Literature DB >> 30207476

Discovery and Validation of Potential Serum Biomarkers for Pediatric Patients with Congenital Heart Diseases by Metabolomics.

Mengjie Yu1, Shuilin Sun1, Jiangqing Yu2,3, Fen Du1, Shouhua Zhang4, Wenlong Yang1, Juhua Xiao5, Baogang Xie1.   

Abstract

To identify and screen serum biomarkers to determine pediatric patients with congenital heart diseases (PCH) from healthy control children (NC), a total of 614 clinically diagnosed subjects from three hospitals, including 491 PCH and 234 NC, were enrolled for nontargeted proton nuclear magnetic resonance spectroscopy (1H NMR)-based and targeted ultra-high-performance liquid chromatography-tandem mass spectroscopy (UPLC-MS/MS)-based metabolomics studies. Nineteen serum metabolites distinguishing PCH from NC were identified by 1H NMR-based metabolomic analysis. The amino acid and choline metabolic pathways were considered to be closely related to PCH. The serum levels of 13 metabolites in these two pathways were further determined by UPLC-MS/MS and observed to be altered significantly in PCH. Taurine, glutamine, and glutamate presented considerable diagnostic value for the diagnosis of PCH (AUROC > 0.80). Logistic regression analysis showed that a combination of four variables, namely, betaine, taurine, glutamine, and phenylalanine, yields a high diagnostic value (AUROC = 0.949) and prediction accuracy (89.1%) for differentiating PCH from the NC, and the sensitivity and specificity were 93.9 and 95.2%, respectively. Further double-blind sample prediction showed that the accuracy of the model was 83.8% for 80 unknown samples. Our results showed that the serum amino acid and choline metabolite levels in PCH were changed considerably. The combination of four metabolites, namely, betaine, taurine, glutamine, and phenylalanine, can be used as potential serum biomarkers in PCH diagnosis, which contributes to the early PCH screening.

Entities:  

Keywords:  diagnostic biomarkers; metabolomics; pediatric patients with congenital heart diseases; predictive modeling

Mesh:

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Year:  2018        PMID: 30207476     DOI: 10.1021/acs.jproteome.8b00466

Source DB:  PubMed          Journal:  J Proteome Res        ISSN: 1535-3893            Impact factor:   4.466


  4 in total

1.  Metabolomic profiling suggests systemic signatures of premature aging induced by Hutchinson-Gilford progeria syndrome.

Authors:  Gustavo Monnerat; Geisa Paulino Caprini Evaristo; Joseph Albert Medeiros Evaristo; Caleb Guedes Miranda Dos Santos; Gabriel Carneiro; Leonardo Maciel; Vânia Oliveira Carvalho; Fábio César Sousa Nogueira; Gilberto Barbosa Domont; Antonio Carlos Campos de Carvalho
Journal:  Metabolomics       Date:  2019-06-28       Impact factor: 4.290

Review 2.  The metabolome identity: basis for discovery of biomarkers in neurodegeneration.

Authors:  Julie-Myrtille Bourgognon; Joern R Steinert
Journal:  Neural Regen Res       Date:  2019-03       Impact factor: 5.135

3.  Identification of metabolomic profile related to adult Fontan pathophysiology.

Authors:  Noriko Motoki; Hirohiko Motoki; Masafumi Utsumi; Shoko Yamazaki; Haruka Obinata; Kohta Takei; Satoshi Yasukochi
Journal:  Int J Cardiol Heart Vasc       Date:  2021-11-24

4.  Comprehensive metabolomic characterization of atrial fibrillation.

Authors:  Chengcan Lu; Chunyan Liu; Di Mei; Mengjie Yu; Jian Bai; Xue Bao; Min Wang; Kejia Fu; Xin Yi; Weihong Ge; Jizhong Shen; Yuzhu Peng; Wei Xu
Journal:  Front Cardiovasc Med       Date:  2022-08-08
  4 in total

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