Basic Study Open Access
Copyright ©The Author(s) 2015. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Gastroenterol. Jul 14, 2015; 21(26): 8032-8042
Published online Jul 14, 2015. doi: 10.3748/wjg.v21.i26.8032
Changes in gene expression in liver tissue from patients with fulminant hepatitis E
Anshu Naik, Amit Goel, Aditya N Sarangi, Nanda Chhavi, Rakesh Aggarwal, Department of Gastroenterology, Sanjay Gandhi Postgraduate Institute of Medical Sciences, Lucknow 226014, India
Vinita Agrawal, Department of Pathology, Sanjay Gandhi Postgraduate Institute of Medical Sciences, Lucknow 226014, India
Vineeta Singh, Sandor Proteomics Pvt Ltd, Hyderabad 500034, India
Shahid Jameel, Virology Group, International Centre for Genetic Engineering and Biotechnology, New Delhi 110067, India
Author contributions: Naik A carried out the laboratory work and data analysis, and prepared the first draft of the manuscript; Goel A carried out initial screening and identification of patients and liver biopsies, and helped in drafting and critical revision of the manuscript; Agrawal V supervised the histological and immunohistochemical studies; Sarangi AN did the microarray data analysis and helped in drafting the related segments of the manuscript, and in critical revision of the manuscript; Chhavi N carried out initial screening and identification of patients and liver biopsies; Singh V did the laboratory work related to microarray analysis; Jameel S conceived the idea, participated in design of the study and interpretation of data, and helped revise the manuscript; Aggarwal R conceived the idea, participated in design of the study, clinical identification of patients, supervision of laboratory work, analysis of microarray data and overall supervision of the work, and helped in drafting and revision of the manuscript; all authors read and approved the final manuscript.
Supported by National Institutes of Health, Bethesda, United States, No. 5R01AI076192.
Institutional review board statement: The study was reviewed and approved by Sanjay Gandhi Postgraduate Institute of Medical Sciences institutional review board. Written, informed consent was obtained from and all patient or their families, as appropriate.
Institutional animal care and use committee statement: Exempt, since this study did not include the use of any animals.
Conflict-of-interest statement: None of the authors listed on the above manuscript had any conflict of interest, either financial or non-financial in relation to this paper.
Data sharing statement: Participants gave informed consent for data sharing. The corresponding author would be willing to share the data as required for the above manuscript with the editors.
Open-Access: This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
Correspondence to: Dr. Rakesh Aggarwal, Department of Gastroenterology, Sanjay Gandhi Postgraduate Institute of Medical Sciences, Lucknow 226014, India. aggarwal.ra@gmail.com
Telephone: +91-522-2494431 Fax: +91-522-2668017
Received: January 29, 2015
Peer-review started: January 30, 2015
First decision: March 10, 2015
Revised: March 27, 2015
Accepted: May 2, 2015
Article in press: May 4, 2015
Published online: July 14, 2015
Processing time: 165 Days and 18.7 Hours

Abstract

AIM: To study host gene expression and number of immune cells in liver tissues from patients with fulminant hepatitis E (FH-E).

METHODS: Microarray-based expression profiling was done using Illumina Human WG-6_v3_BeadChip arrays on post-mortem liver tissue from 5 patients with FH-E, and compared with similar tissue from 6 patients with fulminant hepatitis B (FH-B; disease controls) and normal liver tissue from 6 persons. Differential expression was defined as ≥ 2.0-fold change with Benjamini-Hochberg false discovery rate below 0.05 using t-test in liver tissue from FH-B and FH-E, than healthy liver tissue. For some genes that showed differential expression in FH-E, microarray data were validated using quantitative reverse transcription PCR. Differentially expressed gene lists were then subjected to “Gene Ontology” analysis for biological processes, and pathway analysis using BioCarta database on the DAVID server. In addition, tissue sections were stained for CD4+, CD8+ and CD56+ cells using indirect immunohistochemistry; cells staining positive for each of these markers were counted and compared between groups.

RESULTS: Compared to normal livers, those from patients with FH-E and FH-B showed differential expression of 3377 entities (up-regulated 1703, downregulated 1674) and 2572 entities (up 1164, down 1408), respectively. This included 2142 (up 896, down 1246) entities that were common between the two sets; most of these belonged to metabolic, hemostatic and complement pathways, which are active in normal livers. Gene expression data from livers of patients with FH-E but not those of FH-B showed activation of several immune response pathways, particularly those involving cytotoxic T cells. The fold-change values of mRNA for selected genes in livers from FH-E than in normal liver tissue determined using quantitative reverse transcription PCR showed excellent concordance with microarray analysis. At immunohistochemistry, CD8+ T cells showed an increase in liver biopsies from both FH-E [median 53.4 per arbitrary unit area (range 31.2-99.9)] and FH-B [median 49.3 (19.3-51.0); P = 0.005] compared to control liver tissue [median 6.9 (3.1-14.9)].

CONCLUSION: FH-E patients show CD8+ T cell infiltration and increased gene expression of cytotoxic T cell pathways in liver, suggesting a possible pathogenetic role for these cells.

Key Words: Cytotoxic T cells; Gene expression; Hepatitis E; Hepatitis E virus; Immune response; Liver biopsy; Microarray; Natural killer cells; Pathogenesis

Core tip: Data on pathogenesis of hepatitis E virus (HEV) infection, which is a common cause of acute hepatitis in several developing countries, are quite limited. This manuscript reports our data on microarray-based gene expression analysis and immunohistochemistry in liver tissue from patients with HEV infection, as compared to liver tissue from patients with hepatitis B virus infection and normal liver tissue. These data advance the current knowledge about the pathogenesis of HEV infection.



INTRODUCTION

Hepatitis E virus (HEV), a member of genus Hepevirus in family Hepeviridae, consists of 32-34 nm diameter, icosahedral, non-enveloped virions[1]. It has a 7.2-kb single-stranded, positive-sense RNA genome with three open reading frames (ORFs) that code for a viral non-structural polyprotein (ORF1), the major capsid protein (ORF2) and a phosphoprotein with possible regulatory functions (ORF3)[1]. The virus has at least four genotypes, named 1 to 4[2]; however, these all belong to a single serotype.

HEV infection is common in developing countries of Asia and Africa, where it causes an acute disease, known as hepatitis E, either as water-borne outbreaks or as sporadic cases[3,4], caused by infection through the fecal-oral route. The disease occurs predominantly among young adults and resembles acute hepatitis caused by other hepatotropic viruses. It is usually self-limiting, with overall case fatality rate below 0.5%[3]. However, some patients, in particular pregnant women, develop severe liver injury that progresses to fulminant hepatic failure (FH), which is often fatal. In these areas, the virus belongs most often to genotype 1 and sometimes to genotype 2[3,4].

In areas with lower disease endemicity, such as Europe, North America, Japan, etc., occasional cases with locally-acquired HEV infection have been reported[5]. These are mainly elderly men, often with other co-existing diseases, who are believed to acquire infection with genotype 3 or 4 HEV through ingestion of undercooked meat of HEV-infected animals[6]. In immunosuppressed persons, the infection may become persistent[6].

To develop therapeutic measures against hepatitis E, it is important to understand the pathogenesis of liver injury in this disease. In infection with other hepatotropic viruses, such as the hepatitis A, B and C viruses, tissue injury is mediated not by the infectious agent but is related to the host immune response[7-11]. We have shown that HEV infection is associated with activation of specific cellular immune responses in the peripheral blood[12-16]. However, little data are available on the liver tissue from hepatitis E. Therefore, the mechanism of liver injury in this disease remains unclear.

We therefore studied gene expression profile in liver biopsies from patients with FH due to acute hepatitis E (FH-E), in comparison with those from healthy adults and patients with FH due to acute hepatitis B (FH-B; a disease control group).

MATERIALS AND METHODS
Patients and specimens

Post-mortem needle liver biopsies were obtained from patients dying of FH-E (n = 5) or of FH-B (n = 6). The biopsies were obtained within 30 min after death, and separate pieces were collected in RNALater (Qiagen) and stored at -80 °C for gene expression analysis, and in formalin for histology and immunohistochemistry. In addition, a blood specimen was collected from each subject, for biochemical tests and serological markers of viral hepatitis.

Patients dying more than 2 wk after the onset of disease, and those with major sepsis or clinical evidence of pre-existing liver disease were excluded. Diagnosis of acute hepatitis E was based on detection of IgM anti-HEV (Genelabs, Singapore) in the absence of hepatitis B surface antigen (HBsAg), IgM anti-HBc antibody, anti-hepatitis C virus (HCV) antibody and IgM anti-hepatitis A virus (HAV) antibody (all from BioMerieux, Marcy l'Etoile, France), and that of acute hepatitis B on detection of HBsAg and IgM anti-HBc, in the absence of IgM anti-HEV, anti-HCV and IgM anti-HAV.

In addition, normal liver tissue was obtained from six persons undergoing partial hepatic resection for focal diseases, such as hydatid liver disease, gallbladder cancer without biliary obstruction.

The study was reviewed and approved by Sanjay Gandhi Postgraduate Institute of Medical Sciences institutional review board. Written, informed consent was obtained from all patients or their families, as appropriate.

RNA isolation

Total RNA was isolated from tissue biopsies using RNeasy Protect minikit (Qiagen, Carlsbad, CA). RNA concentration was measured using NanoDrop 1000 spectrophotometer (Nanodrop, Wilmington, DE). RNA integrity was assessed using Bioanalyzer 2100 (Agilent, Santa Clara, CA). Specimens with A260/A280 and A260/A230 ratios > 1.9, and RIN > 8.0 were processed further.

Microarray analysis

Gene expression profiling was done using Illumina Human WG-6_v3_BeadChip arrays (Illumina, San Diego, CA), each containing more than 46000 entities (gene probes or probesets) derived from NCBI, RefSeq and UniGene databases. Poly(A)-RNA was reverse transcribed to complementary DNA (cDNA), using an oligo(dT)-primer that contained a phage T7 RNA polymerase promoter sequence at its 5′-end, followed by conversion to double-stranded cDNA. The double-stranded cDNA was transcribed in vitro to yield large quantities of biotin-labelled anti-sense RNA, which was then hybridised to the bead arrays at 55 °C for 16-18 h, and scanned using an Illumina iScan reader.

Bioinformatic analysis

The array intensity data were initially analysed using Illumina Genome Studio Gene Expression Module (v1.1.1) (Illumina, Cambridge, United Kingdom) for visualisation and normalisation. After quantile normalisation and background correction using medians within the BeadStudio software, the data were exported for further analysis in GeneSpring GX software 11.5 (Agilent).

Differential expression between various subject groups was analyzed using Illumina Custom Algorithm. The normalized data were first subjected to quality check using principal component analysis. This was followed by analysis to determine genes showing differential expression (fold-change ≥ 2.0 and Benjamini-Hochberg false discovery rate < 0.05 using t-test) in liver tissue from patients with FH-B and FH-E, as compared to healthy liver tissue. Such gene lists were then subjected to “Gene Ontology” (GO) analysis for biological processes, and pathway analysis using BioCarta database on the DAVID server (http://david.abcc.ncifcrf.gov). Separate analyses were done for genes that were differentially expressed in both FH-E and FH-B, and those differentially expressed in only one of these.

Validation of microarray results

For some genes that showed differential expression in FH-E, microarray data were validated using quantitative reverse transcription PCR (qRT-PCR). In brief, cDNA was prepared using High-Capacity cDNA Reverse Transcription Kit (Applied Biosystems, Foster City, CA) from 2 μg of RNA. This was followed by real-time PCR in 20-μL reactions comprising of 50 ng cDNA, primers (Appendix 1) and SYBR Green (Applied Biosystems).

The validation assay included liver tissue for all the subjects used for microarray analysis (a biopsy piece other than that used for microarray analysis) and four additional healthy liver tissues. All assays included RNA from peripheral blood mononuclear cells of a healthy person as a calibrator. Glyceraldehyde 3-phosphate dehydrogenase (GAPDH) and 18S rRNA was used as housekeeping genes. Relative fold-change was determined for each specimen and gene from cycle threshold (Ct) values as follows, and compared to fold-change in expression in microarray data:

∆∆Ct= [(∆Ctgene of interest - ∆CtGAPDH)patient - [(∆Ctgene of interest - ∆CtGAPDH)calibrator sample] and Fold change = 2-∆∆Ct.

Immunohistochemistry on liver biopsies

Formalin-fixed, paraffin-embedded liver sections were stained with hematoxylin and eosin, and examined to confirm the presence of acute inflammation in patients with FH, and absence of disease in controls.

In addition, immunohistochemistry (IHC) was performed for specific T-cell subsets (CD4+ and CD8+) and NK cells (CD56+). In brief, formalin-fixed, paraffin-embedded 3-μm liver sections on silanized glass slides (Dako) were fixed at 60 °C overnight. The slides were deparaffinised in xylene and rehydrated in graded alcohol. Antigen retrieval was done in 10 mmol/L EDTA (pH 9.0) at 98 °C for 30 min. After washing with distilled water and Tris-buffered saline (TBS; pH 7.4), endogenous peroxidase was blocked using 3% hydrogen peroxide in methanol for 30 min in dark. Sections were then incubated with monoclonal primary antibodies [prediluted mouse anti-human CD8 (clone C8/144B), CD4 (clone 4B12) or CD56 (clone 123C3) (Dako, Denmark)] for 1 h at room temperature, followed by peroxidase enzyme-labelled secondary antibody (Dako) for 30 min. Diaminobenzidine was used as chromogen to detect the bound antibodies. Slides were counterstained with Mayer’s hematoxylin for 1 min, cleared and mounted with DPX (Sigma-Aldrich). Stained cells were counted in five fields, averaged and expressed as number in an area measuring 73000 μm2.

Statistical analysis

Inter-group comparisons were done using t-test with Benjamini-Hochberg correction in case of gene expression data and Mann-Whitney U test for other quantitative data. Relationship of fold-change in the microarray and real-time PCR data was assessed using Pearson’s correlation coefficient. The statistical methods of this study were reviewed by Dr. Rakesh Aggarwal from Sanjay Gandhi Postgraduate Institute of Medical Sciences, Lucknow, India.

RESULTS

Demographic features and biochemical findings in the three subject groups are shown in Table 1. Alanine aminotransferase levels were higher in FH-B than in FH-E.

Table 1 Characteristics of study subjects in the three groups.
CharacteristicHealthy controls (n = 6)Fulminant hepatitis B (n = 6)Fulminant hepatitis E (n = 5)
Age (yr)52 (30-58)24 (16-60)28 (18-32)
Gender (Male:Female)4:24:21:4
Duration of illness before death (d)-9 (6-14)10 (7-13)
Maximum total serum bilirubin (mg/dL)0.7 (0.4-1.4)21 (13.1-41.4)25 (5.4-32.0)
Serum ALTa (IU/L)30 (21-58)1939 (524-5795)770 (240-1302)
Serum AST (IU/L)28 (18-35)859 (250-2345)458 (332-1000)
Alkaline phosphatase (IU/L)-257 (131-427)306 (164-561)
Serum albumin (g/dL)-2.8 (2.0-3.3)2.8 (2.1-3.2)
Principal component analysis

On principal component analysis of gene expression data (Figure 1), all specimens except one (with FH-B) showed clustering with other specimens in the same group.

Figure 1
Figure 1 Principal component analysis of gene expression data from various specimens included in the study. The components along X, Y and Z axes were 62.54%, 21.17%, and 8.88%, respectively. Patients with fulminant hepatitis E (FH-E) are represented using circles, those with fulminant hepatitis B (FH-B) using triangles and healthy controls using square symbols. The size of markers varies according to their placement on the Z axis. Patients with FH-E and FH-B clustered separately, except for one patient with FH-B who was an outlier (arrow).
Microarray gene expression

A total of 3377 entities, each representing a discrete gene, showed differential expression of ≥ 2-fold with P-value of < 0.05 in liver tissue from patients with FH-E than that from healthy persons (Figure 2); this included 1703 entities with over-expression and 1674 showing reduced expression in FH-E. In liver tissue from FH-B, 2572 entities showed differential expression than in healthy livers (up-regulation 1164, down-regulation 1408).

Figure 2
Figure 2 Venn-diagram showing comparison of number of entities differentially expressed in liver tissue from fulminant hepatitis B or E, as compared to healthy liver tissue. The intersection of two circles shows entities that were differentially expressed in both fulminant hepatitis E and fulminant hepatitis B.

Of the entities differentially expressed in FH-E or FH-B compared to normal liver, 2142 were common (up-regulation in both 896, down-regulation in both 1246) (Figure 2, Appendix 2); none of these entities showed discordance in the direction of differential expression between FH-E and FH-B. In contrast, 1235 entities (Appendix 3) were differentially expressed in FH-E but not in FH-B, and 430 entities (Appendix 4) were differentially expressed in FH-B but not in FH-E.

Gene ontology analysis

Genes differentially expressed in FH-E and FH-B livers: Table 2 lists the biological processes that showed differential regulation on GO analysis of the 2142 entities differentially expressed in both FH-E and FH-B. These included several metabolic processes in which the liver plays an active part, such as general body metabolism, or those whose proteins are mainly synthesized in the liver, such as coagulation pathways and complement system. Further, both the disease conditions showed differential regulation of innate immune responses and humoral immune responses mediated by B cells.

Table 2 Gene Ontology analysis (biological processes) for gene entities differentially expressed in liver tissue from fulminant hepatitis E as compared to normal liver tissue, as well as in fulminant hepatitis B as compared to normal liver tissue.
Gene ontology accessionGene Ontology termP value
GO:0055114Oxidation-reduction process2.68E-40
GO:0006082Organic acid metabolic process4.75E-39
GO:0043436Oxoacid metabolic process2.17E-38
GO:0019752Carboxylic acid metabolic process4.09E-38
GO:0006629Lipid metabolic process3.94E-28
GO:0044281Small molecule metabolic process9.06E-27
GO:0032787Monocarboxylic acid metabolic process3.56E-22
GO:0016054Organic acid catabolic process4.22E-19
GO:0046395Carboxylic acid catabolic process4.22E-19
GO:0044255Cellular lipid metabolic process1.35E-17
GO:0044282Small molecule catabolic process5.16E-17
GO:0044712Single-organism catabolic process5.16E-17
GO:0006631Fatty acid metabolic process2.71E-16
GO:0006520Cellular amino acid metabolic process4.43E-16
GO:0044711Single-organism biosynthetic process8.25E-14
GO:1901605Alpha-amino acid metabolic process1.07E-13
GO:0044283Small molecule biosynthetic process1.60E-13
GO:1901564Organonitrogen compound metabolic process2.46E-11
GO:0009063Cellular amino acid catabolic process4.46E-11
GO:0008610Lipid biosynthetic process8.46E-11
GO:0072376Protein activation cascade3.87E-10
GO:0008202Steroid metabolic process4.10E-10
GO:0016053Organic acid biosynthetic process6.26E-10
GO:0046394Carboxylic acid biosynthetic process6.26E-10
GO:1901566Organonitrogen compound biosynthetic process1.94E-08
GO:0008152Metabolic process4.34E-08
GO:1901606Alpha-amino acid catabolic process4.58E-08
GO:0072329Monocarboxylic acid catabolic process1.40E-07
GO:0007596Blood coagulation1.98E-07
GO:0050817Coagulation1.98E-07
GO:0007599Hemostasis2.83E-07
GO:1901615Organic hydroxy compound metabolic process4.14E-07
GO:0042060Wound healing4.86E-07
GO:0006956Complement activation6.77E-07
GO:0009062Fatty acid catabolic process1.71E-06
GO:0006066Alcohol metabolic process1.82E-06
GO:0008652Cellular amino acid biosynthetic process2.42E-06
GO:0050878Regulation of body fluid levels5.46E-06
GO:0051186Cofactor metabolic process5.50E-06
GO:0006694Steroid biosynthetic process8.32E-06
GO:0044242Cellular lipid catabolic process1.09E-05
GO:0005996Monosaccharide metabolic process0.000012
GO:0051346Negative regulation of hydrolase activity1.28E-05
GO:0005975Carbohydrate metabolic process1.35E-05
GO:0010876Lipid localization5.30E-05
GO:0044710Single-organism metabolic process5.82E-05
GO:0006732Coenzyme metabolic process6.57E-05
GO:0010951Negative regulation of endopeptidase activity7.22E-05
GO:0019318Hexose metabolic process7.95E-05
GO:0006869Lipid transport8.02E-05
GO:0065008Regulation of biological quality8.96E-05
GO:0010466Negative regulation of peptidase activity0.0001
GO:0006006Glucose metabolic process0.0001
GO:0042558Pteridine-containing compound metabolic process0.0002
GO:0043648Dicarboxylic acid metabolic process0.0002
GO:0006958Complement activation, classical pathway0.0004
GO:0006091Generation of precursor metabolites and energy0.0004
GO:0044262Cellular carbohydrate metabolic process0.0004
GO:0006575Cellular modified amino acid metabolic process0.0005
GO:0016051Carbohydrate biosynthetic process0.0005
GO:0072330Monocarboxylic acid biosynthetic process0.0006
GO:00024551Humoral immune response mediated by circulating immunoglobulin0.0010
GO:0044723Single-organism carbohydrate metabolic process0.0010
GO:0019320Hexose catabolic process0.0011
GO:0016052Carbohydrate catabolic process0.0014
GO:0044724Single-organism carbohydrate catabolic process0.0014
GO:0006820Anion transport0.0016
GO:0006007Glucose catabolic process0.0017
GO:0046365Monosaccharide catabolic process0.0018
GO:0046835Carbohydrate phosphorylation0.0020
GO:1901617Organic hydroxy compound biosynthetic process0.0020
GO:00022531Activation of immune response0.0021
GO:0016125Sterol metabolic process0.0022
GO:0006096Glycolysis0.0023
GO:0019395Fatty acid oxidation0.0037
GO:0034440Lipid oxidation0.0037
GO:0046165Alcohol biosynthetic process0.0038
GO:00069591Humoral immune response0.0042
GO:0009611Response to wounding0.0044
GO:0006957Complement activation, alternative pathway0.0044
GO:0006760Folic acid-containing compound metabolic process0.0044
GO:00450871Innate immune response0.0053
GO:0052548Regulation of endopeptidase activity0.0077
GO:0046364Monosaccharide biosynthetic process0.0077
GO:0006790Sulfur compound metabolic process0.0078
GO:0051179Localization0.0079
GO:0052547Regulation of peptidase activity0.0083
GO:0046942Carboxylic acid transport0.0083
GO:0015849Organic acid transport0.0095
GO:0016042Lipid catabolic process0.0113
GO:0015711Organic anion transport0.0113
GO:0051234Establishment of localization0.0113
GO:0006810Transport0.0119
GO:0044092Negative regulation of molecular function0.0126
GO:0019319Hexose biosynthetic process0.0131
GO:0072378Blood coagulation, fibrin clot formation0.0132
GO:0006558L-phenylalanine metabolic process0.0146
GO:0006559L-phenylalanine catabolic process0.0146
GO:0000038Very long-chain fatty acid metabolic process0.0146
GO:0051289Protein homotetramerization0.0146
GO:00022521Immune effector process0.0153
GO:0008203Cholesterol metabolic process0.0153
GO:0009074Aromatic amino acid family catabolic process0.0212
GO:0048806Genitalia development0.0212
GO:00160641Immunoglobulin mediated immune response0.0214
GO:0050819Negative regulation of coagulation0.0214
GO:0043086Negative regulation of catalytic activity0.0224
GO:0034754Cellular hormone metabolic process0.0243
GO:00197241B cell mediated immunity0.0263
GO:0051262Protein tetramerization0.0279
GO:00507781Positive regulation of immune response0.0292
GO:00507761Regulation of immune response0.0341
GO:0006633Fatty acid biosynthetic process0.0372
GO:0003333Amino acid transmembrane transport0.0389
GO:0016126Sterol biosynthetic process0.0416
GO:0006811Ion transport0.0420
GO:0006094Gluconeogenesis0.0474
GO:0001676Long-chain fatty acid metabolic process0.0474

Genes differentially expressed in FH-E but not in FH-B: On GO analysis, the 1235 entities that showed differential expression in FH-E but not in FH-B were related mainly to the immune system pathways (Table 3); for each of these immune pathways, several genes showed upregulation.

Table 3 Results of Gene Ontology analysis (biological processes) for gene entities differentially expressed in liver tissue from fulminant hepatitis E as compared to normal liver, but not in that from fulminant hepatitis B as compared to normal liver.
Gene Ontology termP value
Immune system process11.67E-11
Immune response14.81E-09
Regulation of immune system process15.06E-08
Positive regulation of immune system process12.72E-06
Defense response1.04E-05
Response to wounding1.90E-05
Signaling7.78E-05
Adaptive immune response based on somatic recombination of immune receptors built from immunoglobulin superfamily domains12.40E-04
Adaptive immune response12.40E-04
Response to stimulus3.53E-04
Regulation of cell activation4.65E-04
Inflammatory response16.89E-04
Cell adhesion0.0010
Biological adhesion0.0010
Positive regulation of immune response10.0015
Cell activation0.0018
Signal transduction0.0019
Regulation of leukocyte activation10.0020
Activation of immune response10.0021
Oxidation reduction0.0021
B cell mediated immunity10.0023
Leukocyte mediated immunity10.0026
Positive regulation of response to stimulus0.0027
Regulation of locomotion0.0028
Regulation of immune response10.0030
Phospholipid efflux0.0032
Lymphocyte mediated immunity10.0032
Regulation of cell migration10.0048
Regulation of cell motility10.0048
Response to stress0.0050
Regulation of lymphocyte activation10.0056
Regulation of cellular component movement0.0064
Signal transmission0.0067
Immunoglobulin mediated immune response10.0067
Signaling process0.0067
Small molecule metabolic process0.0083
Cholesterol efflux0.0124
Immune effector process10.0154
Negative regulation of apoptosis0.0161
Positive regulation of cell activation0.0176
Positive regulation of leukocyte activation10.0176
Regulation of response to stimulus0.0177
Negative regulation of cell death0.0179
Negative regulation of programmed cell death0.0179
Regulation of lipid metabolic process0.0180
Signaling pathway0.0206
Acute inflammatory response10.0241
Phospholipid transport0.0257
Regulation of fatty acid metabolic process0.0273
Alcohol metabolic process0.0282
Cholesterol transport0.0310
Sterol transport0.0472

Genes differentially expressed in FH-B but not in FH-E: GO analysis of these entities did not reveal significant changes in any specific pathway.

Pathway analysis

Genes differentially expressed in both FH-E and FH-B: Pathway analysis for the 2142 entities differentially expressed in both FH-E and FH-B using the BioCarta database showed downregulation of several pathways related to metabolic processes, hemostasis, and complement system (Table 4). Appendix 5 shows individual genes involved in each of these pathways.

Table 4 Pathways whose genes were found to be over-represented among entities differentially expressed in both fulminant hepatitis E and fulminant hepatitis B, and in fulminant hepatitis E but not in fulminant hepatitis B (derived using BioCarta through DAVID resource).
BioCarta pathwayGene countP value
In both FH-B vs normal, and FH-E vs normal
Complement pathway100.0002
Intrinsic prothrombin activation pathway100.0002
Nuclear receptors in lipid metabolism and toxicity130.0022
Alternative complement pathway60.0069
Extrinsic prothrombin activation pathway60.0113
Lectin induced complement pathway60.0172
Classical complement pathway60.0172
Acute myocardial infarction60.0248
Vitamin C in the brain40.0385
CBL mediated ligand-induced downregulation of epidermal growth factor receptors50.0543
Catabolic pathways for methionine, isoleucine, threonine and valine30.0955
In FH-E vs normal but not in FH-B vs normal
T cytotoxic cell surface molecules70.0005
T helper cell surface molecules60.0043
Cytotoxic T lymphocyte mediated immune response against target cells70.0022
Co-stimulatory signal during T-cell activation70.0085
Role of epidermal growth factor receptor transactivation by G protein-coupled receptors in cardiac hypertrophy60.0092
T cell receptor signaling pathway100.0049
Lck and Fyn tyrosine kinases in initiation of T cell receptor activation50.0187
Interleukin-7 signal transduction50.0446
Mitochondrial carnitinepalmitoyltransferase system30.0529
T cell receptor and CD3 complex30.0529
Interleukin-17 signaling pathway50.0562

Genes differentially expressed in FH-E but not in FH-B: BioCarta pathways whose genes were significantly over-represented among genes differentially expressed in liver tissue from FH-E compared to normal liver but not in FH-B were mostly related to cellular immune mechanisms (Table 4), e.g., T cytotoxic cell surface molecules, CTL mediated immune response against target cells, T helper cell surface molecules, co-stimulatory signal during T-cell activation, T cell receptor signalling pathway, Lck and Fyn tyrosine kinases in initiation of TCR activation, IL-7 signal transduction, T cell receptor and CD3 complex, IL 17 signalling pathway. Several individual genes involved in these pathways were upregulated in patients with FH-E (Appendix 6).

Genes differentially expressed in FH-B but not in FH-E: Pathway analysis of these 430 entities did not reveal significant change in any pathway.

Validation using qRT-PCR

The fold-change values of mRNA for selected genes (Appendix 1) in livers from FH-E than in normal liver tissue determined using qRT-PCR showed excellent concordance with those at microarray (Figure 3), using either of the two housekeeping genes.

Figure 3
Figure 3 Relationship of fold-change in RNA expression of selected genes in patients with fulminant hepatitis E and fulminant hepatitis B on real-time polymerase chain reaction with fold-change in RNA expression of the same genes on microarray analysis. A and B show the data when reverse transcription polymerase chain reaction results were normalized using the GAPDH gene and 18S rRNA gene as housekeeping gene, respectively.
Immunohistochemistry

IHC showed a few CD4+ positive T-cells and occasional NK cells in all the biopsies. In FH-B as well as FH-E, CD8+ T-cells were found in both the liver parenchyma and the portal areas (Figure 4). The median number of CD8+ T cells was greater in liver tissues from both FH-E [median 53.4 (range 31.2-99.9)]; P = 0.005, 2-sided Mann-Whitney U test) and FH-B [49.3 (19.3-51.0); P = 0.005] than in controls 6.9 (3.1-14.9); however, there was no significant difference between FH-E and FH-B.

Figure 4
Figure 4 Immunohistochemistry for CD8+ cells in liver biopsies shows occasional cytotoxic T-cells in portal tracts of controls (A), and moderate infiltration in HBV (C) and HEV (E); immunostaining for CD4 shows absence of helper T-cells in portal areas of control (B), an occasional cell in HBV (D) and some small aggregates of helper T-cells in HEV (F). A and B: Diaminobenzidine × 400; C-F: Diaminobenzidine × 200. HBV: Hepatitis B virus; HEV: Hepatitis E virus.
DISCUSSION

Host tissue injury during a viral infection may be caused either by virus-induced cell death, or by immune-mediated killing of infected cells. Understanding the underlying mechanism may not only help understand the pathogenesis of a particular viral disease but also provide a lead to development of strategies for countering the host injury. In infection with hepatitis A, B or C virus, liver injury is mediated primarily by the host immune response[7-11]. However, the mechanisms of liver injury in HEV infection remain unclear.

Initial attempts at delineation of mechanism of liver injury caused by HEV were based on observations during experimental HEV infection in non-human primates. In these studies, liver injury appeared after viremia and fecal viral excretion had started declining and coincided with the appearance of anti-HEV antibodies[17-19]. These findings suggested that host immune response was responsible for the hepatocyte killing. This was followed by attempts to determine whether HEV was capable of producing a cytopathic effect in in vitro models. However, these efforts were largely unsuccessful due to failure of this virus to grow well in cell culture. Recent successful culture[20], though in low titers, of some genotypes 3 and 4 HEV isolates has revealed absence of cytotoxicity[21,22], providing some support to the hypothesis that liver injury in HEV infection is unlikely to be virus-mediated.

Human data on cellular immune responses during HEV infection are limited to studies on peripheral blood mononuclear cells (PBMCs). In these studies, we and others have shown proliferation of HEV-specific CD4+ and CD8+ cells, and increased production of various cytokines by PBMCs during acute and convalescent phases of hepatitis E[14,16]. In a study that looked at patients with different disease severities, HEV-specific T-cell responses in PBMCs were weaker in patients with FH-E than in those with uncomplicated acute hepatitis E[12]. However, observations made on circulating immune cells may not faithfully represent those in the immune cells infiltrating the liver, because of preferential localization of certain cells, including virus-specific T cell subsets, in the inflamed tissue[23,24]. Thus, there is a need to study changes in the liver tissue from patients with hepatitis E.

In the current study, we found changes in expression of genes involved in a variety of immune responses, including the innate, humoral and cellular immune pathways in liver tissue from patients with FH-E. Of these, changes in innate and humoral immune responses were also observed in FH-B, indicating that HEV infection may share some of the pathways causing liver cell injury with HBV infection. In contrast, activation of cellular immune pathways was found only in FH-E, and not in FH-B, indicating a specific role for cellular immune response in inducing liver injury during HEV infection.

In particular, we found several T-cell surface molecules such as CD2, CD3 (γ, δ and ε chains) and CD8-alpha to be up-regulated in liver tissue from patients with FH-E. Furthermore, several T-cell signalling molecules, such as Fyn, phospholipase C gamma-1, NFκB1, protein kinase C and ras-related C3 botulinum toxin substrate (rac) were also overexpressed in these livers. These findings may indicate a role for activated CD8+ T cells in the causation of liver injury in HEV infection. An over-expression of CTLA4, which is expressed only on activated T cells, also supports this hypothesis. An alternative explanation for the overexpression of CD2 in liver tissue could be the presence of this marker on the NK cells. Importantly, the increased expression of CD2 in the liver tissue was also associated with over-expression of perforin, the main cytolytic protein contained in the CD8+ T cells and NK cells. The above findings, taken together, indicate that immune-mediated cytotoxicity of CD8+ or NK cells against virus-infected cells may play a role in producing liver damage in HEV infection.

Some other findings in our study may also point to alterations in CD8+ cells. In viral infections, the number of effector CD8 T cells contracts over time with the formation of a population of protective memory cells, which is maintained by IL-7 and IL-15. Our finding of activation of IL-7-mediated signalling in patients with hepatitis E possibly reflects this phenomenon. In addition, the genes for signal transducer and activator of transcription 5 (STAT5), a key molecule involved in the survival of effector and memory CD8 cells[25], and for BCL2, a key survival molecule that is upregulated by STAT5, were overexpressed in FH-E.

The differential expression in livers from patients with FH-E of several genes which were unaffected in FH-B could have been because of changes in any of the several cell types present in the liver, including hepatocytes, Kupffer cells, cholangiocytes, endothelial cells, stellate cells and a variety of immune cells. However, the demonstration of predominant infiltration with CD8+ T cells in the FH-E livers in the current study as well as in two previous reports[26,27], and the fact that the genes that showed differential expression are not expressed much in other cell types, indicate the CD8+ T cells were the most likely source. It may be pertinent to note that since the immune cells constitute only a minority of all the cells in the liver, the absolute gene expression changes within the intrahepatic immune cells must be more marked than is indicated by the overall gene expression data. It may thus be interesting in future to undertake studies on such immune cells after recovering these using techniques such as laser dissection microscopy.

It may be pertinent to compare our results with those from a recent study of gene expression in serial liver tissues from chimpanzees with experimental HEV infection[28]. In this study, differential expression was limited to a few genes that belonged predominantly to the innate immune response pathways, and was weaker than that observed in chimpanzees with HCV infection. Further, the number of upregulated genes peaked sooner after the onset of viremia in HEV infection than with HCV infection. We did find altered expression of some genes involved in innate immune responses; however, these genes were different from those showing significant changes during HEV infection in the chimpanzee study. In this context, it is important to note that comparison of our data with those from the experimentally-infected chimpanzees may not be valid. Our patients had severe liver disease, whereas experimental HEV infection in primates is milder[19,29]. Further, time-kinetics of different types of immune responses vary, with innate immune responses being prominent during the initial phase after viral infection; thus, in human HEV infection, such responses may occur before an infected person becomes symptomatic and hence not picked up. Also, the experimental animals had been inoculated by the intravenous route, whereas humans acquire infection through the oral route.

Though we studied patients with FH-B primarily as disease controls, it may be interesting to compare liver in this condition with healthy livers. Livers from patients with FH-B showed infiltration with CD8+ cells, but no differential expression of genes belonging to cellular immune response pathways. Previous gene expression data in this disease are available from only two Italian patients[30,31]. These patients too showed prominent CD8+ T cell infiltration with little change in expression of genes associated with T cell activity and a prominent upregulation of B cell response, similar to our observations.

Interestingly, though liver tissues from both FH-E and FH-B in our study showed prominent CD8+ T cell infiltration, only FH-E was associated with a cytotoxic T cell transcriptional signature e.g., increased expression of perforin. This suggests that the infiltrating CD8+ T cells in the two diseases behave quite differently. This may hold the key to pathogenesis of liver injury in HEV infection.

We also found reduced expression of several genes associated with metabolic, hemostatic and complement pathways in liver tissue from FH-E as well as FH-B. Liver is a metabolically active organ which produces several body proteins. Since FH, irrespective of its cause, is characterized by marked destruction of hepatocytes, reduction in the expression of these proteins was thus expected in both FH-E and FH-B, as a consequence of the massive liver injury.

Our data are limited by a small sample size, the use of post-mortem tissue, and of patients with severe liver injury at only one time-point. These limitations are related to the fact that liver biopsy, being invasive, is ethically unacceptable in patients with acute liver disease, forcing us to use tissue collected immediately post-mortem. Though our findings may not be entirely applicable to acute uncomplicated hepatitis E, these should be seen in light of the current absence of any human data on immune events in the liver in acute hepatitis E. Further, we compared our data to those from a control group of post-mortem biopsies from FH-B, which would have been susceptible to similar artefacts as those in FH-E.

In conclusion, liver tissue from our patients with FH-E showed infiltration with CD8+ T cells and overexpression of genes involved in T cell immune responses, especially those related to T cell activation, cytotoxicity and IL-7 signalling. The latter changes were not observed in FH-B, and hence were specific to hepatitis E. These data suggest that the severe liver damage in FH-E is mediated by the host T-cell immune response. Further work on this aspect should help us better understand the pathogenesis of liver injury in hepatitis E.

ACKNOWLEDGMENTS

Microarray data analysis was done at Bio-medical Informatics Centre, Sanjay Gandhi Postgraduate Institute of Medical Sciences, Lucknow, India; this center is supported by the Indian Council of Medical Research (ICMR) and Department of Biotechnology, Government of India during this work. ANS was supported by ICMR during this work. The authors thank Dr. Vivek Chandra for analysis comparing the liver biopsy data with in vitro data from HEV ORF3-expressing cells.

COMMENTS
Background

Infection with hepatitis E virus is the most common cause of acute hepatitis in the world. The mechanism of liver injury in this disease and its pathogenesis are yet fully understood. A better understanding of these may allow attempts at therapeutic intervention in patients with this disease.

Research frontiers

Microarray techniques allow study of expression of several genes in tissues from patients with a particular disease and its comparison with those from healthy controls and persons with similar diseases. These techniques have been applied for the study of pathogenesis of several diseases.

Innovations and breakthroughs

The authors used microarray techniques to determine the expression of various genes in the liver tissues from patients dying of hepatitis E and compared this to that in healthy liver tissue (control tissue) and liver tissues from patients dying of a disease with similar morphologic changes but caused by infection with another virus (hepatitis B; disease controls). The data showed several differences in gene expression between these groups. In particular, livers of patients with fulminant hepatitis E, but not those of hepatitis B, showed activation of several immune response pathways, particularly those involving cytotoxic T cells. This difference was observed even though tissues from both hepatitis B and E showed infiltration with cytotoxic T cells.

Applications

All data suggest that immune cells may play a role in the pathogenesis of hepatitis E, though further work is required in this regard.

Peer-review

Minor improvements, such as addition of statistical methods to the manuscript.

Footnotes

P- Reviewer: Ambrosioni J, Li WG, Ma L S- Editor: Qi Y L- Editor: A E- Editor: Ma S

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