HLA-E variants are associated with sustained virological response in HIV/hepatitis C virus-coinfected patients on hepatitis C virus therapy
Guzmán-Fulgencio, Maríaa; Berenguer, Juanb; Rallón, Normac; Fernández-Rodríguez, Amandaa; Miralles, Pilarb; Soriano, Vicentec; Jiménez-Sousa, María A.a; Cosín, Jaimeb; Medrano, Joséc; García-Álvarez, Mónicaa; López, Juan C.b; Benito, José M.c; Resino, Salvadora
aUnidad de Coinfección HIV/Hepatitis, Centro Nacional de Microbiología, Instituto de Salud Carlos III, Majadahonda
bUnidad de Enfermedades Infecciosas/VIH, Hospital General Universitario ’Gregorio Marañón’
cServicio de Enfermedades Infecciosas, Hospital Carlos III, Madrid, Spain.
Correspondence to Salvador Resino, Centro Nacional de Microbiología, Instituto de Salud Carlos III (Campus Majadahonda), Carretera Majadahonda–Pozuelo, Km 2.2, Majadahonda, Madrid 28220, Spain. Tel: +34 918 223 266; fax: +34 918 223 269; e-mail: firstname.lastname@example.org
Received 25 September, 2012
Revised 10 December, 2012
Accepted 23 January, 2013
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Objectives: To analyze whether human leukocyte antigen (HLA)-E allelic variants are associated with and may predict response to peg-interferon (IFN) alpha and ribavirin treatment in HIV/hepatitis C virus (HCV)-coinfected patients.
Design: Retrospective follow-up study.
Methods: We studied 321 naive patients who started HCV treatment. HLA-E genotyping was performed by restriction fragment length polymorphism. A sustained virological response (SVR) was defined as undetectable plasma HCV-RNA up through 24 weeks after the end of HCV treatment.
Results: The HLA-E*0101 allele increased the odds of achieving SVR for all patients [adjusted odds ratio (aOR) = 2.03 (95% confidence interval, 95% CI = 1.35–3.06); P = 0.001], for HCV genotype (GT) 1/4 patients (aOR = 1.62 (95% CI = 1.03–2.54), P = 0.035), and for GT2/3 patients [aOR = 9.87 (95% CI = 2.47–31.89), P = 0.001]. For decision tree analysis, the SVR rate increased from 0 to 82.6% and then to 92.5% in GT2/3 patients when the count of HLA-E*0101 alleles increased. In GT1/4 patients with rs8099917 TT genotype, the SVR rate increased from 33.3 to 54.8% and then to 61.8% when the count of HLA-E*0101 alleles increased. In GT1/4 patients with rs8099917 GT/GG genotype, the SVR rate increased from 15.4 to 22% and then to 44% when the count of HLA-E*0101 alleles increased. The overall percentage of patients correctly classified was 73.2% and the area under the receiver operating characteristic curve (AUROC) was 0.803 ± 0.024.
Conclusion: The HLA-E*0101 allele was associated with increased odds of HCV clearance and could help to predict SVR among HIV/HCV-coinfected patients on HCV therapy. This would be helpful to avoid treatment in those less likely to respond to pegylated-interferon-alpha and ribavirin treatment.
Through the use of HAART, HIV infection has become a chronic disease, and, thus, its mortality has declined . As a result, chronic hepatitis C (CHC) has turned into an important comorbidity and a major cause of death among HIV/hepatitis C virus (HCV)-coinfected patients .
HCV therapy with pegylated-interferon-alpha and ribavirin (pegIFNα/RVB) is still in use among HIV/HCV-coinfected patients , even in combination with new therapies such as telaprevir or boceprevir . However, not all HIV/HCV-coinfected patients achieve the desired sustained virological response (SVR) . Due to this fact, the identification of predictors for HCV therapy success is particularly desirable to ensure an adequate selection of the best candidates and to minimize any undesirable toxicity. To date, the best baseline predictors of response to current HCV therapy are HCV genotype, baseline serum HCV RNA level, liver fibrosis, and SNPs around interleukin 28B (IL28B) gene . However, an unexplained variability in treatment outcome still remains, suggesting that other host genetic factors may play an important role in pegIFNα/RBV treatment success .
The human leukocyte antigen (HLA)-E molecule is a ligand for CD94/NKG2 receptors [CD94/NKG2A (inhibitory) and CD94/NKG2C (activator)] on natural killer (NK) cells and NK cytotoxic T lymphocytes (NK-CTL), as well as a ligand for the αβ-T-cell receptor (TCR) on CD8+ T lymphocytes (CTLs) [7,8]. The HLA-E gene is minimally polymorphic. One single nucleotide substitution (A to G at position 382, exon 3) results in an amino acid change from arginine (R) to a glycine (G) at position 107 of the α2 heavy-chain domain [9,10]. This nonsynonymous change generates two variants (HLA-E*0101 and HLA-E*0103), which differ at only one amino acid position.
HLA-E plays an important role in regulating antiviral immunity . Both HIV and HCV infections are associated with enhanced HLA-E expression, which may contribute to viral persistence as an additional viral evasion strategy targeting the antiviral activities of NK cells [11,12]. Furthermore, the presence of a HLA-E*0101/HLA-E*0101 genotype might confer protection from HIV infection  and HCV infection . Finally, the NK receptor has recently been associated with pegIFNα/RBV therapy-induced clearance, in combination with IL28B genotype [15,16].
The aim of the present study was to analyze whether HLA-E allelic variants are associated with and may predict the response to pegIFNα/RBV treatment in HIV/HCV-coinfected patients.
Patients and methods
We carried out a retrospective follow-up study on 321 HIV/HCV-coinfected patients, who started treatment with pegIFNα/RBV on regular follow-up for the first time, at two reference HIV hospitals located in Madrid, Spain. The study population consisted of HIV/HCV-coinfected individuals who had completed a course of pegIFNα/RBV therapy and were genotyped for HLA-E variants. This study was conducted in accordance with the Declaration of Helsinki. Patients gave their written consent for the study and it was approved by the Institutional Ethics Committee.
Information was obtained from medical records as previously described : age, sex, risk category, weight, height, nadir CD4+ T-cell count, antiretroviral therapy, HCV genotype, and liver fibrosis. In addition, during HCV therapy, a blood sample was taken from each patient to analyze complete blood counts, CD4+ T cells, plasma HIV viral load (HIV-RNA), and plasma HCV viral load (HCV-RNA).
Genomic DNA was extracted from peripheral blood by using Qiagen columns (QIAamp DNA Blood Midi/Maxi; Qiagen, Hilden, Germany). The IL28B polymorphism rs8099917 was genotyped by the Spanish National Genotyping Centre (CeGen; http://http://www.cegen.org/). Genotyping was performed by using the GoldenGate assay with VeraCode Technology (Illumina Inc. San Diego, California, USA). The HLA-E polymorphism rs1264457 was genotyped by PCR restriction fragment length polymorphism (PCR-RFLP) in order to differentiate between HLA-E*0101 and HLA-E*0103 variants. After PCR, fragments were digested by the restriction enzyme HpaII. The PCR amplicon of the HLA-E*0103 allele presents a restriction site for HpaII, producing two fragments of 260 and 20 bp, whereas the HLA-E*0101 allele has no restriction site for the enzyme. Primer sequences have been previously reported .
Hepatitis C therapy
Treatment regimens included pegIFNα 2a or 2b at standard doses (180 μg/week or 1.5 μg/kg per week, respectively) and weight-adjusted RBV dosing (1000 mg/day for patients weighing <75 kg and 1200 mg/day for patients weighing ≥75 kg). Following international guidelines , patients with HCV genotypes 1 or 4 received either 48 or 72 weeks of treatment, and patients with HCV genotype 2 or 3 were treated for 24 or 48 weeks, according to virological response at week 4. Early stopping rules were applied for individuals with suboptimal virological response at week 12 . A SVR was defined as an undetectable serum HCV-RNA level (<10 IU/ml) up through 24 weeks after the end of treatment. Patients not fulfilling SVR criteria were considered as nonresponders.
For this study, we excluded patients from the analysis that had their HCV treatment prematurely interrupted due to adverse events, abandonment, or loss of follow-up. The statistical analysis was carried out by on-treatment analysis of observed data.
The statistical analysis was performed with the Statistical Package for the Social Sciences (SPSS) 15.0 (SPSS Inc., Chicago, Illinois, USA). All P values were two-tailed. Statistical significance was defined as P less than 0.05. Categorical data and proportions were analyzed using the χ2 test or Fisher's exact test. Kruskal–Wallis test was used to compare data among independent groups. P values were adjusted by Bonferroni correction.
Statistically significant deviations from the expected genotypic frequencies were determined using the Hardy–Weinberg principle with a P value cut-off of less than 0.01 . The trend data were tested by Gamma correlation coefficient (γ; values between −1 and +1), a nonparametric test for measuring the correlation between ordinal variables. Next, we performed univariate and multivariate logistic regression analyses to investigate the association between HLA-E alleles and HCV treatment response. In each multiple logistic regression analysis, we included the number of HLA-E*0101 alleles and the most significant covariables, which were selected by a stepwise algorithm (at each step, factors are considered for removal or entry: a P value for entry of 0.20 and exit of 0.15). The covariables included in stepwise analysis were sex, age, BMI (≥25 kg/m2), nadir CD4+ T cells, undetectable HIV-RNA (<50 copies/ml), CD4+ T cells, HAART, HCV-RNA at least 500 000 IU/ml, HCV genotype (GT1/4 vs. GT3), significant fibrosis (F≥2), and rs8099917 TT genotype.
Classification and regression tree (CART) was used to classify SVR according to HLA-E and IL28B genotypes, and HCV genotype. CART is a prognostic system with a hierarchical structure, based on recursive portioning that builds a decision tree to identify subgroups at higher odds of SVR. A number of different configurations were evaluated using 25-fold cross-validation to determine the optimal split. The accuracy was evaluated by calculating area under the receiver operating characteristic curves (AUROC). Criteria to qualify for accuracy were as follows: 0.90–1 = excellent, 0.80–0.90 = good, 0.70–0.80 = fair, and 0.60–0.70 = poor.
Table 1 shows the clinical and epidemiological characteristics of 321 HIV/HCV-coinfected patients on HCV treatment. Of note, patients with HLA-E*0101/*0101 genotype had higher percentages of GT2/3 and the favorable rs8099917 TT genotype, which are both relevant predictive factors of virological response.
Human leukocyte antigen-E alleles are associated with sustained virological response
The Hardy–Weinberg equilibrium was evaluated for rs8099917 at IL28B (P = 0.220) and rs1264457 at HLA-E (P = 0.049), considering equilibrium when P values were higher than the cut-off of 0.01. We analyzed the data according to genetic models of additive, dominant, and recessive inheritance. The additive genetic model showed the strongest association with SVR. In the additive model, the risk conferred by an allele is increased r-fold for heterozygotes and 2r-fold for homozygotes with two copies of a specific allele. In this case, homozygotes for the minor allele, heterozygotes, and homozygotes for the major allele were coded as 0, 1, and 2, respectively.
We found a significant trend of achieving SVR when the number of HLA-E*0101 alleles increased irrespective of the HCV genotype or IL28B genotype (Fig. 1). Moreover, there was also a significant trend of achieving successful virological response for each HLA-E*0101 allele at different endpoints during HCV treatment (see supplementary data, http://links.lww.com/QAD/A315). However, rs8099917 TT was associated with virological response only in GT1/4 patients, but not in GT2/3 patients (see supplementary data, http://links.lww.com/QAD/A315).
Next, we analyzed the influence of the HLA-E*0101 allele on SVR using a logistic regression analysis adjusted by the most relevant characteristics of patients (Table 2). The HLA-E*0101 allele increased odds of achieving SVR [adjusted odds ratio (aOR) = 2.04]. Moreover, patients had increased odds of achieving SVR per HLA-E*0101 allele in patients infected with GT1/4 (aOR = 1.59) or GT2/3 (aOR = 6.51), and patients with rs8099917 TT (aOR = 2.14) or rs8099917 GT/GG (aOR = 2.65). In addition, we did not find any statistically significant interaction between HLA-E and IL28B genotypes regarding HCV therapy response.
Prediction of sustained virological response
Figure 2 shows a decision tree analysis with the three variables that had the highest significant associations with SVR (HCV genotype, IL28B genotype, and HLA-E genotype).
In patients infected with GT2/3, SVR rate increased from 0 to 82.6% and then to 92.5% when the count of HLA-E*0101 alleles increased. In patients infected with GT1/4 and with the favorable rs8099917 TT genotype, SVR rate increased from 33.3 to 54.8% and then to 61.8% when the count of HLA-E*0101 alleles increased. In patients infected with GT1/4 and with the unfavorable rs8099917 GT/GG genotype, SVR rate increased from 15.4 to 22% and then to 44% when the count of HLA-E*0101 alleles increased.
The overall percentage of patients correctly classified (accuracy) was 73.2% and the AUROC of this decision tree was 0.803 ± 0.024. For those patients with a non-SVR response, non-SVR was predicted for only 59.3% of them, which means that 40.7% of the non-SVR patients were inaccurately classified as SVR patients. For those patients with a SVR response, SVR was predicted for 84% of them, which means that 16% of the SVR patients were inaccurately classified as non-SVR patients. After 25-fold cross-validation, the overall percentage of patients correctly classified was 71.7%.
This study shows that patients carrying the HLA-E*0101 allele had a higher probability of successful HCV treatment. Moreover, a predictive model with HCV genotype, rs8099917 genotype, and HLA-E genotype had an accuracy value close to 75%.
The mechanism behind the association between HLA-E and treatment-induced HCV clearance is unknown. On the one hand, a failure in the immune response related to HLA-E may be a reason. As a novel strategy adopted by HCV to evade NK cell-mediated responses, an upregulation of CD94/NKG2A inhibitory receptors is known to occur during HCV infection on both NK cells and NK-CTL, which are more susceptible to inhibition via HLA-E/NKG2A interactions . In addition, the HLA-E*0101/*0101 genotype has been associated with low HLA-E surface expression . Thus, the HLA-E-mediated inhibition of NK cell function could be less effective in carriers of the HLA-E*0101/*0101 genotype, which would help in producing a more effective immune response against HCV. Therefore, as the interaction of HLA-E is NKG2-specific, our data might support the role of NK function in HCV clearance during pegIFNα/RVB therapy via killing virally infected cells . In addition, HIV infection has been associated with deregulated expression of CD94/NKG2A and CD94/NKG2C on both NK cells and CD8+ T cells [23–25]. Thus, the effect of HLA-E polymorphisms might be different in HIV/HCV-coinfected and HCV-monoinfected patients. On the other hand, it might be argued that a more potent T-cell-mediated immune response can explain the better treatment outcomes for patients with the HLA-E*0101/*0101 genotype. These patients have a high frequency of antiviral HLA-E-restricted CD8+ T cells with a high degree of HLA-E-restricted IFN-γ secretion, which is associated with low HCV viral load . Moreover, the natural ligands for HLA-E are nonamer peptides derived from the leader sequence of classical major histocompatibility complex I molecules, which show higher binding affinity to the HLA-E*0103 allele. This increased affinity is due to a higher stability of complexes formed between the leader peptides and HLA-E*0103 compared to those formed by HLA-E*0101 . Under this assumption, it is possible that HLA-E*0101 could more readily be available than HLA-E*0103 to bind to HCV peptides, which would facilitate HLA-E-restricted CD8+ T-cell responses .
IL28B polymorphisms are already used as a predictive marker of treatment response to pegIFNα/RVB in clinical practice . To date, many articles have assessed the influence of IL28B polymorphisms on the SVR in CHC patients, wherein rs8099917 and rs12979860 have been the most studied . Although rs12979860 is more likely to be correlated with SVR in the white population, we recently have shown a strong association of rs8099917 with SVR in HCV/HIV-coinfected patients . In the current study, we did not analyze rs12979860 but only rs8099917, which is in high linkage disequilibrium with rs12979860 in the European population . In addition, rs8099917 has been less studied than rs12979860 in white populations, and therefore additional results involving rs8099917 would be of interest.
Curiously, in our study, we have shown that HLA-E variants had a significant role similar to that of rs8099917 variants in predicting HCV treatment response among HCV/HIV-coinfected patients. Furthermore, the inclusion of both genetic markers had an additive effect on the ability to predict SVR. This genetic evidence supports an underlying physiological mechanism for HCV viral control involving a relationship between IL28B and HLA-E. In agreement with this, Golden-Mason et al. recently reported that higher expression levels of inhibitory NKG2A receptors were present in patients who failed to achieve SVR and in patients carrying the unfavorable IL28B allele. Moreover, it should be noted that there may be a different distribution of favorable and unfavorable genotypes of rs12979860 and rs8099917 in our cohort, and this could affect the relationship found with HLA-E alleles differently.
The combination of IL28B genotype and plasma levels of IFN-γ inducible protein-10 (IP-10) has also been found to be useful to predict SVR among CHC patients [28–31]. IL28B encodes IFN-λ3, which induces HCV antiviral activity through IFN-stimulated genes (ISGs) . The so-called favorable IL28B genotypes (associated with better HCV treatment response) had low hepatic expression levels of IL28B and ISGs, but are induced more strongly after administration of IFN-α treatment . IP-10 is one of those ISGs induced during the immune response against viral infections , but it is unclear why high IP-10 levels are associated with a poor response to HCV therapy. In our study, we found that the accuracy of our algorithm was similar to other models that use a combination of IL28B genotype and IP-10 levels [28–31]. However, we did not have data for IP-10, and it might be possible that the diagnostic accuracy of our algorithm (HCV, IL28B, and HLA-E genotypes) would be enhanced with this biomarker.
This study has other limitations that must be taken into account for the correct interpretation of the data. Our study design is retrospective and contains a low number of patients. All selected patients met a set of criteria for starting HCV treatment (e.g. no alcohol abuse, high CD4 cell counts, controlled HIV replication, and good treatment adherence), and this may have introduced a selection bias. In addition to this, this study was carried out entirely in whites; therefore, as the frequency of these alleles differs among different ethnicities, it would be necessary to perform an independent replication of this study for different ethnic groups. We did not have a second independent cohort of HCV-infected patients in which to confirm the proposed association of HLA-E variants with HCV therapy outcome. Finally, IFN therapy regimens were not identical as they varied in some characteristics such as pegIFNα 2a or 2b and likely RVB dose. Our study is not a clinical trial, and this lack of uniformity may have a significant unaccounted for effect on the interpretation of our results. Instead, each physician administered the appropriate HCV therapy regimen according to his/her criteria and by following local and/or international guidelines. However, the data presented here are entirely derived from routine clinical practice.
In conclusion, the HLA-E*0101 allele was associated with increased odds of HCV clearance and could help to predict SVR among HIV/HCV-coinfected patients on HCV therapy. It would be helpful to categorize patients before HCV therapy so as to avoid prescribing treatment in those less likely to respond to pegIFNα/RVB treatment.
The authors thank the Spanish National Genotyping Center (CeGen) for providing the genotyping services (http://www.cegen.org).
M.G.F. and S.R. performed all statistical analysis, interpretation of the data, and wrote the article. J.B., V.S., and S.R. participated in the study concept and design. J.B., V.S., J.C., J.C.L., and P.M. participated in patient selection, collection of samples, and acquisition of data. A.F.R., M.A.J.S., M.G.A., J.M.B., J.M., and N.R. participated in sample preparation, DNA isolation and genotyping preprocedure, and contributed with critical revision of the article. S.R. supervised the study.
All authors revised the article from a draft by S.R.
This work has been supported by grants given by Instituto de Salud Carlos III (Ref. PI08/0738, ISCIII-RETIC RD12/0017 and PI11/00245 to S.R.; Ref. ISCIII-RETIC RD06/006, PI08/0928, and PI11/01556 to J.B.; and Ref. PI11/00870 to J.M.B.), Fundación para la Investigación y la Prevención del Sida en España (FIPSE) (Ref. 361020/10 to J.B.) and Fundación para la Investigación y la Educación en SIDA (F-IES).
M.G.F., M.G.A., and M.A.J.S. are supported by a grant from Instituto de Salud Carlos III (CM09/00031, CM08/00101, and CM10/00105, respectively).
Conflicts of interest
The authors do not have any commercial or other association that might pose a conflict of interest.
1. Mocroft A, Ledergerber B, Katlama C, Kirk O, Reiss P, d’Arminio Monforte A, et al. Decline in the AIDS and death rates in the EuroSIDA study: an observational study. Lancet 2003; 362:22–29.
2. Lewden C, May T, Rosenthal E, Burty C, Bonnet F, Costagliola D, et al. Changes in causes of death among adults infected by HIV between 2000 and 2005: the ‘Mortalite 2000 and 2005’ surveys (ANRS EN19 and Mortavic). J Acquir Immune Defic Syndr 2008; 48:590–598.
3. Ghany MG, Strader DB, Thomas DL, Seeff LB. Diagnosis, management, and treatment of hepatitis C: an update. Hepatology 2009; 49:1335–1374.
4. Naggie S, Sulkowski MS. Management of patients coinfected with HCV and HIV: a close look at the role for direct-acting antivirals. Gastroenterology 2012; 142:1324–1334.e1323.
5. Calvaruso V, Craxi A. 2011 European Association of the Study of the Liver hepatitis C virus clinical practice guidelines. Liver Int 2012; 32 (Suppl 1):2–8.
6. Soriano V, Poveda E, Vispo E, Labarga P, Rallon N, Barreiro P. Pharmacogenetics of hepatitis C. J Antimicrob Chemother 2012; 67:523–529.
7. Pietra G, Romagnani C, Manzini C, Moretta L, Mingari MC. The emerging role of HLA-E-restricted CD8+ T lymphocytes in the adaptive immune response to pathogens and tumors. J Biomed Biotechnol 2010; 2010:907092.
8. Pietra G, Romagnani C, Mazzarino P, Falco M, Millo E, Moretta A, et al. HLA-E-restricted recognition of cytomegalovirus-derived peptides by human CD8+ cytolytic T lymphocytes. Proc Natl Acad Sci U S A 2003; 100:10896–10901.
9. Grimsley C, Ober C. Population genetic studies of HLA-E: evidence for selection. Hum Immunol 1997; 52:33–40.
10. Ulbrecht M, Couturier A, Martinozzi S, Pla M, Srivastava R, Peterson PA, et al. Cell surface expression of HLA-E: interaction with human beta2-microglobulin and allelic differences. Eur J Immunol 1999; 29:537–547.
11. Nattermann J, Nischalke HD, Hofmeister V, Ahlenstiel G, Zimmermann H, Leifeld L, et al. The HLA-A2 restricted T cell epitope HCV core 35-44 stabilizes HLA-E expression and inhibits cytolysis mediated by natural killer cells. Am J Pathol 2005; 166:443–453.
12. Nattermann J, Nischalke HD, Hofmeister V, Kupfer B, Ahlenstiel G, Feldmann G, et al. HIV-1 infection leads to increased HLA-E expression resulting in impaired function of natural killer cells. Antivir Ther 2005; 10:95–107.
13. Lajoie J, Hargrove J, Zijenah LS, Humphrey JH, Ward BJ, Roger M. Genetic variants in nonclassical major histocompatibility complex class I human leukocyte antigen (HLA)-E and HLA-G molecules are associated with susceptibility to heterosexual acquisition of HIV-1. J Infect Dis 2006; 193:298–301.
14. Schulte D, Vogel M, Langhans B, Kramer B, Korner C, Nischalke HD, et al. The HLA-E(R)/HLA-E(R) genotype affects the natural course of hepatitis C virus (HCV) infection and is associated with HLA-E-restricted recognition of an HCV-derived peptide by interferon-gamma-secreting human CD8(+) T cells. J Infect Dis 2009; 200:1397–1401.
15. Suppiah V, Gaudieri S, Armstrong NJ, O’Connor KS, Berg T, Weltman M, et al. IL28B, HLA-C, and KIR variants additively predict response to therapy in chronic hepatitis C virus infection in a European Cohort: a cross-sectional study. PLoS Med 2011; 8:e1001092.
16. Golden-Mason L, Bambha KM, Cheng L, Howell CD, Taylor MW, Clark PJ, et al. Natural killer inhibitory receptor expression associated with treatment failure and interleukin-28B genotype in patients with chronic hepatitis C. Hepatology 2011; 54:1559–1569.
17. Fernandez-Rodriguez A, Rallon N, Berenguer J, Jimenez-Sousa MA, Cosin J, Guzman-Fulgencio M, et al. Analysis of IL28B alleles with virologic response patterns and plasma cytokine levels in HIV/HCV coinfected patients. AIDS 2013; 27:163–173.
18. Mosaad YM, Abdel-Dayem Y, El-Deek BS, El-Sherbini SM. Association between HLA-E *0101 homozygosity and recurrent miscarriage in Egyptian women. Scand J Immunol 2011; 74:205–209.
19. Soriano V, Puoti M, Sulkowski M, Cargnel A, Benhamou Y, Peters M, et al. Care of patients coinfected with HIV and hepatitis C virus: 2007 updated recommendations from the HCV-HIV International Panel. AIDS 2007; 21:1073–1089.
20. Lunetta KL. Genetic association studies. Circulation 2008; 118:96–101.
21. Strong RK, Holmes MA, Li P, Braun L, Lee N, Geraghty DE. HLA-E allelic variants. Correlating differential expression, peptide affinities, crystal structures, and thermal stabilities. J Biol Chem 2003; 278:5082–5090.
22. Ahlenstiel G, Titerence RH, Koh C, Edlich B, Feld JJ, Rotman Y, et al. Natural killer cells are polarized toward cytotoxicity in chronic hepatitis C in an interferon-alfa-dependent manner. Gastroenterology 2010; 138:325–335–322.e321–322.
23. Costa P, Rusconi S, Mavilio D, Fogli M, Murdaca G, Pende D, et al. Differential disappearance of inhibitory natural killer cell receptors during HAART and possible impairment of HIV-1-specific CD8 cytotoxic T lymphocytes. AIDS 2001; 15:965–974.
24. Zhang R, Xu J, Hong K, Yuan L, Peng H, Tang H, et al. Increased NKG2A found in cytotoxic natural killer subset in HIV-1 patients with advanced clinical status. AIDS 2007; 21 (Suppl 8):S9–S17.
25. Brunetta E, Fogli M, Varchetta S, Bozzo L, Hudspeth KL, Marcenaro E, et al. Chronic HIV-1 viremia reverses NKG2A/NKG2C ratio on natural killer cells in patients with human cytomegalovirus co-infection. AIDS 2010; 24:27–34.
26. Jiménez-Sousa MA, Fernández-Rodríguez A, Guzmán-Fulgencio M, García-Álvarez M, Resino S. Meta-analysis: implications of IL28B polymorphisms in spontaneous and treatment-related clearance for hepatitis C patients. BMC Med 2013; 11:6.
27. Holmes JA, Desmond PV, Thompson AJ. Redefining baseline demographics: the role of genetic testing in hepatitis C virus infection. Clin Liver Dis 2011; 15:497–513.
28. Payer BA, Reiberger T, Aberle J, Ferenci P, Holzmann H, Rieger A, et al. IL28B and interferon-gamma inducible protein 10 for prediction of rapid virologic response and sustained virologic response in HIV-HCV-coinfected patients. Eur J Clin Invest 2012; 42:599–606.
29. Fattovich G, Covolo L, Bibert S, Askarieh G, Lagging M, Clement S, et al. IL28B polymorphisms, IP-10 and viral load predict virological response to therapy in chronic hepatitis C. Aliment Pharmacol Ther 2011; 33:1162–1172.
30. Lagging M, Askarieh G, Negro F, Bibert S, Soderholm J, Westin J, et al. Response prediction in chronic hepatitis C by assessment of IP-10 and IL28B-related single nucleotide polymorphisms. PLoS One 2011; 6:e17232.
31. Darling JM, Aerssens J, Fanning G, McHutchison JG, Goldstein DB, Thompson AJ, et al. Quantitation of pretreatment serum interferon-gamma-inducible protein-10 improves the predictive value of an IL28B gene polymorphism for hepatitis C treatment response. Hepatology 2011; 53:14–22.
32. Marcello T, Grakoui A, Barba-Spaeth G, Machlin ES, Kotenko SV, MacDonald MR, et al. Interferons alpha and lambda inhibit hepatitis C virus replication with distinct signal transduction and gene regulation kinetics. Gastroenterology 2006; 131:1887–1898.
33. Hayes CN, Imamura M, Aikata H, Chayama K. Genetics of IL28B and HCV: response to infection and treatment. Nat Rev Gastroenterol Hepatol 2012; 9:406–417.
34. Kelly C, Klenerman P, Barnes E. Interferon lambdas: the next cytokine storm. Gut 2011; 60:1284–1293.
AIDS; hepatitis C virus clearance; hepatitis C virus therapy; HLA-E; IL28B; single nucleotide polymorphism
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