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PPARγ2 Pro12Ala Polymorphism Is Associated With Sustained Virological Response in HIV/HCV-Coinfected Patients Under HCV Therapy

Fernández-Rodríguez, Amanda PhD*; Berenguer, Juan MD, PhD†,‡; Rallón, Norma PhD§; Jiménez-Sousa, María A. PhD*; López, Juan Carlos MD, PhD; Soriano, Vicente MD, PhD; García-Álvarez, Mónica PhD*; Cosín, Jaime MD, PhD; Martínez, Paula PhD§; Guzmán-Fulgencio, María PhD*; Miralles, Pilar MD; Miguel Benito, José MD, PhD§; Resino, Salvador PhD*

JAIDS Journal of Acquired Immune Deficiency Syndromes: October 1st, 2014 - Volume 67 - Issue 2 - p 113–119
doi: 10.1097/QAI.0000000000000282
Basic and Translational Science

Objectives: To analyze whether peroxisome proliferator-activated receptor gamma (PPARγ2) 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 HCV-treatment, were genotyped for PPARγ2 and interleukin 28B polymorphisms. Genetic data were analyzed under dominant inheritance model. 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 PPARγ2 rs1801282 CG/GG genotype [aOR = 2.93 (95% CI: 1.27 to 6.72) P = 0.011]. When PPARγ2 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 ± 0.028.

Conclusions: The presence of PPARγ2 rs1801282 G allele (Ala variant) was associated with increased odds for achieving SVR in HIV/HCV-coinfected patients on HCV treatment.

*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

Servicio de Enfermedades Infecciosas, Hospital Carlos III, Madrid, Spain.

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:

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.

Received January 03, 2014

Accepted May 13, 2014

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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 (pegIFNα/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 pegIFNα/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 pegIFNα/ribavirin is being a standard of care for GT1 patients.10 Thus, it is still essential the potential ongoing relevance of understanding pegIFNα/ribavirin response predictors. However, not all HIV/HCV-coinfected 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 pegIFNα/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 pegIFNα/ribavirin therapy.16

Peroxisome proliferator-activated receptor gamma (PPARγ) is considered as a “key element” in the glucose homeostasis and lipoprotein metabolism,17 being mainly expressed in adipose tissue.18 The PPARγ gene is located on chromosome 3; and differential splicing of this gene results in 2 different isoforms: PPARγ1 and PPARγ2, differing only in their N-terminal region.19 The increase of PPARγ2 gene transcription results in the upregulation of the insulin-sensitizing factor and the downregulation of the insulin-resistant factor.20 Moreover, PPARγ2 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 PPARγ2 expression.25,26

The most common gene polymorphism in human PPARγ2 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 PPARγ2 isoform.19PPARγ2 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 PPARγ2 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 PPARγ2 rs1801282 polymorphism is associated with the response to pegIFNα/ribavirin treatment in HIV/HCV-coinfected patients, and whether it is able to predict the outcome of HCV treatment.

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We carried out a retrospective follow-up study on 285 European HIV/HCV-coinfected naive patients, who started treatment with pegIFNα/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, α1-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 PPARγ activating drugs, such as thiazolidinediones, during the study.

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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 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 pegIFNα 2a or 2b at standard doses (180 µg·wk−1 or 1.5 µg·kg−1·wk−1, 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 PPARγ2 gene polymorphism rs1801282 and the IL28B polymorphism rs12980275 were genotyped at the Spanish National Genotyping Centre (CeGen; Genotyping was performed by using the GoldenGate assay with VeraCode Technology (Illumina Inc., San Diego, CA).

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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 χ2 test for categorical variables. All SNPs were analyzed for Hardy–Weinberg equilibrium by χ2 test, considering equilibrium when P > 0.001.

For association study, logistic regression analysis was used to investigate the relationship between PPARγ2 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 PPARγ2, 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 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 PPARγ rs1801282 and IL28B rs12980275 polymorphisms.

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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.



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Characteristics of PPARγ2 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 (

The rs1801282 at PPARγ2 and the rs12980275 at IL28B fulfilled the minimum allele frequency >0.05 and were in Hardy–Weinberg equilibrium (P > 0.001).

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PPARγ2 rs1801282 Polymorphism and HCV Virological Response

We analyzed both additive and dominant genetic model for PPARγ2 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 PPARγ2 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 PPARγ2 rs1801282 and IL28B rs12980275 polymorphisms was tested, but the epistasis analysis did not reveal significant results (data not shown). Thus, the association between PPARγ2 CG/GG genotype and SVR was independent of IL28B genotype.

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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 PPARγ2 rs1801282 genotype). In patients infected with GT3, SVR rate increased from 80.3% to 100% when the PPARγ2 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 ± 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%.

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This study shows that HIV/HCV-coinfected patients carrying the PPARγ2 rs1801282 CG/GG genotype (Ala variant) had a higher probability for achieving successful HCV treatment. To our knowledge, our article is the first to describe the relation between PPARγ2 rs1801282 polymorphism and SVR in patients with CHC under pegIFNα/ribavirin therapy. Moreover, the predictive model with HCV genotype, IL28B rs12980275 polymorphism, and PPARγ2 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.

PPARγ2 is a nuclear receptor involved in the regulation of lipid and glucose metabolism19; and an increase of PPARγ2 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 PPARγ2 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, PPARγ2 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 PPARγ2 Ala variant beneficial in lean subjects but detrimental when coexisting with obesity.36–38 Then, it could be possible that PPARγ2 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 PPARγ2 rs1801282 polymorphism on 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 PPARγ2 polymorphism on the response to HCV therapy.

Interestingly, the association detected between PPARγ2 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 pegIFNα/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 PPARγ2 polymorphism effects in other populations. In this regard, the frequency of the favorable PPARγ2 G variant has a marked differential distribution between populations: 12% in whites, 10% in Native Americans, 4% in Japanese, 3% in African 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 PPARγ2 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 pegIFNα/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, PPARγ2 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 PPARγ2 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 PPARγ2 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 long-term consequences in PPARγ2 expression.48 At short-term, an increase in PPARγ2 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 pegIFNα/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 IFNα. For this reason, new IFN-free 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 PPARγ2 is a cornerstone. Thus, further analysis will be needed to determine whether PPARγ2 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 PPARγ2 “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 pegIFNα 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 PPARγ2 expression and also the association of PPARγ2 polymorphism with HCV therapy outcome in a HCV-monoinfected cohort of patients.

In conclusion, the presence of PPARγ2 rs1801282 G allele (Ala variant) was significantly associated with increased odds for achieving SVR in HIV/HCV-coinfected patients on HCV therapy with pegIFNα/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.

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The authors wish to thank the Spanish National Genotyping Center (CeGen) for providing the genotyping services ( The authors also acknowledge the patients in this study for their participation.

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chronic hepatitis C; AIDS; HCV therapy; PPARγ2; single nucleotide polymorphism

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