11909/j.issn.1671-5411.2019.07.002
_version_ 1783443035411972096
author Zhu, Meng-Ruo
Fulati, Zibire
Liu, Yang
Wang, Wen-Shuo
Wu, Qian
Su, Yan-Gang
Chen, Hai-Yan
Shu, Xian-Hong
author_facet Zhu, Meng-Ruo
Fulati, Zibire
Liu, Yang
Wang, Wen-Shuo
Wu, Qian
Su, Yan-Gang
Chen, Hai-Yan
Shu, Xian-Hong
author_sort Zhu, Meng-Ruo
collection PubMed
description OBJECTIVE: To construct a prediction model based on metabolic profiling for predicting the response to cardiac resynchronization therapy (CRT). METHODS: Peripheral venous (PV) and coronary sinus (CS) blood samples were collected from 25 patients with heart failure (HF) at the time of CRT implantation, and PV blood samples were obtained from ten healthy controls. The serum samples were analyzed by liquid chromatography-mass spectrometry (LC-MS). As per the clinical and echocardiographic assessment at the 6-month follow-up, the HF patients were categorized as CRT responders and non-responders. RESULTS: HF patients had altered serum metabolomic profiles that were significantly different from those of the healthy controls. Differential metabolites were also observed between CRT responders and non-responders. A prediction model for CRT response (CRT-Re) was constructed using the concentration levels of the differential metabolites, L-arginine and taurine. The optimal cutoff value of the CRT-Re model was found to be 0.343 by ROC analysis (sensitivity, 88.2%; specificity, 87.5%; Area under curve (AUC) = 0.897, P = 0.002). The concentration levels of the differential metabolites, L-arginine and lysyl-gamma-glutamate, in PV serum were significantly correlated with that in CS serum (r = 0.945 and 0.680, respectively, all P < 0.001). CONCLUSIONS: Our results suggest that serum-based metabolic profiling may be a potential complementary screening tool for predicting the outcome of CRT.
format Online
Article
Text
id pubmed-6689524
institution National Center for Biotechnology Information
language English
publishDate 2019
publisher Science Press
record_format MEDLINE/PubMed
spelling pubmed-66895242019-08-23 The value of serum metabolomics analysis in predicting the response to cardiac resynchronization therapy Zhu, Meng-Ruo Fulati, Zibire Liu, Yang Wang, Wen-Shuo Wu, Qian Su, Yan-Gang Chen, Hai-Yan Shu, Xian-Hong J Geriatr Cardiol Research Article OBJECTIVE: To construct a prediction model based on metabolic profiling for predicting the response to cardiac resynchronization therapy (CRT). METHODS: Peripheral venous (PV) and coronary sinus (CS) blood samples were collected from 25 patients with heart failure (HF) at the time of CRT implantation, and PV blood samples were obtained from ten healthy controls. The serum samples were analyzed by liquid chromatography-mass spectrometry (LC-MS). As per the clinical and echocardiographic assessment at the 6-month follow-up, the HF patients were categorized as CRT responders and non-responders. RESULTS: HF patients had altered serum metabolomic profiles that were significantly different from those of the healthy controls. Differential metabolites were also observed between CRT responders and non-responders. A prediction model for CRT response (CRT-Re) was constructed using the concentration levels of the differential metabolites, L-arginine and taurine. The optimal cutoff value of the CRT-Re model was found to be 0.343 by ROC analysis (sensitivity, 88.2%; specificity, 87.5%; Area under curve (AUC) = 0.897, P = 0.002). The concentration levels of the differential metabolites, L-arginine and lysyl-gamma-glutamate, in PV serum were significantly correlated with that in CS serum (r = 0.945 and 0.680, respectively, all P < 0.001). CONCLUSIONS: Our results suggest that serum-based metabolic profiling may be a potential complementary screening tool for predicting the outcome of CRT. Science Press 2019-07 /pmc/articles/PMC6689524/ /pubmed/31447892 http://dx.doi.org/10.11909/j.issn.1671-5411.2019.07.002 Text en Institute of Geriatric Cardiology http://creativecommons.org/licenses/by-nc-sa/3.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported License, which allows readers to alter, transform, or build upon the article and then distribute the resulting work under the same or similar license to this one. The work must be attributed back to the original author and commercial use is not permitted without specific permission.
spellingShingle Research Article
Zhu, Meng-Ruo
Fulati, Zibire
Liu, Yang
Wang, Wen-Shuo
Wu, Qian
Su, Yan-Gang
Chen, Hai-Yan
Shu, Xian-Hong
The value of serum metabolomics analysis in predicting the response to cardiac resynchronization therapy
title The value of serum metabolomics analysis in predicting the response to cardiac resynchronization therapy
title_full The value of serum metabolomics analysis in predicting the response to cardiac resynchronization therapy
title_fullStr The value of serum metabolomics analysis in predicting the response to cardiac resynchronization therapy
title_full_unstemmed The value of serum metabolomics analysis in predicting the response to cardiac resynchronization therapy
title_short The value of serum metabolomics analysis in predicting the response to cardiac resynchronization therapy
title_sort value of serum metabolomics analysis in predicting the response to cardiac resynchronization therapy
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6689524/
https://www.ncbi.nlm.nih.gov/pubmed/31447892
http://dx.doi.org/10.11909/j.issn.1671-5411.2019.07.002
work_keys_str_mv AT zhumengruo thevalueofserummetabolomicsanalysisinpredictingtheresponsetocardiacresynchronizationtherapy
AT fulatizibire thevalueofserummetabolomicsanalysisinpredictingtheresponsetocardiacresynchronizationtherapy
AT liuyang thevalueofserummetabolomicsanalysisinpredictingtheresponsetocardiacresynchronizationtherapy
AT wangwenshuo thevalueofserummetabolomicsanalysisinpredictingtheresponsetocardiacresynchronizationtherapy
AT wuqian thevalueofserummetabolomicsanalysisinpredictingtheresponsetocardiacresynchronizationtherapy
AT suyangang thevalueofserummetabolomicsanalysisinpredictingtheresponsetocardiacresynchronizationtherapy
AT chenhaiyan thevalueofserummetabolomicsanalysisinpredictingtheresponsetocardiacresynchronizationtherapy
AT shuxianhong thevalueofserummetabolomicsanalysisinpredictingtheresponsetocardiacresynchronizationtherapy
AT zhumengruo valueofserummetabolomicsanalysisinpredictingtheresponsetocardiacresynchronizationtherapy
AT fulatizibire valueofserummetabolomicsanalysisinpredictingtheresponsetocardiacresynchronizationtherapy
AT liuyang valueofserummetabolomicsanalysisinpredictingtheresponsetocardiacresynchronizationtherapy
AT wangwenshuo valueofserummetabolomicsanalysisinpredictingtheresponsetocardiacresynchronizationtherapy
AT wuqian valueofserummetabolomicsanalysisinpredictingtheresponsetocardiacresynchronizationtherapy
AT suyangang valueofserummetabolomicsanalysisinpredictingtheresponsetocardiacresynchronizationtherapy
AT chenhaiyan valueofserummetabolomicsanalysisinpredictingtheresponsetocardiacresynchronizationtherapy
AT shuxianhong valueofserummetabolomicsanalysisinpredictingtheresponsetocardiacresynchronizationtherapy