Chronic infection with hepatitis C virus (HCV) is a major cause of liver disease worldwide . Both HCV and HIV-1 share routes of transmission and establish chronic infections; therefore, coinfection is relatively common . Until recently, standard therapy for chronic hepatitis C was based on a combination of peginterferon (pegIFN) and ribavirin (RBV), given for 6–18 months, depending on early viral kinetics and HCV genotype . Unfortunately, these medications are poorly tolerated and result in low response rates, with less than half of patients achieving permanent HCV clearance . This figure is even lower in HIV/HCV-coinfected patients . Thus, the identification of predictors of treatment success is desirable, in order to select the best candidates for HCV therapy.
A strong association has recently been found between allelic variants of single nucleotide polymorphisms (SNPs) rs12979860 and rs8099917 nearby the IL28B gene coding for IFN-λ3, and response to antiviral treatment in both HCV-monoinfected [4–6] and HIV/HCV-coinfected patients [7–9]. Ge et al.  reported that both rs12979860 and rs8099917 together with another five SNPs (rs12980275, rs12972991, rs8109886, rs4803223, rs12980602) influence treatment outcomes. All these SNPs display different degrees of linkage disequilibrium with rs12979860, which largely explain their effects. The rs12979860 CC genotype has been associated with more than two-fold greater rate of sustained virological response (SVR) than CT or TT genotypes in both HCV-monoinfected  and HIV/HCV-coinfected patients .
The functional mechanism linking the association between these polymorphisms and response to HCV treatment remains unknown. The IFN-λ3, a type III IFN, depicts strong in-vitro activity against HCV . Both IFN-λ3 and IFN-α share signalling pathways within the cells  and may exert an additive effect in their antiviral effect . Thus, hypothetically, individuals carrying the protective genotype (CC) at the IL28B rs12979860 gene may show a differential IL28B expression, whose antiviral effect could be boosted when exogenous IFN-α is given. Prior studies have addressed this issue in the liver and in peripheral blood mononuclear cells (PBMCs) with controversial results [4–6,13–17]. On the other hand, in-vitro studies have found that HCV induces IFN type III expression in the liver, being the degree of induction influenced by hepatic levels of interferon-stimulated genes (ISGs) [18–20]. Given that HCV treatment responses are tightly associated with intrahepatic ISGs expression [21–23], the link between IL28B variants and treatment outcomes could be mediated by a differential expression of ISGs in CC versus non-CC IL28B carriers.
Some in-vivo studies have already explored the association between IL28B genotypes, ISGs expression and response to anti-HCV treatment [13–15,24–27]. Those studies have been conducted mainly on hepatic tissue and most have found a significant association between these variables when using either SNP rs8099917 [13,25] or SNP rs12979860 [14,24,26]. However, a recent study on hepatic tissue concluded that the association between IL28B genotypes and ISGs expression was an artefact, arising from their common association with treatment response. After adjustments, these authors found that ISGs expression was a better predictor of treatment response than IL28B genotypes . Nevertheless, the controversy still exists, as a more recent study  has highlighted that the expression pattern of ISGs may change in distinct cellular compartments. In current clinical practice, liver biopsies are no longer performed in most patients with hepatitis C, limiting the access to liver tissue. So far, only few studies have explored the link between IL28B SNPs genotypes and ISGs expression in PBMCs from HCV-infected patients [25,27]. However, these studies have important limitations to consider their results as conclusive on this topic. The study by Abe et al.  has been subject to criticism, as result of a bias due to an incorrect stratification of patients. Moreover, as mentioned above, HCV/HIV coinfection is quite common and a recent study has shown that HIV infection induces ISGs expression in PBMCs . Therefore, the differential expression of genes according to HCV treatment outcome in the context of HIV/HCV coinfection could be influenced by active HIV replication. Thus, studies with HIV/HCV-coinfected patients with different degrees of HIV-RNA could add an important bias to the results. That is the case of the study by Naggie et al. , also in PBMCs, which included patients with different degrees of HIV viraemia.
In view of the clinical relevance of predicting response to interferon-based therapies, even including oral direct-acting antivirals (DAA), the relevance of HCV/HIV-coinfected patients’ population, particularly difficult-to-treat, and the recent observations that ISGs expression and IL28B genotypes are the major determinants of treatment response, we investigated their link testing PBMCs from HCV/HIV-coinfected patients with undetectable HIV-RNA. As PBMCs are of easier access than liver biopsy material, we expected that our results could be particularly useful for the clinical management of these patients.
Patients and methods
Patients were recruited at Hospital Carlos III, Madrid, Spain. From our cohort of more than 425 HIV/HCV-coinfected patients on a regular follow-up, whose characteristics have already been described elsewhere , we identified 19 individuals who had completed a course of therapy with pegIFNα/RBV, had validated outcomes and adequate stored human cell DNA and RNA material to be included in a genetic subanalysis. Patients with concomitant chronic hepatitis B and/or delta were excluded.
To avoid stratification bias, patients were split out into four groups according to treatment response and IL28B genotype. A detailed description of treatment regimens and criteria used for considering patients with SVR have been described elsewhere . Briefly, SVR was considered only when HCV-RNA values were undetectable 24 weeks after discontinuation of HCV treatment. Individuals experiencing viral rebound within this period were considered as relapsers. To participate in the study, written informed consent was obtained from all individuals, and the study protocol was evaluated and approved by the hospital ethics committee.
Hepatitis C virus viraemia and genotyping
Plasma HCV-RNA was measured using a real-time PCR assay (COBAS TaqMan; Roche, Barcelona, Spain), which has a lower limit of detection of 10 IU/ml. HCV genotyping was performed using a commercial RT-PCR hybridization assay (Versant HCV Genotype v2.0 LiPA; Siemens, Barcelona, Spain), which maximally reduces the chances of HCV genotype misclassification . Plasma HIV-RNA was measured using Versant HIV-1 RNA v3.0 (Siemens), which has a lower limit of detection of 50 copies/ml.
DNA extraction and IL28B genotyping
Genomic DNA was isolated from criopreserved PBMCs using the QIAamp DNA Mini Kit (Qiagen, Valencia, California, USA), following manufacturer's instructions. IL28B genotyping (SNP rs12979860) was conducted at Hospital Carlos III, following procedures already described elsewhere .
Total RNA was isolated from PBMCs using the Ribopure kit (Applied Biosystems/Ambion, Austin, Texas, USA), following manufacturer's instructions. RNA concentrations were measured using the Nanodrop Spectrophotometer ND-100 UV/Vis (Thermo Scientific, Wilmington, Delaware, USA). RNA integrity was verified using the RNA 6000 Nano Kit, using a 2100 Bioanalyzer (Agilent Technologies, Santa Clara, California, USA).
Approximately 200 ng of total RNA was converted to double-stranded DNA, amplified and transcribed to RNA using the QuickAmp Labelling kit one colour (Agilent Technologies). Amplified cRNA was labelled with cyanine 3-CTP and purified using the RNeasy kit (Qiagen). cRNA was hybridized to Human GE 4x44 v2 Microarray slides, which were further processed using the One-colour microarray-based gene expression analysis protocol v6.5 (Agilent Technologies). Array data were obtained using the Feature Extraction v9.5 software.
Real time reverse transcriptase-PCR
A total of 200 ng of total RNA from each sample was converted to cDNA using the High Capacity cDNA Reverse Transcription kit (Applied Biosystems). Real-time PCR was performed on 20 μl using the MicroAmpTM Optical 384-well reaction plate (Applied Biosystems, Foster City, San Mateo, California, USA) testing 2 μl/well of a 1/20 dilution performed in quadruplicate for each cDNA, 1× FastStart Universal SYBR Green Master (Roche, Basel, Switzerland) and 0.2 μmol/l of each couple of oligonucleotides. The sequences of oligonucleotides used are given in the Supplement Table 1, http://links.lww.com/QAD/A287. All oligonucleotides were supplied by Fisher Scientific (Waltham, Massachusetts, USA). PCRs were run on an Applied Biosystems StepOne Plus. Data were collected using StepOne v2.2 (Applied Biosystems) and analysed with Data Assist v1.0 (Applied Biosystems) with the Comparative delta-delta Ct Method (ΔΔCt). Multiple control normalization was performed using the DataAssist software, considering arithmetic means and using ß-actine, glyceraldehyde 3-phosphate dehydrogenase and hypoxanthine phosphoribosyltransferase 1 genes. The t-test was performed and only P values less than 0.05 were considered as statistically significant.
Full statistical analysis and any associated references are available as supplementary information, http://links.lww.com/QAD/A287.
Baseline characteristics of the study population
A total of 19 HCV/HIV-coinfected patients were analysed. Their baseline (pre-HCV treatment) characteristics are depicted in Table 1. Briefly, they were mainly male (68%), with a median age of 39 (38–43) years. Median HCV viral load was 6.5 (5.3–6.8) log IU/ml. All patients were on highly active antiretroviral therapy (HAART) with undetectable HIV-RNA. A recent study  has shown that HAART has a little effect on the virological response to pegIFNα/RBV in HIV/HCV-coinfected patients. The mean CD4 cell count was 644 (460–780) cells/μl. The significant association between IL28B genotype and response to HCV treatment has been reported only for patients infected with HCV genotypes 1 or 4. So, to exclude a potential confounding effect, we only included patients infected with HCV genotypes 1 or 4. Most patients (81%) had null–mild liver fibrosis (Metavir F0-F2 estimates using FibroScan). All four groups had similar baseline characteristics (age P = 0.32; CD4 cell count P = 0.26; HCV viral load P = 0.12; liver fibrosis P = 0.84).
Gene expression profiles on whole genome microarrays were interrogated to identify differentially expressed genes according to two variables: IL28B genotype (CC versus CT) and treatment response to pegIFNα/RBV (SVR versus non-SVR) in HIV/HCV-coinfected patients. In order to eliminate selection bias between both variables, we designed the study with a balanced distribution of individuals regarding both variables: five SVR/CC, four SVR/CT, five non-SVR/CC and five non-SVR/CT. According to IL28B genotype, 56 genes were selected (Supplemental Table 2, http://links.lww.com/QAD/A287) as differentially expressed. The top five downregulated genes in CC patients were forkhead box B1 (FOXB1, 4.03-fold repressed), an open reading frame in chromosome 19 (A_24_P15640 Agilent ID identifier, 3.0-fold repressed), family with sequence similarity 153 member B (FAM153B, 2.7-fold repressed), collagen XVIII alpha 1 (COL18A1, 2.52-fold repressed) and patatin-like phospholipase domain containing 2 (PNPLA2, 2.43-fold repressed). The top five upregulated genes in CC patients corresponded to interleukin-6 (IL6, 3.94-fold overexpressed), serpin peptidase inhibitor B2 (SERPINB2, 3.7-fold overexpressed), epiregulin (EREG, 2.5-fold overexpressed), formyl peptide receptor 2 (FPR2, 2.47-fold overexpressed) and pro-platelet basic protein (PPBP, 2.4-fold overexpressed).
According to HCV treatment response, 42 individual genes were selected (Supplemental Table 3, http://links.lww.com/QAD/A287) as differentially expressed. The top five downregulated genes in SVR patients were lysosomal-associated membrane protein 3 (LAMP3, 4.22-fold repressed), family with sequence similarity 20 member A (FAM20A, 3.6-fold repressed) and three ISGs: indoleamine 2, 3-dioxygenase 1 (IDO1, 5.5-fold repressed), interferon-induced protein with tetratricopeptide repeats 1 (IFIT1, 3.7-fold repressed) and interferon-induced protein with tetratricopeptide repeats 3 (IFIT3, 3.3-fold repressed). Interestingly, most of differentially expressed genes according to HCV treatment response were repressed in SVR patients (37 out of 42). Furthermore, 24 out of 37 downregulated genes in SVR patients are common with a previously published list of ISGs . Moreover, another two repressed genes in SVR patients not present in this ISGs list have shown to be ISGs, interferon-stimulated gene 15 (ISG15) and cytidine monophosphate kinase 2 (CMPK2) that were described as induced by interferon-beta-1b .
Microarray results were validated by quantitative RT-PCR (qRT-PCR). IFIT3, IFI44L and RSAD2 genes were randomly selected to validate microarray data regarding HCV treatment response. All three ISGs were repressed (IFIT3 2.8-fold, IFI44L 2.0-fold and RSAD2 2.6-fold) in SVR compared with non-SVR patients (Fig. 1a) confirming microarray results. IL1B and PNPLA2 genes were randomly selected to validate microarray data regarding IL28B genotype and qRT-PCR confirmed microarray results (Fig. 1b). Expression of IL1B was increased in patients carrying the homozygous CC IL28B genotype (2.2-fold), but this increase was not statistically significant. PNPLA2 mRNA expression was repressed in patients carrying the homozygous CC IL28B genotype (1.3-fold; P < 0.05). ISGs IFIT3, IFI44L and RSAD2 were not differentially expressed by qRT-PCR according to IL28B genotype, reproducing the microarrays results.
Unsupervised hierarchical clustering conducted on differentially expressed genes according to IL28B genotype perfectly distinguished patients carrying the homozygous CC IL28B genotype from those patients carrying the CT IL28B genotype. IL28B CC carriers were defined by two groups of genes: one group of repressed genes and another group of induced genes (Fig. 2a). Similar analysis was performed on differentially expressed genes according to treatment response to pegIFNα/RBV; however, this cluster of genes did not as clearly distinguish among SVR and non-SVR patients (Fig. 2b). Interestingly, the group of ISGs was downregulated in most SVR patients and overexpressed in most non-SVR patients (Fig. 2b). The finding of several killer cell immunoglobulin-like receptors (KIR2DL1, KIR2DL4, KIR2DS2 and KIR2DS4) integrating a cluster of overexpressed genes in non-SVR patients was also interesting.
In-silico pathway analysis
Genes showing differential expression according to IL28B genotype or according to HCV treatment response were analysed to find overrepresented biological pathways using Ingenuity Pathways Analysis. When the group of genes differentially expressed according to IL28B genotype were considered, pathways concerned with communication between immune cells or graft-versus-host disease signalling were found to be significantly enriched (Fig. 3a). In order to have more consistent results GeneDecks software was used for the same purpose (Supplemental Table 4, http://links.lww.com/QAD/A287). This analysis tool confirmed the previous results and showed that graft-versus-host disease was the most significant pathway (P = 1.36 × 10–8), cytokine-mediated signalling pathway the most significant Gene Ontology biological process (P = 1.82 × 10–10) and tumour the most significant disorder (P = 1 × 10–16).
For differentially expressed genes according to HCV treatment response, interferon-signalling and activation of interferon pathways were clearly overrepresented (Fig. 3b). Natural killer cell signalling pathway was also significantly associated with genes selected by treatment response. All these results were also confirmed by GeneDecks (Supplemental Table 5, http://links.lww.com/QAD/A287). Interferon signalling was the most significant pathway (P = 8.67 × 10–12), response to virus the most significant Gene Ontology biological process (P = 1.83 × 10–10) and virus infection the most significant disorder (P = 2.38 × 10–12).
The strong significant association of IL28B polymorphisms with response to pegIFNα/RBV in HCV-infected patients prompted to include the IL28B genotyping as a pretreatment predictor of treatment response. Another genetic tool, baseline levels of ISGs, has been previously described as a predictor of HCV treatment response [21–23]. However, neither the mechanism underlying the ISGs expression nor the functional role of IL28B polymorphism has been so far elucidated. In this context, the fact that IL28B/IFN-λ3 activates the same signal transduction pathway as IFN-α and IFN-β inducing the same genes (ISGs) elicits the hypothesis of a link between IL28B polymorphisms and induction of ISGs. Some groups have addressed this subject with conflicting results [13–15,24,26,27]. Also, these studies have mainly been performed in liver tissue and in HCV-monoinfected patients; therefore, there are scarce data available regarding either another cell-type or HCV/HIV-coinfected patients. The goal of our study was to investigate the link between rs12979860 IL28B genotype and ISGs comparing the expression levels not only of ISGs but also the levels of all human genes in PBMCs from HCV/HIV-coinfected patients, the most difficult-to-treat population, according to pegIFNα/RBV treatment response and according to IL28B genotype. PBMCs are a cell population that is easier to obtain than liver biopsy material in routine clinical practice, and thus, findings from this cell type could be potentially used for clinical management of patients.
Our data showed a different gene expression pattern whether patients were grouped according to treatment response or according to rs12979860 IL28B genotype. Thus, our results do not support a direct link between IL28B genotype and ISGs expression in PBMCS from HIV/HCV-coinfected patients under HAART and with undetectable HIV-RNA. However, as we have not analysed liver tissue samples, we cannot rule out the possibility of a link between IL28B genotype and ISGs expression in this compartment. Nevertheless, our results are in agreement with the study by Dill et al.  using liver tissue from HCV-monoinfected patients, and with the study by Naggie et al.  using PBMCs from HCV/HIV-coinfected patients. However, it must be pointed out that in the study by Naggie et al. , patients with both detectable and undetectable HIV viraemia were included, whereas in our study, only patients with suppressed HIV viraemia were analysed to exclude a potential bias arising from the effect of HIV replication on gene expression profiles . Our results are in contrast with some other studies [13,14,24,25] that have found an association between IL28B genotype and ISGs expression; however, these studies have used an inadequate selection of patients. There was an unequal distribution of patients regarding SVR and IL28B genotype, and as a consequence, there were more SVR patients in the group of IL28B CC genotype and more non-SVR patients in the group of CT IL28B genotype. To rigorously test the link between IL28B polymorphisms and ISGs expression, it is absolutely necessary to design the study with a balanced distribution of individuals regarding treatment response and IL28B genotype. In our study, using an adequate stratification methodology, the microarrays heat map clearly showed that patients carrying the CC IL28B genotype were defined by two groups of genes, one downregulated and another upregulated. These genes were different and were involved in different biological processes than those genes differentially expressed when patients were stratified according to treatment response. In this last case, the heat map revealed that most of differentially expressed genes were downregulated in SVR patients and the majority of them were ISGs. These results, in PBMCs, agree with previous results regarding this issue  and extend our understanding of this finding beyond liver tissue. Furthermore, Dill et al.  demonstrated that both IL28B genotype and ISGs modulation in liver tissue were independently associated with the probability of SVR. In this scenario, our findings regarding the association of ISGs expression with SVR in PBMCs have relevant clinical implications.
The evaluation of ISGs induction in peripheral blood instead of liver tissue might provide valuable information to be considered along with IL28B variants and other well known factors of treatment response, and this could improve the accuracy of predicting models of response such as the Prometheus score index (http://www.fundacionies.com/prometheusindex.php?lang=ing), which is already used in clinical practice to predict the likelihood of treatment response in chronic hepatitis C patients . Improving the accuracy of such models would have a great impact in the therapeutic management of patients, enabling clinicians to better select those patients ideally suited for IFN-based therapy and excluding those with a minimal chance of response avoiding unnecessary toxicities.
Similarly to what has been previously found regarding ISGs induction through HCV treatment [21–23], IFN-signalling and activation of IFN pathway were clearly overrepresented in the group of genes differentially expressed between SVR and non-SVR patients. Accordingly, the most significant biological process was response to virus and the most significant disorder was virus infection. Surprisingly, the IL28B/IFN-λ3 gene was not differentially expressed either according to IL28B genotype or to treatment response. Although counterintuitive, this finding is in agreement with recent published data [4,13]. On the other hand, our findings point to the graft-versus-host disease pathway and the cytokine-mediated signalling pathway as the most significant biological processes involved in the group of genes differentially expressed between carriers of CC and CT IL28B genotype. In particular, the top five upregulated genes in CC carriers were all involved in different processes related to immune response against pathogens and inflammation. IL-6 is a cytokine that is a marker of hepatic inflammation and regeneration ; SERPINB2 is involved in regulation of adaptive immunity (Th1 responses) ; EREG, epiregulin, is involved in proinflammatory cytokine production by macrophages, antigen-presenting cells and innate immunity ; FPR2, a G-protein coupled receptor, is activated by HCV peptide C5A regulating innate and adaptive immunity in the host ; PPBP is a protein belonging to the CXC chemokine family, CXCL7. Chemokines regulate leukocyte migration during physiological and pathological conditions . As chemokines exert their biological activity through interaction with 7-transmembrane spanning G-protein-coupled receptors (GPCR) , it will be interesting to investigate the role of FPR2, a G-protein-coupled receptor, as a receptor of PPBP/CXCL7 in the context of HCV infection. Overall, these findings provide new candidate genes to explore the functional role of IL28B polymorphisms.
There are some criticisms that might arise from this study. The sample size used was relatively small, as the inclusion criteria for this genetic study were extremely strict in order to have four pretty homogeneous groups of patients. In addition, we had to be extremely rigorous with the sample quality (RNA) to develop the microarrays assays, so that from our initial cohort of HIV/HCV-coinfected patients, only 19 samples met the specific conditions for this particular study. However, despite the small sample size, our results from microarray analysis showed that the difference in ISGs expression between responder and nonresponder patients is so clear that even with a small sample size, differences were statistically significant. As reference, the seminal study that tested the association between ISG expression and HCV treatment outcome was conducted by Sarasin- Filipowicz et al. , examining only 16 patients. Another issue that could generate discussion is the cellular type we used: PBMCs. There is the wrong idea that PBMCs are not a good cell population to evaluate ISGs expression. This idea is being drawn by some studies that have misinterpreted the findings of that study showing that there was a statistically significant difference in the number of differentially expressed genes in PBMCs between responder and nonresponder patients, but that this difference was less pronounced compared with the data obtained from liver biopsies . The validation for using PBMCs to investigate ISGs expression during anti-HCV therapy also comes from several other studies that have concluded that changes in IFN-α-inducible genes can be identified in human PBMCs in vivo as well as ex vivo [41–44]. In our study, despite lacking paired liver biopsies and PBMCs, we also demonstrated a clear differentiated pattern of ISGs expression according to treatment outcome in PBMCs from HIV/HCV-coinfected patients on successful HAART.
In summary, our results demonstrate a robust association between ISGs and response to HCV therapy in PBMCs from HIV/HCV-coinfected patients on successful HAART. Moreover, we found a lack of a direct link between rs12979860 IL28B genotypes and ISGs expression in our study population. These results confirm prior findings in HCV-monoinfected patients testing liver tissue specimens . The clinical applicability of our findings is obvious, taking into account the major predictive value of ISGs expression for treatment response and the difficult-to-treat profile of HIV/HCV-coinfected patients. Testing ISGs on PBMCs is clearly an advantage and would support treatment decision making in this population.
We would like to thank all patients who participated in the study. This work was supported in part by grants from Fundación Investigacion y Educacion en SIDA (IES), Red de Investigacion en SIDA (RIS, FIS-RD06/0006), Agencia Lain Entralgo, the NEAT European project and Fondo de Investigación Sanitaria (grant PI11/00870). L.A.L.F. was supported by ‘Programa Miguel Servet FIS CP06/00267’.
N.I.R., L.A.L.F., J.M.B. and V.S. designed the study. N.I.R. and S.F. did the virological studies and collected the specimens. S.F. and N.I.R. performed SNP genotyping. M.I.G., N.I.R. and L.A.L.F. developed all other assays. L.A.L.F. and A.B. performed the statistical analysis. V.S. and J.M.B. were responsible for and analysed the demographics, clinical and therapeutic information of the study population. N.I.R., L.A.L.F., J.M.B. and V.S. wrote the manuscript draft. All authors revised and approved the final submission.
Conflicts of interest
The authors have no financial conflict of interest with this work.
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