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 Table of Contents  
ORIGINAL ARTICLE
Year : 2020  |  Volume : 34  |  Issue : 2  |  Page : 81-85

Determination of hepatitis C viral load and human immunodeficiency virus 1 RNA viral load and their correlation with CD4 cell count in human immunodeficiency virus and hepatitis C virus coinfected patients attending a tertiary care hospital in Northeast India


1 Department of Microbiology, Regional Institute of Medical Sciences, Imphal, Manipur, India
2 Department of Medicine, Regional Institute of Medical Sciences, Imphal, Manipur, India

Date of Submission03-May-2020
Date of Decision15-Sep-2020
Date of Acceptance28-Oct-2020
Date of Web Publication25-Jan-2021

Correspondence Address:
Krossnunpuii
Department of Microbiology, Regional Institute of Medical Sciences, Imphal - 795 004, Manipur
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/jms.jms_33_20

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  Abstract 


Background: Human immunodeficiency virus (HIV)–hepatitis C virus (HCV) coinfection is common due to their shared routes of transmission. Coinfected persons have a higher mortality rate. Some investigators reported an inverse correlation between hepatitis C viral load and CD4 cell count, whereas others have found no such correlation.
Objectives: The objectives of the study were to determine hepatitis C viral load, HIV1 RNA viral load, and CD4 cell count and to find the correlation between hepatitis C viral load, HIV1 RNA viral load, and CD4 cell count in HIV-HCV coinfected patients.
Materials and Methods: A cross-sectional study conducted in RIMS Hospital, Manipur, between September 2016 and August 2018 among 52 HIV and HCV coinfected patients. Hepatitis C viral load and HIV1 RNA viral load were measured using COBAS® TaqMan® HCV Test and COBAS® TaqMan® HIV-1 test, respectively. COBAS® TaqMan® 48 Analyzer was used for automated amplification and detection. BD fluorescent-activated cell sorter count machine was used for CD4 cell count.
Results: Majority of the subjects were male and in the age group of 15–49 years. The most common mode of infection was injecting drug use. There was a statistically insignificant weak negative correlation between hepatitis C viral load and HIV1 RNA viral load, hepatitis C viral load and CD4 cell count, and HIV1 RNA viral load and CD4 cell count.
Conclusion: This study found no correlation between hepatitis C viral load and CD4 cell count, HIV1 RNA viral load and hepatitis C viral load, and HIV1 RNA viral load and CD4 cell count. Along with the free antiretroviral therapy treatment made available, there is a need for strategies to rapidly diagnose HCV infection in HIV-HCV coinfected patients and enhance HCV treatment uptake so as to prevent HCV-related morbidity and mortality in these patients.

Keywords: CD4 cell count, correlation, hepatitis C viral load, human immunodeficiency virus 1 RNA viral load, Manipur


How to cite this article:
Krossnunpuii, Singh HR, Singh KB. Determination of hepatitis C viral load and human immunodeficiency virus 1 RNA viral load and their correlation with CD4 cell count in human immunodeficiency virus and hepatitis C virus coinfected patients attending a tertiary care hospital in Northeast India. J Med Soc 2020;34:81-5

How to cite this URL:
Krossnunpuii, Singh HR, Singh KB. Determination of hepatitis C viral load and human immunodeficiency virus 1 RNA viral load and their correlation with CD4 cell count in human immunodeficiency virus and hepatitis C virus coinfected patients attending a tertiary care hospital in Northeast India. J Med Soc [serial online] 2020 [cited 2021 Mar 2];34:81-5. Available from: https://www.jmedsoc.org/text.asp?2020/34/2/81/307901




  Introduction Top


Globally, an estimated 71 million people have chronic hepatitis C infection. The WHO estimated that in 2016, approximately 399,000 people died from hepatitis C.[1] In India, 12–18 million people are infected with hepatitis C.[2] The estimated prevalence of hepatitis C virus (HCV) infection in India is between 0.5% and 1.5%, with hotspots showing much higher prevalence in some areas of Northeast India, in some tribal populations and in certain parts of Punjab.[3]

Since the beginning of the epidemic, 76 million people have been infected with human immunodeficiency virus (HIV) and about 33 million people have died of HIV/AIDS.[4] Globally, 38.0 million (31.6–44.5 million) people were living with HIV at the end of 2019.[4] India currently harbors 21.40 lakhs HIV-infected patients.[5]

HIV-HCV coinfection is common due to their shared routes of transmission. The global estimate of the burden of HIV-HCV coinfection is 2.75 million, of whom 1.3 million are people who inject drugs (PWID).[6] HIV increases the rate of liver fibrosis (scarring) and progression to end-stage liver disease in patients with HCV infection.[7] The impact of HCV on the natural history of HIV disease is more controversial, with some studies showing an enhanced progression rate and others showing no effect, particularly when there is a response to highly active antiretroviral therapy (HAART).

The course of chronic HCV infection is accelerated in patients coinfected with HIV. Several studies reported that increased HCV RNA levels are found in patients coinfected with HIV and HCV.[8],[9] Some investigators reported an inverse correlation between hepatitis C viral load and CD4 cell count, whereas others have found no such correlation.[8],[10],[11],[12] Hence, the purpose of this study was to find the correlation between hepatitis C viral load, HIV1 RNA viral load, and CD4 cell count in HIV-HCV coinfected patients attending a tertiary care hospital in Northeast India.


  Materials and Methods Top


A cross-sectional study was conducted from September 2016 to August 2018.

Study population

Fifty-two HIV and HCV coinfected patients attending fluorescent-activated cell sorter (FACS) count Center, ICTC and Serology Section, Department of Microbiology and Antiretroviral Therapy (ART) Center, RIMS, Imphal. All the study subjects were on ART and patients on antiviral therapy for HCV infection were excluded from the study.

HCV and HIV1 RNA viral load testing was conducted at DBT-Healthcare Molecular Diagnostic Laboratory and CD4 count testing at FACS Count Center, Department of Microbiology, RIMS, Imphal.

Study tools

Hepatitis C viral load was measured using COBAS® TaqMan® HCV test and HIV1 RNA viral load using COBAS® TaqMan® HIV-1 test. COBAS® TaqMan® 48 Analyzer (Roche Molecular Systems, Inc., USA, 8/2005 version 2.0) was used for automated amplification and detection. CD4 cell count was measured by BD FACSCount system; model no.: 337842. (BD FACSCountTM CD4 reagents :Becton, Dickinson and Company, BD Biosciences, San Jose, CA, USA.)

Data analysis

Data were entered using IBM SPSS Statistics 21 for Windows (IBM Corp. 1995, 2012). The correlation between hepatitis C viral load, HIV1 RNA viral load, and CD4 cell count was determined by Pearson correlation test and P < 0.05 was taken as significant.

Consent

Informed written consent was obtained from all the subjects.

Ethical approval was obtained from the Research Ethics Board, RIMS, Imphal, before the conduct of the study and progress reports were submitted during the study.


  Results Top


In this study, of the total 52 HIV-HCV coinfected subjects, 47 (90.38%) were male and 5 (9.62%) were female. Forty-four of the patients were married and 8 of them were unmarried. Of the 44 married patients, 4 of them had HIV nonreactive spouse, while the spouses' status was unknown in 7 subjects. Based on the history of the participants, the most common route of acquiring HIV infection was injecting drug users (IDU) – 32 (61.54%), while 13 (25%) gave a history of both unprotected sex and IDU. Other routes of infection were blood transfusion and history of only unprotected sex with no history of IDU [Table 1].
Table 1: Gender distribution of different risk factors

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Maximum of them, i.e., 30 (57.8%), obtained high school level education. A higher number (53.8%) of the study population falls in the lower-middle (III) strata of the Kuppuswamy's Socioeconomic Status Scale.

Twenty-seven (51.9%) of the study subjects had their CD4 cell count in between 200 and 500 cells/μl, 21 (40.4%) of them had more than 500 cells/μl, and 4 (7.7%) had CD4 cell count below 200 cells/μl [Figure 1].
Figure 1: CD4 cell count

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Majority, 42 (80.8%), were asymptomatic. The most common symptom among the study subjects was generalized weakness. One of the study subjects had tuberculosis (TB) and under treatment. Three of the study subjects gave a past history of TB and were treated [Figure 2].
Figure 2: Clinical findings

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Of the 52 subjects examined, hepatitis C viral load was obtained in 35 subjects, HIV1 RNA viral load in 21 subjects, and CD4 cell count in all the 52 subjects. Common values for hepatitis C viral load, HIV1 RNA viral load, and CD4 cell count could be detected in 19 subjects only. Hence, hepatitis C viral load, HIV1 RNA viral load, and CD4 cell count mean values and standard deviation were calculated from these 19 subjects only [Table 2].
Table 2: Mean hepatitis C viral load, CD4 cell count, and human immunodeficiency virus viral load of the 19 cases

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  Discussion Top


In this study, of the total 52 HIV-HCV coinfected subjects, 47 (90.38%) were male and 5 (9.62%) were female. A higher number (53.8%) of the study population falls in the lower-middle (III) strata of the Kuppuswamy's Socioeconomic Status Scale. The findings in our study may be due to the practice of high-risk behaviors, lower level of prevention knowledge, and health assistance. Most of the cases in the study were unskilled workers or were unemployed which is in concordance with a study by Pal and Ojha where they found unskilled workers like farmers and unemployed were the most affected group.[13]

In this study, of the 44 married patients, 4 of them had HIV nonreactive spouse, while the spouses' status was unknown in 7 subjects. Effective HIV prevention interventions targeting discordant couples should focus on sustaining health education, increasing psychosocial support services, and increasing medication adherence monitoring.[14] Couple counseling about the risk of HIV transmission via unprotected sex and free condoms made available to these couples should reduce the risk of transmission.

Based on the history of the participants, the most common route of acquiring HIV infection was IDU which was exclusively seen among the males, while unprotected sex exposure was the only mode of transmission in the five female subjects and one male subject. The WHO estimated that 13 million IDUs exist in the world and 1.7 million of them are living with HIV and the estimated global prevalence of hepatitis C in PWID is 67%.[15] The essential transmission control strategies for IDUs which should minimize the transmission of HIV into the general population are through decreasing IDU, reducing sharing of injecting equipment, and promoting safe sex.[16],[17]

Ten of the patients had their HIV-HCV status known for long, i.e., 19.23% of them had HIV-HCV coinfection for more than 10 years, while maximum of them, i.e., 80.77% (42), had their HIV-HCV status known for <10 years at the time of the study. Majority of the patients, i.e., 36 (69.2%) of them, knew their HCV status within 1 year of knowing their HIV status, while 14 (26.9%) took more than 1 year to know their HCV status after knowing their HIV status and 2 of them knew their HCV status before their HIV status.

HIV-HCV coinfection complicated ART treatment of HIV infection, as several antiretroviral drugs are poorly tolerated by coinfected patients. It would be beneficial if all PWIDs who come for HIV testing are tested for HCV also at the same time. HCV-HIV coinfection among PWID in Manipur is very high, highlighting the urgent need for effective prevention, diagnosis, and treatment.

Correlation analysis was done between hepatitis C viral load and HIV1 RNA viral load of the 19 cases using SPSS and there was a statistically insignificant weak negative correlation (r = −0.175, P = 0.473). Daar et al. in their study found that hepatitis C viral load and HIV1 RNA viral load were directly related (P = 0.008).[18] Ragni and Bontempo demonstrated in their study that HCV/HIV coinfected hemophiliacs treated with HAART developed a persistent and significant increase in HCV viral load, which is temporally related to a persistent decrease in HIV viral load.[19]

The correlation analysis between hepatitis C viral load and CD4 cell count of the 19 cases found a statistically insignificant weak negative correlation (r = −0.200, P = 0.411). This finding is in concordance with a study done by Sherman et al. and Dragoni et al. (r = −0.23, P = 0.08).[20],[21] However, a study by Matthews-Greer et al. found a significant negative correlation between hepatitis C viral load and CD4 cell count in the coinfected group (r = −0.4, P < 0.05).[12]

There was a weak negative correlation between HIV1 RNA viral load and CD4 cell count, but it was statistically insignificant (r = −0.217, P = 0.372). This finding is in contrast to Dragoni et al. and Kannangai et al. where they found a significant inverse correlation between CD4 cell count and HIV1 RNA viral load (r = −0.37, P = 0.01 and r = −0.55, P < 0.01).[21],[22] However, our finding is in concordance with a study conducted by Bonacini et al. where they also found no significant correlation between hepatitis C viral load and with either HIV1 RNA viral load or CD4 cell count in coinfected patients.[23]

Several studies before the era of HAART showed no impact of HCV on HIV disease progression, while others suggested accelerated HIV disease progression. HIV-HCV coinfection complicated ART treatment of HIV infection, as several antiretroviral drugs are poorly tolerated by coinfected patients. Hepatotoxicity of ART drugs can be reduced after the successful treatment of chronic hepatitis C in coinfected patients. HCV treatment offers the possibility of eradicating HCV in a defined treatment period. This is potentially advantageous for the subsequent management of patient with HIV infection. Chronic hepatitis C infection has been associated with liver-related mortality in HIV-HCV coinfected patients in multiple settings. Persons coinfected with HIV-HCV have a higher mortality rate and higher rate of hospitalization than patients infected with HIV alone.

All the study subjects were on ART but none on antiviral therapy for HCV. Hence, in these circumstances, even though they are taking ART, they are still prone to opportunistic infections. Therefore, caution and alertness about immunity is indispensable among these coinfected groups to prevent disease progression and death. Further studies will be needed to see if HCV treatment leads to lower immune activation levels and rise in CD4 cell counts in these patients. Coinfection influence each other, may accelerate the clinical progress to both the diseases, and treatment success for one disease is undermined when the other is neglected and may even cause death of the patient.


  Conclusion Top


Uncertainties remain regarding the real effect of coinfection with HIV and HCV on the progression and outcomes of these viral infections. This study found no correlation between hepatitis C viral load and CD4 cell count, HIV1 RNA viral load and hepatitis C viral load, and HIV1 RNA viral load and CD4 cell count in HIV-HCV coinfected individuals.

There is an urgent need for more data and research findings on detailed disease burden, effect of coinfection on each other, their mechanisms as well as treatment responses. Along with the free ART treatment made available, there is a need for strategies to rapidly diagnose HCV infection in HIV-HCV coinfected patients and enhance HCV treatment uptake so as to prevent HCV-related morbidity and mortality in these patients.

Limitations

The real disease duration could not be estimated as this was a cross-sectional study. This study could not evaluate the effect of anti-HCV therapy outcome on the CD4 cell count as patients on antiviral therapy for HCV were exclusion criteria. The sample size was not big enough to represent the population in the study area.

Acknowledgment

The authors would like to thank DBT Nodal Cell, Tezpur University (Assam), Ministry of Science and Technology, Government of India, for their financial support under MD/MS Thesis Award Phase -11 & 12 (2016-2017 ) from DBT Nodal Cell, Tezpur University (Assam), Ministry of Science and Technology, Government of India, (Sanction No: BT/Med/15/Vision NER/2011, dated: November 2, 2011; Memo No: TU/DBT NC/MD/MS/P11 12/299 dated 27/03/2018), all the individuals who participated in this study and all the staffs of CD4 count centre and DBT Molecular Diagnostic Laboratory, Department of Microbiology, RIMS, Imphal, Manipur, India for their cooperation and technical assistance during the study.

Financial support and sponsorship

Financial support received under MD/MS Thesis Award Phase -11 & 12 (2016-2017 ) from DBT Nodal Cell, Tezpur University (Assam), Ministry of Science and Technology, Government of India, (Sanction No: BT/Med/15/Vision NER/2011, dated: November 2, 2011; Memo No: TU/DBT NC/MD/MS/P11 12/299 dated 27/03/2018).

Conflicts of interest

There are no conflicts of interest.



 
  References Top

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