|Year : 2013 | Volume
| Issue : 4 | Page : 354-359
A study of changing trends of prevalence and genotypic distribution of hepatitis C virus among high risk groups in North India
A Chakravarti, A Ashraf, S Malik
Department of Microbiology, Maulana Azad Medical College, New Delhi, India
|Date of Submission||20-Jul-2012|
|Date of Acceptance||06-Sep-2013|
|Date of Web Publication||25-Sep-2013|
Department of Microbiology, Maulana Azad Medical College, New Delhi
Source of Support: This study was funded by research grants
from University Grant Commission, Bahadurshah Zafar Marg,
New Delhi.110002 (INDIA), Conflict of Interest: None
Purpose: Hepatitis C virus (HCV) has emerged as a leading cause of chronic hepatitis, liver cirrhosis and hepatocellular carcinoma. There is a great variability in HCV's geographical presence, transmission routes, genotypic distribution etc., in studied populations. We undertook this study in a North Indian hospital on patients of chronic liver disease to observe any emerging trend in risk groups, transmission patterns, genotypic distribution of the virus in this geographical region and its correlation with viral load. Materials and Methods: There were 54 anti-HCV positive patients including 31 HCV Ribonucleic acid (RNA) positive patients were included in the study. HCV genotyping was carried out by restriction fragment length polymorphism (RFLP) followed by direct sequencing of the core region. Viral load estimation was carried out by Taqman real time polymerase chain reaction system. Results: In 45/54 (83.3%) anti-HCV positive patients, iatrogenic procedures were responsible for transmission with blood transfusion alone responsible in 36/54 (67%). Genotype 3 was observed to be the commonest type found in all risk groups followed by type 1 and 2. Subtype 3b (35.5%) was found more prevalent than subtype 3a. A higher frequency of subtype 1b (19.4%) was also seen. Genotype 1 was associated with a significantly higher viral load compared to genotypes 3 and 2. No significant difference was observed in the biochemical profile among the three genotypes except for the levels of the enzyme, aspartate aminotransferase (AST). Conclusions: Iatrogenic procedures, especially contaminated blood transfusion etc., still contributes significantly to the pool of HCV infection. Genotype 3 is the predominant genotype in North India, though the subtype distribution within genotype 3 may be changing. The association of severe liver disease is significantly more with genotype 1 as evidenced by higher viral load and deranged AST levels.
Keywords: Genotypes, geographic distribution, hepatitis C virus, risk groups, subtypes
|How to cite this article:|
Chakravarti A, Ashraf A, Malik S. A study of changing trends of prevalence and genotypic distribution of hepatitis C virus among high risk groups in North India. Indian J Med Microbiol 2013;31:354-9
|How to cite this URL:|
Chakravarti A, Ashraf A, Malik S. A study of changing trends of prevalence and genotypic distribution of hepatitis C virus among high risk groups in North India. Indian J Med Microbiol [serial online] 2013 [cited 2020 Sep 29];31:354-9. Available from: http://www.ijmm.org/text.asp?2013/31/4/354/118877
| ~ Introduction|| |
Hepatitis C virus (HCV), since its discovery in 1989, has been considered a leading cause of chronic hepatitis which can progress to liver cirrhosis and hepatocellular carcinoma.  World Health Organisation (WHO) estimated the global prevalence of hepatitis C as 3% and approximately 170 million persons at risk of fulminant hepatitis. 
There is a great variability in HCV's geographical distribution, transmission routes and other factors in the studied populations. High prevalence is found in developing countries with limited resources and facilities such as in Asia and Africa and low-prevalence in developed nations such as in North America, North and West Europe and Australia. 
Variability also exists in the transmission routes. Transmission of HCV related to blood-products has decreased in most developed countries.  The HCV genotypes too have distinct geographical distribution and may have a bearing on the duration of treatment and outcome,  although the impact of HCV genotype in progression of disease is still controversial. 
Studies in India have revealed a seroprevalence of 1.8% of HCV infection among the general population.  But the impact of HCV infection in India may still be just emerging with serious shortcomings in the country's blood banking system as well as the health administration's inability to curb reuse of unsterilised needles. 
The high prevalence of hepatitis C and the need to understand its epidemiology warrants periodic surveillance of the disease to determine specific healthcare measures for disease prevention and control. We undertook this study in a North Indian hospital on patients of chronic liver disease to observe any emerging trend in risk groups, transmission patterns, genotypic distribution in this geographical region and its correlation with viral load, if any.
| ~ Materials and Methods|| |
The study was conducted in Virology Laboratory, Department of Microbiology, of a tertiary care Teaching Hospital, New Delhi. Adult patients with chronic hepatitis, who attended the medical outpatient department and wards of the hospital, during 2009 to 2012, were recruited in the study. A detailed medical history and clinical examination including risk factors was undertaken. The diagnosis of chronic liver disease (CLD) was made on the basis of clinical features, liver function profile, ultrasonographic findings, endoscopy and liver biopsy wherever indicated and feasible. The study protocol was approved by the Institutional Ethics Committee. Written informed consent was obtained from all study subjects. Performa was maintained for each patient containing clinical information about his/her previous exposure to risk factors.
Patients with established CLD or elevated alanine aminotransferase (ALT) level were included.
Patients positive for Hepatitis B surface antigen (HBsAg), Immunoglobulin M antibody to hepatitis B core antigen (HBcIgM), Human immunodeficiency virus (HIV) or those having history of alcohol intake were excluded from the study.
Five ml of blood sample was aseptically collected in plain vial from the study subjects. Serum was separated and aliquoted in different vials and stored at -70°C until tested. Repeated freezing and thawing was avoided. The following tests were performed in all serum samples:
Screening for HBsAg and anti-HCV antibody was carried out with the help of commercially available Enzyme-Linked Immunosorbent Assay (ELISA) kits (Hepalisa and Microlisa, J. Mitra and Co., India).
HBsAg-using commercially available ELISA Kit- (Hepalisa, J. Mitra and Co., India), as per manufacturer instructions. HBcIgM-using commercially available ELISA Kit (Bio-Rad, France), as per manufacturer instructions.
Anti-HCV antibodies-using commercially available third generation ELISA Kits which comprised of Core, E1, E2, NS3, NS4 and NS5 antigens of HCV (Microlisa, J. Mitra and Co., India), as per manufacturer instructions. HBsAg positive samples were excluded while anti-HCV antibodies positive samples were further proce ssed for next step evaluation.
Detection of hepatitis C virus ribonucleic acid by reverse transcription-polymerase chain reaction
HCV Ribonucleic acid (RNA) extraction: HCV viral RNA was extracted from the serum sample using high pure viral RNA extraction kit (Roche Diagnostics, Mannheim, GmbH, Germany), according to manufacturers' instructions. HCV RNA was extracted from 200 μl serum and eluted in 50 μl of elution buffer. Eluted RNA was stored at -80°C until further processed.
RT-PCR (Reverse transcription polymerase chain reaction)
RT-PCR was carried out by modified method of Mellor et al. 
The RNA was denatured by heating at 70°C for 3 min prior to RT-PCR, and reverse transcribed at 42°C for 60 min, in a PCR tube containing 1X RT buffer, 10 mM deoxyribonucleoside triphosphates, 20 U RNase inhibitor, 50 U murine leukemia virus reverse transcriptase, 20 pmol primer (core region P1: 5 × ATGTACCCCATGAG/TA/GTCGGC 3 × anti-sense) to a final volume of 20 μl. The c-DNA product was denatured at 95°C for 5 min, then cooled at 4°C for 5 min and used for direct PCR.
Direct polymerase chain reaction
Direct PCR was performed in the reaction mixture containing PCR buffer (10×), 2 mM MgCl 2 , 10 mM deoxynucleotide triphosphates (dNTPs), 20 pmoles primers (sense P2: 5′ACTGCCTGATAGGGTGC TTGCG AG 3′) and anti-sense (P1: 5′ ATGTACCCCATGAG/TA/GTCGGC 3′) for 5 × NCR core region, 0.75 U Taq Deoxyribonucleic Acid (DNA) polymerase, in a total reaction volume of 25 μl.
Nested-PCR was performed in a reaction mixture containing PCR buffer (10×) 2 mM MgCl 2 , 10 mM dNTPs, 20 pmoles primers (sense P3: 5′ ACTGCCTGATAGGGTGCTTG CGAG3′) and anti-sense (P4: 5' ATGTACCCCATGAG/TA/GTCGGC 3′) for 5 × NCR core region, 0.75 U Taq DNA polymerase, in a total reaction volume of 25 μl. The thermal cycling condition of direct and nested PCR was as previously described. 
Amplified PCR product was electrophoresed in ethidium bromide stained 2% nusieve agarose gel (Sigma-Aldrich, USA) and was visualised under a ultraviolet (UV) transilluminator and gel documentation (Alpha Innotech, San Leandro, USA) unit for identifying desired 405 bp fragment using molecular weight marker ɸX174/HaeIII digested product. Positive and negative controls were also included [Figure 1].
|Figure 1: Ethidium bromide stained 2% agarose gel electrophoresis from 5'NCR‑Core region: 405 bp product, Lane1-Negative control; Lanes 2, 3, 4, 5, and 6-Patient samples; Lane7-Molecular Weight marker 50 bp; Lane8-positive control. NCR: Non coding region, bp: Base pair|
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Hepatitis C virus ribonucleic acid quantification
Quantitative HCV RT-PCR was performed using the light cycler taqman master mix kit (Roche Diagnostics GmbH, Mannheim, Germany) on Roche Light cycler version 2.0. by the method of Martell et al.  Each specimen was analysed in duplicate and the mean value reported as the viremic level in the serum. The unit of the HCV RNA quantification was copies/ml. A total of seven standards of different copy numbers were included in HCV RNA quantification assay, range of standard used in quantitative analysis was 10 2 -10 8 copies/ml. A known quantity of internal standard was included in each preparation of HCV RNA. RT-PCR of a region in the 5' untranslated region was performed as suggested by the manufacturer, i.e., 95°C for 20 sec and followed by further 45 cycles at 95°C for 10 sec, 58°C for 15 sec, 72°C for 10 sec with final cooling at 40°C for 30 sec.
Hepatitis C virus ribonucleic acid genotyping
The restriction fragment length polymorphism (RFLP) analysis was carried out using method of Chinchai et al.  In RFLP, the nested PCR product of RNA positive samples (20 μl-30 μl) was digested with the three enzymes Accl, Mbol and BstN1 and incubated at 37°C for overnight in a specific endonuclease buffer. The digested product was loaded onto 3% nusieve agarose gel and the restriction pattern was analysed using Gel-Doc System (Alpha Innotech, San Leandro, USA) [Figure 2].
|Figure 2: Restriction fragment length polymorphism digestion pattern (dp) in 3% agarose gel of 5' non‑coding region‑core, genotype 1a-Lane 1 Acc1 dp, Lane 2 Mbo1 dp Genotype 3b-Lane 3 Acc1 dp, Lane 4 Mbo1 dp Genotype3a-Lane 5 Acc1 dp, Lane 6 Mbo1 dp 7 = positive control (uncleaved polymerase chain reaction product 405 bp) 8 = Molecular weight marker 50bp DNA ladder|
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The nested PCR product and sense primer were used for sequencing reaction. The sequencing was done by the Sanger dideoxy method.  This was followed by detection of the HCV sequence on Beckman Coulter CEQ8000 genetic analysis system (Fullerton, USA).
Mann-Whitney and ANOVA tests were used to apply Graph pad Prism five to analyze the biochemical profile and viral load with different genotypes of HCV RNA positive samples. P < 0.05 was regarded as statistically significant.
| ~ Results|| |
A total of 226 patients were recruited in the study. Six patients, whose samples were found positive for HBsAg were excluded from the study. No sample was found positive for HBcIgM and HIV. Thus, 220 patients were included in the final analysis. Majority of these patients belonged to Delhi and the neighbouring small towns and villages. These patients could be divided into five major risk groups (blood transfusion recipients, IV drug users, unsafe medical procedures (including injections and minor surgeries not requiring blood transfusion), dental procedures and tattooing. Of the 220 patients screened, 54 (26%) were found positive for anti HCV antibody. 38/220 (17.2%) patients were found to have active infection HCV RNA positive [Table 1].
Thirty-one HCV RNA positive samples were subjected to genotype determination using RFLP followed by direct sequencing. Genotype 3 was the commonest type observed in 19 (61.2%) patients and was the commonest genotype in all risk groups [Table 2]. Other genotypes such as Type 4, 5 and 6 were not detected. Further distribution of genotypes into different subtypes and association of subtypes with sex, age groups and different risk groups is given in [Table 3].
|Table 3: Different characteristics of HCV infected patients according to genotypes|
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The accession numbers of the sequenced isolates were KC789868, KC789852.KC789869.KC789864 and KC789870.
Viral load quantification was carried out in HCV RNA positive patients. The average viral load of patients infected with genotype 1 was significantly higher than those infected with genotype 3 and 2 (P < 0.023) [Table 4]. The relation between HCV genotypes and serum levels of liver enzymes as well as other biochemical parameters were also studied [Table 4]. Of all these, aspartate aminotransferase (AST) levels showed significant difference among the three groups of HCV genotypes (P < 0.0001) [Table 4].
|Table 4: Biochemical profile and viral load of HCV positive patients with different genotypes|
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| ~ Discussion|| |
Overall, 25% seropositivity for HCV infection in patients with CLD was observed in this study. Among the 54 anti HCV antibody positive patients, in about 45/54 (83.3%), iatrogenic procedures [Table 1] were responsible for transmission with blood transfusion alone responsible in 36/54 (67%). This is unlike HIV and Hepatitis B infection, where other routes such as heterosexual contact are significant. In most of the developed world, HCV transmission through blood transfusion has been reduced to negligible numbers through effective implementation of corrective measures. In India, mandatory screening of blood for HCV was introduced as late as 2002.  However, this study and other reports suggest that transmission of HCV through unscreened blood still continues to be a significant problem.  This indicates the need for more strict implementation of blood screening procedures. Besides, the blood banking industry should progress towards newer available stringent screening techniques such as Nucleic acid Amplification tests to ensure reduction of the residual risk of transfusion transmitted infections. This tool could provide the next large step in ensuring safe blood transfusion practice in India. 
There is also an urgent need of increasing awareness among the medical care providers about safe injection and other medical or surgical procedures, especially in smaller towns and in rural settings where injectable therapies or dental procedures may be performed by untrained individuals using unsterilised syringes or equipment. In a lifetime, it is usually common to undergo several sittings for dental procedures. In India, especially in smaller towns or villages, it is a widely held belief that intramuscular injections are more effective than oral medications thus exposing the population to the risk of unnecessary injections. 
HCV genotypes show differing distributions in different geographic regions. In the United States, about 70% of cases are caused by genotype 1, 20% by genotype 2, and about 1% by each of the other genotypes.  Genotype 1 is also the most common in South America and Europe.  In India, genotype 3 has been predominant in the Northern, Eastern as well as Western region,  while in South India, genotypes 1 and 3 have been reported in decreasing order of frequency. HCV genotype 4 and 6 have been reported exclusively from South India. , Genotype 3 has also been reported to be the commonest type from the neighbouring countries of Nepal and Pakistan, while in the eastern countries of Thailand, Vietnam and Japan, genotype 1 is the most prevalent type.  Knowledge of regional distribution of HCV genotypes is important since this could influence configuration of diagnostic assays as well as vaccine designs.  In accordance with earlier published data from northern regions of India, we observed type 3 to be the commonest type in all risk groups followed by type 1 and 2. However, within genotype 3, we observed that subtype 3a (25.8%), the current most prevalent subtype as reported in all previous reports from this region, has been replaced by subtype 3b (35.5%). ,, Though, there may not be any therapeutic ramifications of this change, this could be the first indication of changing trend of HCV subtypes. We also found a higher frequency of subtype 1b (19.4%) as compared to previous studies (5.5-8.16%). , Recently, a study in Venezuela demonstrated replacement of HCV genotype 1b by genotype 2 over a 10-year period.  Any change in distribution of HCV genotypes/subtypes needs to be closely monitored in further studies as this could have serious therapeutic implications.
For physicians, knowing the genotype of Hepatitis C is helpful in deciding type and duration of therapy.  Several clinical trials of Pegylated interferon/ribavirin therapy have revealed significant differences in response rates for the various HCV genotypes. Individuals with genotypes 2 and 3 are more likely than individuals with genotype 1 to respond to therapy with alpha interferon or the combination of alpha interferon and ribavirin.  One probable reason for more treatment failures with HCV genotype 1 could be its efficient replication ability enabling it to establish higher viral RNA compared to other genotypes.  In the present study, patients with HCV genotype 1 had significantly higher viral load as compared to genotype 2 and 3. Patients with high viral load present a poor response to interferon therapy than those with lower levels. The probability of a relapse after cessation of therapy is higher in patients with high HCV RNA copy numbers prior to therapy. 
It has earlier been reported that HCV genotype distribution varies with age. In a study from neighbouring Pakistan, subtypes 1a/1b were seen more commonly in younger patients, while subtypes 2a/2b and 3a/3b were more prevalent in older patients.  Though statistically insignificant, we found a higher percentage 38.7% (13/19) of genotype 3 (3a/3b) in the 18-40 yr olds in this study [Table 3]. There is evidence suggesting that different types of HCV genotypes/subtypes may be associated with different transmission routes.  In this study, we didn't find any significant genotypic association with specific route of transmission [Table 3].
To conclude, the present study highlighted that iatrogenic procedures such as unscreened blood transfusion, injections or dental procedures still contribute significantly to the pool of HCV infection. Genotype 3 is still the predominant genotype in the northern region of India. However, the subtype distribution within genotype 3 may be changing. The severity of liver disease is significantly more commonly associated with genotype 1 as evidenced by higher viral load and deranged biochemical profile, especially in levels of AST.
| ~ Acknowledgement|| |
The authors also thankfully acknowledge Dr. P. Kar, Director Professor, Department of Medicine for providing support to the study.
| ~ References|| |
|1.||Hofgärtner WT, Polyak SJ, Sullivan DG, Carithers RL Jr, Gretch DR. Mutations in the NS5A gene of hepatitis C virus in North American patients infected with HCV genotype 1a or 1b. J Med Virol 1997;53:118-26. |
|2.||WHO. Diseases; Hepatitis C. Available from: http://www.who.int/csr/disease/hepatitis/whocdscsrlyo2003/en/index3.html. [Last accessed on 2012 Jul 15]. |
|3.||Paraboni ML, Sbeghen MD, Wolff FH, Moreira LB. Risk factors for infection with different hepatitis C virus genotypes in southern Brazil. Scientiﬁc World Journal 2012;2012:doi:10.1100/2012/946954. |
|4.||Mukhopadhya A. Hepatitis C in India. J Biosci 2008;33:465-73. |
|5.||Fried MW, Shiffman ML, Reddy KR, Smith C, Marinos G, Gonçales FL Jr, et al. Peginterferon alpha-2a plus ribavirin for chronic hepatitis C virus infection. N Engl J Med 2002;347:975-82. |
|6.||Hoofnagle JH. Course and outcome of hepatitis C. Hepatology 2002;36:S21-9. |
|7.||Panigrahi AK, Panda SK, Dixit RK, Rao KU, Acharya SK, Dasrathy S, et al. Magnitude of hepatitis C virus infection in India: Prevalence in healthy blood donors, acute and chronic liver disease. J Med Virol 1997;51:167-74. |
|8.||Mellor J, Holmes EC, Jarvis LM, Yap PL, Simmonds P. Investigation of the pattern of hepatitis C virus sequence diversity in different geographical regions: Implications for virus classification. The international HCV collaborative study group. J Gen Virol 1995;76:2493-507. |
|9.||Verma V, Chakravarti A. Comparision of 5′ noncoding-core region with 5′ noncoding region of HCV by RT PCR: Importance and clinical application. Curr Microbiol 2008;57:206-11. |
|10.||Martell M, Gomez J, Esteban JI, Sauleda S, Quer J, Cabot B, et al. High-throughput real-time reverse transcription-PCR quantitation of hepatitis C virus RNA. J Clin Microbiol 1999;37:327-32. |
|11.||Chinchai T, Labout J, Noppornpanth S, Theamboonlers A, Haagmans BL, Osterhaus AD, et al. Comparative study of different methods to genotype hepatitis C virus type 6 variants. J Virol Methods 2003;109:195-201. |
|12.||Sanger F, Nicklen S, Coulson AR. DNA sequencing with chain-terminating inhibitors. Proc Natl Acad Sci U S A 1977;74:5463-7. |
|13.||Makroo RN, Choudhury N, Jagannathan L, Parihar-Malhotra M, Raina V, Chaudhary RK, et al. Multicenter evaluation of individual donor nucleic acid testing (NAT) for simultaneous detection of human immunodeficiency virus -1 and hepatitis B and C viruses in Indian blood donors. Indian J Med Res 2008;127:140-7. |
|14.||Raghuraman S, Abraham P. HCV genotyping in India-Quo Vadis? Indian J Med Res 2004;119:9-11. |
|15.||Wilkins T, Malcolm JK, Raina D, Schade RR. Hepatitis C: Diagnosis and treatment. Am Fam Physician 2010;81:1351-7. |
|16.||Rosen HR. Clinical practice. Chronic hepatitis C infection. N Engl J Med 2011;364:2429-38. |
|17.||Hissar SS, Goyal A, Kumar M, Pandey C, Suneetha PV, Sood A, et al. Hepatitis C virus genotype 3 predominates in North and Central India and is associated with significant histopathologic liver disease. J Med Virol 2006;78:452-8. |
|18.||Valliammai T, Thyagarajan SP, Zuckelmam AJ, Harrison TJ. Diversity of genotype of hepatitis C virus in southern India. J Gen Virol 1995;76:711-6. |
|19.||Idrees M, Riazuddin S. Frequency distribution of hepatitis C virus genotypes in different regions of Pakistan and their possible routes of transmission. BMC Infect Dis 2008;8:69. |
|20.||Chakravarti A, Dogra G, Verma V, Srivastava AP. Distribution pattern of HCV genotypes and its association with viral load. Indian J Med Res 2011;133:326-31. |
|21.||Pujol FH, Loureiro CL. Replacement of hepatitis C virus genotype 1b by genotype 2 over a 10 year period in Venezuela. J Clin Gastroenterol 2007;41:518-20. |
|22.||Pang PS, Planet PJ, Glenn JS. The evolution of the major hepatitis C genotypes and correlates with clinical response to interferon therapy. PLoS One 2009;4:e6579. |
|23.||Dusheiko G, Schmilovitz-Weiss H, Brown D, McOmish F, Yap PL, Sherlock S, et al. Hepatitis C virus genotypes. An investigation of type specific differences in geographic origin and disease. Hepatology 1994;19:13-8. |
|24.||Pawlotsky JM, Bastie A, Pellet C, Remire J, Darthuy F, Wolfe L, et al. Significance of indeterminate third-generation hepatitis C virus recombinant immunoblot assay. J Clin Microbiol 1996;34:80-3. |
[Figure 1], [Figure 2]
[Table 1], [Table 2], [Table 3], [Table 4]
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