A plasma peptidomic signature reveals extracellular matrix remodeling and predicts prognosis in alcohol-associated hepatitis

Author:

Sayed Khaled12ORCID,Dolin Christine E.3,Wilkey Daniel W.3,Li Jiang4ORCID,Sato Toshifumi4,Beier Juliane I.45,Argemi Josepmaria46ORCID,Vatsalya Vatsalya78,McClain Craig J.78,Bataller Ramon9ORCID,Wahed Abdus S.10,Merchant Michael L.38,Benos Panayiotis V.1,Arteel Gavin E.45

Affiliation:

1. Department of Epidemiology, University of Florida, Gainesville, Florida, USA

2. Department of Electrical & Computer Engineering and Computer Science, University of New Haven, West Haven, Connecticut, USA

3. Department of Medicine, University of Louisville, Louisville, Kentucky, USA

4. Department of Medicine, Division of Gastroenterology, Hepatology and Nutrition, University of Pittsburgh, Pittsburgh, Pennsylvania, USA

5. Pittsburgh Liver Research Center, University of Pittsburgh, Pittsburgh, Pennsylvania, USA

6. Department of Internal Medicine, Clinical University of Navarra, Navarra, Spain

7. Department of Medicine, Division of Gastroenterology, Hepatology and Nutrition, University of Louisville, Louisville, Kentucky, USA

8. University of Louisville Alcohol Research Center, University of Louisville, Louisville, Kentucky, USA

9. Liver Unit, Hospital Clinic. Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain

10. Department of Biostatistics and Computational Biology, University of Rochester, Rochester, New York, USA

Abstract

Background: Alcohol-associated hepatitis (AH) is plagued with high mortality and difficulty in identifying at-risk patients. The extracellular matrix undergoes significant remodeling during inflammatory liver injury and could potentially be used for mortality prediction. Methods: EDTA plasma samples were collected from patients with AH (n = 62); Model for End-Stage Liver Disease score defined AH severity as moderate (12–20; n = 28) and severe (>20; n = 34). The peptidome data were collected by high resolution, high mass accuracy UPLC-MS. Univariate and multivariate analyses identified differentially abundant peptides, which were used for Gene Ontology, parent protein matrisomal composition, and protease involvement. Machine-learning methods were used to develop mortality predictors. Results: Analysis of plasma peptides from patients with AH and healthy controls identified over 1600 significant peptide features corresponding to 130 proteins. These were enriched for extracellular matrix fragments in AH samples, likely related to the turnover of hepatic-derived proteins. Analysis of moderate versus severe AH peptidomes was dominated by changes in peptides from collagen 1A1 and fibrinogen A proteins. The dominant proteases for the AH peptidome spectrum appear to be CAPN1 and MMP12. Causal graphical modeling identified 3 peptides directly linked to 90-day mortality in >90% of the learned graphs. These peptides improved the accuracy of mortality prediction over the Model for End-Stage Liver Disease score and were used to create a clinically applicable mortality prediction assay. Conclusions: A signature based on plasma peptidome is a novel, noninvasive method for prognosis stratification in patients with AH. Our results could also lead to new mechanistic and/or surrogate biomarkers to identify new AH mechanisms.

Publisher

Ovid Technologies (Wolters Kluwer Health)

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