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Transcriptomics unveils immune metabolic disruption and a novel biomarker of mortality in patients with HBV-related acute-on-chronic liver failure.
Liang, Xi; Li, Peng; Jiang, Jing; Xin, Jiaojiao; Luo, Jinjin; Li, Jiaqi; Chen, Pengcheng; Ren, Keke; Zhou, Qian; Guo, Beibei; Zhou, Xingping; Chen, Jiaxian; He, Lulu; Yang, Hui; Hu, Wen; Ma, Shiwen; Li, Bingqi; Chen, Xin; Shi, Dongyan; Li, Jun.
Afiliación
  • Liang X; Precision Medicine Center, Taizhou Central Hospital (Taizhou University Hospital), Taizhou, 318000, China.
  • Li P; State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, National Medical Center for Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310003, China.
  • Jiang J; State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, National Medical Center for Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310003, China.
  • Xin J; State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, National Medical Center for Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310003, China.
  • Luo J; State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, National Medical Center for Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310003, China.
  • Li J; State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, National Medical Center for Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310003, China.
  • Chen P; State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, National Medical Center for Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310003, China.
  • Ren K; Institute of Big Data and Artificial Intelligence in Medicine, School of Electronics and Information Engineering, Taizhou University, Taizhou, China.
  • Zhou Q; State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, National Medical Center for Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310003, China.
  • Guo B; State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, National Medical Center for Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310003, China.
  • Zhou X; State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, National Medical Center for Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310003, China.
  • Chen J; State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, National Medical Center for Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310003, China.
  • He L; State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, National Medical Center for Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310003, China.
  • Yang H; State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, National Medical Center for Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310003, China.
  • Hu W; State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, National Medical Center for Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310003, China.
  • Ma S; State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, National Medical Center for Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310003, China.
  • Li B; State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, National Medical Center for Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310003, China.
  • Chen X; State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, National Medical Center for Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310003, China.
  • Shi D; Institute of Pharmaceutical Biotechnology and the First Affiliated Hospital, Department of Radiation Oncology, Zhejiang University School of Medicine, Hangzhou, China.
  • Li J; Joint Institute for Genetics and Genome Medicine between Zhejiang University and University of Toronto, Zhejiang University, Hangzhou, China.
JHEP Rep ; 5(9): 100848, 2023 Sep.
Article en En | MEDLINE | ID: mdl-37583946
ABSTRACT
Background &

Aims:

HBV-related acute-on-chronic liver failure (HBV-ACLF) is a complex syndrome associated with high short-term mortality. This study aims to reveal the molecular basis and identify novel HBV-ACLF biomarkers.

Methods:

Seventy patients with HBV-ACLF and different short-term (28 days) outcomes underwent transcriptome sequencing using peripheral blood mononuclear cells. Candidate biomarkers were confirmed in two external cohorts using ELISA.

Results:

Cellular composition analysis with peripheral blood mononuclear cell transcriptomics showed that the proportions of monocytes, T cells and natural killer cells were significantly correlated with 28-day mortality. Significant metabolic dysregulation of carbohydrate, energy and amino acid metabolism was observed in ACLF non-survivors. V-set and immunoglobulin domain-containing 4 (VSIG4) was the most robust predictor of patient survival (adjusted p = 1.74 × 10-16; variable importance in the projection = 1.21; AUROC = 0.89) and was significantly correlated with pathways involved in the progression of ACLF, including inflammation, oxidative phosphorylation, tricarboxylic acid cycle and T-cell activation/differentiation. Plasma VSIG4 analysis externally validated its diagnostic value in ACLF (compared with chronic liver disease and healthy groups, AUROC = 0.983). The prognostic performance for 28-/90-day mortality (AUROCs = 0.769/0.767) was comparable to that of three commonly used scores (COSSH-ACLFs, 0.867/0.884; CLIF-C ACLFs, 0.840/0.835; MELD-Na, 0.710/0.737). Plasma VSIG4 level, as an independent predictor, could be used to improve the prognostic performance of clinical scores. Risk stratification based on VSIG4 expression levels (>122 µg/ml) identified patients with ACLF at a high risk of death. The generality of VSIG4 in other etiologies was validated.

Conclusions:

This study reveals that immune-metabolism disorder underlies poor ACLF outcomes. VSIG4 may be helpful as a diagnostic and prognostic biomarker in clinical practice. Impact and implications Acute-on-chronic liver failure (ACLF) is a lethal clinical syndrome associated with high mortality. We found significant immune cell alterations and metabolic dysregulation that were linked to high mortality in patients with HBV-ACLF based on transcriptomics using peripheral blood mononuclear cells. We identified VSIG4 (V-set and immunoglobulin domain-containing 4) as a diagnostic and prognostic biomarker in ACLF, which could specifically identify patients with ACLF at a high risk of death.
Palabras clave

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: JHEP Rep Año: 2023 Tipo del documento: Article País de afiliación: China

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: JHEP Rep Año: 2023 Tipo del documento: Article País de afiliación: China
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