ArticleScientific reports2017
A Metabolomics Signature Linked To Liver Fibrosis In The Serum Of Transplanted Hepatitis C Patients.
Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed.
- Plasma sphingolipids predict advanced liver fibrosis development in patients with type 2 diabetes.Diabetes, obesity & metabolism · 2025Article
- Liver fibrosis and cirrhosis in the multi-omics era: mechanisms and therapeutic perspectives from human and animal models.Frontiers in cellular and infection microbiology · 2025Review
- Metabolomics in liver diseases: A novel alternative for liver biopsy?World journal of hepatology · 2024Article
- A Comprehensive Review of Liver Allograft Fibrosis and Steatosis: From Cause to Diagnosis.Transplantation direct · 2023Review
- Gender-Specific Differences in Serum Sphingomyelin Species in Patients with Hepatitis C Virus Infection-Sphingomyelin Species Are Related to the Model of End-Stage Liver Disease (MELD) Score in Male Patients.International journal of molecular sciences · 2023Article
- NMR-Based Metabolomics to Evaluate Individual Response to Treatments.Handbook of experimental pharmacology · 2023Article
- Metabolomics in viral hepatitis: advances and review.Frontiers in cellular and infection microbiology · 2023Review
- Recent Progress and Future Direction for the Application of Multiomics Data in Clinical Liver Transplantation.Journal of clinical and translational hepatology · 2022Review
- Serum metabolic signatures of schizophrenia patients complicated with hepatitis B virus infection: AFrontiers in psychiatry · 2022Article
- Metabolomics in infectious diseases and drug discovery.Molecular omics · 2021Review
- Metabolic fingerprint of progression of chronic hepatitis B: changes in the metabolome and novel diagnostic possibilities.Metabolomics : Official journal of the Metabolomic Society · 2021Article
- Early detection of metabolic changes in drug-induced steatosis using metabolomics approaches.RSC advances · 2020Article
- Bile Acid Changes Associated With Liver Fibrosis and Steatosis in the Mexican-American Population of South Texas.Hepatology communications · 2020Article
- Reprogramming of cellular metabolic pathways by human oncogenic viruses.Current opinion in virology · 2019Review
- Review
- The metabolic fingerprints of HCV and HBV infections studied by Nuclear Magnetic Resonance Spectroscopy.Scientific reports · 2019Article
- A Pilot Study of Serum Sphingomyelin Dynamics in Subjects with Severe Obesity and Non-alcoholic Steatohepatitis after Sleeve Gastrectomy.Obesity surgery · 2019Article
- A Lipidomics Study Reveals Lipid Signatures Associated with Early Allograft Dysfunction in Living Donor Liver Transplantation.Journal of clinical medicine · 2018Article
- Molecular signatures of liver dysfunction are distinct in fungal and bacterial infections in mice.Theranostics · 2018Article
Corrections and comments
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Authors and funding
13 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Liver fibrosis must be evaluated in patients with hepatitis C virus (HCV) after liver transplantation because its severity affects their prognosis and the recurrence of HCV. Since invasive biopsy is still the gold standard to identify patients at risk of graft loss from rapid fibrosis progression, it becomes crucial the development of new accurate, non-invasive methods that allow repetitive examination of the patients. Therefore, we have developed a non-invasive, accurate model to distinguish those patients with different liver fibrosis stages. Two hundred and three patients with HCV were histologically classified (METAVIR) into five categories of fibrosis one year after liver transplantation. In this cross-sectional study, patients at fibrosis stages F0-F1 (n = 134) were categorised as "slow fibrosers" and F2-F4 (n = 69) as "rapid fibrosers". Chloroform/methanol serum extracts were analysed by reverse ultra-high performance liquid chromatography coupled to mass spectrometry. A diagnostic model was built through linear discriminant analyses. An algorithm consisting of two sphingomyelins and two phosphatidylcholines accurately classifies rapid and slow fibrosers after transplantation. The proposed model yielded an AUROC of 0.92, 71% sensitivity, 85% specificity, and 84% accuracy. Moreover, specific bile acids and sphingomyelins increased notably along with liver fibrosis severity, differentiating between rapid and slow fibrosers.
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