Hepatitis C Virus (HCV) Genotype 3 is Associated with Higher Grade of Liver Fibrosis in Hepatitis C Virus Infected Patients

Research Article

Austin J HIV/AIDS Res. 2016; 3(3): 1030.

Hepatitis C Virus (HCV) Genotype 3 is Associated with Higher Grade of Liver Fibrosis in Hepatitis C Virus Infected Patients

Kundu N¹, Gupta E¹*, Rastogi A², Kumar G³ and Khurana J¹

¹Department of Clinical Virology, Institute of Liver and Biliary Sciences, New Delhi, India

²Department of Clinical Pathology, Institute of Liver and Biliary Sciences, New Delhi, India

³Department of Research, Institute of Liver and Biliary Sciences, New Delhi, India

*Corresponding author: Gupta E, Department of Clinical Virology, Institute of Liver and Biliary Sciences, New Delhi, India

Received: September 20, 2016; Accepted: November 01, 2016; Published: November 03, 2016


In Chronic hepatitis C (CHC), one of the most important causes of chronic liver diseases, exact association of viral factors such as Genotype and viral load with fibrosis is not yet determined.

Objective: To investigate relationship between HCV genotypes, viral load, biochemical markers and degree of liver fibrosis in patients with chronic HCV infection.

Materials and Methods: Retrospective analysis of 887 HCV positive patients was done. Liver biopsy was done in 154 patients and degree of fibrosis was evaluated by modified ISHAK scoring system. HCV viral load was determined by COBAS TaqMan HCV test v2.0 (Roche Molecular System Inc, Branchburg, NJ, USA) and genotyping was performed by Linear Array HCV Genotyping Test (Roche Molecular System Inc, Branchburg, NJ, USA).

Result: The mean age of study population was 47.63 (±15.08) years and male: female ratio was 2.68:1. Overall mean HCV viral load was 6.26x105 (±12.52) IU/ml, mean ALT level 62.65 (±2.16) IU/ml, mean AST level 43.0 (±2.03) IU/ml and mean total bilirubin level 1.00 (±0.19) mg/dl. Genotype 3 (69.4%) was most common genotype followed by 1 (25.6%) and 4 (4.6%). The biochemical markers (ALT, AST and total bilirubin) were significantly higher in patients with genotype 3 as compared to genotype1 (p=0.036, 0.000 and 0.012 respectively). Of 154 patients, fibrosis score <3 was seen in 96 (62.5%) patients and =3 in the remaining 58 (37.5%) patients. Genotype 3 was significantly correlated with higher (=3) fibrosis score (p=0.009).

Conclusion: Genotype 3 was found to be significantly associated with higher liver fibrosis which may have implications in clinical management of genotype 3 infected patients.

Keywords: Chronic hepatitis; Hepatitis C virus; Genotypes; Fibrosis


HCV: Hepatitis C virus; CHC: Chronic hepatitis C; HBV: Hepatitis B Virus; HIV: Human Immunodeficiency virus; FPR: Fibrosis progression Rate; OPD: Outpatient; ICU: Intensive care units; HIS: Hospital Information System; CMIA: Chemiluminiscence Micropartice Immunoassay; RNA: Ribonucleic Acid; RT-PCR: Reverse transcription-polymerase chain reaction; CHB: Chronic Hepatitis B; ILBS: Institute of Liver and Biliary Sciences; FDA: Food and Drug Administration; ALT: Alanine Amino Transferase; AST: Aspartate Amino Transferase; SPSS: Statistical Package for Social Studies; IU/ml: international unit per millilitre; mg/dl: Milligram per Decilitre; HCC: Hepato-Cellular Carcinoma


Approximately 3% of the world’s populations, (more than 350 million people) are chronically infected with hepatitis C virus (HCV) [1]. Chronic hepatitis C (CHC) is one of the most important causes of chronic liver diseases ranging from mild inflammation to fibrosis, cirrhosis and hepatocellular carcinoma, associated with the increased morbidity and mortality [2]. The identification of factors affecting fibrosis progression is critical for the optimal management of infected patients [3]. Factors associated with rapid progression of fibrosis include demographic characteristics (such as older age at infection and male sex), host genetic factors, viral co-infections (with the hepatitis B [HBV] or the human immunodeficiency virus [HIV]), metabolic features (such as steatosis, insulin resistance or iron overload) and exposure to toxic agents (alcohol, tobacco or cannabis) [4]. The estimation of fibrosis progression rate (FPR) based on the ratio of fibrosis stage to disease duration has been shown to reflect the true fibrosis progression. Recent studies have suggested that some viral genotypes, such as genotype 3, are associated with more rapid fibrosis progression than other genotypes [5-7].

It is well established fact that in HCV infected patients, the clinical findings, genotypes and viral load are strong predictors for the outcome of antiviral therapy [8]. Several authors tried to develop correlations between various non-invasive markers of liver damage (serum hyaluronic acid levels, collagen level, platelet count, serum bilirubin levels and elevated transaminases levels) with HCV viral load and genotypes in HCV infected patients, but no clear conclusions were formed [9-13].

This study was conducted to find the prevalence of HCV genotypes in Delhi, and to further investigate relation of these genotypes with liver fibrosis and disease activity markers. The correlation of genotype with severity of histopathological disease has not been studied from India, and only few studies have correlated viral load, biochemical markers with genotypes.

Materials and Methods


In the retrospective analysis, a total of 887 patients were enrolled according to inclusion/ exclusion criteria from the people visiting outpatient (OPD) or those admitted in wards/intensive care units (ICUs) of our hospital during January 2011 to July 2014. The liver biopsy was done only in 157/887 patients (according to the indication of biopsy as per institute’s protocol). The study was approved by the Ethics Committee of the institute. A detailed clinical history and clinical examination results were obtained from HIS (hospital information system) of the institute.

Inclusion criteria: Patient’s positive both for Anti HCV antibodies using 3rd generation Anti HCV chemiluminiscence micropartice immunoassay (CMIA) (Anti HCV Architect System, Abott, Weisbaden, Germany) and HCV Ribonucleic Acid (RNA) detection by reverse transcription-polymerase chain reaction (RTPCR).

Exclusion criteria: Patients with co-infections [chronic hepatitis B (CHB) or HIV], other non- infectious causes of chronic liver disease, history of alcohol intake, taking immunosuppressive drugs and chronic renal insufficiency were excluded from the study.


Peripheral blood (serum and plasma) samples were collected from each patient for enzyme immunoassays, the measurement of biochemical markers of liver damage and the investigation of viral ribonucleic acid (RNA) and HCV genotyping by molecular biology techniques. HCV serology and biochemical markers were tested using commercially available chemiluminiscent microparticle immunoassay method (CMIA) (Abott Laboratories, Chicago, IL, USA).

Quantitative measurement of hepatitis C viral load

Plasma sample collected from each patient was used to extract HCV RNA using high pure viral RNA extraction as per manufacturer’s instructions (Roche Diagnostic GmbH, Mannheim, Germany). The eluted RNA was stored at -70°C until use. HCV RNA load was determined by FDA approved COBAS TaqMan HCV test v2.0 (Roche Molecular System Inc, Branchburg, NJ, USA). The linear range of this real time PCR assay is 25IU/ml to 3.9x108 IU/ml and lower limit of detection is 25IU/ml.

HCV genotype analysis

Genotyping was performed by Linear Array HCV Genotyping Test (Roche Molecular System Inc, Branchburg, NJ, USA).

Histological evaluation of biopsy samples

The modified ISHAK scoring system was used to grade degree of fibrosis and histological activity in liver biopsy samples at department of Pathology, institute of Liver and Biliary Sciences (ILBS) [14]. Liver biopsies were evaluated by two independent pathologists without former information to patient’s history. Liver histological staging was based on six scores of fibrosis: as score 0 (no fibrosis), 1 (mild fibrosis of some portal areas without septa), 2 (mild fibrosis of most portal areas without septa), 3 (moderate fibrosis with occasional septa), 4 (fibrous expansion of portal areas with marked bridging [portal to portal (P-P) as well as portal to central (P-C)), 5(marked bridging (P-P and/or P-C) with occasional nodules (incomplete cirrhosis), 6(Cirrhosis, probable or definite). These scores were further grouped as 0(no fibrosis), 1-2 (mild fibrosis) and =3 (moderate fibrosis to cirrhosis) [14].

Association of HCV genotypes with viral and host factors

HCV genotypes were correlated with viral load, host biochemical markers (alanine aminotransferase (ALT); aspartate amino transferase (AST) and total bilirubin) and liver biopsy study results. Different markers were also correlated with fibrosis staging and histologic activity index.

Statistical analysis

The statistical analysis was performed using the statistical package for social studies (SPSS) version 17 for windows. Student t-test and Chi-square tests were applied to evaluate differences in proportions. P value <0.05 was considered significant. The normal values of alanine aminotransferase (ALT), aspartate aminotransferase (AST) and total bilirubin level were (~5-40 IU/ mL), (~10-40 IU/ mL) and (< 1.0 mg/ dl) respectively. Multiple regression analysis was used to evaluate independent associations between HCV genotypes and individual demographic characteristics, biochemical values and viral load to identify variables association within different genotypes. For further analysis of different blood markers with respect to genotypes, only genotypes 1 and 3 were studied because of very small sample size in other two groups (using Mann-Whitney test). The correlation of serum markers and viral load was analyzed by Spearman’s correlation for non parametric data.


Of the total 887 patients included in study, 646 (73%) were males while 241(27%) were females. The mean age of the study population was 47.63 (± 15.08) years. The most frequently detected genotype was 3 (69.4%) followed by 1 (25.6%) and 4 (4.6%). The genotype 2 was detected in only 3(0.3%) patients. The frequency distribution of different genotypes according to age and gender is given in Table 1.