Metabolomics as a tool to predict the risk of decompensation or liver-related death in patients with compensated cirrhosis-Reference-Cited by-同舟云学术

Metabolomics as a tool to predict the risk of decompensation or liver-related death in patients with compensated cirrhosis

Published:2023-02-23 Issue:6 Volume:77 Page:2052-2062
ISSN:0270-9139
Container-title:Hepatology
language:en
Short-container-title:

Author:

Nicoară-Farcău Oana¹²^ORCID,Lozano Juan J.³⁴^ORCID,Alonso Cristina⁵^ORCID,Sidorova Julia³⁴^ORCID,Villanueva Càndid⁴⁶⁷^ORCID,Albillos Augustín⁴⁸^ORCID,Genescà Joan⁴⁷⁹^ORCID,Llop Elba⁴¹⁰^ORCID,Calleja Jose L.⁴¹⁰^ORCID,Aracil Carles¹¹^ORCID,Bañares Rafael⁴¹²^ORCID,Morillas Rosa⁴⁷¹³^ORCID,Poca Maria⁴⁶^ORCID,Peñas Beatriz⁴⁸^ORCID,Augustin Salvador⁴⁷⁹^ORCID,Tantău Marcel²^ORCID,Thompson Marcos¹¹⁴^ORCID,Perez-Campuzano Valeria¹^ORCID,Baiges Anna¹⁴^ORCID,Turon Fanny¹⁴^ORCID,Hernández-Gea Virginia¹⁴^ORCID,Abraldes Juan G.¹⁴¹⁵^ORCID,Tapias Edilmar A.⁴⁶^ORCID,Torres Ferran¹⁶¹⁷^ORCID,Bosch Jaime¹⁴¹⁸^ORCID,García-Pagán Juan C.¹⁴^ORCID,

Affiliation:

1. Barcelona Hepatic Hemodynamic Laboratory, Liver Unit, Hospital Clínic, Institut de Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), University of Barcelona, Barcelona, Spain

2. Gastroenterology Department, Regional Institute of Gastroenterology and Hepatology ‘Prof. Dr. Octavian Fodor’, University of Medicine and Pharmacy ‘Iuliu Hatieganu’, Cluj-Napoca, Romania

3. Bioinformatics Platform, Institut de Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain

4. Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBERehd), Instituto De Salud Carlos III, Spain

5. OWL Metabolomics, Bizkaia, Spain

6. Hospital De La Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau (IIB Sant Pau), Barcelona, Spain

7. Autonomus University of Barcelona, Barcelona, Spain

8. Ramón y Cajal University Hospital, Ramón y Cajal Institute of Health Research (IRYCIS), University of Alcalá, Madrid, Spain

9. Liver Unit, Hospital Universitari Vall d’Hebron, Vall d’Hebron Institute of Research (VHIR), Vall d’Hebron Barcelona Hospital Campus, Barcelona, Spain

10. Puerta de Hierro University Hospital, Puerta de Hierro Hospital, Research Institute, Autonomous University of Madrid, Madrid, Spain

11. Institute of Biomedical Research, Arnau de Vilanova University Hospital (IRBLleida), Lleida, Spain

12. Gregorio Marañón University General Hospital, Gregorio Marañón Sanitary Research Institute, Faculty of Medicine, Complutense University of Madrid, Madrid, Spain

13. Hepatology Department, Hospital Germans Trias I Pujol, Germans Trias I Pujol Research Institute, Badalona, Spain

14. Hepatology Department, Hospital Universitario Austral, Buenos Aires, Argentina

15. Liver Unit, University of Alberta, Edmonton, Alberta, Canada

16. Medical Statistics Core Facility, Hospital Clínic, Institut de Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain

17. Biostatistics Unit, Medical School, Universitat Autònoma de Barcelona, Barcelona, Spain

18. Department of Visceral Surgery and Medicine, Inselspital, Bern University Hospital, Switzerland

Abstract

Background and Aims: Patients with compensated cirrhosis with clinically significant portal hypertension (CSPH: HVPG >10 mm Hg) have a high risk of decompensation. HVPG is, however, an invasive procedure not available in all centers. The present study aims to assess whether metabolomics can improve the capacity of clinical models in predicting clinical outcomes in these compensated patients. Approach and Results: This is a nested study from the PREDESCI cohort (an RCT of nonselective beta-blockers vs. placebo in 201 patients with compensated cirrhosis and CSPH), including 167 patients for whom a blood sample was collected. A targeted metabolomic serum analysis, using ultra-high-performance liquid chromatography-mass spectrometry, was performed. Metabolites underwent univariate time-to-event cox regression analysis. Top-ranked metabolites were selected using Log-Rank p-value to generate a stepwise cox model. Comparison between models was done using DeLong test. Eighty-two patients with CSPH were randomized to nonselective beta-blockers and 85 to placebo. Thirty-three patients developed the main endpoint (decompensation/liver-related death). The model, including HVPG, Child-Pugh, and treatment received (HVPG/Clinical model), had a C-index of 0.748 (CI95% 0.664–0.827). The addition of 2 metabolites, ceramide (d18:1/22:0) and methionine (HVPG/Clinical/Metabolite model), significantly improved the model’s performance [C-index of 0.808 (CI95% 0.735–0.882); p=0.032]. The combination of these 2 metabolites together with Child-Pugh and the type of treatment received (Clinical/Metabolite model) had a C-index of 0.785 (CI95% 0.710–0.860), not significantly different from the HVPG-based models including or not metabolites. Conclusions: In patients with compensated cirrhosis and CSPH, metabolomics improves the capacity of clinical models and achieves similar predictive capacity than models including HVPG.

Publisher

Ovid Technologies (Wolters Kluwer Health)

Subject

Hepatology

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