Dataset Information

Knowledge-based identification of soluble biomarkers: hepatic fibrosis in NAFLD as an example.

ABSTRACT: The discovery of biomarkers is often performed using high-throughput proteomics-based platforms and is limited to the molecules recognized by a given set of purified and validated antigens or antibodies. Knowledge-based, or systems biology, approaches that involve the analysis of integrated data, predominantly molecular pathways and networks may infer quantitative changes in the levels of biomolecules not included by the given assay from the levels of the analytes profiled. In this study we attempted to use a knowledge-based approach to predict biomarkers reflecting the changes in underlying protein phosphorylation events using Nonalcoholic Fatty Liver Disease (NAFLD) as a model. Two soluble biomarkers, CCL-2 and FasL, were inferred in silico as relevant to NAFLD pathogenesis. Predictive performance of these biomarkers was studied using serum samples collected from patients with histologically proven NAFLD. Serum levels of both molecules, in combination with clinical and demographic data, were predictive of hepatic fibrosis in a cohort of NAFLD patients. Our study suggests that (1) NASH-specific disruption of the kinase-driven signaling cascades in visceral adipose tissue lead to detectable changes in the levels of soluble molecules released into the bloodstream, and (2) biomarkers discovered in silico could contribute to predictive models for non-malignant chronic diseases.

SUBMITTER: Page S

PROVIDER: S-EPMC3566090 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

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Knowledge-based identification of soluble biomarkers: hepatic fibrosis in NAFLD as an example.

Page Sandra S Birerdinc Aybike A Estep Michael M Stepanova Maria M Afendy Arian A Petricoin Emanuel E Younossi Zobair Z Chandhoke Vikas V Baranova Ancha A

PloS one 20130206 2

The discovery of biomarkers is often performed using high-throughput proteomics-based platforms and is limited to the molecules recognized by a given set of purified and validated antigens or antibodies. Knowledge-based, or systems biology, approaches that involve the analysis of integrated data, predominantly molecular pathways and networks may infer quantitative changes in the levels of biomolecules not included by the given assay from the levels of the analytes profiled. In this study we atte ...[more]

PMID: 23405244

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Project description:BACKGROUND & AIMS:In patients with non-alcoholic fatty liver disease (NAFLD), liver biopsy is the gold standard to detect non-alcoholic steatohepatitis (NASH) and stage liver fibrosis. We aimed to identify differentially expressed mRNAs and non-coding RNAs in serum samples of biopsy-diagnosed mild and severe NAFLD patients with respect to controls and to each other. METHODS:We first performed a whole transcriptome analysis through microarray (n = 12: four Control: CTRL; four mild NAFLD: NAS ? 4 F0; four severe NAFLD NAS ? 5 F3), followed by validation of selected transcripts through real-time PCRs in an independent internal cohort of 88 subjects (63 NAFLD, 25 CTRL) and in an external cohort of 50 NAFLD patients. A similar analysis was also performed on liver biopsies and HepG2 cells exposed to oleate:palmitate or only palmitate (cellular model of NAFL/NASH) at intracellular/extracellular levels. Transcript correlation with histological/clinical data was also analysed. RESULTS:We identified several differentially expressed coding/non-coding RNAs in each group of the study cohort. We validated the up-regulation of UBE2V1, BNIP3L mRNAs, RP11-128N14.5 lncRNA, TGFB2/TGFB2-OT1 coding/lncRNA in patients with NAS ? 5 (vs NAS ? 4) and the up-regulation of HBA2 mRNA, TGFB2/TGFB2-OT1 coding/lncRNA in patients with Fibrosis stages = 3-4 (vs F = 0-2). In in vitro models: UBE2V1, RP11-128N14.5 and TGFB2/TGFB2-OT1 had an increasing expression trend ranging from CTRL to oleate:palmitate or only palmitate-treated cells both at intracellular and extracellular level, while BNIP3L was up-regulated only at extracellular level. UBE2V1, RP11-128N14.5, TGFB2/TGFB2-OT1 and HBA2 up-regulation was also observed at histological level. UBE2V1, RP11-128N14.5, BNIP3L and TGFB2/TGFB2-OT1 correlated with histological/biochemical data. Combinations of TGFB2/TGFB2-OT1 + Fibrosis Index based on the four factors (FIB-4) showed an Area Under the Curve (AUC) of 0.891 (P = 3.00E-06) or TGFB2/TGFB2-OT1 + Fibroscan (AUC = 0.892, P = 2.00E-06) improved the detection of F = 3-4 with respect to F = 0-2 fibrosis stages. CONCLUSIONS:We identified specific serum coding/non-coding RNA profiles in severe and mild NAFLD patients that possibly mirror the molecular mechanisms underlying NAFLD progression towards NASH/fibrosis. TGFB2/TGFB2-OT1 detection improves FIB-4/Fibroscan diagnostic performance for advanced fibrosis discrimination.

Dataset Information

Knowledge-based identification of soluble biomarkers: hepatic fibrosis in NAFLD as an example.

Publications

Knowledge-based identification of soluble biomarkers: hepatic fibrosis in NAFLD as an example.

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