Analysis of Differentially Expressed Proteins Involved in Autoimmune Cirrhosis and Normal Serum by iTRAQ Proteomics

Abstract

Purpose: In order to study the candidate biomarkers in autoimmune cirrhosis (AIC).

Experimental design: Isobaric tags are first implemented for relative and absolute quantitation technology on proteins prepared from serum obtained from AIC and normal controls. Proteins found to be differentially expressed are identified with liquid chromatography electrospray ionization tandem mass spectrometry by using a Q Exactive classic ion trap mass spectrometer.

Results: 108 proteins (32 upregulated and 76 downregulated proteins) are identified from AIC samples, compared with the normal controls. Gene Ontology enrichment analysis, KEGG pathway analysis, and protein-protein interaction map by STRING show that they associate with multiple functional groups, including ion binding activity, peptidase activity, and enzyme regulator activity. Finally, the von Willebrand factor, insulin-like growth factor-binding protein complex acid labile subunit, transthyretin, adiponectin proteins are identified with western blot as candidate biomarkers for AIC.

Conclusions and clinical relevance: These findings offer a comprehensive profile of the AIC proteome about candidate biomarkers and provide a useful basis for further analysis of the pathogenic mechanism of AIC.

Keywords: LC-ESI MS/MS; autoimmune cirrhosis; autoimmune hepatitis; biomarker; iTRAQ.

Figure 1

General work flow and summary of the present study. iTRAQ technology was applied to identify the differentially expressed proteins in autoimmune cirrhosis and normal controls. At the end of the study, we combined the results of bioinformatics analysis to identify vWF, adiponectin, IFGALS, and transthyretin proteins as candidate biomarkers for autoimmune cirrhosis.

Figure 2

Identification and analysis of the autoimmune cirrhosis proteome. A) Total spectra, spectra identified, distinct peptides, proteins before grouping, and proteins detected from iTRAQ proteomic analysis. B) Protein numbers were grouped based on protein mass. C) Protein numbers were distinguished on the basis of peptide numbers. D) The identified proteins were classified into pie charts according to the protein's sequence coverage.

Figure 3

GO assignment of differential expression of proteins in autoimmune cirrhosis. A) Molecular function. B) Cellular component. C) Biological processes.

Figure 4

Interaction network analysis of differential expression of proteins. In this network, nodes are proteins, lines represent functional associations between proteins, and different line colors represent the types of evidence for the predicted functional association. A red line indicates the presence of fusion evidence; a green line indicates neighborhood evidence; a blue line indicates co‐ocurrence evidence; a purple line indicates experimental evidence; a yellow line indicates text mining evidence; a light blue line indicates database evidence; a black line indicates coexpression evidence.

Figure 5

MS/MS spectrum to show the iTRAQ quantification. A representative MS/MS spectrum showed peptide signatures for vWF, adiponectin, IFGALS, transthyretin, pIgR, apoA1, apoE, and gelsolin. Ratios of iTRAQ tags indicate the relative abundance of the eight proteins individually in autoimmune cirrhosis serum compared to corresponding control samples.

Figure 6

Western blot validation of selected proteins in the iTRAQ data set. Representative western blots for three proteins validated in serum with vWF, adiponectin, IFGALS, pIgR, transthyretin, apoA, apoE, and gelsolin. Data are expressed as the mean. Control (n = 120), AIH (n = 90), AIC (n = 90), HBV (n = 120), HCV (n = 120). *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001.

Figure 7

Receiver operating characteristic (ROC) curves for selected proteins in autoimmune cirrhosis and autoimmune hepatitis. ROC analysis for vWF alone, adiponectin alone, IFGALS alone, pIgR alone, transthyretin alone, apoA alone, apoE alone, gelsolin alone, and their combination in the diagnosis of AIC and AIH.