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Analysis of a urinary biomarker panel for clinical outcomes assessment in cirrhosis.
PLoS One. 2015; 10(6):e0128145.Plos

Abstract

BACKGROUND

Biomarkers are potentially useful in assessment of outcomes in patients with cirrhosis, but information is very limited. Given the large number of biomarkers, adequate choice of which biomarker(s) to investigate first is important.

AIM

Analysis of potential usefulness of a panel of urinary biomarkers in outcome assessment in cirrhosis.

PATIENTS AND METHODS

Fifty-five patients with acute decompensation of cirrhosis were studied: 39 had Acute Kidney Injury (AKI) (Prerenal 12, type-1 HRS (hepatorenal syndrome) 15 and Acute Tubular Necrosis (ATN) 12) and 16 acute decompensation without AKI. Thirty-four patients had Acute-on-chronic liver failure (ACLF). A panel of 12 urinary biomarkers was assessed, using a multiplex assay, for their relationship with ATN, ACLF and mortality.

RESULTS

Biomarker with best accuracy for ATN diagnosis was NGAL (neutrophil-gelatinase associated lipocalin): 36 [26-125], 104 [58-208] and 1807 [494-3,716] μg/g creatinine in Prerenal-AKI, type-1 HRS and ATN, respectively; p<0.0001 (AUROC 0.957). Other attractive biomarkers for ATN diagnosis were IL-18, albumin, trefoil-factor-3 (TFF-3) and glutathione-S-transferase-π (GST-π) Biomarkers with less accuracy for ATN AUCROC<0.8 were β2-microglobulin, calbindin, cystatin-C, clusterin and KIM-1 (kidney injury molecule-1). For ACLF, the biomarker with the best accuracy was NGAL (ACLF vs. No-ACLF: 165 [67-676] and 32 [19-40] μg/g creatinine; respectively; p<0.0001; AUROC 0.878). Interestingly, other biomarkers with high accuracy for ACLF were osteopontin, albumin, and TFF-3. Biomarkers with best accuracy for prognosis were those associated with ACLF.

CONCLUSIONS

A number of biomarkers appear promising for differential diagnosis between ATN and other types of AKI. The most interesting biomarkers for ACLF and prognosis are NGAL, osteopontin, albumin, and TFF-3. These results support the role of major inflammatory reaction in the pathogenesis of ACLF.

Authors+Show Affiliations

Liver Unit, Hospital Clínic, University of Barcelona, Barcelona, Catalunya, Spain; Institut d'Investigacions Biomèdiques August-Pi-Sunyer (IDIBAPS), Barcelona, Spain; Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBEREHED), Barcelona, Spain; Instituto Reina Sofía de Investigación Nefrológica (IRSIN), Barcelona, Spain.Liver Unit, Hospital Clínic, University of Barcelona, Barcelona, Catalunya, Spain; Institut d'Investigacions Biomèdiques August-Pi-Sunyer (IDIBAPS), Barcelona, Spain; Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBEREHED), Barcelona, Spain; Instituto Reina Sofía de Investigación Nefrológica (IRSIN), Barcelona, Spain.Liver Unit, Hospital Clínic, University of Barcelona, Barcelona, Catalunya, Spain; Institut d'Investigacions Biomèdiques August-Pi-Sunyer (IDIBAPS), Barcelona, Spain; Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBEREHED), Barcelona, Spain; Instituto Reina Sofía de Investigación Nefrológica (IRSIN), Barcelona, Spain.Liver Unit, Hospital Clínic, University of Barcelona, Barcelona, Catalunya, Spain; Institut d'Investigacions Biomèdiques August-Pi-Sunyer (IDIBAPS), Barcelona, Spain; Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBEREHED), Barcelona, Spain; Instituto Reina Sofía de Investigación Nefrológica (IRSIN), Barcelona, Spain.Liver Unit, Hospital Clínic, University of Barcelona, Barcelona, Catalunya, Spain; Institut d'Investigacions Biomèdiques August-Pi-Sunyer (IDIBAPS), Barcelona, Spain; Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBEREHED), Barcelona, Spain; Instituto Reina Sofía de Investigación Nefrológica (IRSIN), Barcelona, Spain.Institut d'Investigacions Biomèdiques August-Pi-Sunyer (IDIBAPS), Barcelona, Spain; Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBEREHED), Barcelona, Spain; Biochemistry and Molecular Genetics Department, Hospital Clínic, University of Barcelona, Barcelona, Catalunya, Spain.Liver Unit, Hospital Clínic, University of Barcelona, Barcelona, Catalunya, Spain; Institut d'Investigacions Biomèdiques August-Pi-Sunyer (IDIBAPS), Barcelona, Spain; Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBEREHED), Barcelona, Spain; Instituto Reina Sofía de Investigación Nefrológica (IRSIN), Barcelona, Spain.Liver Unit, Hospital Clínic, University of Barcelona, Barcelona, Catalunya, Spain; Institut d'Investigacions Biomèdiques August-Pi-Sunyer (IDIBAPS), Barcelona, Spain; Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBEREHED), Barcelona, Spain; Instituto Reina Sofía de Investigación Nefrológica (IRSIN), Barcelona, Spain.Liver Unit, Hospital Clínic, University of Barcelona, Barcelona, Catalunya, Spain; Institut d'Investigacions Biomèdiques August-Pi-Sunyer (IDIBAPS), Barcelona, Spain; Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBEREHED), Barcelona, Spain; Instituto Reina Sofía de Investigación Nefrológica (IRSIN), Barcelona, Spain.Liver Unit, Hospital Clínic, University of Barcelona, Barcelona, Catalunya, Spain; Institut d'Investigacions Biomèdiques August-Pi-Sunyer (IDIBAPS), Barcelona, Spain; Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBEREHED), Barcelona, Spain; Instituto Reina Sofía de Investigación Nefrológica (IRSIN), Barcelona, Spain.Liver Unit, Hospital Clínic, University of Barcelona, Barcelona, Catalunya, Spain; Institut d'Investigacions Biomèdiques August-Pi-Sunyer (IDIBAPS), Barcelona, Spain; Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBEREHED), Barcelona, Spain; Instituto Reina Sofía de Investigación Nefrológica (IRSIN), Barcelona, Spain.Institut d'Investigacions Biomèdiques August-Pi-Sunyer (IDIBAPS), Barcelona, Spain; Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBEREHED), Barcelona, Spain; Biochemistry and Molecular Genetics Department, Hospital Clínic, University of Barcelona, Barcelona, Catalunya, Spain.Liver Unit, Hospital Clínic, University of Barcelona, Barcelona, Catalunya, Spain; Institut d'Investigacions Biomèdiques August-Pi-Sunyer (IDIBAPS), Barcelona, Spain; Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBEREHED), Barcelona, Spain; Instituto Reina Sofía de Investigación Nefrológica (IRSIN), Barcelona, Spain.Liver Unit, Hospital Clínic, University of Barcelona, Barcelona, Catalunya, Spain; Institut d'Investigacions Biomèdiques August-Pi-Sunyer (IDIBAPS), Barcelona, Spain; Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBEREHED), Barcelona, Spain; Instituto Reina Sofía de Investigación Nefrológica (IRSIN), Barcelona, Spain.

Pub Type(s)

Journal Article
Research Support, Non-U.S. Gov't

Language

eng

PubMed ID

26042740

Citation

Ariza, Xavier, et al. "Analysis of a Urinary Biomarker Panel for Clinical Outcomes Assessment in Cirrhosis." PloS One, vol. 10, no. 6, 2015, pp. e0128145.
Ariza X, Solà E, Elia C, et al. Analysis of a urinary biomarker panel for clinical outcomes assessment in cirrhosis. PLoS ONE. 2015;10(6):e0128145.
Ariza, X., Solà, E., Elia, C., Barreto, R., Moreira, R., Morales-Ruiz, M., Graupera, I., Rodríguez, E., Huelin, P., Solé, C., Fernández, J., Jiménez, W., Arroyo, V., & Ginès, P. (2015). Analysis of a urinary biomarker panel for clinical outcomes assessment in cirrhosis. PloS One, 10(6), e0128145. https://doi.org/10.1371/journal.pone.0128145
Ariza X, et al. Analysis of a Urinary Biomarker Panel for Clinical Outcomes Assessment in Cirrhosis. PLoS ONE. 2015;10(6):e0128145. PubMed PMID: 26042740.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Analysis of a urinary biomarker panel for clinical outcomes assessment in cirrhosis. AU - Ariza,Xavier, AU - Solà,Elsa, AU - Elia,Chiara, AU - Barreto,Rogelio, AU - Moreira,Rebeca, AU - Morales-Ruiz,Manuel, AU - Graupera,Isabel, AU - Rodríguez,Ezequiel, AU - Huelin,Patricia, AU - Solé,Cristina, AU - Fernández,Javier, AU - Jiménez,Wladimiro, AU - Arroyo,Vicente, AU - Ginès,Pere, Y1 - 2015/06/04/ PY - 2015/02/10/received PY - 2015/04/22/accepted PY - 2015/6/5/entrez PY - 2015/6/5/pubmed PY - 2016/5/4/medline SP - e0128145 EP - e0128145 JF - PloS one JO - PLoS ONE VL - 10 IS - 6 N2 - BACKGROUND: Biomarkers are potentially useful in assessment of outcomes in patients with cirrhosis, but information is very limited. Given the large number of biomarkers, adequate choice of which biomarker(s) to investigate first is important. AIM: Analysis of potential usefulness of a panel of urinary biomarkers in outcome assessment in cirrhosis. PATIENTS AND METHODS: Fifty-five patients with acute decompensation of cirrhosis were studied: 39 had Acute Kidney Injury (AKI) (Prerenal 12, type-1 HRS (hepatorenal syndrome) 15 and Acute Tubular Necrosis (ATN) 12) and 16 acute decompensation without AKI. Thirty-four patients had Acute-on-chronic liver failure (ACLF). A panel of 12 urinary biomarkers was assessed, using a multiplex assay, for their relationship with ATN, ACLF and mortality. RESULTS: Biomarker with best accuracy for ATN diagnosis was NGAL (neutrophil-gelatinase associated lipocalin): 36 [26-125], 104 [58-208] and 1807 [494-3,716] μg/g creatinine in Prerenal-AKI, type-1 HRS and ATN, respectively; p<0.0001 (AUROC 0.957). Other attractive biomarkers for ATN diagnosis were IL-18, albumin, trefoil-factor-3 (TFF-3) and glutathione-S-transferase-π (GST-π) Biomarkers with less accuracy for ATN AUCROC<0.8 were β2-microglobulin, calbindin, cystatin-C, clusterin and KIM-1 (kidney injury molecule-1). For ACLF, the biomarker with the best accuracy was NGAL (ACLF vs. No-ACLF: 165 [67-676] and 32 [19-40] μg/g creatinine; respectively; p<0.0001; AUROC 0.878). Interestingly, other biomarkers with high accuracy for ACLF were osteopontin, albumin, and TFF-3. Biomarkers with best accuracy for prognosis were those associated with ACLF. CONCLUSIONS: A number of biomarkers appear promising for differential diagnosis between ATN and other types of AKI. The most interesting biomarkers for ACLF and prognosis are NGAL, osteopontin, albumin, and TFF-3. These results support the role of major inflammatory reaction in the pathogenesis of ACLF. SN - 1932-6203 UR - https://www.unboundmedicine.com/medline/citation/26042740/Analysis_of_a_urinary_biomarker_panel_for_clinical_outcomes_assessment_in_cirrhosis_ L2 - http://dx.plos.org/10.1371/journal.pone.0128145 DB - PRIME DP - Unbound Medicine ER -