Metabolic Differences among Patients with Cirrhosis Using Q Exactive Hybrid Quadrupole Orbitrap Mass Spectrometry Technology

The hospitalization and mortality rates of patients gradually increase following the onset and progression of liver cirrhosis (LC). We aimed to help define clinical stage and better target interventions by detecting the expression of specific metabolites in patients with different stages of LC via Q...

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Veröffentlicht in:Journal of proteome research 2024-12, Vol.23 (12), p.5352-5359
Hauptverfasser: Xiao, Ying, Lu, Jie, Xu, Suyan, Wu, Zhinian, Wang, Wei, Ji, Ru, Guo, Tingyu, Qi, Zeqiang, Tong, Hua, Wang, Yadong, Zhao, Caiyan
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container_issue 12
container_start_page 5352
container_title Journal of proteome research
container_volume 23
creator Xiao, Ying
Lu, Jie
Xu, Suyan
Wu, Zhinian
Wang, Wei
Ji, Ru
Guo, Tingyu
Qi, Zeqiang
Tong, Hua
Wang, Yadong
Zhao, Caiyan
description The hospitalization and mortality rates of patients gradually increase following the onset and progression of liver cirrhosis (LC). We aimed to help define clinical stage and better target interventions by detecting the expression of specific metabolites in patients with different stages of LC via Q Exactive hybrid quadrupole orbitrap mass spectrometry (UPLC-Q-Exactive) technology. This noninterventional observation case–control study involved 139 patients with LC or acute-on-chronic liver failure (ACLF) in a Chinese hospital between October 2022 and April 2023. Serum specimens were analyzed for multiple metabolite levels using UPLC-Q-Exactive. Data were processed to screen for differentially accumulated metabolites (DAMs). Short time-series expression miner (STEM) analysis and enrichment analysis were performed to assess cirrhosis progression biomarkers. Following univariate and multivariate analyses, a Venn diagram indicated nine significant DAMs in common among groups. STEM analysis showed 8′-hydroxyabscisic acid, HDCA, pyruvate-3-phosphate, indospicine, eplerenone, and DEHP as significant; their levels first peaked [Child–Turcotte–Pugh (CTP) class B peaked] and then decreased with CTP grade aggravation. Significant differences among 8′-hydroxyabscisic acid, eplerenone, and DEHP were observed among LC comorbidities and between subgroups. Therefore, serum levels of six DAMs may characterize metabolomic changes, determine the severity of LC, and predict the development of ACLF.
doi_str_mv 10.1021/acs.jproteome.4c00437
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We aimed to help define clinical stage and better target interventions by detecting the expression of specific metabolites in patients with different stages of LC via Q Exactive hybrid quadrupole orbitrap mass spectrometry (UPLC-Q-Exactive) technology. This noninterventional observation case–control study involved 139 patients with LC or acute-on-chronic liver failure (ACLF) in a Chinese hospital between October 2022 and April 2023. Serum specimens were analyzed for multiple metabolite levels using UPLC-Q-Exactive. Data were processed to screen for differentially accumulated metabolites (DAMs). Short time-series expression miner (STEM) analysis and enrichment analysis were performed to assess cirrhosis progression biomarkers. Following univariate and multivariate analyses, a Venn diagram indicated nine significant DAMs in common among groups. STEM analysis showed 8′-hydroxyabscisic acid, HDCA, pyruvate-3-phosphate, indospicine, eplerenone, and DEHP as significant; their levels first peaked [Child–Turcotte–Pugh (CTP) class B peaked] and then decreased with CTP grade aggravation. Significant differences among 8′-hydroxyabscisic acid, eplerenone, and DEHP were observed among LC comorbidities and between subgroups. 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subjects Acute-On-Chronic Liver Failure - blood
Acute-On-Chronic Liver Failure - metabolism
Adult
Aged
Biomarkers - blood
Case-Control Studies
Disease Progression
Female
Humans
Liver Cirrhosis - blood
Liver Cirrhosis - metabolism
Male
Mass Spectrometry - methods
Metabolome
Metabolomics - methods
Middle Aged
title Metabolic Differences among Patients with Cirrhosis Using Q Exactive Hybrid Quadrupole Orbitrap Mass Spectrometry Technology
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