BASIC
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TRANSLATIONAL SCIENCE
PPARg2 Pro12Ala Polymorphism Is Associated With Sustained Virological Response in HIV/HCV-Coinfected Patients Under HCV Therapy Amanda Fernández-Rodríguez, PhD,* Juan Berenguer, MD, PhD,†‡ Norma Rallón, PhD,§ María A. Jiménez-Sousa, PhD,* Juan Carlos López, MD, PhD,† Vicente Soriano, MD, PhD,k Mónica García-Álvarez, PhD,* Jaime Cosín, MD, PhD,† Paula Martínez, PhD,§ María Guzmán-Fulgencio, PhD,* Pilar Miralles, MD,† José Miguel Benito, MD, PhD,§ and Salvador Resino, PhD*
Objectives: To analyze whether peroxisome proliferator-activated receptor gamma (PPARg2) rs1801282 (Pro12Ala) polymorphism is associated with the response to pegylated-interferon-alpha plus ribavirin treatment in HIV/hepatitis C virus (HCV)-coinfected patients, and whether it is able to predict the outcome of HCV treatment.
Design: Retrospective follow-up study. Methods: Two hundred eighty-five naive patients, who started HCVtreatment, were genotyped for PPARg2 and interleukin 28B polymorphisms. Genetic data were analyzed under dominant inheritance model. Received for publication January 3, 2014; accepted May 13, 2014. From the *Unidad de Infección viral e Inmunidad, Centro Nacional de Microbiología, Instituto de Salud Carlos III, Majadahonda, Madrid, Spain; †Unidad de Enfermedades Infecciosas/VIH; Hospital General Universitario “Gregorio Marañón,” Madrid, Spain; ‡Instituto de Investigación Sanitaria Gregorio Marañón (IiSGM), Madrid, Spain; §IIS-Fundación Jiménez Díaz, Universidad Autónoma de Madrid, Madrid Spain; and kServicio de Enfermedades Infecciosas, Hospital Carlos III, Madrid, Spain. Supported by grants given by Fondo de Investigacion de Sanidad en España (FIS) (Spanish Health Founds for Research) (Grant Nos. PI08/0738, PI11/ 00245; PI11/00870, PI08/0928, and PI11/01556), Red Española de Investigación en SIDA (RIS) (AIDS Research Network) (Grant Nos. RD12/ 0017/0024, RD12/0017/0004, and RD12/0017/0031), “Fundación para la Investigación y la Prevención del Sida en España” (FIPSE) (Grant No. 361020/10). This work has been funded by the Grants RD12/0017/0024 and RD12/0017/0004 as part of the National R + D + I and cofinanced by the ISCIII-General Subdirectorate for Assessment and the European Regional Development Fund (ERDF). A.F.R., M.G.-F., M.G.-A., and M.A.J.-S. are supported by “Instituto de Salud Carlos III” (Grant Nos. UIPY-1377/08, RD12/0017/0024, CD12/00442, and CD13/00013, respectively). J.B. is an investigator from the Programa de Intensificación de la Actividad Investigadora en el Sistema Nacional de Salud (I3SNS). A.F.R. and S.R. performed all statistical analysis, interpretation of the data, and wrote the manuscript. 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., and N.R. participated in sample preparation, DNA isolation and genotyping preprocedure, and contributed with critical revision of the manuscript. S.R. supervised the study. The authors have no conflicts of interest to disclose. Correspondence to: Salvador Resino, PhD, Centro Nacional de Microbiología, Instituto de Salud Carlos III (Campus Majadahonda), Carretera Majadahonda- Pozuelo, Km 2.2; 28220 Majadahonda, Madrid, Spain (e-mail: [email protected]). Copyright © 2014 by Lippincott Williams & Wilkins
Sustained virological response (SVR) was defined as undetectable HCV viremia through 24 weeks after the end of HCV treatment.
Results: The variables significantly associated with SVR in a multivariate analysis were HCV-genotype (GT) 3 {adjusted odds ratio [aOR] = 7.66 [95% of confidence interval (95% CI): 3.96 to 14.81] P , 0.001}, HCV-viremia ,500,000 IU/mL [aOR = 2.20 (95% CI: 1.16 to 4.15] P = 0.015), no/mild liver fibrosis (F , 2) [aOR = 1.92 (95% CI: 1.08 to 3.42) P = 0.026], IL28B rs12980275 AA genotype [aOR = 2.70 (95% CI: 1.54 to 4.71) P , 0.001], and PPARg2 rs1801282 CG/GG genotype [aOR = 2.93 (95% CI: 1.27 to 6.72) P = 0.011]. When PPARg2 rs1801282 genotype was included in a decision tree analysis, HCV-GT3 patients with CG/GG genotype had increased SVR from 80.3% to 100%. In GT1/4 patients, rs12980275 AA carriers had increased SVR from 58.7% to 78.6%, and rs12980275 AG/GG carriers had increased SVR from 28.7% to 35.7%. The overall percentage of patients correctly classified was 71.6% and the area under the receiver operating characteristic curves was 0.766 6 0.028. Conclusions: The presence of PPARg2 rs1801282 G allele (Ala variant) was associated with increased odds for achieving SVR in HIV/HCV-coinfected patients on HCV treatment. Key Words: chronic hepatitis C, AIDS, HCV therapy, PPARg2, single nucleotide polymorphism (J Acquir Immune Defic Syndr 2014;67:113–119)
INTRODUCTION The combination antiretroviral therapy (cART) has made of HIV infection a chronic manageable infection in the western world.1 In this setting, chronic hepatitis C (CHC) has turned into an important comorbidity and a major cause of death among HIV/hepatitis C virus (HCV)-coinfected patients.2–4 However, the mechanisms underlying the accelerated of these diseases in HIV/HCV-coinfected patients are not well understood.5 HCV therapy with pegylated-interferon-alpha plus ribavirin (pegIFNa/ribavirin) is still in use among HIV/ HCV-coinfected patients but the effectiveness of this treatment is limited.6 Nowadays, the new direct-acting antivirals (DAAs) are generally being administered in combination with
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pegIFNa/ribavirin,7,8 but the potential use of these DAAs in HIV/HCV-coinfected patients has numerous challenges, such as the choice of patients to treat possible interaction between antiretroviral drugs and the DAAs, and uncertainty regarding the safety and effectiveness of the combination therapy in this population.7,8 Recently, sofosbuvir has been approved, a nucleotide analogue HCV NS5B polymerase inhibitor, which offers better tolerability and efficacy across all HCV genotypes (GTs),9 and its combination with pegIFNa/ribavirin is being a standard of care for GT1 patients.10 Thus, it is still essential the potential ongoing relevance of understanding pegIFNa/ ribavirin response predictors. However, not all HIV/HCVcoinfected patients achieve the desired sustained virological response (SVR).11 The identification of predictors for HCV therapy might help to ensure an adequate selection of the best candidates and to minimize any undesirable toxicity. To date, the best baseline predictors for HCV therapy are HCV genotype, HCV viremia, liver fibrosis, and single-nucleotide polymorphisms (SNPs) around interleukin 28B (IL28B) gene.12 Additionally, important metabolic anomalies have been detected in HIV/HCV-coinfected patients,13 such as insulin resistance (IR) and type 2 diabetes mellitus (T2DM), which has been related to lower SVR in pegIFNa/ribavirin therapy.14,15 However, an unexplained variability in HCV treatment outcome still remains, which suggests that other host genetic factors may play an important role in pegIFNa/ ribavirin therapy.16 Peroxisome proliferator-activated receptor gamma (PPARg) is considered as a “key element” in the glucose homeostasis and lipoprotein metabolism,17 being mainly expressed in adipose tissue.18 The PPARg gene is located on chromosome 3; and differential splicing of this gene results in 2 different isoforms: PPARg1 and PPARg2, differing only in their N-terminal region.19 The increase of PPARg2 gene transcription results in the upregulation of the insulin-sensitizing factor and the downregulation of the insulin-resistant factor.20 Moreover, PPARg2 expression in adipocytes seems to be negatively influenced by both HIV proteins21,22 and antiretroviral drugs,23,24 while some HCV proteins (core and NS5A) increase hepatic lipid accumulation by induction of activation and PPARg2 expression.25,26 The most common gene polymorphism in human PPARg2 gene is the rs1801282 (Pro12Ala) polymorphism, resulting from a cytosine–guanine exchange (CCA-to-GCA missense mutation) in exon 2 (codon 12), which involves an amino acid change from proline (Pro) to alanine (Ala), affecting the NH2-terminal residue that defines the adipocyte-specific PPARg2 isoform.19 PPARg2 rs1801282 Ala variant (G allele) has been associated with lower risk of IR and T2DM.27,28 To date, there are only 3 articles about PPARg2 effects in HIV patients,29–31 but only 1 found an association between rs1801282 (Pro12Ala) polymorphism and T2DM in HIV-infected patients with metabolic syndrome.31 With all these data, it would be expected that rs1801282 (Pro12Ala) polymorphism would be associated with response to HCV treatment. Consequently, the aim of the study was to analyze whether PPARg2 rs1801282 polymorphism is associated with the response to pegIFNa/ribavirin treatment in
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HIV/HCV-coinfected patients, and whether it is able to predict the outcome of HCV treatment.
PATIENTS AND METHODS Patients We carried out a retrospective follow-up study on 285 European HIV/HCV-coinfected naive patients, who started treatment with pegIFNa/ribavirin on regular follow-up from October 2000 to June 2010, at 2 reference HIV hospitals located in Madrid, Spain. The study was approved by the Institutional Review Board and the Research Ethic Committee of the Instituto de Salud Carlos III (ISCIII). This study was conducted in accordance with the Declaration of Helsinki, and patients gave their written consent for the study. The criteria for starting HCV antiviral treatment were (1) inclusion criteria: HIV infection, CHC, no clinical evidence of hepatic decompensation, detectable HCV RNA by polymerase chain reaction, negative for hepatitis B surface antigen, CD4+ lymphocyte count higher than 200 cells per cubic millimeter, and stable cART or no need for cART. (2) Exclusion criteria: Active opportunistic infections, active drug or alcohol addiction, and other concomitant diseases or conditions such as diabetes, nephropathies, autoimmune diseases, hemochromatosis, primary biliary cirrhosis, Wilson’s disease, a1-antitrypsin deficiency, and neoplasia. Furthermore, we included only patients who fulfilled the HCV treatment and who had an available DNA sample for DNA genotyping. None of the patients were taking PPARg activating drugs, such as thiazolidinediones, during the study.
Clinical and Laboratory Data Clinical and epidemiological data were obtained from medical records. Body mass index was calculated as the weight in kilograms divided by the square of the height in meters. HIV-infected patients are frequently infected with HCV due to both viruses share routes of transmissions. Unfortunately, we did not have detailed information about the moment of both HIV and HCV infections. Thus, we assumed that our patients were infected by both viruses almost simultaneously. The majority of patients (254 of 285) had a history of intravenous drug use, and it was estimated that the infection with both viruses started from the first year they shared needles and other injection paraphernalia.32 Additionally, 31 nonintravenous drug use patients could be determined with uncertainty because the risk factors were unsafe sexual practices [homo (n = 9) and heterosexual (n = 15)], hemoderivates (n = 1) and unknown (n = 7). Liver fibrosis was assessed by different methods, depending on the Hospital: (1) At Hospital General Universitario “Gregorio Marañón” was used liver biopsy33; and fibrosis score was estimated following the criteria established by the METAVIR Cooperative Study Group: F0, no fibrosis; F1, portal fibrosis; F2, periportal fibrosis or rare portal–portal septa; F3, fibrous septa with architectural distortion but with no obvious cirrhosis (bridging fibrosis); and F4, definite cirrhosis. (2) At Hospital Carlos III was used transient Ó 2014 Lippincott Williams & Wilkins
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elastometry (FibroScan; Echosens, Paris, France)34; and liver stiffness values #7.0, between 7.1 and 9.4, between 9.5 and 12.4, and $12.5 were considered to correspond with Metavir scores F0–F1, F2, F3, and F4, respectively. HCV-RNA viral load was measured by quantitative polymerase chain reaction (Cobas Amplicor HCV Monitor Test, Branchburg, NJ and COBAS AmpliPrep/COBAS TaqMan HCV test). Results were reported in International Units per milliliter (IU/mL), with a lower limit of detection of 10 IU/mL. Treatment regimens included pegIFNa 2a or 2b at standard doses (180 mg$wk21 or 1.5 mg$kg21$wk21, respectively) plus weight-adjusted ribavirin dosing (1000 mg/d for patients weighing ,75 kg and 1200 mg/d for patients weighing $75 kg). 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. A SVR was defined as an undetectable serum HCV-RNA level (,10 IU/mL) at week 24 after the end of the treatment. The PPARg2 gene polymorphism rs1801282 and the IL28B polymorphism rs12980275 were genotyped at the Spanish National Genotyping Centre (CeGen; http://www.cegen.org/). Genotyping was performed by using the GoldenGate assay with VeraCode Technology (Illumina Inc., San Diego, CA).
Statistics The statistical analysis was performed by on-treatment analysis of observed data using the Statistical Package for the Social Sciences (SPSS) (version 15.0, SPSS Inc., Chicago, IL) and PLINK software.35 All P values were 2-tailed. Statistical significance was defined as P , 0.05. For the description of the study population, P values were estimated with nonparametric tests: Mann–Whitney U test was used for continuous variable and x2 test for categorical variables. All SNPs were analyzed for Hardy–Weinberg equilibrium by x2 test, considering equilibrium when P . 0.001. For association study, logistic regression analysis was used to investigate the relationship between PPARg2 rs1801282 polymorphism and HCV-therapy response. These analyses were adjusted by the most important clinical and epidemiological characteristics, which were selected by a stepwise algorithm (a P value for entry and exit of 0.05 and 0.10, respectively). The variables used were age (,45 vs. $45 years), gender (female vs. male), body mass index (,25 vs. $25 kg/m2), CD4+ nadir (,200 vs. $200 cells/mm3), cART (no vs. yes), undetectable plasma HIV-RNA viral load (,50 vs. $50 copies/mL), HCV genotype (GT3 vs. GT1/4), HCV-RNA viral load (,500,000 vs. $500,000 IU/mL), significant fibrosis (F , 2 vs. F $ 2), and IL28B polymorphism (AA vs. AG/GG). Classification and regression tree analysis was used to classify SVR according to PPARg2, IL28B genotypes, and HCV-genotype. Classification and regression tree 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. Criteria to Ó 2014 Lippincott Williams & Wilkins
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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. The epistasis was tested under a regression model to evaluate the interaction between both PPARg rs1801282 and IL28B rs12980275 polymorphisms.
RESULTS Patients Table 1 shows the clinical and epidemiological characteristics for all 285 patients on HCV treatment stratified by rs1801282 genotype. A total of 197 of 285 patients were HCV-genotype 1/4 (GT1/4) and 88 were HCV-genotype 3 (GT3). We only find significant differences in HIV-RNA viral load according to rs1801282 genotype distribution, where lower HIV viremia was mainly detected in CC genotype patients.
Characteristics of PPARg2 Polymorphism Patients with rs1801282 CC genotype were 86% of total. In our data set, genotypes frequency for CG/GG (0.14) was in accordance with minimum allele frequency listed on the NCBI SNP database, where the frequency for CG/GG genotypes ranged from 0.12 to 0.25 (http://www.ncbi.nlm. nih.gov/projects/SNP/snp_ref.cgi?rs=1801282). The rs1801282 at PPARg2 and the rs12980275 at IL28B fulfilled the minimum allele frequency .0.05 and were in Hardy–Weinberg equilibrium (P . 0.001).
PPARg2 rs1801282 Polymorphism and HCV Virological Response We analyzed both additive and dominant genetic model for PPARg2 rs1801282 polymorphism, and we found that dominant model for rs1801282 G allele (Ala variant) was the best fitting our data, although the additive model was also significant. Therefore, comparison groups were CC genotype (2 copies of major allele) vs. CG/GG genotype (combining heterozygotes and homozygotes for minor allele). Figure 1 shows the variables that had a strong association with SVR. From a total of 10 clinical and epidemiological characteristics (listed above), we found that patients with HCV genotype 3 [adjusted odds ratio (aOR) = 7.66; P , 0.001], HCV-RNA ,500,000 IU/mL (aOR = 2.20; P = 0.015), no/mild liver fibrosis (F , 2) (aOR = 1.92; P = 0.026), favorable IL28B genotype (rs12980275 AA) (aOR = 2.70; P , 0.001), and PPARg2 rs1801282 CG/GG genotype (aOR = 2.93; P = 0.011) had a higher likelihood for achieving SVR (Fig. 1). In addition, the interaction between both PPARg2 rs1801282 and IL28B rs12980275 polymorphisms was tested, but the epistasis analysis did not reveal significant results (data not shown). Thus, the association between PPARg2 CG/GG genotype and SVR was independent of IL28B genotype.
Prediction of Sustained Virological Response Figure 2 shows a decision tree analysis with the 3 variables that had the highest significant associations with SVR (HCV genotype, IL28B rs12980275 genotype, and PPARg2 www.jaids.com |
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TABLE 1. Main Baseline Epidemiological and Clinical Characteristics of HIV/HCV-Coinfected Patients on HCV Therapy According to PPARg2 rs1801282 Polymorphism PPARg2 All patients N Male Age, yrs $45 BMI, kg/m2 $25 IVDU cART HIV markers Nadir CD4+ T-cells/mL Nadir CD4+ ,200 cells/mL CD4+ T-cells/mL CD4+ $500 cells/mL HIV-RNA ,50 copies/mL HCV markers HCV-genotype 1/4 HCV-genotype 3 HCV-RNA $500.000 IU/mL Liver fibrosis Significant fibrosis (F $ 2) Advanced fibrosis (F $ 3) IL28B genotype rs12980275 AA
285 218 41.5 74 23.1 82 253 239 224.0 157 468.0 130 216
(100%) (76.5%) (38.6–45.1) (26%) (21.1–25.4) (28.8%) (88.8%) (83.9%) (133.0–330.0) (55.1%) (364.0–683.0) (45.6%) (75.8%)
rs1801282 CG/GG 40 27 43.0 11 22.3 10 35 37 229.5 24 473.0 17 36
(14%) (67.5%) (39.0–46.7) (27.5%) (20.8–25.3) (25%) (87.5%) (92.5%) (144.0–355.5) (60%) (367.5–613.5) (42.5%) (90%)
rs1801282 CC 245 191 41.1 63 23.2 72 218 202 224 133 465.0 113 180
P*
(86%) (78%) (38.6–45.1) (25.7%) (21.2–25.5) (29.4%) (89%) (82.4%)
— 0.148 0.372 0.811 0.238 0.508 0.828 0.109
(131.0–322.0) (54.3%) (361.0–696.0) (46.1%) (73.5%)
0.690 0.501 0.719 0.654 0.031
197 (69.1%) 88 (30.9%) 208 (73%)
28 (70.0%) 12 (30%) 30 (75.0%)
169 (69%) 76 (31%) 178 (72.7%)
0.897 0.897 0.757
181 (63.5%) 99 (34.7%)
26 (65%) 16 (40.0%)
155 (63.3%) 83 (33.9%)
0.833 0.451
126 (44.2%)
21 (52.5%)
105 (42.9%)
0.273
Values expressed as absolute number (percentage) and median (percentiles 25 and 75). Sometimes, the percentages were not calculated from all patients because some data were missing. *The tests used to analyze the data were x2 and Mann–Whitney. In bold, P values with statistical significance. IVDU, intravenous drug users.
rs1801282 genotype). In patients infected with GT3, SVR rate increased from 80.3% to 100% when the PPARg2 CG/ GG genotype was taken into account regardless of IL28B genotype. In patients infected with GT1/4, SVR rate increased from 40.1% to 78.6% when both rs12980275 AA and rs1801282 CG/GG genotypes were considered. Moreover, in patients bearing the unfavorable rs12980275 AG/GG genotype, SVR increased from 28.7% to 35.7% in those patients with rs1801282 CG/GG genotypes. The overall percentage of patients correctly classified (accuracy) was 71.6%, and the area under the receiver operating characteristic curve of this decision tree was 0.766 6 0.028. For those patients with a non-SVR response,
non-SVR was predicted for 65.4% of them, which means that 34.6% of the non-SVR patients were inaccurately classified as SVR patients. For those patients with a SVR response, 77% of the patients were accurately classified as SVR, which means that 23% of the SVR patients were misclassified as non-SVR patients. After 25-fold cross-validation, the overall percentage of patients correctly classified was 71.3%.
DISCUSSION This study shows that HIV/HCV-coinfected patients carrying the PPARg2 rs1801282 CG/GG genotype (Ala variant) had a higher probability for achieving successful HCV
FIGURE 1. Summary of adjusted odds ratios (aOR) for the most significant variables for achieving sustained virological response (SVR) in HIV/HCV coinfected patients on HCV therapy. These data were adjusted by the significant variables: HCVgenotype (GT3 vs. GT1/4), HCV-RNA (,500,000 IU/mL vs. $500,000 IU/mL), significant fibrosis (F,2 vs. F$2), IL28B polymorphism (AA vs. AG/ GG), and PPARg2 (CG/GG vs. CC) polymorphism. Abbreviations: HCV, Hepatitis C virus; HCV-RNA, HCV plasma viral load; IL28B, gene of interleukin 28B; PPARg2, gene of peroxisome proliferatoractivated receptor gamma 2.
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FIGURE 2. Distribution of patients with sustained virological response (SVR) according to IL28B, PPARg2 and HCV genotypes. The test used to analyze the data was a classification and regression tree (CART), which builts a decision tree to identify subgroups at higher odds of SVR. Abbreviations: SVR, sustained virological response; HCV, hepatitis C virus; IL28B, gene of interleukin 28B; PPARg2, gene of peroxisome proliferator-activated receptor gamma 2.
treatment. To our knowledge, our article is the first to describe the relation between PPARg2 rs1801282 polymorphism and SVR in patients with CHC under pegIFNa/ribavirin therapy. Moreover, the predictive model with HCV genotype, IL28B rs12980275 polymorphism, and PPARg2 rs1801282 polymorphism had an accuracy value above 70%. Thus, this work might be important to optimize the HCV treatment of these patients, and it may be seen as the basis for additional more comprehensive studies addressing this issue. PPARg2 is a nuclear receptor involved in the regulation of lipid and glucose metabolism19; and an increase of PPARg2 gene transcription results in the upregulation of the insulin-sensitizing factor and downregulation of the insulin-resistant factor.20 However, although the Pro12Ala variant at PPARg2 gene seems to be an important modulator in metabolic control, the exact mechanism by which the rs1801282 polymorphism acts is not well understood.19 With regard to this, PPARg2 Ala variant has been associated with lower risk of IR and T2DM in epidemiological studies.27,28 In addition, experimental studies have found that the Pro12Ala genotype seems to be sensitive to environmental and especially nutritional factors, being the PPARg2 Ala variant beneficial in lean subjects but detrimental when coexisting with obesity.36–38 Then, it could be possible that PPARg2 rs1801282 polymorphism might be indirectly related to response to HCV therapy through regulating IR in patients with CHC. However, we could not analyze the influence of IR on SVR in our study because we only had available homeostasis model assessment (HOMA) data for 45% of patients. Clinical data were entirely derived from routine clinical practice, and unfortunately, HOMA data were not collected for some of the patients. It would be highly interesting to have sufficient data to evaluate whether the effect of PPARg2 rs1801282 polymorphism on Ó 2014 Lippincott Williams & Wilkins
SVR might be mediated by IR or, on the contrary, rs1801282 is an independent factor associated with SVR. However, only 45% of HOMA data is insufficient to be analyzed because genetic association studies need a larger sample size, and we have initially a limited number of patients. Further analyses are needed to study the influence of HOMA in the effect of PPARg2 polymorphism on the response to HCV therapy. Interestingly, the association detected between PPARg2 Pro12Ala polymorphism and SVR was similar to the one detected between IL28B rs12980275 polymorphism and SVR, displaying rs1801282, a high predictive value for discriminating between nonresponder patients and patients who achieved SVR. To date, many articles have assessed the influence of IL28B polymorphisms on SVR in patients with CHC, being rs12980275, rs8099917, and rs12979860 the most studied.39 Consequently, IL28B polymorphisms are already being used as predictive markers of response to pegIFNa/RVB therapy in clinical practice.12 Although rs12979860 is more likely to be correlated with SVR in the white population, we have recently shown a strong association of rs12980275 with SVR in HCV/HIV-coinfected patients.40 In the present study, we analyzed rs12980275, which is also in high linkage disequilibrium with rs12979860 in the European population.41 In addition, rs12980275 has been less studied than rs12979860 in white populations, and therefore additional results involving rs12980275 would be of interest. Our study was performed entirely in whites, and, it would be necessary to perform an independent replication of this study for different ethnic groups to discern PPARg2 polymorphism effects in other populations. In this regard, the frequency of the favorable PPARg2 G variant has a marked differential distribution between populations: 12% in whites, 10% in Native Americans, 4% in Japanese, 3% in African www.jaids.com |
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Americans, and 1% in Chinese, among others.42 This differential distribution may explain much of the observed clinical differences between ethnicities in several diseases such as diabetes retinopathy, T2DM, and diabetic nephropathy, where PPARg2 G allele confers protected effects only for whites.27,43–45 In addition to host factors, HCV genotype is also a well-known predictor of response to pegIFNa/RBV therapy because HIV/HCV-infected patients with GT1/4 show poorer SVR rate (30%–40%) than patients with GT2/3 (70%– 80%).46 As commented above, in our study, PPARg2 rs1801282 genotype was able to improve the prediction of SVR independently of IL28B rs12980275 polymorphism; although this improvement was different depending on the HCV genotype of the patient. On the 1 hand, in HCV GT3 patients, the presence of rs1801282 CG/GG genotypes increased SVR rate from 80.3% to 100%, regardless of IL28B genotype; although this improvement might be too small to draw conclusions. On the other hand, in HCV GT1/4 patients, only those keeping together rs12980275 AA and rs1801282 CG/GG genotypes, had an increase of SVR rate from 40.1% to 78.6%. With the aim of a better understanding of PPARg2 rs1801282 role, we analyzed its possible functional effect in silico by using Patrocles webtool.47 This SNP could be involved in the modulation of gene expression because the sequence with the G allele seems to be targeted by the microRNA mir-455. The microRNAs are short (20–24 nucleotides) noncoding RNAs that are involved in posttranscriptional regulation of gene expression by modifying the stability and translation of mRNAs. This finding is in accordance with the reduced expression of PPARg2 gene detected in rs1801282 G carriers because the microRNA would target only the mRNA sequences with the G allele, which would be degraded and therefore less protein would be translated. Furthermore, the differences may be the result of short- and longterm consequences in PPARg2 expression.48 At short-term, an increase in PPARg2 activation promotes the differentiation of new adipocytes that may secrete cytokines and hormones, improving insulin sensitivity. At long-term, it may lead to overweight, increase of fatty acids, and IR. The pegIFNa/ribavirin therapy remains the backbone of some HCV treatment strategies, but unfortunately, some patients are nonresponder and besides IFNs side effects some others are contraindicated to IFNa. For this reason, new IFNfree regimens are being used in GT2/3 patients and are also being developed for GT1 patients, in both cases with a very high response rate.49 In this new context, the combination therapy with potent DAAs might obscure the influence on treatment efficacy of IL28B polymorphisms and other SNPs. However, some authors have still suggested that IL28B genotype plays a key role for certain IFN-free regimens because several clinical trials have revealed an association between IL28B polymorphisms and treatment efficacy.50 Therefore, IL28B genotype could remain relevant to individualize the choice of treatment. Moreover, scarce data are available about the interaction of IFN-free regimens and lipid and glucose metabolism, where PPARg2 is a cornerstone. Thus, further analysis will be needed to determine whether PPARg2
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rs1801282 polymorphism could provide additional information to select patients with better or worse response to treatment. Finally, although the data presented here are entirely derived from routine clinical practice and thus may be more suitable in the real context of anti-HCV treatment, some comments have to be made to correctly interpret our data: (1) The study design was retrospective, which entails a lack of uniformity, and contains a limited number of patients. For example, the imbalance in the distribution of patients between PPARg2 “unfavourable” CC genotype and the “favourable” genotypes (heterozygous CG plus homozygous GG) related to undetectable HIV viral load. However, we think that this is a minor drawback because there was no difference in CD4+ count and percentage of patients on cART. Besides, logistic regression model was adjusted by cART and undetectable HIV viral load. (2) 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. (3) HCV therapy regimens were not identical because they varied in some characteristics such as pegIFNa 2a or 2b and likely ribavirin dose. Instead, each physician administered the appropriate HCV therapy regimen according to his/ her criteria and by following local and/or international guidelines. Further analyses are needed to study the molecular effects of the G allele on PPARg2 expression and also the association of PPARg2 polymorphism with HCV therapy outcome in a HCV-monoinfected cohort of patients. In conclusion, the presence of PPARg2 rs1801282 G allele (Ala variant) was significantly associated with increased odds for achieving SVR in HIV/HCV-coinfected patients on HCV therapy with pegIFNa/ribavirin. This information could be useful to better understand the CHC pathophysiology and to help in the prediction of the virological response after HCV therapy.
ACKNOWLEDGMENTS The authors wish to thank the Spanish National Genotyping Center (CeGen) for providing the genotyping services (http://www.cegen.org). The authors also acknowledge the patients in this study for their participation. REFERENCES 1. Mocroft A, Ledergerber B, Katlama C, et al. Decline in the AIDS and death rates in the EuroSIDA study: an observational study. Lancet. 2003; 362:22–29. 2. Macias J, Berenguer J, Japon MA, et al. Fast fibrosis progression between repeated liver biopsies in patients coinfected with human immunodeficiency virus/hepatitis C virus. Hepatology. 2009;50:1056–1063. 3. Lewden C, May T, Rosenthal E, 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. 4. Graham CS, Baden LR, Yu E, et al. Influence of human immunodeficiency virus infection on the course of hepatitis C virus infection: a metaanalysis. Clin Infect Dis. 2001;33:562–569. 5. Operskalski EA, Kovacs A. HIV/HCV co-infection: pathogenesis, clinical complications, treatment, and new therapeutic technologies. Curr HIV/AIDS Rep. 2011;8:12–22.
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6. Ghany MG, Strader DB, Thomas DL, et al. Diagnosis, management, and treatment of hepatitis C: an update. Hepatology. 2009;49:1335–1374. 7. Rockstroh JK, Bhagani S. Managing HIV/hepatitis C co-infection in the era of direct acting antivirals. BMC Med. 2013;11:234. 8. Sulkowski MS. HCV therapy in HIV-infected patients. Liver Int. 2013;33 (suppl 1):63–67. 9. Delemos AS, Chung RT. Hepatitis C treatment: an incipient therapeutic revolution. Trends Mol Med. 2014;20:315–321. 10. Lawitz E, Mangia A, Wyles D, et al. Sofosbuvir for previously untreated chronic hepatitis C infection. N Engl J Med. 2013;368:1878–1887. 11. 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.e3–1334 e3. 12. 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. 13. Kotler DP. Hepatitis C, human immunodeficiency virus and metabolic syndrome: interactions. Liver Int. 2009;29(suppl 2):38–46. 14. Ryan P, Resino S, Miralles P, et al. Insulin resistance impairs response to interferon plus ribavirin in patients coinfected with HIV and hepatitis C virus. J Acquir Immune Defic Syndr. 2010;55:176–181. 15. Eslam M, Lopez-Cortes LF, Romero-Gomez M. The role of insulin resistance in HIV/hepatitis C virus-coinfected patients. Curr Opin HIV AIDS. 2011;6:553–558. 16. Soriano V, Poveda E, Vispo E, et al. Pharmacogenetics of hepatitis C. J Antimicrob Chemother. 2012;67:523–529. 17. Wahli W, Michalik L. PPARs at the crossroads of lipid signaling and inflammation. Trends Endocrinol Metab. 2012;23:351–363. 18. Tontonoz P, SB. Fat and beyond: the diverse biology of PPARgamma. Annu Rev Biochem. 2008;77:289–312. 19. Jeninga EH, Gurnell M, Kalkhoven E. Functional implications of genetic variation in human PPARgamma. Trends Endocrinol Metab. 2009;20: 380–387. 20. Saraf N, Sharma PK, Mondal SC, et al. Role of PPARg2 transcription factor in thiazolidinedione-induced insulin sensitization. J Pharm Pharmacol. 2012;64:161–171. 21. Otake K, Omoto S, Yamamoto T, et al. HIV-1 Nef protein in the nucleus influences adipogenesis as well as viral transcription through the peroxisome proliferator-activated receptors. AIDS. 2004;18:189–198. 22. Shrivastav S, Kino T, Cunningham T, et al. Human immunodeficiency virus (HIV)-1 viral protein R suppresses transcriptional activity of peroxisome proliferator-activated receptor {gamma} and inhibits adipocyte differentiation: implications for HIV-associated lipodystrophy. Mol Endocrinol. 2008;22:234–247. 23. Diaz-Delfin J, Domingo P, Mateo MG, et al. Effects of rilpivirine on human adipocyte differentiation, gene expression, and release of adipokines and cytokines. Antimicrob Agents Chemother. 2012;56:3369–3375. 24. Mencarelli A, Francisci D, Renga B, et al. Ritonavir-induced lipoatrophy and dyslipidaemia is reversed by the anti-inflammatory drug leflunomide in a PPAR-gamma-dependent manner. Antivir Ther. 2012;17:669–678. 25. Kim K, Kim KH, Ha E, et al. Hepatitis C virus NS5A protein increases hepatic lipid accumulation via induction of activation and expression of PPARgamma. FEBS lett. 2009;583:2720–2726. 26. Kim KH, Hong SP, Kim K, et al. HCV core protein induces hepatic lipid accumulation by activating SREBP1 and PPARgamma. Biochem Biophys Res Commun. 2007;355:883–888. 27. Huguenin GV, Rosa G. The Ala allele in the PPAR-gamma2 gene is associated with reduced risk of type 2 diabetes mellitus in Caucasians and improved insulin sensitivity in overweight subjects. Br J Nutr. 2010; 104:488–497. 28. Gouda HN, Sagoo GS, Harding AH, et al. The association between the peroxisome proliferator-activated receptor-gamma2 (PPARG2) Pro12Ala gene variant and type 2 diabetes mellitus: a HuGE review and metaanalysis. Am J Epidemiol. 2010;171:645–655. 29. Saumoy M, Veloso S, Alonso-Villaverde C, et al. PPARgamma Pro12Ala polymorphism in HIV-1-infected patients with HAART-related lipodystrophy. Curr HIV Res. 2009;7:533–540.
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30. Hung YP, Lee NY, Lin SH, et al. Effects of PPARgamma and RBP4 gene variants on metabolic syndrome in HIV-infected patients with antiretroviral therapy. PLoS One. 2012;7:e49102. 31. Nazih H, Raffi F, Taieb A, et al. Peroxisome proliferator activating receptor alpha and gamma polymorphisms and metabolic abnormalities in HIV-infected patients receiving highly active antiretroviral therapy: the ANRS CO8 APROCO-COPILOTE study. AIDS Res Hum Retroviruses. 2012;28:393–399. 32. Thorpe LE, Ouellet LJ, Hershow R, et al. Risk of hepatitis C virus infection among young adult injection drug users who share injection equipment. Am J Epidemiol. 2002;155:645–653. 33. Resino S, Seoane JA, Bellon JM, et al. An artificial neural network improves the non-invasive diagnosis of significant fibrosis in HIV/HCV coinfected patients. J Infect. 2011;62:77–86. 34. Tuma P, Medrano J, Resino S, et al. Incidence of liver cirrhosis in HIVinfected patients with chronic hepatitis B or C in the era of highly active antiretroviral therapy. Antivir Ther. 2010;15:881–886. 35. Purcell S, Neale B, Todd-Brown K, et al. PLINK: a tool set for wholegenome association and population-based linkage analyses. Am J Hum Genet. 2007;81:559–575. 36. Heikkinen S, Argmann C, Feige JN, et al. The Pro12Ala PPARgamma2 variant determines metabolism at the gene-environment interface. Cell metab. 2009;9:88–98. 37. Luan J, Browne PO, Harding AH, et al. Evidence for gene-nutrient interaction at the PPARgamma locus. Diabetes. 2001;50:686–689. 38. Memisoglu A, Hu FB, Hankinson SE, et al. Interaction between a peroxisome proliferator-activated receptor gamma gene polymorphism and dietary fat intake in relation to body mass. Hum Mol Genet. 2003;12: 2923–2929. 39. Jimenez-Sousa MA, Fernandez-Rodriguez A, Guzman-Fulgencio M, et al. Meta-analysis: implications of interleukin-28B polymorphisms in spontaneous and treatment-related clearance for patients with hepatitis C. BMC Med. 2013;11:6. 40. Fernandez-Rodriguez A, Rallon N, Berenguer J, et al. Analysis of IL28B alleles with virologic response patterns and plasma cytokine levels in HIV/HCV-coinfected patients. AIDS. 2013;27:163–173. 41. 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. 42. Stumvoll M, Haring H. The peroxisome proliferator-activated receptorgamma2 Pro12Ala polymorphism. Diabetes. 2002;51:2341–2347. 43. Ma J, Li Y, Zhou F, et al. Meta-analysis of association between the Pro12Ala polymorphism of the peroxisome proliferator-activated receptor-gamma2 gene and diabetic retinopathy in Caucasians and Asians. Mol Vis. 2012;18:2352–2360. 44. Liu G, Zhou TB, Jiang Z, et al. Relationship between PPARgamma Pro12Ala gene polymorphism and type 2 diabetic nephropathy risk in Asian population: results from a meta-analysis. J Recep Signal Transduct Res. 2014;34:131–136. 45. Zhou TB, Guo XF, Yin SS. Association of peroxisome proliferatoractivated receptor gamma Pro12Ala gene polymorphism with type 2 diabetic nephropathy risk in Caucasian population. J Receptor Signal Transduction Research. 2014;34:180–184. 46. Hadigan C, Kottilil S. Hepatitis C virus infection and coinfection with human immunodeficiency virus: challenges and advancements in management. JAMA. 2011;306:294–301. 47. Hiard S, Charlier C, Coppieters W, et al. Patrocles: a database of polymorphic miRNA-mediated gene regulation in vertebrates. Nucleic Acids Res. 2010;38:D640–D651. 48. Ferre P. The biology of peroxisome proliferator-activated receptors: relationship with lipid metabolism and insulin sensitivity. Diabetes. 2004;53 (suppl 1):S43–S50. 49. Pawlotsky JM. New hepatitis C Therapies: the Toolbox, strategies, and challenges. Gastroenterology. 2014;146:1176–1192. 50. Matsuura K, Watanabe T, Tanaka Y. Role of IL28B for chronic hepatitis C treatment toward personalized medicine. J Gastroenterol Hepatol. 2014;29:241–249.
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PPARg2 Pro12Ala Polymorphism Is Associated With Sustained Virological Response in HIV/HCV-Coinfected Patients Under HCV Therapy Amanda Fernández-Rodríguez, PhD,* Juan Berenguer, MD, PhD,†‡ Norma Rallón, PhD,§ María A. Jiménez-Sousa, PhD,* Juan Carlos López, MD, PhD,† Vicente Soriano, MD, PhD,k Mónica García-Álvarez, PhD,* Jaime Cosín, MD, PhD,† Paula Martínez, PhD,§ María Guzmán-Fulgencio, PhD,* Pilar Miralles, MD,† José Miguel Benito, MD, PhD,§ and Salvador Resino, PhD*
Objectives: To analyze whether peroxisome proliferator-activated receptor gamma (PPARg2) rs1801282 (Pro12Ala) polymorphism is associated with the response to pegylated-interferon-alpha plus ribavirin treatment in HIV/hepatitis C virus (HCV)-coinfected patients, and whether it is able to predict the outcome of HCV treatment.
Design: Retrospective follow-up study. Methods: Two hundred eighty-five naive patients, who started HCVtreatment, were genotyped for PPARg2 and interleukin 28B polymorphisms. Genetic data were analyzed under dominant inheritance model. Received for publication January 3, 2014; accepted May 13, 2014. From the *Unidad de Infección viral e Inmunidad, Centro Nacional de Microbiología, Instituto de Salud Carlos III, Majadahonda, Madrid, Spain; †Unidad de Enfermedades Infecciosas/VIH; Hospital General Universitario “Gregorio Marañón,” Madrid, Spain; ‡Instituto de Investigación Sanitaria Gregorio Marañón (IiSGM), Madrid, Spain; §IIS-Fundación Jiménez Díaz, Universidad Autónoma de Madrid, Madrid Spain; and kServicio de Enfermedades Infecciosas, Hospital Carlos III, Madrid, Spain. Supported by grants given by Fondo de Investigacion de Sanidad en España (FIS) (Spanish Health Founds for Research) (Grant Nos. PI08/0738, PI11/ 00245; PI11/00870, PI08/0928, and PI11/01556), Red Española de Investigación en SIDA (RIS) (AIDS Research Network) (Grant Nos. RD12/ 0017/0024, RD12/0017/0004, and RD12/0017/0031), “Fundación para la Investigación y la Prevención del Sida en España” (FIPSE) (Grant No. 361020/10). This work has been funded by the Grants RD12/0017/0024 and RD12/0017/0004 as part of the National R + D + I and cofinanced by the ISCIII-General Subdirectorate for Assessment and the European Regional Development Fund (ERDF). A.F.R., M.G.-F., M.G.-A., and M.A.J.-S. are supported by “Instituto de Salud Carlos III” (Grant Nos. UIPY-1377/08, RD12/0017/0024, CD12/00442, and CD13/00013, respectively). J.B. is an investigator from the Programa de Intensificación de la Actividad Investigadora en el Sistema Nacional de Salud (I3SNS). A.F.R. and S.R. performed all statistical analysis, interpretation of the data, and wrote the manuscript. 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., and N.R. participated in sample preparation, DNA isolation and genotyping preprocedure, and contributed with critical revision of the manuscript. S.R. supervised the study. The authors have no conflicts of interest to disclose. Correspondence to: Salvador Resino, PhD, Centro Nacional de Microbiología, Instituto de Salud Carlos III (Campus Majadahonda), Carretera Majadahonda- Pozuelo, Km 2.2; 28220 Majadahonda, Madrid, Spain (e-mail: [email protected]). Copyright © 2014 by Lippincott Williams & Wilkins
Sustained virological response (SVR) was defined as undetectable HCV viremia through 24 weeks after the end of HCV treatment.
Results: The variables significantly associated with SVR in a multivariate analysis were HCV-genotype (GT) 3 {adjusted odds ratio [aOR] = 7.66 [95% of confidence interval (95% CI): 3.96 to 14.81] P , 0.001}, HCV-viremia ,500,000 IU/mL [aOR = 2.20 (95% CI: 1.16 to 4.15] P = 0.015), no/mild liver fibrosis (F , 2) [aOR = 1.92 (95% CI: 1.08 to 3.42) P = 0.026], IL28B rs12980275 AA genotype [aOR = 2.70 (95% CI: 1.54 to 4.71) P , 0.001], and PPARg2 rs1801282 CG/GG genotype [aOR = 2.93 (95% CI: 1.27 to 6.72) P = 0.011]. When PPARg2 rs1801282 genotype was included in a decision tree analysis, HCV-GT3 patients with CG/GG genotype had increased SVR from 80.3% to 100%. In GT1/4 patients, rs12980275 AA carriers had increased SVR from 58.7% to 78.6%, and rs12980275 AG/GG carriers had increased SVR from 28.7% to 35.7%. The overall percentage of patients correctly classified was 71.6% and the area under the receiver operating characteristic curves was 0.766 6 0.028. Conclusions: The presence of PPARg2 rs1801282 G allele (Ala variant) was associated with increased odds for achieving SVR in HIV/HCV-coinfected patients on HCV treatment. Key Words: chronic hepatitis C, AIDS, HCV therapy, PPARg2, single nucleotide polymorphism (J Acquir Immune Defic Syndr 2014;67:113–119)
INTRODUCTION The combination antiretroviral therapy (cART) has made of HIV infection a chronic manageable infection in the western world.1 In this setting, chronic hepatitis C (CHC) has turned into an important comorbidity and a major cause of death among HIV/hepatitis C virus (HCV)-coinfected patients.2–4 However, the mechanisms underlying the accelerated of these diseases in HIV/HCV-coinfected patients are not well understood.5 HCV therapy with pegylated-interferon-alpha plus ribavirin (pegIFNa/ribavirin) is still in use among HIV/ HCV-coinfected patients but the effectiveness of this treatment is limited.6 Nowadays, the new direct-acting antivirals (DAAs) are generally being administered in combination with
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pegIFNa/ribavirin,7,8 but the potential use of these DAAs in HIV/HCV-coinfected patients has numerous challenges, such as the choice of patients to treat possible interaction between antiretroviral drugs and the DAAs, and uncertainty regarding the safety and effectiveness of the combination therapy in this population.7,8 Recently, sofosbuvir has been approved, a nucleotide analogue HCV NS5B polymerase inhibitor, which offers better tolerability and efficacy across all HCV genotypes (GTs),9 and its combination with pegIFNa/ribavirin is being a standard of care for GT1 patients.10 Thus, it is still essential the potential ongoing relevance of understanding pegIFNa/ ribavirin response predictors. However, not all HIV/HCVcoinfected patients achieve the desired sustained virological response (SVR).11 The identification of predictors for HCV therapy might help to ensure an adequate selection of the best candidates and to minimize any undesirable toxicity. To date, the best baseline predictors for HCV therapy are HCV genotype, HCV viremia, liver fibrosis, and single-nucleotide polymorphisms (SNPs) around interleukin 28B (IL28B) gene.12 Additionally, important metabolic anomalies have been detected in HIV/HCV-coinfected patients,13 such as insulin resistance (IR) and type 2 diabetes mellitus (T2DM), which has been related to lower SVR in pegIFNa/ribavirin therapy.14,15 However, an unexplained variability in HCV treatment outcome still remains, which suggests that other host genetic factors may play an important role in pegIFNa/ ribavirin therapy.16 Peroxisome proliferator-activated receptor gamma (PPARg) is considered as a “key element” in the glucose homeostasis and lipoprotein metabolism,17 being mainly expressed in adipose tissue.18 The PPARg gene is located on chromosome 3; and differential splicing of this gene results in 2 different isoforms: PPARg1 and PPARg2, differing only in their N-terminal region.19 The increase of PPARg2 gene transcription results in the upregulation of the insulin-sensitizing factor and the downregulation of the insulin-resistant factor.20 Moreover, PPARg2 expression in adipocytes seems to be negatively influenced by both HIV proteins21,22 and antiretroviral drugs,23,24 while some HCV proteins (core and NS5A) increase hepatic lipid accumulation by induction of activation and PPARg2 expression.25,26 The most common gene polymorphism in human PPARg2 gene is the rs1801282 (Pro12Ala) polymorphism, resulting from a cytosine–guanine exchange (CCA-to-GCA missense mutation) in exon 2 (codon 12), which involves an amino acid change from proline (Pro) to alanine (Ala), affecting the NH2-terminal residue that defines the adipocyte-specific PPARg2 isoform.19 PPARg2 rs1801282 Ala variant (G allele) has been associated with lower risk of IR and T2DM.27,28 To date, there are only 3 articles about PPARg2 effects in HIV patients,29–31 but only 1 found an association between rs1801282 (Pro12Ala) polymorphism and T2DM in HIV-infected patients with metabolic syndrome.31 With all these data, it would be expected that rs1801282 (Pro12Ala) polymorphism would be associated with response to HCV treatment. Consequently, the aim of the study was to analyze whether PPARg2 rs1801282 polymorphism is associated with the response to pegIFNa/ribavirin treatment in
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HIV/HCV-coinfected patients, and whether it is able to predict the outcome of HCV treatment.
PATIENTS AND METHODS Patients We carried out a retrospective follow-up study on 285 European HIV/HCV-coinfected naive patients, who started treatment with pegIFNa/ribavirin on regular follow-up from October 2000 to June 2010, at 2 reference HIV hospitals located in Madrid, Spain. The study was approved by the Institutional Review Board and the Research Ethic Committee of the Instituto de Salud Carlos III (ISCIII). This study was conducted in accordance with the Declaration of Helsinki, and patients gave their written consent for the study. The criteria for starting HCV antiviral treatment were (1) inclusion criteria: HIV infection, CHC, no clinical evidence of hepatic decompensation, detectable HCV RNA by polymerase chain reaction, negative for hepatitis B surface antigen, CD4+ lymphocyte count higher than 200 cells per cubic millimeter, and stable cART or no need for cART. (2) Exclusion criteria: Active opportunistic infections, active drug or alcohol addiction, and other concomitant diseases or conditions such as diabetes, nephropathies, autoimmune diseases, hemochromatosis, primary biliary cirrhosis, Wilson’s disease, a1-antitrypsin deficiency, and neoplasia. Furthermore, we included only patients who fulfilled the HCV treatment and who had an available DNA sample for DNA genotyping. None of the patients were taking PPARg activating drugs, such as thiazolidinediones, during the study.
Clinical and Laboratory Data Clinical and epidemiological data were obtained from medical records. Body mass index was calculated as the weight in kilograms divided by the square of the height in meters. HIV-infected patients are frequently infected with HCV due to both viruses share routes of transmissions. Unfortunately, we did not have detailed information about the moment of both HIV and HCV infections. Thus, we assumed that our patients were infected by both viruses almost simultaneously. The majority of patients (254 of 285) had a history of intravenous drug use, and it was estimated that the infection with both viruses started from the first year they shared needles and other injection paraphernalia.32 Additionally, 31 nonintravenous drug use patients could be determined with uncertainty because the risk factors were unsafe sexual practices [homo (n = 9) and heterosexual (n = 15)], hemoderivates (n = 1) and unknown (n = 7). Liver fibrosis was assessed by different methods, depending on the Hospital: (1) At Hospital General Universitario “Gregorio Marañón” was used liver biopsy33; and fibrosis score was estimated following the criteria established by the METAVIR Cooperative Study Group: F0, no fibrosis; F1, portal fibrosis; F2, periportal fibrosis or rare portal–portal septa; F3, fibrous septa with architectural distortion but with no obvious cirrhosis (bridging fibrosis); and F4, definite cirrhosis. (2) At Hospital Carlos III was used transient Ó 2014 Lippincott Williams & Wilkins
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elastometry (FibroScan; Echosens, Paris, France)34; and liver stiffness values #7.0, between 7.1 and 9.4, between 9.5 and 12.4, and $12.5 were considered to correspond with Metavir scores F0–F1, F2, F3, and F4, respectively. HCV-RNA viral load was measured by quantitative polymerase chain reaction (Cobas Amplicor HCV Monitor Test, Branchburg, NJ and COBAS AmpliPrep/COBAS TaqMan HCV test). Results were reported in International Units per milliliter (IU/mL), with a lower limit of detection of 10 IU/mL. Treatment regimens included pegIFNa 2a or 2b at standard doses (180 mg$wk21 or 1.5 mg$kg21$wk21, respectively) plus weight-adjusted ribavirin dosing (1000 mg/d for patients weighing ,75 kg and 1200 mg/d for patients weighing $75 kg). 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. A SVR was defined as an undetectable serum HCV-RNA level (,10 IU/mL) at week 24 after the end of the treatment. The PPARg2 gene polymorphism rs1801282 and the IL28B polymorphism rs12980275 were genotyped at the Spanish National Genotyping Centre (CeGen; http://www.cegen.org/). Genotyping was performed by using the GoldenGate assay with VeraCode Technology (Illumina Inc., San Diego, CA).
Statistics The statistical analysis was performed by on-treatment analysis of observed data using the Statistical Package for the Social Sciences (SPSS) (version 15.0, SPSS Inc., Chicago, IL) and PLINK software.35 All P values were 2-tailed. Statistical significance was defined as P , 0.05. For the description of the study population, P values were estimated with nonparametric tests: Mann–Whitney U test was used for continuous variable and x2 test for categorical variables. All SNPs were analyzed for Hardy–Weinberg equilibrium by x2 test, considering equilibrium when P . 0.001. For association study, logistic regression analysis was used to investigate the relationship between PPARg2 rs1801282 polymorphism and HCV-therapy response. These analyses were adjusted by the most important clinical and epidemiological characteristics, which were selected by a stepwise algorithm (a P value for entry and exit of 0.05 and 0.10, respectively). The variables used were age (,45 vs. $45 years), gender (female vs. male), body mass index (,25 vs. $25 kg/m2), CD4+ nadir (,200 vs. $200 cells/mm3), cART (no vs. yes), undetectable plasma HIV-RNA viral load (,50 vs. $50 copies/mL), HCV genotype (GT3 vs. GT1/4), HCV-RNA viral load (,500,000 vs. $500,000 IU/mL), significant fibrosis (F , 2 vs. F $ 2), and IL28B polymorphism (AA vs. AG/GG). Classification and regression tree analysis was used to classify SVR according to PPARg2, IL28B genotypes, and HCV-genotype. Classification and regression tree 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. Criteria to Ó 2014 Lippincott Williams & Wilkins
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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. The epistasis was tested under a regression model to evaluate the interaction between both PPARg rs1801282 and IL28B rs12980275 polymorphisms.
RESULTS Patients Table 1 shows the clinical and epidemiological characteristics for all 285 patients on HCV treatment stratified by rs1801282 genotype. A total of 197 of 285 patients were HCV-genotype 1/4 (GT1/4) and 88 were HCV-genotype 3 (GT3). We only find significant differences in HIV-RNA viral load according to rs1801282 genotype distribution, where lower HIV viremia was mainly detected in CC genotype patients.
Characteristics of PPARg2 Polymorphism Patients with rs1801282 CC genotype were 86% of total. In our data set, genotypes frequency for CG/GG (0.14) was in accordance with minimum allele frequency listed on the NCBI SNP database, where the frequency for CG/GG genotypes ranged from 0.12 to 0.25 (http://www.ncbi.nlm. nih.gov/projects/SNP/snp_ref.cgi?rs=1801282). The rs1801282 at PPARg2 and the rs12980275 at IL28B fulfilled the minimum allele frequency .0.05 and were in Hardy–Weinberg equilibrium (P . 0.001).
PPARg2 rs1801282 Polymorphism and HCV Virological Response We analyzed both additive and dominant genetic model for PPARg2 rs1801282 polymorphism, and we found that dominant model for rs1801282 G allele (Ala variant) was the best fitting our data, although the additive model was also significant. Therefore, comparison groups were CC genotype (2 copies of major allele) vs. CG/GG genotype (combining heterozygotes and homozygotes for minor allele). Figure 1 shows the variables that had a strong association with SVR. From a total of 10 clinical and epidemiological characteristics (listed above), we found that patients with HCV genotype 3 [adjusted odds ratio (aOR) = 7.66; P , 0.001], HCV-RNA ,500,000 IU/mL (aOR = 2.20; P = 0.015), no/mild liver fibrosis (F , 2) (aOR = 1.92; P = 0.026), favorable IL28B genotype (rs12980275 AA) (aOR = 2.70; P , 0.001), and PPARg2 rs1801282 CG/GG genotype (aOR = 2.93; P = 0.011) had a higher likelihood for achieving SVR (Fig. 1). In addition, the interaction between both PPARg2 rs1801282 and IL28B rs12980275 polymorphisms was tested, but the epistasis analysis did not reveal significant results (data not shown). Thus, the association between PPARg2 CG/GG genotype and SVR was independent of IL28B genotype.
Prediction of Sustained Virological Response Figure 2 shows a decision tree analysis with the 3 variables that had the highest significant associations with SVR (HCV genotype, IL28B rs12980275 genotype, and PPARg2 www.jaids.com |
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TABLE 1. Main Baseline Epidemiological and Clinical Characteristics of HIV/HCV-Coinfected Patients on HCV Therapy According to PPARg2 rs1801282 Polymorphism PPARg2 All patients N Male Age, yrs $45 BMI, kg/m2 $25 IVDU cART HIV markers Nadir CD4+ T-cells/mL Nadir CD4+ ,200 cells/mL CD4+ T-cells/mL CD4+ $500 cells/mL HIV-RNA ,50 copies/mL HCV markers HCV-genotype 1/4 HCV-genotype 3 HCV-RNA $500.000 IU/mL Liver fibrosis Significant fibrosis (F $ 2) Advanced fibrosis (F $ 3) IL28B genotype rs12980275 AA
285 218 41.5 74 23.1 82 253 239 224.0 157 468.0 130 216
(100%) (76.5%) (38.6–45.1) (26%) (21.1–25.4) (28.8%) (88.8%) (83.9%) (133.0–330.0) (55.1%) (364.0–683.0) (45.6%) (75.8%)
rs1801282 CG/GG 40 27 43.0 11 22.3 10 35 37 229.5 24 473.0 17 36
(14%) (67.5%) (39.0–46.7) (27.5%) (20.8–25.3) (25%) (87.5%) (92.5%) (144.0–355.5) (60%) (367.5–613.5) (42.5%) (90%)
rs1801282 CC 245 191 41.1 63 23.2 72 218 202 224 133 465.0 113 180
P*
(86%) (78%) (38.6–45.1) (25.7%) (21.2–25.5) (29.4%) (89%) (82.4%)
— 0.148 0.372 0.811 0.238 0.508 0.828 0.109
(131.0–322.0) (54.3%) (361.0–696.0) (46.1%) (73.5%)
0.690 0.501 0.719 0.654 0.031
197 (69.1%) 88 (30.9%) 208 (73%)
28 (70.0%) 12 (30%) 30 (75.0%)
169 (69%) 76 (31%) 178 (72.7%)
0.897 0.897 0.757
181 (63.5%) 99 (34.7%)
26 (65%) 16 (40.0%)
155 (63.3%) 83 (33.9%)
0.833 0.451
126 (44.2%)
21 (52.5%)
105 (42.9%)
0.273
Values expressed as absolute number (percentage) and median (percentiles 25 and 75). Sometimes, the percentages were not calculated from all patients because some data were missing. *The tests used to analyze the data were x2 and Mann–Whitney. In bold, P values with statistical significance. IVDU, intravenous drug users.
rs1801282 genotype). In patients infected with GT3, SVR rate increased from 80.3% to 100% when the PPARg2 CG/ GG genotype was taken into account regardless of IL28B genotype. In patients infected with GT1/4, SVR rate increased from 40.1% to 78.6% when both rs12980275 AA and rs1801282 CG/GG genotypes were considered. Moreover, in patients bearing the unfavorable rs12980275 AG/GG genotype, SVR increased from 28.7% to 35.7% in those patients with rs1801282 CG/GG genotypes. The overall percentage of patients correctly classified (accuracy) was 71.6%, and the area under the receiver operating characteristic curve of this decision tree was 0.766 6 0.028. For those patients with a non-SVR response,
non-SVR was predicted for 65.4% of them, which means that 34.6% of the non-SVR patients were inaccurately classified as SVR patients. For those patients with a SVR response, 77% of the patients were accurately classified as SVR, which means that 23% of the SVR patients were misclassified as non-SVR patients. After 25-fold cross-validation, the overall percentage of patients correctly classified was 71.3%.
DISCUSSION This study shows that HIV/HCV-coinfected patients carrying the PPARg2 rs1801282 CG/GG genotype (Ala variant) had a higher probability for achieving successful HCV
FIGURE 1. Summary of adjusted odds ratios (aOR) for the most significant variables for achieving sustained virological response (SVR) in HIV/HCV coinfected patients on HCV therapy. These data were adjusted by the significant variables: HCVgenotype (GT3 vs. GT1/4), HCV-RNA (,500,000 IU/mL vs. $500,000 IU/mL), significant fibrosis (F,2 vs. F$2), IL28B polymorphism (AA vs. AG/ GG), and PPARg2 (CG/GG vs. CC) polymorphism. Abbreviations: HCV, Hepatitis C virus; HCV-RNA, HCV plasma viral load; IL28B, gene of interleukin 28B; PPARg2, gene of peroxisome proliferatoractivated receptor gamma 2.
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PPARg2 Variant and HCV Treatment
FIGURE 2. Distribution of patients with sustained virological response (SVR) according to IL28B, PPARg2 and HCV genotypes. The test used to analyze the data was a classification and regression tree (CART), which builts a decision tree to identify subgroups at higher odds of SVR. Abbreviations: SVR, sustained virological response; HCV, hepatitis C virus; IL28B, gene of interleukin 28B; PPARg2, gene of peroxisome proliferator-activated receptor gamma 2.
treatment. To our knowledge, our article is the first to describe the relation between PPARg2 rs1801282 polymorphism and SVR in patients with CHC under pegIFNa/ribavirin therapy. Moreover, the predictive model with HCV genotype, IL28B rs12980275 polymorphism, and PPARg2 rs1801282 polymorphism had an accuracy value above 70%. Thus, this work might be important to optimize the HCV treatment of these patients, and it may be seen as the basis for additional more comprehensive studies addressing this issue. PPARg2 is a nuclear receptor involved in the regulation of lipid and glucose metabolism19; and an increase of PPARg2 gene transcription results in the upregulation of the insulin-sensitizing factor and downregulation of the insulin-resistant factor.20 However, although the Pro12Ala variant at PPARg2 gene seems to be an important modulator in metabolic control, the exact mechanism by which the rs1801282 polymorphism acts is not well understood.19 With regard to this, PPARg2 Ala variant has been associated with lower risk of IR and T2DM in epidemiological studies.27,28 In addition, experimental studies have found that the Pro12Ala genotype seems to be sensitive to environmental and especially nutritional factors, being the PPARg2 Ala variant beneficial in lean subjects but detrimental when coexisting with obesity.36–38 Then, it could be possible that PPARg2 rs1801282 polymorphism might be indirectly related to response to HCV therapy through regulating IR in patients with CHC. However, we could not analyze the influence of IR on SVR in our study because we only had available homeostasis model assessment (HOMA) data for 45% of patients. Clinical data were entirely derived from routine clinical practice, and unfortunately, HOMA data were not collected for some of the patients. It would be highly interesting to have sufficient data to evaluate whether the effect of PPARg2 rs1801282 polymorphism on Ó 2014 Lippincott Williams & Wilkins
SVR might be mediated by IR or, on the contrary, rs1801282 is an independent factor associated with SVR. However, only 45% of HOMA data is insufficient to be analyzed because genetic association studies need a larger sample size, and we have initially a limited number of patients. Further analyses are needed to study the influence of HOMA in the effect of PPARg2 polymorphism on the response to HCV therapy. Interestingly, the association detected between PPARg2 Pro12Ala polymorphism and SVR was similar to the one detected between IL28B rs12980275 polymorphism and SVR, displaying rs1801282, a high predictive value for discriminating between nonresponder patients and patients who achieved SVR. To date, many articles have assessed the influence of IL28B polymorphisms on SVR in patients with CHC, being rs12980275, rs8099917, and rs12979860 the most studied.39 Consequently, IL28B polymorphisms are already being used as predictive markers of response to pegIFNa/RVB therapy in clinical practice.12 Although rs12979860 is more likely to be correlated with SVR in the white population, we have recently shown a strong association of rs12980275 with SVR in HCV/HIV-coinfected patients.40 In the present study, we analyzed rs12980275, which is also in high linkage disequilibrium with rs12979860 in the European population.41 In addition, rs12980275 has been less studied than rs12979860 in white populations, and therefore additional results involving rs12980275 would be of interest. Our study was performed entirely in whites, and, it would be necessary to perform an independent replication of this study for different ethnic groups to discern PPARg2 polymorphism effects in other populations. In this regard, the frequency of the favorable PPARg2 G variant has a marked differential distribution between populations: 12% in whites, 10% in Native Americans, 4% in Japanese, 3% in African www.jaids.com |
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Americans, and 1% in Chinese, among others.42 This differential distribution may explain much of the observed clinical differences between ethnicities in several diseases such as diabetes retinopathy, T2DM, and diabetic nephropathy, where PPARg2 G allele confers protected effects only for whites.27,43–45 In addition to host factors, HCV genotype is also a well-known predictor of response to pegIFNa/RBV therapy because HIV/HCV-infected patients with GT1/4 show poorer SVR rate (30%–40%) than patients with GT2/3 (70%– 80%).46 As commented above, in our study, PPARg2 rs1801282 genotype was able to improve the prediction of SVR independently of IL28B rs12980275 polymorphism; although this improvement was different depending on the HCV genotype of the patient. On the 1 hand, in HCV GT3 patients, the presence of rs1801282 CG/GG genotypes increased SVR rate from 80.3% to 100%, regardless of IL28B genotype; although this improvement might be too small to draw conclusions. On the other hand, in HCV GT1/4 patients, only those keeping together rs12980275 AA and rs1801282 CG/GG genotypes, had an increase of SVR rate from 40.1% to 78.6%. With the aim of a better understanding of PPARg2 rs1801282 role, we analyzed its possible functional effect in silico by using Patrocles webtool.47 This SNP could be involved in the modulation of gene expression because the sequence with the G allele seems to be targeted by the microRNA mir-455. The microRNAs are short (20–24 nucleotides) noncoding RNAs that are involved in posttranscriptional regulation of gene expression by modifying the stability and translation of mRNAs. This finding is in accordance with the reduced expression of PPARg2 gene detected in rs1801282 G carriers because the microRNA would target only the mRNA sequences with the G allele, which would be degraded and therefore less protein would be translated. Furthermore, the differences may be the result of short- and longterm consequences in PPARg2 expression.48 At short-term, an increase in PPARg2 activation promotes the differentiation of new adipocytes that may secrete cytokines and hormones, improving insulin sensitivity. At long-term, it may lead to overweight, increase of fatty acids, and IR. The pegIFNa/ribavirin therapy remains the backbone of some HCV treatment strategies, but unfortunately, some patients are nonresponder and besides IFNs side effects some others are contraindicated to IFNa. For this reason, new IFNfree regimens are being used in GT2/3 patients and are also being developed for GT1 patients, in both cases with a very high response rate.49 In this new context, the combination therapy with potent DAAs might obscure the influence on treatment efficacy of IL28B polymorphisms and other SNPs. However, some authors have still suggested that IL28B genotype plays a key role for certain IFN-free regimens because several clinical trials have revealed an association between IL28B polymorphisms and treatment efficacy.50 Therefore, IL28B genotype could remain relevant to individualize the choice of treatment. Moreover, scarce data are available about the interaction of IFN-free regimens and lipid and glucose metabolism, where PPARg2 is a cornerstone. Thus, further analysis will be needed to determine whether PPARg2
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rs1801282 polymorphism could provide additional information to select patients with better or worse response to treatment. Finally, although the data presented here are entirely derived from routine clinical practice and thus may be more suitable in the real context of anti-HCV treatment, some comments have to be made to correctly interpret our data: (1) The study design was retrospective, which entails a lack of uniformity, and contains a limited number of patients. For example, the imbalance in the distribution of patients between PPARg2 “unfavourable” CC genotype and the “favourable” genotypes (heterozygous CG plus homozygous GG) related to undetectable HIV viral load. However, we think that this is a minor drawback because there was no difference in CD4+ count and percentage of patients on cART. Besides, logistic regression model was adjusted by cART and undetectable HIV viral load. (2) 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. (3) HCV therapy regimens were not identical because they varied in some characteristics such as pegIFNa 2a or 2b and likely ribavirin dose. Instead, each physician administered the appropriate HCV therapy regimen according to his/ her criteria and by following local and/or international guidelines. Further analyses are needed to study the molecular effects of the G allele on PPARg2 expression and also the association of PPARg2 polymorphism with HCV therapy outcome in a HCV-monoinfected cohort of patients. In conclusion, the presence of PPARg2 rs1801282 G allele (Ala variant) was significantly associated with increased odds for achieving SVR in HIV/HCV-coinfected patients on HCV therapy with pegIFNa/ribavirin. This information could be useful to better understand the CHC pathophysiology and to help in the prediction of the virological response after HCV therapy.
ACKNOWLEDGMENTS The authors wish to thank the Spanish National Genotyping Center (CeGen) for providing the genotyping services (http://www.cegen.org). The authors also acknowledge the patients in this study for their participation. REFERENCES 1. Mocroft A, Ledergerber B, Katlama C, et al. Decline in the AIDS and death rates in the EuroSIDA study: an observational study. Lancet. 2003; 362:22–29. 2. Macias J, Berenguer J, Japon MA, et al. Fast fibrosis progression between repeated liver biopsies in patients coinfected with human immunodeficiency virus/hepatitis C virus. Hepatology. 2009;50:1056–1063. 3. Lewden C, May T, Rosenthal E, 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. 4. Graham CS, Baden LR, Yu E, et al. Influence of human immunodeficiency virus infection on the course of hepatitis C virus infection: a metaanalysis. Clin Infect Dis. 2001;33:562–569. 5. Operskalski EA, Kovacs A. HIV/HCV co-infection: pathogenesis, clinical complications, treatment, and new therapeutic technologies. Curr HIV/AIDS Rep. 2011;8:12–22.
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6. Ghany MG, Strader DB, Thomas DL, et al. Diagnosis, management, and treatment of hepatitis C: an update. Hepatology. 2009;49:1335–1374. 7. Rockstroh JK, Bhagani S. Managing HIV/hepatitis C co-infection in the era of direct acting antivirals. BMC Med. 2013;11:234. 8. Sulkowski MS. HCV therapy in HIV-infected patients. Liver Int. 2013;33 (suppl 1):63–67. 9. Delemos AS, Chung RT. Hepatitis C treatment: an incipient therapeutic revolution. Trends Mol Med. 2014;20:315–321. 10. Lawitz E, Mangia A, Wyles D, et al. Sofosbuvir for previously untreated chronic hepatitis C infection. N Engl J Med. 2013;368:1878–1887. 11. 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.e3–1334 e3. 12. 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. 13. Kotler DP. Hepatitis C, human immunodeficiency virus and metabolic syndrome: interactions. Liver Int. 2009;29(suppl 2):38–46. 14. Ryan P, Resino S, Miralles P, et al. Insulin resistance impairs response to interferon plus ribavirin in patients coinfected with HIV and hepatitis C virus. J Acquir Immune Defic Syndr. 2010;55:176–181. 15. Eslam M, Lopez-Cortes LF, Romero-Gomez M. The role of insulin resistance in HIV/hepatitis C virus-coinfected patients. Curr Opin HIV AIDS. 2011;6:553–558. 16. Soriano V, Poveda E, Vispo E, et al. Pharmacogenetics of hepatitis C. J Antimicrob Chemother. 2012;67:523–529. 17. Wahli W, Michalik L. PPARs at the crossroads of lipid signaling and inflammation. Trends Endocrinol Metab. 2012;23:351–363. 18. Tontonoz P, SB. Fat and beyond: the diverse biology of PPARgamma. Annu Rev Biochem. 2008;77:289–312. 19. Jeninga EH, Gurnell M, Kalkhoven E. Functional implications of genetic variation in human PPARgamma. Trends Endocrinol Metab. 2009;20: 380–387. 20. Saraf N, Sharma PK, Mondal SC, et al. Role of PPARg2 transcription factor in thiazolidinedione-induced insulin sensitization. J Pharm Pharmacol. 2012;64:161–171. 21. Otake K, Omoto S, Yamamoto T, et al. HIV-1 Nef protein in the nucleus influences adipogenesis as well as viral transcription through the peroxisome proliferator-activated receptors. AIDS. 2004;18:189–198. 22. Shrivastav S, Kino T, Cunningham T, et al. Human immunodeficiency virus (HIV)-1 viral protein R suppresses transcriptional activity of peroxisome proliferator-activated receptor {gamma} and inhibits adipocyte differentiation: implications for HIV-associated lipodystrophy. Mol Endocrinol. 2008;22:234–247. 23. Diaz-Delfin J, Domingo P, Mateo MG, et al. Effects of rilpivirine on human adipocyte differentiation, gene expression, and release of adipokines and cytokines. Antimicrob Agents Chemother. 2012;56:3369–3375. 24. Mencarelli A, Francisci D, Renga B, et al. Ritonavir-induced lipoatrophy and dyslipidaemia is reversed by the anti-inflammatory drug leflunomide in a PPAR-gamma-dependent manner. Antivir Ther. 2012;17:669–678. 25. Kim K, Kim KH, Ha E, et al. Hepatitis C virus NS5A protein increases hepatic lipid accumulation via induction of activation and expression of PPARgamma. FEBS lett. 2009;583:2720–2726. 26. Kim KH, Hong SP, Kim K, et al. HCV core protein induces hepatic lipid accumulation by activating SREBP1 and PPARgamma. Biochem Biophys Res Commun. 2007;355:883–888. 27. Huguenin GV, Rosa G. The Ala allele in the PPAR-gamma2 gene is associated with reduced risk of type 2 diabetes mellitus in Caucasians and improved insulin sensitivity in overweight subjects. Br J Nutr. 2010; 104:488–497. 28. Gouda HN, Sagoo GS, Harding AH, et al. The association between the peroxisome proliferator-activated receptor-gamma2 (PPARG2) Pro12Ala gene variant and type 2 diabetes mellitus: a HuGE review and metaanalysis. Am J Epidemiol. 2010;171:645–655. 29. Saumoy M, Veloso S, Alonso-Villaverde C, et al. PPARgamma Pro12Ala polymorphism in HIV-1-infected patients with HAART-related lipodystrophy. Curr HIV Res. 2009;7:533–540.
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30. Hung YP, Lee NY, Lin SH, et al. Effects of PPARgamma and RBP4 gene variants on metabolic syndrome in HIV-infected patients with antiretroviral therapy. PLoS One. 2012;7:e49102. 31. Nazih H, Raffi F, Taieb A, et al. Peroxisome proliferator activating receptor alpha and gamma polymorphisms and metabolic abnormalities in HIV-infected patients receiving highly active antiretroviral therapy: the ANRS CO8 APROCO-COPILOTE study. AIDS Res Hum Retroviruses. 2012;28:393–399. 32. Thorpe LE, Ouellet LJ, Hershow R, et al. Risk of hepatitis C virus infection among young adult injection drug users who share injection equipment. Am J Epidemiol. 2002;155:645–653. 33. Resino S, Seoane JA, Bellon JM, et al. An artificial neural network improves the non-invasive diagnosis of significant fibrosis in HIV/HCV coinfected patients. J Infect. 2011;62:77–86. 34. Tuma P, Medrano J, Resino S, et al. Incidence of liver cirrhosis in HIVinfected patients with chronic hepatitis B or C in the era of highly active antiretroviral therapy. Antivir Ther. 2010;15:881–886. 35. Purcell S, Neale B, Todd-Brown K, et al. PLINK: a tool set for wholegenome association and population-based linkage analyses. Am J Hum Genet. 2007;81:559–575. 36. Heikkinen S, Argmann C, Feige JN, et al. The Pro12Ala PPARgamma2 variant determines metabolism at the gene-environment interface. Cell metab. 2009;9:88–98. 37. Luan J, Browne PO, Harding AH, et al. Evidence for gene-nutrient interaction at the PPARgamma locus. Diabetes. 2001;50:686–689. 38. Memisoglu A, Hu FB, Hankinson SE, et al. Interaction between a peroxisome proliferator-activated receptor gamma gene polymorphism and dietary fat intake in relation to body mass. Hum Mol Genet. 2003;12: 2923–2929. 39. Jimenez-Sousa MA, Fernandez-Rodriguez A, Guzman-Fulgencio M, et al. Meta-analysis: implications of interleukin-28B polymorphisms in spontaneous and treatment-related clearance for patients with hepatitis C. BMC Med. 2013;11:6. 40. Fernandez-Rodriguez A, Rallon N, Berenguer J, et al. Analysis of IL28B alleles with virologic response patterns and plasma cytokine levels in HIV/HCV-coinfected patients. AIDS. 2013;27:163–173. 41. 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. 42. Stumvoll M, Haring H. The peroxisome proliferator-activated receptorgamma2 Pro12Ala polymorphism. Diabetes. 2002;51:2341–2347. 43. Ma J, Li Y, Zhou F, et al. Meta-analysis of association between the Pro12Ala polymorphism of the peroxisome proliferator-activated receptor-gamma2 gene and diabetic retinopathy in Caucasians and Asians. Mol Vis. 2012;18:2352–2360. 44. Liu G, Zhou TB, Jiang Z, et al. Relationship between PPARgamma Pro12Ala gene polymorphism and type 2 diabetic nephropathy risk in Asian population: results from a meta-analysis. J Recep Signal Transduct Res. 2014;34:131–136. 45. Zhou TB, Guo XF, Yin SS. Association of peroxisome proliferatoractivated receptor gamma Pro12Ala gene polymorphism with type 2 diabetic nephropathy risk in Caucasian population. J Receptor Signal Transduction Research. 2014;34:180–184. 46. Hadigan C, Kottilil S. Hepatitis C virus infection and coinfection with human immunodeficiency virus: challenges and advancements in management. JAMA. 2011;306:294–301. 47. Hiard S, Charlier C, Coppieters W, et al. Patrocles: a database of polymorphic miRNA-mediated gene regulation in vertebrates. Nucleic Acids Res. 2010;38:D640–D651. 48. Ferre P. The biology of peroxisome proliferator-activated receptors: relationship with lipid metabolism and insulin sensitivity. Diabetes. 2004;53 (suppl 1):S43–S50. 49. Pawlotsky JM. New hepatitis C Therapies: the Toolbox, strategies, and challenges. Gastroenterology. 2014;146:1176–1192. 50. Matsuura K, Watanabe T, Tanaka Y. Role of IL28B for chronic hepatitis C treatment toward personalized medicine. J Gastroenterol Hepatol. 2014;29:241–249.
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