Research Article
ISSN: 2475 3432

Cellular and Molecular Profiling of Hepatitis C Virus (HCV) and to Study its Genotypic Heterogeneity in Clinical Isolates

Vijay Kumar1&2, Narotam Sharma*1, Dalel Singh2, Satish Chandra Nautiyal1, Baljeet Singh3
1Central Molecular Research Laboratory, Shri Guru Ram Rai Institute of Medical and Health Sciences, SGRR University, Dehradun, Uttarakhand, India
2OPJS University, Churu, Rajasthan, India
3Department of Microbiology, Kurukshetra University, Kurukshetra, Haryana, India
Corresponding author: Narotam Sharma
Scientist, Central Molecular Research Laboratory, Shri Guru Ram Rai Institute of Medical and Health Sciences, SGRR University, Dehradun 248001(Uttarakhand), India.E-mail: sharmanarotam5@gmail.com
Received Date: June 18, 2018 Accepted Date: July 12, 2018 Published Date: August 21, 2018
Citation: Narotam Sharma et al. (2018), Cellular and Molecular Profiling of Hepatitis C Virus (HCV) and to Study its Genotypic Heterogeneity in Clinical Isolates. Int J Biotech & Bioeng. 4:6, 119-123.
Copyright: ©2018 Narotam Sharma et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited


The distribution of HCV genotypes vary according to the geographical region. Genotypes 1-3 are widely distributed throughout the world. The outcome of HCV genotyping is of almost clinical value. Current research work was carried out to study the Cellular and Molecular profiling of Hepatitis C Virus (HCV) and its clinical importance that includes the correlation of the different laboratory parameters with respect to HCV RNA Viral load and its genotypes. 94 EDTA blood samples were collected from HCV reactive patients and further processed for cellular and molecular profiling. Out of 94 HCV RNA quantified, 42 (44.6%) were TND, 52(55.4%) with HCV RNA viral load >34 IU/ml. HCV genotype 3 came in 21 (65.62%) cases followed by HCV genotype 1a with 4 (12.5%) and 6 with 3(9.37%) and 1b with 2 with 6.25%. SGOT, SGPT, Alkaline phosphatase, Bilirubin and Globulin was elevated in 28 (62%), 22(48.88%), 23 (51.11%), 12(26.66%) and 20(44.44%) respectively. Maximum number of cases with HCV RNA Viral load was found in the 1.00 X 104 -1.00 X 107 IU/ml range with 27 cases. The HCV genotype 3 is one of the most replicating virus known to damage hepatic cells & thus requires proper line of treatment thoroughly during the diagnosis. Thus, the area of molecular testing for the diagnosis and management of HCV infection has shown steady improvement in technology and standardization. Further to say, development of proper algorithm by combining the profiling of cellular, molecular and Biochemical studies can be a new era for the proper management of this virus.

Keywords:  Hepatocellular carcinoma, Real Time PCR, Viral load, Genotyping, Reverse transcription




Introduction


Viral hepatitis has developed as a major public health problem throughout the world affecting several hundreds of millions of people (1-7). Viral hepatitis is a cause of substantial morbidity and mortality in the human population, both from acute infection and chronic sequel that include, in the case of hepatitis B, C and D, chronic active hepatitis and cirrhosis (8,9). Hepatocellular carcinoma, which is one of the ten most common cancers worldwide, is closely associated with hepatitis B, and at least in some regions of the world with hepatitis C virus (10-13). There are very few studies on the clinical co-relation of HCV RNA viral load and its implications on other affected organs of the body, as well as the impact of different HCV Genotype/s for the proper management of the patients from the northern parts of India (14-17). Thus, the current research work was carried out to study the Cellular and Molecular profiling of Hepatitis C Virus (HCV) and its clinical importance that includes the correlation of the different laboratory parameters with respect to HCV RNA Viral load and its genotypes.

Materials and Methods


94 EDTA blood samples were collected from HCV reactive patients from different departments of Shri Mahant Indiresh Hospital, Dehradun, Uttarakhand, India, which includes OPDs and IPDs of Gastroenterology, Medicine, Gynecology, Pediatrics, Tuberculosis and Chest and Surgery. The serum was separated from all of the 94 samples and RNA was extracted using Qiagen QIAamp Viral RNA mini kit (cat. No. 52904), Germany. Extracted RNA was further utilized as template for HCV RNA quantification, which was quantified by the utilization of Rotor Gene Q 5 Plex Real Time PCR machine. For all the 94 clinical samples, the viral load was estimated. Further, for the same master mix was prepared for the quantification of HCV RNA by the usage of Artus Amplification Kit from Qiagen (catalog no. 4518263). The Hepatitis C Virus RG Master A and B reagents and enzymes were utilized for the reverse transcription and specific amplification of a 240 bp region of 5’-3’ untranslated region [UTR] of HCV genome. HCV RNA was quantified within the range of 34 IU/ml to 1.00×108IU/ml (as depicted in Table 2). HCV genotyping characterization was done with the usage of Real Time PCR technology utilizing Hepatitis C Virus Genotype Diagnostic Kit (PCR-Fluorescence Probing) from Sansure, Korea, Biotech kit (Reference Number S3034E). This diagnostic protocol uses magnetic bead technology to extract HCV-RNA from serum. By applying one-step RT-PCR technology, the kit uses several specific pairs of HCV primers to target conserved regions of different HCV genotypes, including genotypes 1b, 1, 2, 3, 4, 5 and 6, as well as Taqman fluorescence probes to achieve genotyping detection of HCV RNA through fluorescent signal changes.

Results

Out of 94 HCV RNA quantified, 42 (44.6%) cases came with target not detected and 52(55.4%) were with HCV RNA viral load >34 IU/ml. Further the cases greater than or equal to 34 IU/ml (Table 3) with HCV RNA viral load greater than 500 IU/ml were considered for the HCV genotyping. 32 cases were considered for HCV genotyping because the HCV RNA viral load was above 500 IU/ml. Out of 32 cases, subjected for HCV genotyping, HCV genotype 3 was the most prevalent which came in 21 (65.62%) cases followed by HCV genotype 1a with 4 (12.5%) cases followed by HCV genotype 6 with 3(9.37%) cases followed by HCV genotype 1b with 2 (6.25%). In 3.12% cases HCV genotype 2 and 4 came (table 2). Biochemical investigation was done for 86 cases including SGOT, SGPT, Alkaline Phosphatase, albumin and globulin with high HCV RNA viral load (>34 IU/ml) and with cases in which target was not detected. It was observed that out of 45 cases where the HCV RNA viral load was >34 IU/ml, parameters SGOT, SGPT, Alkaline phosphatase, Bilirubin and Globulin was elevated in 28 (62%), 22(48.88%), 23 (51.11%), 12(26.66%) and 20(44.44%) respectively. When studied gender wise prevalence of HCV viral infections both the gender came with nearly equal proportion with 47.3% for male and 66.6% for female (Table 1)

ijbb Digital images
Table 1: Age wise distribution of Hepatitis C Viral infection.

It was also analyzed that the age group 21-40 and 41-60 years of age were with high HCV RNA viral load with 56.25% and 52.4% cases respectively. HCV genotype and subtype were studied in different spectrum of HCV RNA viral titer ranging from 1.00x103 10/ml to 1.00x108 10/ml. It was seen that maximum number of cases with HCV RNA Viral load in different ranges was found in the 1.00 X 104 -1.00 X 107 IU/ml range (table 2).

ijbb Digital images
Table 2:Spectrum of HCV RNA viral load w.r.t. its genotype/s detected.

In this range a total of 27 cases were there where in the same range HCV genotype 3 was the most prevalent which was found in 17 cases out of 27 cases considered for the same, followed by HCV genotype 1a and 6 with 3 cases each (tabulated in table 12). Present study reveals about the co- relation of different HCV RNA viral load w.r.t to biochemical profiling. Out of 86 cases considered for comparative evaluation of Molecular and Biochemical, profiling it was seen that in 45 cases, HCV RNA viral load was ≥ 34 IU/ml, whereas 41 cases came with target not detected. It was analyzed that out of 45 cases where HCV RNA was detected, SGOT, SGPT, AP, Bilirubin and Globulin was raised in 28 (62.22%), 22 (48.88%), 23 (51.11%),12 (26.66%) and 20(44.44%) respectively. In 41 cases, target was not detected, but SGOT, SGPT, AP, Bilirubin and Globulin was elevated in 12 (29.26%), 7 (17.07%), 11(24.44%), 10(24.39%) and 7(17.07%) cases respectively (table 3).

ijbb Digital images
Table 3: Comparative results interpretation for biochemical investigations and HCV RNA viral load. 1SGOT= Serum glutamic oxaloacetic transaminase
2SGPT= Serum glutamic pyruvic transaminase
3AP = Alkaline phosphatase

Discussion


According to the WHO, there are 180 million people affected with HCV worldwide and about 12.5 million carriers in India (18, 19). Hepatocellular carcinoma accounts for 85 to 90% of the cases of primary liver cancer. Chronic hepatitis and cirrhosis constitute the major preneoplastic conditions in the majority of HCC. The risk of developing HCC for a patient with HCV-related cirrhosis is approximately 2-6% per year (20, 21). HCC risk increases to 17-fold in HCV-infected patients compared to HCV-negative subjects. In general, HCC develops only after two or more decades of HCV infection and the increased risk is restricted largely to patients with cirrhosis or advanced fibrosis. HCV Quantification & Genotypes is known to have a distinct pattern of geographic distribution. The genotype/s determination depends based on target-conserved region in the genome of HCV. This study used a quantitative assay to measure virus load in individuals infected with different HCV genotypes. Real time PCR remains to date the most reproducible and sensitive technique to track the putative presence of virions, passively absorbed or replicating, in cells. Present study reveals that out of total 94 clinical samples, processed 52(55.4%) cases were with HCV RNA high viral load and 42(44.6) cases were with target not detected. The study is very relevant for the proper management of the patients infected with HCV and undergoing treatment. As the HCV RNA, viral loads will be responsible for the monitoring of the therapy provided by the clinicians. Increase, decrease as well as no change in HCV RNA viral load is also essential for studying further the drug resistance, susceptibility pattern in HCV infected patients.

The high viral load cases must be further processed for genotyping. Knowing the viral load before starting treatment is useful because patients with “high” viral loads can have a difficult time getting the virus to become completely undetectable on treatment. Target not detected are the cases were the hepatitis C virus is present in the bloodstream, but at a very low level, too low to be measured by a quantitative test. Unlike the flu virus, which has an incubation period of less than a week, incubation for chronic HCV can take between 14 to 180 days. The incubation for acute hepatitis C is typically about six to 10 weeks. The incubation period of HCV differs from that of other types of hepatitis. Viral infection may also be depending on the age of an individual and its immunity. Cases with 41-60 years of age group in the present study were mostly affected with HCV infection, having maximum number of HCV RNA high viral load with 42 cases. This might be due to repeatedly being exposed to infected blood. The age group of 0-20 years were least susceptible with 3 cases positive for HCV infection. This may be due to protective antibody titer against HCV due to vaccination in early age. Accretion of nucleotide switch in the HCV genome results in diversification and evolution into different genotypes. Differences among HCV genotypes in geographic distributions have provided investigators with epidemiologic markers that can be used to find the source of HCV infection in a given population & for further prognosis.

This assay enabled us to detect 6 HCV genotype (1a, 1b, 2, 3, 4, 5, 6). However, HCV genotype 3 was most frequently detected. HCV genotype 3 is also the most common genotype in India and Pakistan. HCV genotype 3 contributes to the development of steatosis (fatty liver disease) and insulin resistance, both of which can directly influence HCV disease progression including cirrhosis and liver cancer. This may also contribute to the risk of liver failure. There is evidence to suggest that people with this genotype experience a faster rate of fibrosis progression. This means that the liver tissue may thicken and scar faster than that of someone with a different genotype. Our study were also with maximum number of cases with HCV RNA viral load >500 IU/ml with HCV genotype 3, which was found in 65.62% patients. Thus, the genomic composition of the HCV and its difference in genetic expression can play an important role for the management of the patients affected by this lethal virus. HCV genotype 1a is the other genotype common. Study revealed that the prevalence of genotype 1a in HCC patients was significantly higher than in chronic hepatitis and liver cirrhosis patients. Multiple logistic regression analysis revealed that, after adjusting for age and serum HCV RNA levels, HCV genotype 1b infection was still a significant risk factor. However, there are conflicting reports on the relationship between the biochemical markers of inflammation alanine transaminase (ALT), histological degree of inflammation, and serum HCV-RNA levels by reverse transcription (RT)-PCR. In individuals with chronic hepatitis C, viral load and elevated serum ALT levels may have clinical relevance.

ALT is most concentrated in liver and released into the bloodstream as the result of liver injury. It, therefore, serves as a fairly specific indicator of liver status. SGOT is normally found in a diversity of tissues including liver, heart, muscle, kidney, and brain. It is released into serum when any one of these tissues is damaged. It is, therefore, not a highly specific indicator of liver injury. The present study revealed that SGOT levels varied significantly among the three groups of HCV genotypes. All other biochemical parameters were deranged but changes remained non-significant as also reported earlier. A low globulin level in patients with hepatitis C can be a sign of cirrhosis (advanced liver disease). Globulin levels can go up and down slightly. Very low globulin levels can cause symptoms of edema, or fluid accumulation, in the abdomen (called ascites) or in the leg. Low levels of total protein in the blood can occur because of impaired function of the liver.

A high alkaline phosphatase level does not reflect liver damage or inflammation. A high alkaline phosphatase level occurs when there is a blockage of flow in the biliary tract or a buildup of pressure in the liver--often caused by a gallstone or scarring in the bile ducts. The level of SGOT, SGPT, Alkaline phosphatase, Bilirubin and Globulin are found maximum in high HCV RNA viral load cases in comparison to target not detected in the current study.

Conclusion

The distribution of HCV genotypes vary according to the geographical region. Genotypes 1-3 are widely distributed throughout the world. The outcome of HCV genotyping is of almost clinical value as there are various regimens were available to treat different types of HCV genotypes like Simeprevir, Sofosbuvir etc for genotype 1. Sofosbuvir/R for genotype 2 & Sofosbuvir/R for genotype 3. But as we conclude the most common regimen to treat the HCV infection for all genotypes was Sofosbuvir, interferons, Ribavirin, Viramidine etc. These are various alternative therapies also available to treat Hepatitis C infection like Milk Thistle, Green tea extract, Glycyrrhizin but currently there is no vaccine available to prevent the Hepatitis C infection. The HCV genotype 3 is one of the most replicating virus known to damage hepatic cells & thus requires proper line of treatment thoroughly during the diagnosis. Thus, the area of molecular testing for the diagnosis and management of HCV infection has shown steady improvement in technology and standardization. Further to say, development of proper algorithm by combining the profiling of cellular, molecular and Biochemical studies can be a new era for the proper management of this virus.

Acknowledgment


The authors are grateful to Honorable Chairman, Shri Guru Ram Rai Education Mission for his kind support and guidance.

Conflict of interest:

None

References:

  1. Gubler, Duane J (2002). “The global emergence/resurgence of arboviral diseases as public health problems.” Archives of medical research33, no. 4: 330-342.
  2. Alberti, Alfredo, Luisa Benvegnù, Silvia Boccato, Roberta Pistis, Alessia Ferrari, and Giada Sebastiani (2004). “Natural history of hepatitis C and prognostic factors of disease progression.” In Conference on the Management of patients with viral hepatitis, pp. 35-46.
  3. Alter, Miriam J (2002). “Prevention of spread of hepatitis C.” Hepatology36, no. 5B.
  4. Bendinelli, Mauro, Mauro Pistello, Fabrizio Maggi, Claudia Fornai, Giulia Freer, and Maria Linda Vatteroni (2001). “Molecular properties, biology, and clinical implications of TT virus, a recently identified widespread infectious agent of humans.” Clinical microbiology reviews14, no. 1 : 98-113
  5. Banerjee, D., and K. R. Reddy (2016). “Review article: safety and tolerability of direct‐acting anti‐viral agents in the new era of hepatitis C therapy.” Alimentary pharmacology & therapeutics43, no. 6 : 674-696
  6. Bartenschlager, Ralf, Michael Frese, and Thomas Pietschmann (2004). “Novel insights into hepatitis C virus replication and persistence.” Advances in virus research63: 71-180.
  7. Cannalire, Rolando, Maria Letizia Barreca, Giuseppe Manfroni, and Violetta Cecchetti (2015). “A journey around the medicinal chemistry of hepatitis C virus inhibitors targeting NS4B: from target to preclinical drug candidates.” Journal of medicinal chemistry59, no. 1: 16-41.
  8. Cartwright, Lisa (2013). “How to Have Social Media in an Invisible Pandemic1.” The International Encyclopedia of Media Studies.
  9. Chen, Jizheng, Yang Zhao, Chao Zhang, Hairong Chen, Jin Feng, Xiumei Chi, Yu Pan et al (2014). “Persistent hepatitis C virus infections and hepatopathological manifestations in immune-competent humanized mice.” Cell research24, no. 9: 1050-1066.
  10. Cooper, S., A.L. Erickson, E.J. Adams, J. Kansopon, A.J. Weiner, D.Y. Chien, M. Houghton, P. Parham, and C.M. Walker. (1999). Analysis of a successful immune response against hepatitis C virus. Immunity.10:439–449.
  11. Csete, Joanne, Adeeba Kamarulzaman, Michel Kazatchkine, Frederick Altice, Marek Balicki, Julia Buxton, Javier Cepeda et al (2016). “Public Health and International Drug Policy: Report of the Johns Hopkins–Lancet Commission on Drug Policy and Health.” Lancet (London, England)387, no. 10026: 1427.
  12. Degenhardt, Louisa, Amanda J. Baxter, Yong Yi Lee, Wayne Hall, Grant E. Sara, Nicole Johns, Abraham Flaxman, Harvey A. Whiteford, and Theo Vos (2014). “The global epidemiology and burden of psychostimulant dependence: findings from the Global Burden of Disease Study 2010.” Drug and Alcohol Dependence137: 36-47.
  13. D.B. Smith, J. Bukh, C. Kuiken, et al., (2014). Expanded classification of hepatitis C virus into 7 genotypes and 67 subtypes: updated criteria and genotype assignment web resource Hepatology, 59, pp. 318–327
  14. Hussain, Zahid. “Genomic Heterogeneity of Hepatitis Viruses (AE): Role in Clinical Implications and Treatment.” In Practical Management of Chronic Viral Hepatitis. InTech, 2013.Fattahi, Mohammadreza, Abdorrasoul Malekpour, Mojtaba Mortazavi, Alireza Safarpour, and Nasrin Naseri (2014). “The characteristics of rare codon clusters in the genome and proteins of hepatitis C virus; a bioinformatics look.” Middle East journal of digestive diseases6, no. 4: 214.
  15. Graham, Camilla S., and Tracy Swan (2015). “A path to eradication of hepatitis C in low-and middle-income countries.” Antiviral research119: 89-96.
  16. Kim, W. Ray (2002). “Global epidemiology and burden of hepatitis C.” Microbes and infection4, no. 12 : 1219-1225.
  17. Kopilović, B., M. Poljak, K. Seme, and I. Klavs (2015). “Hepatitis C virus infection among pregnant women in Slovenia: study on 31,849 samples obtained in four screening rounds during 1999, 2003, 2009 and 2013.” Romania., 10.
  18. Mindolli, Preeti B., and Manjunath P. Salmani. “Seroprevalence of Hepatitis C virus in a tertiary care centre in Vijaypur, Karnataka, India.” Int J Curr Microbiol App Sci 4 (2015): 956-5.
  19. Li, Hui-Chun, and Shih-Yen Lo (2015). “Hepatitis C virus: Virology, diagnosis and treatment.” World journal of hepatology7, no. 10 : 1377.
  20. Lieff, Susan, Kim A. Boggess, Amy P. Murtha, Heather Jared, Phoebus N. Madianos, Kevin Moss, James Beck, and Steven Offenbacher (2004). “The oral conditions and pregnancy study: periodontal status of a cohort of pregnant women.” Journal of periodontology75, no. 1 : 116-126.
  21. Lohmann, Volker, and Ralf Bartenschlager (2013). “On the History of Hepatitis C Virus Cell Culture Systems: Miniperspective.” Journal of medicinal chemistry57, no. 5 : 1627-1642.
  22. Madny, Ahmed G., and Adam A. Adam (2014). “Seroprevalence of Hepatitis C Virus among type 2 diabetes mellitus patients in blue nile state, Sudan.” American Journal of Research Communication N2 : 141-147.
  23. Martin, Natasha K., Peter Vickerman, Jason Grebely, Margaret Hellard, Sharon J. Hutchinson, Viviane D. Lima, Graham R. Foster et al., (2013). “Hepatitis C virus treatment for prevention among people who inject drugs: Modeling treatment scale‐up in the age of direct‐acting antivirals.” Hepatology58, no. 5 : 1598-1609
  24. Nouroz, Faisal, Sidra Shaheen, Ghulam Mujtaba, and Shumaila Noreen (2015). “An overview on hepatitis C virus genotypes and its control.” Egyptian Journal of Medical Human Genetics16, no. 4 : 291-298.
  25. Riaz, Saba, Muhammad Faisal Bashir, Saleem Haider, and Naeem Rahid (2016). “Association of genotypes with viral load and biochemical markers in HCV-infected Sindhi patients.” brazilian journal of microbiology47, no. 4 : 980-986
  26. Roller, Louis, and Jenny Gowan (2016). “Disease state management: Hepatitis and hepatitis C.” AJP: The Australian Journal of Pharmacy97, no. 1151 : 66.
  27. Vieyres, Gabrielle, Jean Dubuisson, and Thomas Pietschmann (2014). “Incorporation of hepatitis C virus E1 and E2 glycoproteins: the keystones on a peculiar virion.” Viruses6, no. 3: 1149-1187.
  28. Wantuck, J. M., A. Ahmed, and M. H. Nguyen (2014). “Review article: the epidemiology and therapy of chronic hepatitis C genotypes 4, 5 and 6.” Alimentary pharmacology & therapeutics39.2: 137-147.

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