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Friday, August 3, 2012

Glucose Abnormalities in Pre-diabetic Chronic Hepatitis C Patients Receiving Peginterferon Plus Ribavirin Therapy


From Liver International

The Outcomes of Glucose Abnormalities in Pre-diabetic Chronic Hepatitis C Patients Receiving Peginterferon Plus Ribavirin Therapy

Jee-Fu Huang; Ming-Lung Yu; Chung-Feng Huang; Suh-Hang Hank Juo; Chia-Yen Dai; Ming-Yen Hsieh; Nei-Jen Hou; Ming-Lun Yeh; Meng-Hsuan Hsieh; Jeng-Fu Yang; Zu-Yau Lin; Shinn-Chern Chen; Shyi-Jang Shin; Wan-Long Chuang
Posted: 08/03/2012; Liver International. 2012;32(6):962-969. © 2012 Blackwell Publishing

Full Text @ Medscape

AbstractBackground/Aims Pre-diabetes is a risk factor for type 2 diabetes mellitus (DM) development. This study aimed to elucidate the impact of treatment response on sequential changes in glucose abnormalities in pre-diabetic chronic hepatitis C (CHC) patients.

Methods Chronic Hepatitis C patients with a baseline haemoglobin A1C (A1C) range 5.7–6.4% who achieved 80/80/80 adherence were prospectively recruited. All patients received current peginterferon-based recommendations. The primary outcome measurement was their A1C level at the end of follow-up (EOF). The interaction between variants of the IL28B gene and outcomes of glucose metabolism was also measured.

Results A total of 181 consecutive CHC patients were enrolled. The mean A1C at EOF was 5.82 ± 0.41%, which was significantly lower than the baseline level (5.93 ± 0.21%, P < 0.001). At EOF, 63 (34.8%) patients became normoglycaemic, whereas 10 (5.5%) patients developed DM. The sustained virological response (SVR) rates of 63 normoglycaemics, 108 pre-diabetics and 10 diabetic patients at the EOF were 92.1%, 84.3% and 50% respectively (normoglycaemics vs. diabetics P = 0.003; pre-diabetics vs. diabetics P = 0.02). Achievement of an SVR was the only predictive factor associated with normoglycaemia development at EOF by multivariate logistic regression analysis (Odds ratio = 2.6, P = 0.04). The prevalence of the interleukin 28B rs8099917 TT variant in patients who developed DM (70.0%) at EOF tended to be lower than that in patients with pre-diabetics (87.0%) or normoglycaemics (92.1%).

Conclusion Successful eradication of HCV improves glucose abnormalities in pre-diabetic CHC patients.

Methods
Patient Selection
Eligible patients were treatment-naive Taiwanese patients with CHC, aged 18–65 years, who (1) were seropositive for HCV antibodies and HCV RNA positive; (2) had undergone a liver biopsy within 6 months before entry, the result of which was consistent with chronic hepatitis; (3) displayed an increased serum alanine aminotransferase (ALT) level, defined as > 1.5 times the upper limit of the normal range for at least two measurements within 6 months preceding the study entry. Other eligibility criteria included neutrophil count > 1500/mm3, platelet count > 9 × 104/mm3, haemoglobin concentration > 12 g/dl for men and 11 g/dl for women, serum creatinine concentration < 1.5 mg/dl, no pregnancy or lactation and the use of a reliable method of contraception for women. Patients with hepatitis B surface antigen seropositive, HIV infection, autoimmune hepatitis, primary biliary cirrhosis, sclerosing cholangitis, Wilson's disease, α1-antitrypsin deficiency, decompensated cirrhosis (Child–Pugh class B or C), overt hepatic failure, current alcohol misuse or history of alcohol misuse (>20 g/day), psychiatric condition, previous liver transplantation, or evidence of hepatocellular carcinoma were excluded from the study.

Study Design
This study was an investigator-initiated study. This prospective, open-label, multi-centre study was conducted in one medical centre and two regional core hospitals in Taiwan. The ethical committee of the Kaohsiung Medical University Hospital approved the study before it began. Written informed consent for interview, anthropomorphic measurements, blood sampling and medical record review were obtained from patients prior to enrolment. Before treatment, all patients underwent a 12-h overnight fast before blood tests, which included HCV RNA quantitative and genotype tests, fasting plasma glucose, insulin, cholesterol, triglycerides and ALT levels. In addition to histological data, anthropometric data, which included body weight and height, were measured using standardized techniques.

All the enrolled patients received either pegIFN α-2a (Pegasys; Hoffmann-La Roche, Basal, Switzerland) at a dose of 180 μg/week subcutaneously or pegIFN α-2b (PEG-Intron; Schering-Plough Inc., Kenilworth, NJ, USA) at a dose of 100–120 μg/week subcutaneously and oral RBV 1000–1200 mg/day in two divided doses for 24 weeks. The dose of RBV was based on body weight (1000 mg RBV for weight < 75 kg and 1200 mg RBV for weight > 75 kg). The genotype-1 (G-1) and the genotype-2 or 3 (G-2/3) patients received 48-week, and 24-week, respectively, duration of treatment. All patients were monitored for a further 24 weeks after the end of the treatment. End of follow-up (EOF) was defined as the visit 24 weeks after the end of the treatment. Patients had biweekly outpatient visits during the first month and monthly visits during the rest of the treatment period and during the 24-week follow-up period. At each visit, they underwent a physical examination, and adverse events were recorded. Treatment adherence was monitored via patient's treatment diaries and the return of used and unused pre-filled syringes and drug containers. A sustained SVR was defined as a patient showing clearance of HCV RNA by the end of treatment and at EOF.
Patients who had received at least 80% of total PegIFN dose, at least 80% of total RBV dose and completed at least 80% of total study duration (80/80/80 adherence) were recruited into further analysis. At EOF, anthropomorphic measurements, blood sampling, IR and β-cell function were performed.

Laboratory Analyses
Hepatitis B surface Antigen and anti–HCV antibody were detected using a third-generation, commercially available enzyme-linked immunosorbent assay kit (AxSYM 3.0; Abbott Laboratories, Chicago, IL, USA). Detection of serum HCV RNA was performed using a standardized automated qualitative reverse transcription polymerase chain reaction assay (COBAS AMPLICOR Hepatitis C Virus Test, ver. 2.0; Roche, Branchburg, NJ, USA). The detection limit was 50 IU/ml. HCV genotypes 1a, 1b, 2a, 2b and 3a were determined using the Okamoto method.[30] FPG, cholesterol, triglycerides and ALT levels were measured on a multichannel autoanalyser (Hitachi Inc, Tokyo, Japan). Fasting serum insulin levels were measured using radioimmunoassay (Diagnostic Products Co., Los Angeles, CA, USA).

The definition of pre-diabetes and DM were made according to the American Diabetes Association criteria.[13] Briefly, patients with twice the FPG levels > 126 mg/dl of previous medical records, A1C >6.5%, previously established diagnosis of DM, and currently taking any form of hypoglycaemic drugs or insulin injections were categorized as having known or clinical DM. For those without known or clinical DM, pre-diabetes was diagnosed if their A1C levels ranged between 5.7% and 6.4%.

Insulin Resistance was calculated on the basis of fasting plasma glucose (FPG) and insulin levels, according to the homeostasis model assessment (HOMA) method.[31] The formulas for the HOMA-IR = FPG (mg/dl) × fasting insulin level (μU/ml)/405. IR was considered elevated when it was > 2.5.[18]

Histological Analyses
Biopsy samples were stained with haematoxylin-eosin and the results were then reported by one pathologist who was blinded to the treatment of each patient. Histological grading of chronic hepatitis was made based on histological activity index (HAI) of Knodell et al.[32] Liver histology was staged according to the Metavir scoring systems.[33] The extent of hepatic steatosis was assessed using light microscope and scored as none (0–5%), mild (5–33%), moderate (33–66%) and severe (>66%), according to the area occupied by fatty hepatocytes.[34]

IL-28B Genotyping Previous GWAS have indicated that SNPs rs12979860 and rs8099917 are related to treatment outcome of HCV G-1 infection among Caucasians and African Americans.[26, 27] On the other hand, rs12980275, rs11881222, rs7248668, rs8105790, rs8099917, rs4803219 and rs10853728 were demonstrated to be associated with antiviral treatment responses based on GWAS and replication study in Asian ethnicity.[25] Since the minor allele frequencies of rs12980275, rs11881222 and rs7248668 are all less than 1% in Taiwanese[35] and thereby rs8105790, rs8099917, rs4803219 and rs10853728 were selected as candidate SNPs in the present study. Genotypes of the patients were determined using the ABI TaqMan® SNP genotyping assays (Applied Biosystems, Foster City, CA, USA) by using the pre-designed commercial genotyping assays (ABI Assay ID: C__11710096_10; Applied Biosystems). Briefly, PCR primers and two allelic-specific probes were designed to detect specific SNP target. The PCR reactions were performed in the 96-well microplates with ABI 7500 real-time PCR (Applied Biosystems). Allele discrimination was achieved by detecting fluorescence using its System SDS software version 1.2.3. In our previous study [28], rs8105790, rs8099917 and rs4803219 were noted to be in very strong linkage disequilibrium with one another (r2 = 0.94–0.96). Therefore, rs8099917 and rs10853728 were selected for final analysis with respect to other variables in the current study.

Statistical Analyses
Frequency was compared between groups using the χ2 test, with the Yates correction or Fisher's exact test. Results are expressed as mean values ± standard deviation (SD) and were compared between groups using analysis of variance and the Student's t-test, or nonparametric Mann–Whitney U-test when appropriate. Serum HCV RNA levels were expressed after logarithmic transformation of original values.
The Hardy–Weinberg disequilibrium test was performed for each SNP. Linkage disequilibrium index (Lewontin's *D' and r2) was calculated using Haploview version 4.2 software. The frequencies of the rare alleles of rs8099917 and rs10853728 genotypes were too low and we combined the rare homozygote and heterozygote together while analysing these two SNPs.
The strength of each association is presented as the odds ratio (OR) with 95% confidence interval (CI) and P value. All statistical analyses were based on two-sided hypothesis tests with a significance level of P < 0.05. Quality control procedures, database processing and analyses were performed using the spss 12.0 statistical package (SPSS Inc., Chicago, IL, USA).

Results
Patient Demographic and Baseline Characteristics
From July 2006 to November 2009, a total of 793 patients received treatment and agreed to participate in the study. There were 241 patients of normoglycaemia, 263 patients of pre-diabetes and 289 patients of T2DM respectively. The treatment was discontinued in 24 pre-diabetes patients (severe adverse event in 11, loss of follow-up in 13 patients respectively). Fifty-eight patients were excluded from the study because they did not achieve the 80/80/80 adherence goal. A total of 181 pre-diabetic CHC patients (106 men, mean age = 53.6 ± 10.5 years) were enrolled into the analysis. Their baseline demographic data are shown in Table 1. The mean HbA1c was 5.93 ± 0.21%. They included 92 (50.8%) patients of G-1 and 89 patients of G-non-1 infection. The mean viral load was 5.3 ± 1.01 logs IU/ml. SVR was achieved by 85.1% (154/181) of all patients. It was achieved by 77.2% (71/92) of G-1 patients and by 93.3% (83/89) of G-non-1 patients. Those 154 patients who achieved SVR significantly had a lower age, a lower HAI score and a lower viral load than those who did not (Table 1). The SVR patients had a higher cholesterol level than their non-SVR counterparts (180.1 ± 36.1 vs. 159.9 ± 35.6 mg/dl, P = 0.03). The mean baseline HbA1c was not significantly different between SVR and non-SVR patients. There was also no statistical significance between the SVR and non-SVR patients in terms of gender, BMI, ALT, TG, advanced fibrosis, steatosis and HOMA-IR.

The rs8099917 TT genotype had a significantly higher rate than GT/GG genotypes in achieving an SVR (91.6% vs. 66.7%, P = 0.003). However, the significance was only observed in 92 G-1 patients (92.9% vs. 61.1%, P = 0.001), but not in 89 G-non-1 patients (91.5% vs. 88.0%, P = 0.47). There was no significant linkage between rs10853728 CC genotype and SVR achievement. Multivariate logistic regression analysis of variables associated with the achievement of an SVR such as age, gender, BMI, fibrosis stages, extent of steatosis, baseline HOMA-IR, genotypes viral load and rs8099917 TT genotype was performed. It demonstrated that rs8099917 TT genotype was a significant predictor for SVR (OR = 6.03, 95% CI = 1.38–26.40, P = 0.02), whilst G-1 infection (OR = 0.15, 95% CI = 0.03–0.73, P = 0.02) and baseline high IR (>2.5) (OR = 0.28, 95% CI = 0.08–0.95, P = 0.04) were the negative variables associated with SVR achievement (Table 2).

The Interplay between SVR and Sequential A1C Changes at EOF
There was a significant reduction of mean body weight after therapy (from 66.4 ± 10.3 kg of baseline to 64.4 ± 9.9 kg of EOF, P < 0.001). The mean A1C at EOF was 5.82 ± 0.41%, which was significantly lower than baseline level (5.93 ± 0.21%, P < 0.001). The improvement was observed in those G-non-1 (from 5.94 ± 0.21 to 5.80 ± 0.31%, P < 0.001), but not in G-1 (from 5.93 ± 0.22 to 5.85 ± 0.49%, P = 0.1) patients. At EOF, 63 (34.8%) patients had their A1C <5.7%, 108 (59.7%) patients remained to be pre-diabetics, whilst 10 (5.5%) patients became diabetic (A1C > 6.5%). The significant reduction of body weight after therapy was observed in the 63 patients regressed to normoglycaemia (from 65.1 ± 9.8 kg of baseline to 62.6 ± 9.4 kg of EOF, P < 0.001) and 108 patients who remained pre-diabetics (from 66.6 ± 10.5 kg of baseline to 64.9 ± 10.0 kg of EOF, P < 0.001) at EOF, whereas there was no significant weight change in 10 patients who progressed to diabetic at EOF (from 68.3 ± 11.4 kg of baseline to 67.1 ± 11.4 kg of EOF, P = 0.17). There was a significant increasing trend of SVR dependent of glucose abnormalities at EOF, ranging from 50% (5/10) in diabetics, 84.3% (91/108) in pre-diabetics and 92.1% (58/63) in normoglycaemics respectively (Fig. 1).



Figure 1.
Sustained virological response rate according to treatment outcomes of glucose metabolism in pre-diabetic chronic hepatitis C patients.

Multivariate logistic regression analysis of variables associated with the development of normoglycaemia such as age, gender, BMI, sequential body weight change, fibrosis stages, extent of steatosis, baseline HOMA-IR, genotypes, viral load and achievement of an SVR was performed. Achievement of an SVR was the only predictive factor associated with the development of normoglycaemia at EOF (OR = 2.64, 95% CI = 1.10–6.76, P = 0.04). On the other side, high IR (>2.5) was the predictor associated with the development of DM after therapy (OR = 7.18, 95% CI = 1.44–35.90, P = 0.02).
IL28B Variants Affecting IR and Treatment Outcome of Glucose Abnormalities

The prevalence of rs8099917 TT variant in 37 patients with baseline high IR (>2.5) was 92.0%, which was comparable to that (88.7%) of 144 patients without high IR (P = 0.67). No significant difference of rs10853728 CC variant existence was also observed in patients with and without baseline high IR (64.0% vs. 62.9%, P = 0.84). The lack of significance was found according to different genotypes.

The interaction between treatment outcomes of glucose abnormalities and IL28B genomic variants was also analysed. The prevalence of rs8099917 TT variant in patients with normoglycaemia, pre-diabetes and DM after treatment were 92.1% (58/63), 87.0% (94/108), and 70.0% (7/10) respectively. However, no statistical significance was reached (Fig. 2). There was also no significant difference of rs10853728 CC variant in these three groups of patients (69.4% of normoglycaemia, 58.7% of pre-diabetes, and 62.5% of DM respectively).


Figure 2.
The proportion of IL28B rs8099917 TT genotype according to treatment outcomes of glucose metabolism in pre-diabetic chronic hepatitis C patients.

Introduction
Hepatitis C virus (HCV) infection is the major cause of cirrhosis and hepatocellular carcinoma worldwide.[1, 2] There is robust experimental and clinical data showing the prominent association between chronic HCV (CHC) and type 2 diabetes mellitus (DM).[3–7] For those without known DM, there was a 3.5-folds increase in the prevalence of glucose abnormalities in CHC patients in comparison with that in controls.[8] In addition to its various extrahepatic manifestations [9-12], HCV infection is currently considered to be a diabetogenic factor.

Diabetes Mellitus, a common endocrine disorder develops in a stepwise fashion manifesting from normoglycaemia, pre-diabetes, subclinical DM, to clinical DM.[13, 14] Recently, serum haemoglobin (A1C) level has been adapted as a simple tool for the identification of persons with glucose abnormalities. Pre-diabetes, defined as A1C between 5.7% and 6.4%, carries a relatively high risk for future development of DM and even dyslipidemia and cardiovascular disease.[15] However, little information has been obtained in this special group of CHC patients in terms of treatment efficacy, treatment outcomes, sequential change of insulin resistance (IR) and the interaction with genomic profiles.

Pegylated interferon (PegIFN)-α plus ribavirin (RBV) combination therapy has become the mainstream for the treatment of CHC.[16, 17] Previous studies have demonstrated that IR, the main drive of glucose abnormalities, is a predictor of sustained virological response (SVR) to antiviral therapy.[18] Meanwhile, clearance of HCV improved IR and β-cell function, and may ameliorate inflammation.[19, 20] However, IFN can exacerbate an existing autoimmune tendency, which may subsequently precipitate immune-mediated abnormalities de novo, thus leading to emergence of IR and subsequent DM.[21–24] Therefore, the outcomes of pre-diabetic CHC patients after receiving PegIFN/RBV therapy remain to be determined.
Recently
, studies based on genome-wide associated studies (GWAS) have showed that single nucleotide polymorphisms (SNPs) at and/or near the interleukin 28B (IL28B) gene, which encodes interferon-λ, play a critical role in the treatment efficacy of HCV infection.[25–29] Therefore, the interplay between IL28B genetic variants and IR and its related outcomes after antiviral therapy in CHC patients deserves to be elucidated.
This study aimed to elucidate the treatment outcome with respect to glucose abnormalities in pre-diabetic CHC patients receiving PegIFN/RBV combination therapy. The associated factors, including host factor of interleukin 28B-related genomic data, leading the treatment outcome were also analysed.


DiscussionPre-diabetes, defined as the patients with their A1C levels that ranged between 5.7% and 6.4%, carries a potential risk for future development of DM and cardiovascular event. An elevated serum insulin level subsequent to beta-cell hyperfunction aiming to maintain glucose homeostasis was the main figure at this phase of glucose abnormalities. Therefore, it provides an excellent scope of view aiming to elucidate the impact of antiviral therapy on the outcome of glucose abnormalities. The present study, to our knowledge, is the first to delineate the characteristics of glucose abnormalities after PegIFN/RBV combination therapy in this special group. It is also the first to elucidate the interplay between IR and IL28B gene variants in CHC patients. Our results demonstrated that their A1C could be significantly ameliorated at EOF, albeit the improvement was only observed in those G-non-1 patients, but not in G-1 patients. A total of 34.8% patients recovered from their pre-diabetic status, whereas 5.5% patients became diabetic after PegIFN/RBV combination therapy. Meanwhile, we demonstrated that the treatment outcome of glucose abnormalities was significantly associated with SVR, and achievement of an SVR was the only predictive factor associated with the restoration of normoglycaemia at EOF. With respect to the impact of IL 28B gene variants on the treatment efficacy, we demonstrated that those pre-diabetic CHC patients carrying the rs8099917 TT genotype had a higher chance of cure with current standard of care regimens. However, there was no significant association between IL28B gene variants and glucose abnormalities, either IR or outcome of glucose abnormalities. The current study therefore provided a comprehensive clarification of aforementioned issues in pre-diabetic CHC patients.

The A1C is a standard biomarker of glycaemia and plays a critical role in the management of DM patients. It correlates well with both micro- and macro-vascular complications and is widely used as a simple and accurate tool for identification of the suite of glucose abnormalities as well as glycaemic management.[13] Structured interventional strategies, such as increasing physical activity, body weight reduction and certain pharmacological agents, have been proved to prevent or delay the development of DM upon diagnosis of pre-diabetes.[36, 37] Our results further addressed that A1C could also be effectively ameliorated by antiviral therapy. Of note and intriguingly, 34.8% CHC patients could be recovered from their pre-diabetic status. The achievement of an SVR was a predictive factor associated with the recovery in current study. Our data were a complementary result echoing previous studies[18, 19, 38] showing that IR and/or glucose abnormalities are independent predictors of SVR in CHC patients treated with antiviral therapy and clearance of HCV improves IR, β-cell function and hepatic expression of insulin receptor substrate-1 and -2, the major intracellular trafficking determinants of glucose metabolism. Noteworthy was that we recruited those who achieved 80/80/80 adherence of combination therapy into analysis, which may reflect the real interaction between efficacy of antiviral therapy and the outcome measurement. It thus reinforced the diabetogenic effect of HCV infection and may imply that antiviral treatment is an important interventional strategy for pre-diabetes in CHC patients.

Previous study by Gomez M et al.[39] demonstrated that with an average follow-up period of 27 ± 17 months in a cohort of 734 patients with normal glucose metabolism, 16.9% CHC patients developed glucose abnormalities: 1% of DM and 15.9% of impaired fasting glucose (IFG). Our study provided a consistent result demonstrating that achievement of an SVR reduced the risk of glucose abnormalities. We further addressed that the state of glucose abnormalities could be reversed with SVR achievement. Meanwhile, there was a positive correlation between SVR and outcomes of glucose metabolism in our patients. Whether or not the tendency of improvement of glucose abnormalities continues with a longer follow-up period deserves to be clarified in the future study.
On the other side, both IFN and RBV may trigger immune activation, leading to the unexpected immune response events in addition to therapeutic effects.[40–42] Schreuder et al.[24] showed that the incidence of development of type 1 and type 2 DM during combination therapy were 2.6%, and 1.6% respectively. We observed 5.5% patients became diabetic after treatment and half of them were responders. High IR before treatment was the predictor associated with the development of DM in the current study. Our results were somewhat discordant with previous observation that those who developed IFG or DM were all non-responders and the determining variables were fibrosis stage and SVR achievement. Different background of glucose metabolism, a lower BMI, a lower proportion of family history, different genotypic distribution as well as ethnic difference may in a large part contribute to the discrepancy. Our results may imply that HCV clearance cannot completely prevent the development of T2DM in genetically predisposed individuals, particularly in those who did not have effective intervention for IR reduction, such as lifestyle modification and weight reduction.
Besides viral factors, host susceptibility such as genetic variations has recently been proposed to play an important role in the treatment efficacy of PegIFN/RBV combination therapy.[25, 28] We demonstrated that rs8099917 TT genotype was a significant predictor associated with SVR with current standard of care regimens, which is a consistent finding with previous observation.[25] However, the linkage between IL 28B gene variants and IR-associated glucose abnormalities deserves to be elucidated since IFN-λ, the encoded protein of IL28B gene, may induce immune responses.[23] The current study demonstrated that although the rs8099917 TT genotype had an impact on treatment efficacy in G-1 patients, it was not significantly associated with baseline IR. There was also no significant association between treatment outcomes of glucose abnormalities and IL28B genomic variants (rs8099917 TT and rs10853728 CC variants). It may suggest that the emergence of IR in CHC is evolved from the multi-factorial, complex context encompassing viral proteins, cytokine cascades, native and adaptive immune responses and environmental factors. Intriguingly, despite no statistical significance being reached, the prevalence of rs8099917 TT variant in patients who developed DM tended to be lower than patients with pre-diabetes and normoglycaemia. Previous Taiwanese studies showed that G-2 patients with the rs8099917 TT genotype had a lower viral load and a dose–response relationship existed between HCV viral load and IR.[28, 43] Therefore, the real scenario between rs8099917 TT genotype and IR in different phases of glucose abnormalities deserves to be further evaluated in a long-term fashion.

In conclusion, this study in pre-diabetic Taiwanese CHC patients demonstrated that A1C of patients could be significantly ameliorated, particularly in those G-non-1 patients. At EOF, one-third of patients recovered from pre-diabetes after PegIFN/RBV combination therapy and achievement of an SVR was the only predictive factor associated with the recovery. It may imply that pre-diabetes is a potential reversible process with antiviral therapy in CHC. The lack of significant association between IL28B gene variants and IR and treatment outcomes of glucose abnormalities may suggest the limited role of genomic factor in this issue. Additional long-term follow-up study will be needed for clarification.


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