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| ORIGINAL ARTICLE |
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| Year : 2017 | Volume
: 35
| Issue : 4 | Page : 563-567 |
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Seroprevalence, risk factors and genotype distribution for Hepatitis C infection: A study from rural hospital in Maharashtra
Satish Ramchandrra Patil1, Kailash D Datkhile2, MV Ghorpade1, Supriya Satish Patil3, Satish V Kakade3
1 Department of Microbiology, Krishna Institute of Medical Sciences, Karad, Maharashtra, India
2 Department of Molecular Biology and Genetics, Krishna Institute of Medical Sciences, Karad, Maharashtra, India
3 Department of Community Medicine, Krishna Institute of Medical Sciences, Karad, Maharashtra, India
| Date of Web Publication | 1-Feb-2018 |
Correspondence Address:
Dr. Satish Ramchandrra Patil
Department of Microbiology, Krishna Institute of Medical Sciences, Karad - 415 110, Maharashtra
India
 Source of Support: None, Conflict of Interest: None  | Check |
DOI: 10.4103/ijmm.IJMM_16_96
Background and Objectives: Hepatitis C is global health problem affecting a significant portion of the world's population. Available data in Western Maharashtra on seroprevalence, risk factors and genotype distribution are very limited. Objectives: The present study was carried out to estimate the seroprevalence, factors influencing transmission and distribution of genotype of hepatitis C virus (HCV) in a hospital-based population. Materials and Methods: This was a cross-sectional, hospital-based study. A total of 25193 serum samples were tested for HCV and HBV infection. All samples from HCV antibody-positive patients were subjected for HCV RNA detection and genotype. Chi-square, unpaired t-test, logistic regression analysis was used for statistical analysis. Results: The seroprevalence for anti-HCV-Ab was 0.46%. Backward multivariate logistic regression analysis revealed increasing age; alcoholic, blood transfusion and dialysis were significant risk factors. Of 116 patients with HCV, 8 (6.89%) patients had HCV-HBV co-infection. The most common genotype (61.90%) was 3 followed by Genotype 1 (38.09%). Conclusions: In the present study, significant risk factors were a history of blood transfusion, habit of alcohol, dialysis. The prevention of HCV infection can be achieved by screening of blood and blood products and creating awareness about risk factors. Since the efficacy of current and new therapies differ by genotype, genotype study is essential.
Keywords: Genotype, hepatitis C virus, risk factors, seroprevalence
How to cite this article:
Patil SR, Datkhile KD, Ghorpade M V, Patil SS, Kakade SV. Seroprevalence, risk factors and genotype distribution for Hepatitis C infection: A study from rural hospital in Maharashtra. Indian J Med Microbiol 2017;35:563-7 |
How to cite this URL:
Patil SR, Datkhile KD, Ghorpade M V, Patil SS, Kakade SV. Seroprevalence, risk factors and genotype distribution for Hepatitis C infection: A study from rural hospital in Maharashtra. Indian J Med Microbiol [serial online] 2017 [cited 2021 Jan 26];35:563-7. Available from: https://www.ijmm.org/text.asp?2017/35/4/563/224416 |
| ~ Introduction | |  |
Hepatitis C is global health problem affecting a significant portion of the world's population. Every year, 3–4 million people are infected with the hepatitis C virus (HCV). About 150 million people are chronically infected and at risk of developing liver cirrhosis and/or liver cancer. HCV is one of the silent killer diseases which are spreading undetected.[1]
Hepatitis C is an emerging infection in India and is already responsible for a significant proportion of liver disease in various states. However, the prevalence appears to be highly variable (patchy), according to the geographical site or the population group analysed (0.09%–7.89%). Most of the studies of prevalence have been conducted in blood banks.[2] Blood donor groups are usually young adults, and the majority are males, hence seroprevalence in other age groups such as children, aged and in females cannot be estimated.
Knowledge of the distribution of HCV genotypes has important clinical implications since the efficacy of current and new therapies differ by genotype. In India, Lole et al.[3] showed that the infection with Genotype 3 was predominant in North, West and East Indian population, whereas Genotype 1 was shown to be the predominant genotype in South India.
A tertiary care hospital catering to the needs of a large population represents an important centre for the serological survey. The present study was carried out to estimate the seroprevalence, factors influencing transmission and distribution of genotype of HCV in a hospital-based population.
| ~ Materials and Methods | | |
A cross-sectional, hospital-based study was carried out in tertiary care hospital from rural Maharashtra. The sample size was determined using the formula:
The maximum of minimum sample sizes was 19112. A total of 25193 serum samples were tested for HCV and HBV infection from the patients who registered at the outpatient departments or were admitted to the tertiary care hospital and were advised to undergo HCV antibody testing and HBV surface antigen testing during March 2010 to September 2012. Informed consent was obtained from these patients. This study was approved by the Institutional Ethical Committee.
Hepatitis C virus ELISA
Qualisa HCV (Qualpro Diagnostics) third generation ELISA was used for the detection of HCV antibodies.
Hepatitis B surface antigen (HBsAg)-ErbaLisa
For hepatitis B surface antigen (HBsAg), we used ErbaLisa Hepatitis B (Transasia Bio-Medicals Ltd), and the tests were performed as per the manufacturer's instructions.
Qualitative reverse transcription polymerase chain reaction for hepatitis C virus RNA and hepatitis C virus genotyping
All samples from HCV antibody-positive patients were subjected for HCV RNA detection. HCV viral RNA was extracted from 200 μL of serum samples of patients using Trizol reagent method for RNA isolation as per the manufacturer's instructions (Sigma-Aldrich). Reverse transcription-polymerase chain reaction (PCR) was used to detect HCV RNA. cDNA synthesis was carried out with the help of 3B BIOHCV kit by 3B BlackBio Biotech India. cDNA was transcribed using specific outer antisense primers from highly conserved 5' Non-coding Region (JENS1-5' ACT GTC TTC ACG CAG AAA GCG TCT AGC CAT-3' and JENS2-5' CGA GAC CTC CCG GGG CAC TCG CAA GCA CCC-3') in the reverse transcription reaction mixture.[4]
Direct PCR for first amplification reaction was performed in the reaction mixture containing 1X PCR buffer, 200 μmol/μl dNTPs, 1 U Taq DNA polymerase (Bangalore GeNei) and 10 pmol primers JENS1 and JENS2 in a total reaction volume of 50 μl along with cDNA.
Nested PCR was performed in the reaction mixture containing 1X PCR buffer, 200 μmol/μl dNTPs, 10 pmol primers JENS3 (5'ACG CAG AAA GCG TCT AGC CAT GGC GTT AGT 3') and JENS4 (5' TCC CGG GGC ACT CGC AAG CAC CCT ATC AGG 3'). The final amplified PCR products obtained after each round of Nested PCR were subjected to agarose gel electrophoresis. The nested PCR product purified by PCR purification kit (Thermo Scientific) was used for DNA sequencing. A total of 21 samples were genotyped using PCR followed by DNA sequencing which was carried out using ABI PRISM 310 Analyzer (Anshul Biotechnologies, Bengaluru). The phylogenetic analysis of derived nucleotide sequences was performed using NCBI/BLAST network service.
Data were analysed using SPSS-20 version. Univariate analysis was carried out using Chi-square test and unpaired t-test. Variables showing significance that is P < 0.05 were included to carry step-wise logistic regression analysis.
| ~ Results | | |
A total of 25193 serum samples were tested for hepatitis C antibodies. Out of that 116, 0.46% (95% confidence interval [CI]: 0.45–0.46) samples showed the presence of anti-HCV-Ab. The seroprevalence was 0.45% (95% CI: 0.44–0.45); 0.47% (95% CI: 0.46–0.47) and 0.46% (95% CI: 0.45–0.46) in 2010, 2011 and 2012, respectively.
Out of total 25193 patients, 9394 (37.3%) were male and 15799 (62.7%) were female. The seroprevalence for anti-HCV-Ab was higher in males 0.67% as compared to females 0.33% and the difference was statistically significant (χ2 = 14.440; df = 1; P < 0.001). The highest seroprevalence 1.12% was found to be among 41–50 years age group. Among males, seroprevalence was higher 1.10% in > 61 years age group, and among females, it was higher (1.31%) in 41–50 years age group. Low seroprevalence (0.28%) was reported in children (<14 yrs) and 15–30 years age group [Table 1]. The age group-wise difference in seroprevalence was statistically significant (χ2 = 22.550; df = 5; P < 0.001). The mean age (41.89 ± 18.38) of anti-HCV-Ab-positive patient was significantly higher than the mean age (34.11 ± 17.53) of anti-HCV-Ab-negative patient (t = 4.765; P < 0.001). | Table 1: Age and sex distribution of hospital-based population with anti-hepatitis C virus antibody seropositivity
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The prevalence of hepatitis C infection was significantly higher in patients with a history of blood transfusion; for shaving habit that is going to barber is (borderline significance), tattooing, skin and ear piercing, history of dialysis, habit of alcohol and occupation (P < 0.05), whereas the prevalence of hepatitis C infection was not found to be significantly associated with education and habit of tobacco (P > 0.05). Backward multivariate logistic regression (MLR) analysis revealed increasing age; alcoholic, blood transfusion and dialysis were significantly associated with HCV positivity [Table 2]. The MLR model with cut-off probability 0.0028 (i.e., ≥0.0028 indicates HCV positive and <0.0028 indicates HCV negative) could identify 71.8% correct results as compared to results of Elisa. In comparison to Elisa, correct identification of HCV positive by the MLR model was 71.6% (83 out of 116) while identification of HCV negative was 71.8% (18013 out of 25077). | Table 2: Multivariate logistic regression model predicting ‘hepatitis C virus positivity’
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In the present study, 116 (0.46%) were positive for anti-HCV-Ab and 473 (1.87%) were positive for HBsAg. Of 116 patients with HCV, 8 (6.89%) patients had HCV-HBV co-infection. The HCV antibody positive cases were 116, but the HCV-RNA was found in 21 cases [Figure 1]. The genotype studied of this 21 cases showed the most common Genotype 3 (61.90%) followed by Genotype 1 (38.09%). Further distribution of genotypes into different subtypes was shown in a phylogenic tree analysis [Figure 2]. The Genotype 3 was observed in 13 samples (61.90%) patients. Of these twenty-one, 12 showed subtype 3a (57.14), 1 had subtype 3b (4.76%) and 8 patients showed Genotype 1 (38.09%) where subtype 1a (19.04%) and 1b (19.04%). Genotype 2 was not seen in any of the patients as well as other genotypes such as type 4, 5 and 6 were not detected. The prevalence of HCV genotypes did not differ with age and sex. | Figure 1: Representative 2% agarose gel image showing screening of serum samples for the presence of hepatitis C virus RNA. Lane M (100 bp molecular weight marker), Lane 1: Positive control; Lane 2: Negative control, Lane 3, 4, 6, 7, 8 showing amplification of 285 bp fragment indicating hepatitis C virus-positive samples. Lane 5 and 9 showing negative samples
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 | Figure 2: Phylogenetic analysis of hepatitis C virus isolates based on the nucleotide sequence obtained after DNA sequencing
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All sample sequences and reference sequences reported in GenBank were aligned manually considering the secondary structures present in the 5'-UTR. Aligned sequences were subjected to construct phylogenetic tree followed by bootstrapping analysis. Unrooted neighbour-joining tree [Figure 2] showed the presence of clades 1–7 as separate genetic lineages. This leads to a phylogenetic appearance, in which each major branch (genotype) divides into multiple new branches (subtypes) at a similar time in evolutionary history.
| ~ Discussion | | |
The seroprevalence of anti HCV-Ab among hospital-based population was found to be 0.46% while seroprevalence in the year 2010 was 0.45%; 0.47%, 0.46% in the year 2011 and 2012, respectively. This seroprevalence is much similar to the seroprevalence reported in an earlier study from Jaipur (Rajasthan) carried out in 2010 which was 0.28%.[5] Another study which was carried out in Mangalore, Karnataka, reported seroprevalence of 0.2%.[6] The seroprevalence reported in this study is much lower than another hospital-based study carried out in Jaipur (Rajasthan) over two years.[7] A rural survey from Maharashtra involving more than 1000 villagers showed a very low prevalence rate of HCV infection of 0.09% only.[8] The most systematic population-based study from West Bengal reported the prevalence of 0.87%.[9]
In a hospital-based study from South India; seroprevalence was 4.8%.[10] In a study carried out in Cuttack, Orissa, found seroprevalence rate of 1.57% in total and 2.12% from healthy voluntary blood donors.[11]
The seroprevalence of hepatitis C among general population is 3% to 7% in different parts of Pakistan.[12] The prevalence was 5.9% in hospital-based study done in Mauritius [13] and in Ethiopia, 6% of patients attending a clinic for neurologic disorder-tested positive for anti-HCV.[14] The seroprevalence of HCV has a considerable geographical variation, which may be explained by different distributions and different contributions of risk factors in different study regions.
In the present study, seroprevalence was significantly higher 0.67% in males than females 0.33% [Table 1]. Several other studies have reported that the prevalence was higher in males than females.[5],[6],[7] A study from South India reported that there was no statistically significant difference in the exposure rates of males and females.[10]
The highest seroprevalence 1.12% was found to be among the age group 41–50 years [Table 1]. The maximum proportion of seropositive individuals were seen in the higher age groups, 70.38% of seropositive individuals were above 35 years of age, 18.05% were between 12 and 35 years and 5.55% were under 12 years of age.[7] The earlier study carried out in this part reported the highest seroprevalence 1.5% in the age group of 41–50 years.[15] The prevalence seems to increase with age either because of the continuing risks of exposure or due to a cohort effect, with a decline in risk in recent times.[10] In a West Bengal study, maximal prevalence was in the older age group >60 years 1.5% as opposed to the lowest prevalence in the age group <10 years 0.31%.[9]
Backward MLR analysis revealed increasing age; alcoholic, blood transfusion and dialysis were significantly associated with HCV positivity [Table 2]. Using MLR model, we can identify patients who are at risk of HCV infection. In a study carried out at Mardan hospital-based study, the significant risk factors were reused syringes, blood recipients, dental procedures and surgical operations.[16] Another study reported high anti-HCV positivity rate in dialysis patients.[17]
In the present study of 116 patients with HCV, 8 (6.89%) patients had HCV-HBV co-infection. This was similar to the findings of a study in Manipur.[18] Sharma et al.[7] reported that 5.5% of all the positive samples were also positive for HBsAg.
In the present study, the most common genotype was 3 (61.90%); followed by Genotype 1 (38.09%). Our study findings correspond to other Indian studies. HCV genotypes predominant in India are Genotypes 3 and 1, constituting approximately 60 and 30% of the six genotypes, respectively. Genotype 4 constitutes about 4%, the remaining genotypes contributing to <2% each.[19] HCV Types 1a, 1b, 2a, 3a, 3b and 3 g have been identified in the earlier studies from Northern and Western India.[20],[21] Study on samples from many parts of India also found high prevalence of Genotype 3.[21]
As there is no vaccine available for HCV, the prevention of HCV infection can be achieved by screening of blood and blood products, avoiding sharing of needles or injecting equipment. Effectiveness of treatment depends on genotype, so further genotype studies are necessary for proper treatment of the diagnosed patients.
| ~ Conclusion | | |
As there is no vaccine available for HCV, the prevention of HCV infection can be achieved by screening of blood and blood products, avoiding sharing of needles or injecting equipment. Effectiveness of treatment depends on genotype, so further genotype studies are necessary for proper treatment of the diagnosed patients.
Financial support and sponsorship
Nil.
Conflicts of interest
There are no conflicts of interest.
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[Figure 1], [Figure 2]
[Table 1], [Table 2]
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