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Abstract

  1. Top of page
  2. Abstract
  3. Patients and Methods
  4. Results
  5. Discussion
  6. References
  7. Supporting Information

Fibrosis progression is the main determinant of liver disease outcome in chronic hepatitis C, being influenced by environmental and host factors. Recently, a cirrhosis risk score (CRS) based on seven single-nucleotide polymorphisms was proposed as genetic predictor of cirrhosis in hepatitis C. To assess the role of CRS in predicting fibrosis progression in patients with initially no or minimal to moderate fibrosis, we investigated 271 untreated patients with chronic hepatitis C having initial liver biopsy showing METAVIR stage F0 (n = 104), F1 (n = 101), or F2 (n = 59) who had been followed up without antiviral therapies for at least 60 months (mean 108.5 ± 71.5 months) and had a liver biopsy at the end of this observation period. Of these, 24.4% showed no histologic progression, 75.6% progressed by at least one stage, 45.0% progressed by at least two stages, and 10.3% progressed by more than two stages. The mean CRS was significantly higher (P = 0.005) in patients with fibrosis progression compared with those without progression, and this difference was particularly evident (P = 0.002) with F0 on initial biopsy. Mean CRS scores were not associated with degree of fibrosis progression. The relative risk of fibrosis progression increased with increasing CRS values. This association was significant in males but not in females and was most evident in males with F0 at initial biopsy (odds ratio 16.5, 95% confidence interval 1.6–166; P= 0.02) in the presence of high CRS. Multivariate analysis confirmed the significant association of CRS score with fibrosis progression. The predictive value of CRS was confirmed in hepatitis C virus patients admitting significant alcohol intake. Conclusion: Host genetics defined by CRS predict fibrosis progression in males with initially mild chronic hepatitis C and may become a useful parameter for prognostic evaluation and treatment decision. (HEPATOLOGY 2009.)

Chronic infection with hepatitis C virus (HCV) is a major cause of chronic liver disease, cirrhosis, and hepatocellular carcinoma worldwide and is the most common reason for liver transplantation in many western countries.1–3

Natural history studies indicate that only a subgroup of patients chronically infected with HCV eventually progress to cirrhosis and to end-stage liver disease and that rates and speed of progression are extremely variable in individual cases. Patients infected with chronic hepatitis C may indeed behave as rapid, intermediate, or slow/no progressors, with time to development of cirrhosis ranging from a few years to several decades.4

Univariate and multivariate analysis applied to cross-sectional and longitudinal studies have identified several variables that significantly influence rate of disease progression in chronic HCV infection. Viral parameters, i.e. the HCV genotype and serum viral levels have minor impact on the clinical phenotype in untreated patients while environmental and host factors play a more relevant role.5, 6 Alcohol intake and coinfection with hepatitis B virus (HBV) or human immunodeficiency virus (HIV) have been clearly proven to accelerate fibrosis progression and development of end-stage liver complications in HCV patients.7–9 As far as host factors are concerned, age at infection,10 male sex,11 immunosuppression, and presence of metabolic syndrome and/or of type II diabetes have all been associated with more severe and progressive liver disease.12–14

Increasing evidence indicates that genetic factors may have a major influence on the natural history of chronic liver disease of different etiologies, including hepatitis C. Special interest has been focused on the identification of candidate genes involved in hepatic fibrogenesis, considering that liver fibrosis, the hallmark of liver disease progression to cirrhosis, is a dynamic process in which multiple genes are likely to interact with environmental factors. Several single-nucleotide polymorphisms (SNPs) have been described as being associated with fibrosis progression in HCV patients, including single-nucleotide mutations in the genes encoding for IFNγ, TNFα, inerleukin-10, low-density lipoprotein, factor V Leiden, and the monocyte chemotatic protein 2.6, 15, 16 Most of these findings were from studies conducted in rather small cohorts of patients and have not been confirmed in independent series. Conflicting results have been obtained in other studies that have assessed variations in genes that might be involved in the regulation of the immune response to HCV. Using a nonhypothesis, functional genome scan approach, Huang et al.17 identified a seven-gene variant signature, termed the cirrhosis risk score (CRS) that is associated with development of cirrhosis in patients chronically infected with HCV. In this study, high CRS scores, derived from an algorithm based on a constellation of seven SNPs, showed a positive predictive value of 82% to 96% in diagnosing patients with cirrhosis, and the area under the receiver operating characteristic curves was 0.73 in the validation cohort compared with 0.53 for clinical factors alone. Although the study by Huang et al. indicates that a high CRS is associated with presence of cirrhosis in HCV patients, no longitudinal studies have been conducted to assess the prognostic value of the CRS seven-gene signature in HCV patients presenting with no/minimal liver fibrosis. Therefore, we evaluated in this study whether the CRS can predict fibrosis progression in a large cohort of untreated patients with initially mild chronic hepatitis C and variable degree of fibrosis progression over a prolonged follow-up of 5 to 10 years.

Patients and Methods

  1. Top of page
  2. Abstract
  3. Patients and Methods
  4. Results
  5. Discussion
  6. References
  7. Supporting Information

Patients.

This study was conducted in patients with chronic hepatitis C who underwent a diagnostic liver biopsy at the University of Padova or at the University of Verona between 1980 and 1996, and had a follow-up liver biopsy taken at least 60 months later after an observation period without antiviral therapy. The inclusion criteria were: (1) no fibrosis or presence of mild to moderate fibrosis (METAVIR stage F0-F2) fibrosis at initial liver biopsy; (2) serological evidence of chronic hepatitis C as defined by the presence of anti-HCV positivity with persistent (>6 months) HCV RNA positivity in serum; and (3) a pair of liver biopsies of adequate size for fibrosis staging (>15 mm with more than seven portal tracts). For patients seen initially before 1990, having an initial diagnosis of chronic non-A non-B hepatitis, reclassification as hepatitis C was done retrospectively on stored serum samples. Patients coinfected with HBV or HIV, or with type II diabetes or severe obesity/metabolic syndrome (body mass index >32) were excluded in order to avoid interference by these cofactors known to have a profound effect on disease progression in chronic hepatitis C. On the other hand, the analysis of the association between genetic polymorphisms and disease progression was adjusted for male sex and age, two other variables known to affect fibrosis progression in hepatitis C. None of the patients had received antiviral treatments prior to inclusion in the study or received treatment during the follow-up period preceding the second liver biopsy. This is explained by the fact that most of the patients were initially observed and followed up in the 1980s and early 1990s, when antiviral treatments for HCV were either not yet available or of limited efficacy and the initial mild stage of liver disease was not considered an indication for treatment. A total of 271 patients with the above characteristics and without significant alcohol intake (<30 g/day) were included as the main study cohort. There were 150 (55.4%) male and 121 (44.6%) female patients with a mean age at initial biopsy of 48 ± 10.7 years (mean ± SD). Serum alanine aminotransferase levels were elevated at baseline and or during follow-up in 225 cases, whereas the remaining 49 (18%) had persistently normal levels. The HCV genotype was determined in 264 (96.3%) of the patients and was found to be HCV-1 in 160 (59.1%), HCV-2 in 56 (20.8%), HCV-3 in 31 (11.3%), and HCV-4 in 14 (5.1%). All patients were Caucasians. In order to assess whether the CRS genetic signature could predict fibrosis progression in HCV patients even in the presence of a frequent and significant disease cofactor such as alcohol, we also investigated 49 additional HCV patients admitting daily alcohol intake >30 g (median, 55 g [range, 30–101 g]). In this group, 35 were males and 14 females, mean age was 42 ± 13.1 years with 26 cases infected with HCV-1 and 23 with HCV-3. All patients gave their informed consent to participate in the study that was conducted according to the ethical guidelines of the 1975 Declaration of Helsinki.

Liver Biopsy Evaluation.

Paired liver biopsies were available in all patients with a time interval of 5 years or more (mean 106.48 ± 71.47 months [range, 60–316 months]). In all patients, liver biopsy had been obtained using the Menghini technique with a 1.6-mm needle. The median biopsy length was 29 mm (range, 15–61 mm), and the median number of portal tracts was 11 (range, 7–23). Liver biopsies were evaluated by a pathologist (M. G.) who was unaware of demographic and clinical data and of the sequence biopsies that were obtained. Fibrosis stages were defined using the METAVIR scoring system,18 and progression of fibrosis was defined according to changes in METAVIR fibrosis score between the first and second biopsy in each patient. Individual progression rates were also calculated as METAVIR fibrosis units per year.

Seven-SNP Signature (CRS) Genotyping.

For each patient, genomic DNA was isolated from whole blood and the genotypes for the seven SNPs in the CRS signature plus a sex marker were simultaneously determined using a multiplex polymerase chain reaction and oligonucleotide ligation research assay. Briefly, eight distinct amplicons were generated by polymerase chain reaction and subsequently genotyped by oligonucleotide ligation reaction. For a given marker, oligonucleotide ligation genotyping was accomplished by target amplicon directed hybridization and subsequent ligation of the allele-specific oligonucleotides, differing at their 3′ terminal base and containing a 5′ complementary sequence tag for a specific oligonucleotide-conjugated Luminex bead, with a common ligation-specific oligonucleotide containing a 3′-conjugated biotin molecule (Celera Diagnostic, Alameda, CA). The genotype-specific ligation products were hybridized to derivatized Luminex Beads, labeled with a strepdavidin-phycoerythrin reporter molecule, and analyzed on a Luminex TM system (Luminex, Austin, TX). Genotypes were determined automatically by a generic research software that compares the ratio of fluorescent signals between the two alleles.

Cirrhosis Risk Score.

Marker selection and building steps for developing the CRS algorithm have been described in detail previously. In the present study, the value of CRS was calculated for each patient using the original Naïve-Bayes formula.17 The seven SNPs contributing to the CRS signature are: AZIN 1 (on chromosome 8), TLR4 (on chromosome 9), TRPM5 (on chromosome 11), AQP2 (on chromosome 12), and three additional polymorphisms (on chromosomes 1, 3, and 15) not fully characterized.17 For a more detailed description of the formula used to calculate CRS in each individual patient, see Huang et al.17 and the Supporting Information.

Statistical Methods.

The continuous distribution of CRS was assessed for association with fibrosis progression using the Wilcoxon rank-sum test for comparisons of two groups or the Kruskal-Wallis test for comparisons of more than two groups. Patients were classified as having low (CRS < 0.5), moderate (0.5 ≥ CRS ≤ 0.7), or high (CRS ≥ 0.7) risk of fibrosis progression as described,17 and the Armitage trend test was used to test the association of the CRS with the proportion of patients showing progression of more than one unit of METAVIR score. Logistic regression was performed to estimate the effect of CRS on progression after adjustment for sex, age at infection, age at first biopsy, and interval between the first and second biopsies.

Results

  1. Top of page
  2. Abstract
  3. Patients and Methods
  4. Results
  5. Discussion
  6. References
  7. Supporting Information

Liver Biopsy Findings and Fibrosis Progression.

Table 1 describes the 271 patients without significant alcohol intake with the proportions of them who showed stable or progressive fibrosis between the first and second liver biopsy, grouped according to the initial stage of fibrosis. Most patients had no (F0, n = 104 [38.4%]) or minimal (F1, n = 108 [39.8%]) fibrosis in their initial liver biopsy, whereas 59 (21.8%) had stage F2 fibrosis. Fibrosis progression by at least one METAVIR stage in the follow-up biopsy was observed in 205 patients (75.6%), including 80 with stage F0 (39.0%), 74 with stage F1 (36.1%), and 51 with stage F2 (24.9%) in the initial biopsy. When only progressors were considered, individual fibrosis changes over time, expressed as METAVIR fibrosis units per year, were 0.216 ± 0.12 (mean ± standard deviation; median, 0.204 [range, 0.024–0.864]). Progression by two or more METAVIR stages was seen in 122 (45%) patients. Progression by more than two METAVIR stages correlated with longer time interval between biopsies. As an example, there were 17 (16.3%) patients with F0 in the initial biopsy who progressed to stage F3 (n = 10) or F4 (n = 7). The mean time interval between biopsies in these patients was 324 ± 156 months (median, 276 months) compared with 104 ± 20.5 months (median, 108 months) in patients with stage F0 at initial biopsy who did not progress or showed one- or two-stage fibrosis progression. Because the size of the liver biopsy may affect the evaluation of fibrosis stage, we compared the first and second biopsies in patients who did or did not show fibrosis progression. As shown in Table 2, size and number of portal tracts of the first and second biopsies did not differ significantly in nonprogressors and progressors, independently of the degree of progression.

Table 1. Changes in METAVIR Fibrosis Score Between First and Second Biopsy in 271 Patients with Chronic Hepatitis C
First BiopsySecond Biopsy, n (%)Total, n (%)
F0F1F2F3F4
024 (23.1)27 (26.0)36 (34.6)10 (9.6)7 (6.7)104 (38.4)
F10 (0)34 (31.5)40 (37.0)23 (21.3)11 (10.2)108 (39.9)
F20 (0)0 (0)8 (13.6)16 (27.1)35 (59.3)59 (21.8)
Total24 (8.9)61 (22.5)84 (31.0)49 (18.1)53 (19.6)271 (100)
Table 2. Size of Liver Biopsy and Number of Portal Tracts in Paired Samples from 271 HCV Patients, According to Fibrosis Progression During the Observation Period
 Length, mmNo. of Portal Tracts
First BiopsySecond BiopsyFirst BiopsySecond Biopsy
  1. Values are expressed as the mean ± standard deviation. All differences are not statistically significant.

All cases24 ± 1127 ± 1410 ± 811 ± 9
Nonprogressors22 ± 924 ± 129 ± 410 ± 6
Progressors (any stage)25 ± 1328 ± 1612 ± 711 ± 9
Progressors (≥2 METAVIR stage)24 ± 1027 ± 1511 ± 613 ± 10

Fibrosis progression was found to be significantly associated with male sex (odds ratio [OR] 2.3552, 95% confidence interval [CI] 1.3351–4.1547; P = 0.003), higher METAVIR fibrosis stage (OR 1.21, 95% CI 1.07–1.35; P = 0.02) in the initial biopsy, and longer time between the first and second biopsy (OR 1.019, 95% CI 1.006–1.032; P = 0.05). Fibrosis progression in the follow-up biopsy also correlated with inflammation activity grade in the first biopsy (OR 2.34, 95% CI 1.11–4.32; P = 0.01) In contrast, age at diagnosis (P = 0.14), age at first biopsy (P = 0.55), and the HCV genotype (P = 0.21) were not associated with fibrosis progression.

Distribution of CRS According to Fibrosis Progression.

The mean CRS was 0.531 ± 0.21 in patients without fibrosis progression during follow-up and 0.635 ± 0.19 in those with progression (any METAVIR stage), and this difference was statistically significant (P = 0.005). On the other hand, no significant differences were seen in mean CRS when patients who progressed by one (mean CRS ± standard deviation, 0.627 ± 0.18), two (0.655 ± 0.19), three (0.588 ± 0.24), or four (0.629 ± 0.14) METAVIR stages were compared. When only patients with stage F0 at initial biopsy were considered, nonprogressors again showed significantly lower mean CRS (0.499 ± 0.22) compared with progressors (0.655 ± 0.18; P = 0.002), whereas no significant differences were seen in relation to the degree of progression between the first and second biopsy (progressors by one stage, mean CRS 0.669 ± 0.18; by two stages, 0.6584 ± 0.17; by three stages, 0.626 ± 0.22; by four stages, 0.629 ± 0.14). Accordingly, there was no significant association between CRS score and the individual rate of fibrosis progression calculated as METAVIR fibrosis units per year (data not shown).

Rates of Progression According to CRS Risk Groups.

Patients were classified into three risk subgroups according to CRS score as proposed by Huang et al.17 (low risk, CRS < 0.5; moderate risk, CRS 0.5–0.7; high risk, CRS > 0.7). The percentages of patients showing fibrosis progression in the second liver biopsy according to CRS risk and to the initial fibrosis stage are described in Table 3. Among those patients with stage F0 at the initial biopsy and who showed fibrosis progression (more than one METAVIR stage), 56.7%, 79.4%, and 90.0% fell into the low, moderate, and high CRS risk groups, respectively. Compared with patients in the low-risk group, the OR for progression was 2.95 (95% CI 0.98–8.87) for the intermediate-risk group and 6.88 (1.95–24.3) for the high-risk group.

Table 3. Percentage of Patients with Fibrosis Progression According to Initial Fibrosis Stage and CRS Score
Initial BiopsyCRSTotal PatientsProgressed Patients, n (%)95% CI
F0-F2Low8252 (63.4)52.4–74.4
 Intermediate8969 (77.5)68.3–86.8
 High10084 (84.0)76.3–91.7
F0-F1    
 Low6338 (60.3)47.4–73.2
 Intermediate6849 (72.1)60.7–83.5
 High8167 (82.7)73.9–91.6
F0    
 Low3017 (56.7)37.3–76.1
 Intermediate3427 (79.4)64.4–94.5
 High4036 (90.0)79.4–100.0

Multivariate Analysis Modeling Fibrosis Progression as a Function of CRS Risk Score.

Multivariate analysis was performed to assess the association of CRS risk on fibrosis progression after adjustment for sex, age at diagnosis, age at first biopsy, and interval between the first and second biopsy (Table 4).

Table 4. Odds Ratios for Fibrosis Progression (≥1 METAVIR Stage) After Adjustment for Sex, Age at Diagnosis, Age at First Biopsy, and Interval Between First and Second Biopsy
SexCRSF0 at Initial BiopsyF0-F2 at Initial Biopsy
OR (95% Cl)P ValueP Trend*OR (95% Cl)P ValueP Trend*
  • *

    Armitage trend test for increasing odds of progression across low, intermediate, and high CRS groups.

AllHigh4.98 (1.28–19.28)0.020.00122.03 (0.95–4.37)0.0640.0014
 Intermediate3.70 (1.11–12.30)0.03 1.90 (0.97–3.84)0.073 
 Low1 (ref)  1 (ref)  
MaleHigh16.53 (1.64–166.12)0.0060.0194.70 (1.57–14.1)0.0060.0091
 Intermediate11.15 (1.15–108.48)0.04 4.18 (1.24–14.1)0.02 
 Low1 (ref)  1 (ref)  
FemaleHigh3.24 (0.46–22.89)0.240.071.04 (0.34–3.16)0.950.38
 Intermediate2.38 (0.53–10.72)0.26 1.30 (0.54–3.12)0.55 
 Low1 (ref)  1 (ref)  

The association of the CRS score with fibrosis progression remained significant after adjustment for the other variables.

Table 4 describes the results of this analysis in relation to initial fibrosis, sex and CRS score. When male and female patients were considered together, cases with moderate or high CRS score showed an adjusted OR for fibrosis progression that was higher compared with cases with low CRS, and this difference was statistically significant for the subgroup with stage F0 at initial biopsy.

The association of CRS score with fibrosis progression was highly significant in male patients, whereas no significant association was seen in female patients. Indeed, only male patients with moderate or high CRS scores had a significantly higher OR for fibrosis progression compared with those with low CRS. This association in male patients was largely independent of the initial fibrosis stage. The highest OR was seen in male patients with stage F0 in the initial biopsy and high CRS score (OR 16.5, 95% CI 1.6–166; P = 0.02). On the other hand, CRS scores were not associated with fibrosis progression in female patients, independent of the initial fibrosis score. To assess the possible effects of interaction between CRS risk and sex on fibrosis progression, the logistic regression models were fit with an interaction term of CRS risk and sex. However, no significant interactions were found between CRS risk and sex.

CRS and Fibrosis Progression in HCV Patients with Significant (>30 g/day) Alcohol Intake.

Some degree of fibrosis progression was seen in all 49 HCV patients who admitted significant alcohol intake during follow-up. However, 19 of these patients had minimal progression by only one METAVIR stage, whereas the remaining 30 showed histological progression by two or more METAVIR stages. Because the median interval between liver biopsies was similar in these two subgroups (74 versus 82 months) it was possible to analyze the contribution of the CRS signature on fibrosis progression in the presence of alcohol intake by comparing the 19 slow progressors to the 30 rapid progressors. The mean CRS was 0.561 + 0.11 in the former and 0.674 + 018 in the latter, and this difference was statistically significant (P = 0.049). There were 15 patients with a low-risk CRS, 15 with an intermediate-risk CRS and 19 with CRS > 0.70 (high-risk). Significant fibrosis progression (more than METAVIR stages) was seen in 5 (33.3%), 7 (46.6%), and 18 (94.7%) patients, respectively. These findings, though obtained in a rather small cohort of patients, indicate that the CRS genetic signature remains predictive of fibrosis progression in HCV-infected individuals, even in the presence of significant alcohol intake.

Discussion

  1. Top of page
  2. Abstract
  3. Patients and Methods
  4. Results
  5. Discussion
  6. References
  7. Supporting Information

There is increasing evidence that genetic factors might influence the natural history and outcome of a variety of chronic liver diseases, including hepatitis C. Race has been shown to affect liver fibrosis progression in HCV-infected individuals,19, 20 and numerous studies have implicated polymorphisms of specific genes in liver disease progression due to HCV infection. However, many of these studies were conducted in small case series and/or series with short follow-up periods, and have thus generated conflicting results8; consequently, understanding of the pathogenetic significance and possible clinical implications of the reported findings is still incomplete and complex. This is because progression in chronic hepatitis C most likely involves several genes, making it more difficult to define the relative contribution of each single one. Furthermore, many environmental cofactors and several common comorbidities are known to affect the course of liver disease progression with HCV, and their prominent effect may hinder the emergence of any underlying genetic predisposition affecting the rapidity of disease progression.

The association between CRS and cirrhosis was established by Huang et al.17 in a cross-sectional study comparing a control group of HCV patients without fibrosis (F0 by METAVIR) with a case group with HCV bridging fibrosis/cirrhosis. Our study has now confirmed the prognostic value of CRS in hepatitis C by showing its association with the risk of developing liver fibrosis and cirrhosis in patients with no/mild fibrosis in the initial biopsy followed prospectively. In our study, we included quite a high number of patients with F0 at initial biopsy due to the large cohort of such cases that was available for analysis, because in the past they were not considered for antiviral therapy with a clear indication to follow-up monitoring with sequential liver biopsies. Our results indicate that the prognostic value of CRS appears particularly solid in this subgroup of patients. Although it is true that this result could have been magnified by the fact that in patients with stage F0 at baseline the follow-up biopsies could only show stability or progression, but not regression, compared with cases starting from other stages of disease, it should also be noted that this is still the category of HCV patients in whom the decision to treat or observe would greatly benefit from the availability of solid prognostic markers.

The fact that severe disease progression may indeed occur even in HCV patients with stage F0 in initial biopsy was confirmed by our data, indicating that 17% eventually developed stage F3 or F4 fibrosis. Although chronic hepatitis C is a rather slow disease in most cases and takes decades to progress to advanced fibrosis, a subgroup of more rapid progressors has been clearly described in the literature. On the other hand, our patients with stage F0 in initial biopsy who progressed to stage F3 or F4 had a time interval between biopsies that was significantly higher compared with other patients and showed progression to advanced fibrosis over a period of more than 20 years. This type of progression is compatible with outcome modeling based on what has been described in the literature in similar patients followed for shorter periods.21, 22

In our study, the predictive value of high CRS was evident and statistically significant in male patients with HCV, but not in female patients. The inability to show a significant association of the CRS with fibrosis progression among females could be due to a lack of statistical power, considering that progression of hepatitis C is usually slower in female patients and that the follow-up period in our study was 5 to 10 years. For example, assuming that the true progression rate (one or more METAVIR stages) for female patients with stage F0-F2 at initial biopsy and intermediate CRS is 70%, our study had an 80% power to detect a significant trend in the proportion of females progressing when the high and low groups differ from the intermediate group by 16% or more (56%, 72%, and 88% progressors in low, intermediate, and high groups, respectively). Among females with stage F0 at initial biopsy, an 80% power would be achieved only when the low and high groups differed by 27% or more (43%, 70%, and 92% progressors in low, intermediate, and high groups, respectively). Alternatively, the seven SNPs included in the building of CRS may not play a relevant role in fibrosis progression among female patients for reasons that warrant further study.

However, the prognostic value of CRS was excellent in male patients, particularly in those with stage F0 at initial biopsy, independent of other variables, such as age and time interval between biopsies. This observation is particularly relevant when considering the potential role for the use of CRS in assessing a patient in clinical practice. HCV-infected cases with stage F0 at biopsy are usually considered to have a mild, nonprogressive form of liver disease and are not indicated for antiviral therapy. Our study shows that male patients with F0 and high CRS (>0.70) have a significant risk of disease progression over time, behaving as rapid progressors and therefore, may deserve immediate treatment. Further studies are now needed to assess whether the predictability of CRS in males, and particularly in females with HCV might be improved by expanding the panel of SNPs and/or by recalibrating the currently used predictive model.

Progression of chronic hepatitis C is known to be profoundly influenced by several cofactors, the most frequently described and encountered in clinical practice being alcohol, HBV–HIV coinfections, and, according to more recent recognition, liver steatosis and insulin resistance. We have shown here that the prognostic value of the CRS signature on fibrosis progression holds true even in HCV patients who abuse alcohol. The role of CRS in predicting liver disease outcome in HCV patients with other viral coinfections or metabolic syndrome—as well as in hepatitis B, nonalcoholic fatty liver, and other chronic liver diseases—deserves adequate future evaluation.

References

  1. Top of page
  2. Abstract
  3. Patients and Methods
  4. Results
  5. Discussion
  6. References
  7. Supporting Information
  • 1
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Supporting Information

  1. Top of page
  2. Abstract
  3. Patients and Methods
  4. Results
  5. Discussion
  6. References
  7. Supporting Information

Additional Supporting Information may be found in the online version of this article.

FilenameFormatSizeDescription
HEP_23111_sm_SupTabs.rtf16KSupplementary table 1: CRS algorithm. Supplementary table 2: Conditional probabilities (p) of each SNP used to calculate individual CRS.

Please note: Wiley Blackwell is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.