Prevalence of HIV/HCV co-infection amongst HIV serodiscordant couples in Thika, Kenya

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PREVALENCE OF HIV/HCV CO-INFECTION AMONGST HIV SERODISCORDANT COUPLES IN THIKA, KENYA

SUSAN WAIRIMU WAWERU (B.Sc.) P150/21569/2010

A Thesis Submitted In Partial Fulfilment of the Requirement for the

Award of the Degree of Master of Science in Infectious Diseases

(Immunology) in the School of Medicine, Kenyatta University

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DECLARATION

This thesis is my original work and has not been presented for a degree in any other university or any other award.

Signature: __________________________ Date: _________________________ Susan Wairimu Waweru (P150/21569/2010)

Department of Medical Laboratory Sciences

SUPERVISORS

We confirm that the work reported in this thesis was carried out by the candidate under our supervision.

Signature: __________________________ Date: _________________________ Dr. Margaret Muturi

Department of Medical Laboratory Sciences Kenyatta University

Signature: __________________________ Date: _________________________ Dr. Kenneth Ngure

College of Health Sciences

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DEDICATION

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ACKNOWLEDGEMENT

I sincerely would like to thank my supervisors Dr. Margaret Muturi and Dr. Kenneth Ngure for their never ending patience and their huge input to making this thesis complete. I would also like to thank Dr. Nelly Mugo for giving me the opportunity to carry out my research at CTRL, KNH and Dr Bhavna Chohan who took the time to advice me on both the technical and theoretical aspects of the research. I also would like to thank all the laboratory staff at CTRL, KNH and Irene at KAVI for their technical input to the research work.

Special thanks to my parents David and Jane Waweru for their continuous support both financially and morally. Mum, you constantly encouraged me to complete my thesis even when striking a work and school balance seemed almost impossible. For this, I thank God and I thank you for constantly keeping me in your prayers. I would also like to thank my sisters Wambui Muriithi, Karira, Njoki and Gathoni Waweru for encouraging me to keep at it even when the going got tough.

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TABLE OF CONTENTS

DECLARATION ... ii

DEDICATION ... iii

ACKNOWLEDGEMENT ... iv

TABLE OF CONTENTS ... v

LIST OF TABLES ... x

LIST OF FIGURES ... xi

ABBREVIATIONS AND ACRONYMS ... xii

ABSTRACT ... xiv

1.0INTRODUCTION ... 1

1.1 Background information ... 1

1.2 Statement of the Problem ... 3

1.3 Justification ... 4

1.4 Research questions ... 5

1.5 Hypotheses ... 5

1.6 Objectives ... 6

1.6.1 General Objective ... 6

1.6.2 Specific Objectives ... 6

1.7 Significance of the study ... 6

2.0LITERATUREREVIEW ... 7

2.1 HIV Virus ... 7

2.1.1 Epidemiology of HIV/AIDS ... 9

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2.1.3 Diagnosis, Treatment and Control of HIV... 14

2.2 Modes of Transmission and Groups at risk of HIV infection ... 16

2.2.1 Serodiscordancy ... 17

2.2.2 Causes of resistance to HIV amongst HESN individuals ... 18

2.3 Hepatitis C Virus (HCV) ... 20

2.3.1 Epidemiology of HCV ... 20

2.3.2 Pathogenesis of HCV ... 22

2.3.3 Diagnosis, Treatment and Control of HCV ... 23

2.4 HIV/ HCV co-infection ... 24

2.4.1 Effects of HIV/HCV co-infection on health ... 25

2.4.2 Epidemiology of HIV/HCV co-infection globally and in Kenya ... 27

2.4.3 Immune responses in HIV/HCV co- infected individuals ... 29

3.0METHODOLOGY ... 32

3.1 Study Site ... 32

3.2 Study Design ... 32

3.3 Sample Size ... 32

3.4 Study Samples ... 33

3.5 Study sampling technique ... 33

3.6 Study Population ... 33

3.7 Murex anti- HCV ELISA for detection of antibodies to HCV in human serum and plasma ... 34

3.7.1 Results interpretation ... 35

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3.9 Ethical Approval ... 36

4.0RESULTS ... 37

4.1 Socio demographic information ... 37

4.1.1 Participants Age ... 37

4.1.2 Participants Gender ... 38

4.2 Participants HIV status ... 39

4.3 Prevalence of HCV amongst all the participants ... 39

4.3.1 Prevalence of HCV by HIV status ... 40

4.3.2 Prevalence of HCV by Gender ... 41

4.4 Prevalence of HIV/HCV co-infection ... 41

4.4.1 HIV/HCV co-infection by gender... 41

4.4.2 HIV/HCV co-infection by age ... 42

4.5 Correlation between HIV Viral load and CD4+ cell counts amongst HIV/HCV co- infected participants ... 42

4.6 Correlation between HIV Viral load and CD8+ cell counts amongst HIV/HCV co- infected participants ... 43

4.7 HIV viral load count by the HIV/HCV co-infected versus HIV mono-infected participants ... 44

4.8 CD4+ counts in HIV/HCV co-infected versus HIV mono-infected participants ... 46

4.9 CD8+ counts by HIV/HCV co-infected versus HIV mono-infected individuals ... 47

5.0DISCUSSION,CONCLUSIONANDRECOMMENDATIONS ... 49

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5.1.1 Participants Age ... 49

5.1.2 Participants Gender ... 49

5.2 Prevalence of HCV among all the participants ... 49

5.2.1 Prevalence of HCV by HIV status ... 51

5.3 HIV/HCV co-infection ... 51

5.3.1 Prevalence of HIV/HCV co-infection... 51

5.3.2 HIV/HCV co- infection by gender... 53

5.3.3 Correlation between HIV Viral load and CD4+ counts amongst HIV/HCV co- infected participants ... 53

5.3.4 Correlation between HIV viral load and CD8+ counts amongst HIV/HCV Co-infected participants ... 55

5.3.5 HIV Viral load count by HIV/HCV Co- infection status ... 56

5.3.6 CD4+ counts by HIV/HCV co-infected versus HIV mono-infected participants ... 57

5.3.7 CD8+ counts by HIV/HCV co- infected HIV mono-infected participants ... 58

5.4 Limitations ... 58

5.5 Conclusion ... 58

5.6 Recommendations ... 59

REFERENCES ... 60

APPENDICES ... 73

Appendix I: KNH/UON ethical approval ... 73

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Appendix III: Informed consent for HIV positive individuals from parent study ... 75

Appendix IV: Informed consent for HIV negative individuals from parent study ... 84

Appendix V: Data from parent study ... 93

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LIST OF TABLES

Table 4.1: Age distribution of the participants... 37

Table 4.2: Prevalence of HCV amongst all the participants ... 39

Table 4.3: Prevalence of HCV by HIV status ... 40

Table 4.4: Prevalence of HCV by Gender ... 41

Table 4.5: Prevalence of HIV/HCV co-infection ... 41

Table 4.6: HIV/HCV co-infection by gender ... 42

Table 4.7: HIV/HCV co-infection by age ... 42

Table 4.8: HIV Viral load by HIV/HCV co- infection ... 45

Table 4.9: CD4+ counts by HIV/HCV co-infection ... 47

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LIST OF FIGURES

Figure 2.1: Structure of HIV Virus ... 9

Figure 2.2: Estimated number of people living with HIV in 2012 and trends by global region ... 10

Figure 2.3: HIV prevalence among Kenyan women and men aged 15 - 64 years, KAIS 2007 and 2012 ... 11

Figure 2.4: HIV prevalence in Kenya amongst persons aged 15-64 years by NASCOP region ... 12

Figure 2.5: Map of estimated anti-HCV seroprevalence by GBD ... 22

Figure 4.1: Age distribution of the participants. ... 38

Figure 4.2: Participants Gender... 39

Figure 4.3: Prevalence of HCV amongst all the participants ... 40

Figure 4.4: Correlation between HIV viral load and CD4+ count for HIV/HCV co-infected participants ... 43

Figure 4.5: Correlation between HIV viral load and CD8+ count for HIV/HCV co- infected participants ... 44

Figure 4.6: Comparison of HIV viral load by HIV mono-infected participants and HIV/HCV co- infected participants... 45

Figure 4.7: Comparison of CD4+ counts by HIV mono-infected participants and HIV/HCV co-infected participants... 46

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ABBREVIATIONS AND ACRONYMS

AIDS Acquired immunodeficiency syndrome

Anti- HCV Antibodies to HCV

APC Antigen presenting cells

CCR5 Chemokine receptor 5

CD4+ Cluster of differentiation 4

CD8+ Cluster of differentiation 8

cDNA Complementary deoxyribonucleic acid

CTL Cytotoxic T lymphocyte

CTRL Clinical trials research laboratory

CXCR4 Chemokine receptor 4

DNA Deoxyribonucleic acid

ELISA Enzyme linked immunoabsorbent assay

GBD Global burden of disease

HAART Highly active antiretroviral therapy

HAV Hepatitis A virus

HBV Hepatitis B virus

HCV Hepatitis C virus

HSV Herpes simplex virus

HESN HIV-1 exposed but seronegative

HIV Human immunodeficiency virus

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IFNαβ Interferon alpha beta

IgG Immunogobulin G

IgM Immunoglobulin M

IDU Injection drug use

IDVUs Intravenous drug users

IQR Interquartile range

KAIS Kenya Aids Indicator Survey

KNH Kenyatta National Hospital

LPS Lipopolysaccharide

MHC Major histocompatibility complex

NASCOP National aids & STI control programme

NF-κB Nuclear factor kappa-light-chain-enhancer of activated B cells

RNA Ribonucleic acid

RT Reverse transcriptase

SD Standard Deviation

TB Tuberculosis

TLR4 Toll like receptor 4

TNF Tumour necrosis factor

UNAIDS Joint United Nations programme on HIV/AIDS

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ABSTRACT

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CHAPTER ONE 1.0INTRODUCTION

1.1 Background information

Acquired immunodeficiency syndrome (AIDS) remains a challenge for healthcare systems around the world as a consequence of its health and also its social impact (Agusti et al., 2014). Human Immunodeficiency virus (HIV) attacks and renders ineffective the human immune system and leads to acquired immunodeficiency syndrome (AIDS), which leaves those with AIDS open to a variety of opportunistic infections (Turkoski, 2006). This is mainly because HIV infects and destroys the CD4+ T cells that are responsible for coordinating the immune response against antigens, pathogens and cancerous cells (Manavi, 2006).

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There are two types of HIV positive couples: serodiscordant couples and

seroconcordant couples. Serodiscordancy (only one partner infected) arises when one partner either comes into the union already infected or becomes infected later through extramarital sexual contact. Positive seroconcordancy (both partners infected) arises when the infected partner transmits HIV to the previously uninfected partner or when both partners are infected outside the union, either prior to the union and/or through extramarital sexual contact. Recent studies demonstrate that married or cohabiting serodiscordant couples are an important source of new HIV infections

in sub-Saharan Africa (Bishop et al., 2010).

Viral hepatitis is a disease as old as the history of medicine, and was referred to by Hippocrates over 2000 years ago (Otedo, 2004). In 1989, the virus responsible for most transfusion associated hepatitis non- A non- B hepatitis (NANBH) was identified and cloned and named hepatitis C (HCV) (WHO, 2002). Chronic Hepatits C is a major cause of liver cirrhosis and hepatocellular carcinoma worldwide (Baumert et al., 2014). Hepatitis C accounts for 25% of all liver cancers representing the leading indication for liver transplantation. HCV infections are common worldwide, with 3-4 million new infections yearly and infection rates as high as 5% in some countries (Bernstein et al., 2014). It is estimated 170 million people (3% of the world’s population) have HCV. This estimate is more than 4 times the number of

people living with HIV (Chan et al., 2008; WHO, 2002).

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are an estimated 12.7 million people in the world who inject drugs and 13% of them are living with HIV. Of the estimated 35 million people living with HIV, some 4-5 million people have HCV (UNAIDS Gap report, 2014). The prevalence of HIV/HCV co-infection in the general population in Kenya is estimated to be 0.2-0.9% (Fukuda

et al., 2008) and in East Sub Saharan Africa it is estimated to be 2% (Flaxman et al., 2013). Recent studies have found increased levels of immune activation in HIV/HCV co-infected individuals as compared to HIV mono infected subjects. Immune defects caused by HIV or HCV could alter the course of secondary infection and dysregulated innate immune responses could contribute to a more rapid disease progression (Gonzales et al., 2010).

Currently, there is inadequate data on the prevalence of HIV/HCV co- infection in Kenya. The aim of this study was to determine the prevalence of HCV infection amongst HIV serodiscordant couples and to determine the correlation of CD4+/CD8+ cell count with HIV viral load in co-infected individuals in order to curb the spread of the disease as HIV/HCV co-infection leads to immune defects which could contribute to a more rapid disease progression.

1.2 Statement of the Problem

Many patients with HIV may have co-infection with one or more hepatitis viruses. Co-infections contribute to HIV-related pathogenesis and often increase viral load in HIV infected people, thereby causing a more rapid progression to AIDS (Modjarrad

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very dynamic. The prevalence also varies with different risk groups. The prevalence of HCV infection amongst HIV serodiscordant couples in Kenya is not well known. It is also not known how the CD4+ and CD8+ counts correlate with HIV viral load in HIV/HCV co-infected individuals. This study focused on determining the prevalence of HCV and how the CD4+ and CD8+ counts correlate with HIV viral load in HIV/HCV amongst HIV serodiscordant couples in Thika, Kiambu County in order to curb the spread of the disease as HIV/HCV co- infection leads to immune defects which could contribute to a more rapid disease progression.

1.3 Justification

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formulation of some policies that will help in curbing the spread of HIV/HCV co-infection amongst the population and specifically in HIV serodiscordant couples.

1.4 Research questions

i) What are the demographic characteristics of the HIV/HCV co-infected individuals?

ii) What is the seroprevalence of HCV amongst a cohort of HIV serodiscordant couples?

iii) What is the correlation between CD4+ cell counts and HIV viral loads in HIV/HCV co-infected individuals?

iv) What is the correlation between CD8+ cell counts and HIV viral loads in HIV/HCV co-infected individuals?

1.5 Hypotheses

i) The prevalence of HIV/ HCV co- infection amongst HIV serodiscordant couples is low.

ii) HIV and Hepatitis C virus co-infection will have no effect on CD4+/CD8+ cell counts.

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1.6 Objectives

1.6.1 General Objective

To determine the seroprevalence of HCV amongst HIV serodiscordant couples and the correlation of CD4+/CD8+ cell count with HIV viral load in co- infected individuals.

1.6.2 Specific Objectives

i) To analyse the demographic characteristics of the HIV/HCV co-infected individuals.

ii) To determine the seroprevalence of HCV amongst a cohort of HIV serodiscordant couples.

iii) To determine the correlation between CD4+ cell counts and HIV viral loads in HIV/HCV co-infected individuals.

iv) To determine the correlation between CD8+ cell counts and HIV viral loads in HIV/HCV co-infected individuals.

1.7 Significance of the study

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CHAPTER TWO

2.0LITERATUREREVIEW 2.1 HIV Virus

Acquired immunodeficiency syndrome (AIDS) is a disease caused by infection with the Human immunodeficiency virus (HIV), a lentivirus that is transmitted by sexual contact, injection of infected blood or blood-derived products and from mother-to-child (Girard et al., 2006). Basically, AIDS is characterized by the progressive depletion of CD4+ Helper T-cells, which are the preferred target of the virus, resulting in an immunodeficiency syndrome that paves way to opportunistic infections. There are at least 3 variants of HIV, HIV-1, HIV-2 and HIV-0, of which the best studied, is HIV-1. HIV-1 and HIV-2 are closely related, although in most countries HIV-1 is the principal cause of AIDS. HIV-2 is less pathogenic, causing a slower progression to AIDS, and is confined to West Africa (Assossou et al., 2011; Girard et al., 2006).

Both HIV-1 and HIV-2 have similar transmission routes, cellular targets and AIDS defining related symptoms. However, as compared with 1 infection, HIV-2 infection is characterized by lower transmission rates, a longer asymptomatic stage, a slower decline in CD4+ T-cell counts, and a lower mortality rate. Progressive immune dysfunction and AIDS develop in most persons who have untreated infection with HIV-1 only, as compared with only 20 to 30% of persons infected with HIV-2 only (Biague et al., 2012).

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genetic make-up HIV-1 viruses are further sub divided into groups namely pandemic group M (Major) and less prevalent groups O (Outlier), N (nonM/ nonO) and P (Assossou et al 2011; Simon et al., 2006). Most of the HIV-1 strains responsible for the AIDS pandemic belong to group M, which have evolved in humans to form 9 genetic subtypes, also known as clades and are designated by letters A-D, F-H, J and K, two sets of subtypes (A1, A2, A3, A4 and F1 and F2), circulating recombinant forms (CRFs) and a single recombinant (URFs) which results from the recombination of two or more subtypes (Bottani et al., 2014; Girard et al., 2006). Subtype C predominates in Africa and India, and accounted for 48% of cases of HIV-1 in 2007 worldwide. Subtype B predominates in Western Europe, the Americas, and Australia (Celum et al., 2014).

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Figure 2.1: Structure of HIV Virus (Gelderblom, 1991)

2.1.1 Epidemiology of HIV/AIDS

Globally, an estimated 36.9 million (34.3-41.4 million) people were living with HIV and 1.2 million [980,000-1.6 million] people died from AIDS-related causes worldwide in 2014 (UNAIDS fact sheet, 2015). Sub-Saharan Africa still bears an inordinate share of the global HIV burden with 25.8 million (24.0-28.7 million) adults and children living with HIV (UNAIDS fact sheet, 2015).

Nearly 1 in every 20 adults (4.9%) are living with HIV in Sub- Saharan Africa accounting for 66% of the people living with HIV worldwide (Eckstein et al., 2013;

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2012. The reduction in global HIV incidence is largely due to reductions in heterosexual transmission (Figure 2.2).

North America West and Central Europe Eastern Europe and Central Asia 860 000 1.3 million

1.3 million Incidence → Incidence →

Incidence →

Caribbean North Africa and Middle East South &,East Asia

250 000 Incidence ↓ 260 000 Incidence 4.8 million Incidence ↓

Sub Saharan Africa Oceania 25 million 51000 Incidence ↓

Incidence ↓

Latin America

1·5 million Incidence →

Figure 2.2: Estimated number of people living with HIV in 2012 and trends in the incidence of new infections from 2001 to 2012 by global region (Celum et al., 2014).

While AIDS was most likely present in Africa for many decades earlier, it was only in the summer of 1981 that the disease emerged in the human population as an outbreak of Pneumocystis carinii pneumonia among homosexual men in the USA (Girard et al., 2011). The first identified case of HIV in Kenya was recorded in 1986.

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Results from the Kenya AIDS Indicator survey (KAIS) indicated that by the end of 2012, 5.6% of Kenyan adults age 15-64 were infected with HIV. According to the survey, more than 1.1 million Kenyans are living with HIV/AIDS (NASCOP-KAIS, 2012). Results from the Kenya AIDS Indicator survey (KAIS) indicated that by the end of 2007, 7.2% of Kenyan adults age 15-64 were infected with HIV, which translated to more than 1.4 million living with HIV/AIDS. These results indicate that HIV prevalence among adults aged 15 to 64 years decreased nationally from 7.2%, (KAIS, 2007) to 5.6% in 2012 (NASCOP-KAIS, 2012). This decline was observed for both females and males as shown in Figure 2.3.

Figure 2.3: HIV prevalence among Kenyan women and men aged 15 - 64 years, KAIS 2007 and 2012 (NASCOP-KAIS, 2012).

8.5

5.5

7.2

6.9

4.4

5.6

0

1

2

3

4

5

6

7

8

9

Female

Male

Total

P

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rce

n

t

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According to the NASCOP-KAIS (2012) report, the distribution of HIV infections varied across the country. Prevalence was highest in Nyanza region at 15.1% and lowest in the Eastern North region at 2.1%. Central province, in which Kiambu County falls, had a prevalence of 3.8% as shown in figure 2.4 (NASCOP-KAIS, 2012).

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2.1.2 Pathogenesis of HIV

The main target of HIV is activated CD4+ T lymphocytes. Infection begins with the attachment of the virions to the cell surface of the target cell (Princen et al., 2005). These cells bind with high affinity to the HIV envelope glycoprotein gp120 and can retain infectious particles for days, thus facilitating the presentation of the virus to susceptible cells (Fauci, 2007).

Two chemokine receptors- CCR5, predominantly expressed on macrophages and CD4 T-cells and CXCR4, expressed on activated T-cells are the major co-receptors for HIV. Entry of HIV is via interactions with CD4 and the chemokine coreceptors. Other cells bearing CD4 and chemokine receptors are also infected, including resting CD4 T cells, monocytes and macrophages, and dendritic cells (Celum et al., 2014; Janeway et al., 2005).

The replication cycle of HIV in its target cell begins with the binding of viral gp120 to the CD4+ molecule, its receptor on the host-cell surface. Once gp120 binds to CD4+, the glycoprotein undergoes a conformational change that facilitates its binding to a cellular co receptor, uncovering the co-receptor binding site and subsequently the hydrophobic amino- terminal domain of gp41 (Fauci, 2007; Lever, 2005; Princen

et al., 2005). Reverse transcriptase (p64) transcribes the viral RNA into a complementary copy (cDNA). The viral cDNA is then integrated into the host cell genome by viral integrase. The integrated cDNA is known as the provirus (Janeway

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transcription factor) in activated CD4+ T-cells. NFkB binds to promoters thereby initiating transcription of viral RNA (Janeway et al., 2005).

After fusion with the host cell membrane, infection is established. An early burst of viremia and rapid dissemination of virus to lymphoid organs, particularly the gut-associated lymphoid tissue, are major factors in the establishment of the chronic and persistent infection that is a hallmark of HIV disease. Migration of infected T-lymphocytes, dendritic cells, macrophages and virions into the regional lymphoid tissues takes place within 3-5 days (Fauci, 2007). Direct contact between these virus harbouring cells, susceptible macrophages and CD4 T+ cells within the lymph node germinal centers i.e the spleen and bone marrow results in an increase in virus replication, usually within 14 days (Goodenow et al., 2003; Simon et al., 2006).

2.1.3 Diagnosis, Treatment and Control of HIV

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Six classes of antiretroviral agents currently exist namely Nucleoside reverse transcriptase inhibitors (NRTIs), Nonnucleoside reverse transcriptase inhibitors (NNRTIs), Protease inhibitors (PIs), Integrase inhibitors (IIs), Fusion inhibitors (FIs) and Chemokine receptor antagonists (CRAs). Each class targets a different step in the viral life cycle as the virus infects a CD4+ T lymphocyte or other target cell. The use of these agents in clinical practice is largely dictated by their ease or complexity of use, side-effect profile, efficacy based on clinical evidence, practice guidelines and clinician preference (Rathbun et al., 2013).

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Introduction of serological HIV assays that detect both immunoglobulin G (IgG) and IgM referred to as third generation assays and those that combine detection of HIV antigen and antibodies, referred to as fourth generation assays has shortened the diagnostic window and allowed earlier reliable detection of HIV infection (Back et al., 2011, Branson et al., 2011). Point of Care tests have become increasingly popular over the past several years. These tests provide rapid, on-site HIV results in a format that is relatively easy for clinic staff to perform. A variety of other assays are essential to confirm positive antibody screens.

The enzyme-linked immunosorbent assay (ELISA), or enzyme immunoassay (EIA), is a test commonly employed as a confirmatory test for HIV as was done in the parent study, as it has a high sensitivity. Western blot, line immunoassay, and indirect immunofluorscence assay, are highly specific and play a central role in diagnostic algorithms. Molecular RNA assays are highly sensitive during early infection. Western blot and polymerase chain reaction (PCR) provide an adjunct to antibody testing or provide additional information for the clinician treating HIV positive patients (Branson et al., 2011; Fearon, 2005).

2.2 Modes of Transmission and Groups at risk of HIV infection

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It has been suggested that up to 50% of new HIV infections are acquired from newly infected individuals, due to both the high level of plasma viral load during the early phase of disease and to virus-specific properties. Acute HIV infection, which causes very high plasma viral loads in the first few months, is an important driver of HIV epidemics (Celum et al., 2014; Girard et al., 2011).

Men who have sex with men (MSM) have a higher risk of infection because receptive anal intercourse has a relative risk of 1.43%, which is about 10 times higher that of receptive vaginal intercourse. Not all exposures to HIV, however, lead to infection and not all HIV infections lead to AIDS. Approximately a third of infants born to HIV infected mothers acquire infection while hetero-sexual transmission occurs approximately after between 1 out of 100 and 1 out of 1000 exposures, haemophiliacs exposed to infected blood products do not consistently get infected and some commercial sex workers and seronegative partners in serodiscordant couples appear to remain uninfected despite repeated extensive exposure to HIV (Girard et al., 2011).

2.2.1 Serodiscordancy

Emerging data indicate that a large proportion of new infections in Sub Saharan

Africa occur in stable HIV discordant relationships and with increased testing of

couples it has become apparent that a large proportion of couples affected by HIV

are HIV serodiscordant (Achando et al., 2011; Bruyn et al., 2007). Demographic

and health surveys (DHS) show that between 45% and 75% of married HIV positive

individuals have HIV negative spouses. This affirms the importance of HIV

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The current knowledge of HIV pathogenesis suggests that genetic variation can

modulate the immune response and viral replication. Certain persons exhibit

resistance to HIV infection despite multiple and repeated exposures to the virus.

They are known as HIV exposed, but seronegative (HESN) individuals (Biasin et al.,

2010). Approximately 15% of HIV exposed seronegative individuals repeatedly

resist infection, a phenomenon that has been observed in all investigated

HIV-exposed cohorts (Clerici et al., 2010). This group includes persons who have

repeated unprotected sexual intercourse with a seropositive (SP) individual, such as

HIV discordant couples, sex workers from areas of high HIV prevalence and men who have sex with men. This particular cohort of individuals represents an optimal chance to identify new therapeutic or vaccine targets (Estrada et al., 2013).

2.2.2 Causes of resistance to HIV amongst HESN individuals

The reasons for possible resistance to HIV infection in HESN subjects remain controversial and under investigation, although several nonmutually exclusive mechanisms have been proposed. First, there are known genetic factors at play such as the CCR5Δ32 mutation which occurs in a small proportion of humans that results

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Another mechanism proposed to account for HIV resistance in HESN is an overall CD4+ T cell quiescence, as defined by decreased expression of activation markers, cytokine secretion and gene expression profiling in HESN commercial sex workers. This reduced T cell activation has been proposed to be at least partially due to an increased percentage of regulatory T cells (Tregs). Tregs, a subset of CD4+ T cells, have demonstrated roles in regulating the immune system under homeostatic conditions as well as during infection. Tregs can suppress proliferation and function of several immune cell types, including Th1, Th2, and Th17 CD4+ T cells and CD8+ T cells. Moreover, they can modulate the migration of immune cells to the site of infection (Baeten et al., 2013).

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This study’s aim was to determine the prevalence of HCV infection amongst serodiscordant couples in Thika, Kiambu County and to determine the correlation of CD4+ CD8+ count with HIV viral load in co- infected individuals, as given its contribution to the spread of the HIV/AIDS epidemic, it is imperative to better understand HIV discordancy and its correlates.

2.3 Hepatitis C Virus (HCV)

Hepatitis C virus (HCV) is a single stranded RNA virus, classified into the Hepacivirinae genus, belonging to the Flaviviridae family (Santiago et al., 2006). Hepatitis C is usually spread by sharing infected needles with a carrier, from receiving infected blood and from accidental exposure to infected blood. The most efficient means of HCV transmission is percutaneous exposure to blood, with transmission efficiency 10 times higher for HCV than for HIV. Some people acquire infection through non parenteral means that have not been fully defined, but include sexual transmission in persons with high risk behaviours, although transmission of HCV is less common than that of HBV and HIV (Mayer et al., 2012; WHO HCV report, 2002). The target cells for HCV infection are mainly hepatocytes but its tropism seems to be wider than previously presumed. HCV genome sequences have been found in extra hepatic cells such as circulating lymphocytes (T and B cells) and antigen presenting cells (Chevallier et al., 2003).

2.3.1 Epidemiology of HCV

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HCV (antibodies to HCV) prevalence, where as industrialized countries in North America, Western Europe and Australia are known to have lower prevalence, as shown in figure 2.5 (Flaxman et al., 2013).

One of the most important features of HCV is its high degree of genetic variability. Variability of the HCV genome has led to its classification into six main genotypes, each with several subtypes, based on sequence data. Genotypes 1-3 account for almost all infections in Japan, U.S.A and Europe. Genotype 4 is prevalent in Egypt and Democratic republic of Congo, genotype 5 in South Africa and genotype 6 in Hong Kong (Chan et al., 2008; Fukuda et al., 2008). Fukuda et al in 2008 performed a study among a cohort of drug users in Kenya and found genotype 1 as being predominant amongst the drug users. Most infections with this pathogen are persistent.

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Figure 2.5: Map of estimated anti-HCV seroprevalence by GBD (Global burden of disease) region (Flaxman et al., 2013).

2.3.2 Pathogenesis of HCV

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regulatory factor 3 (IRF-3) target genes, and lambda (type III) interferons induce innate immune programs and drive the maturation of adaptive immunity for the control of infection (Rosen, 2011).

The coordinated activities of CD4+ T cells and cytotoxic CD8+ T cells, primed in the context of HLA class II and I alleles, respectively, on antigen presenting cells, are critically important for the control of acute HCV infection. Mutations in viral epitopes that are targeted by cytotoxic CD8+ T cells can allow the virus to escape immune mediated clearance. Up-regulation of inhibitory receptors on exhausted (functionally impaired) T cells is another mechanism of T-cell dysfunction during chronic infection (Rosen, 2011).

2.3.3 Diagnosis, Treatment and Control of HCV

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At present, there is no available preventive vaccine against HCV infection and the consensus therapeutic treatment, consisting of pegylated interferon-alpha (pegIFN-alpha) in combination with Ribavirin, is poorly effective against some viral genotypes (Santiago et al., 2006). Interferon alfa is a potent inhibitor of HCV replication that acts by inducing interferon-stimulated host genes that have antiviral functions. Its pegylated form remains a mainstay of HCV therapy. Ribavirin, a key component of the therapeutic regimen, acts synergistically with and is used in combination with interferon alfa in the treatment of HCV infection; it probably has multiple mechanisms of action (Ghany et al., 2013).

2.4 HIV/ HCV co-infection

HCV is common among patients with HIV because of shared routes of viral transmission. HCV and HIV are both transmitted parenterally (Koziel et al., 2007; Santiago et al., 2006). There are an estimated 12.7 million people in the world who inject drugs and 13% of them are living with HIV. Of the estimated 35 million people living with HIV, some 4-5 million people have HCV (UNAIDS Gap report, 2014). HIV is known to affect the epidemiology, transmission, pathogenesis and natural history of HCV infection, primarily due to the immunosuppressive effects of HIV.

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individuals due to the increased risk of hepatoxicity of HAART and the likelihood of onset of an AIDS-defining illness (Barett et al., 2011; Lakew et al 2013). In the setting of HIV infection especially when HIV associated immunodeficiency progresses, HCV establishes chronic infection even more frequently and the rate of development of liver disease accelerates (Barett et al., 2011). Compared with HCV infection alone, co-infection with HIV increases HCV levels in plasma (Hu et al., 2008).

In Kenya, the HIV epidemic has been well documented. However, little data exists on HCV co- infection amongst HIV positive patients. This study therefore focussed on immune trends and responses in a cohort of discordant couples with HIV/HCV co- infection as it has become apparent that a large proportion of couples affected by HIV are HIV serodiscordant (Achando et al., 2011). There is also need for new data to guide on diagnosis and management of HIV/HCV co- infection, which may lead to the implementation of important health policies.

2.4.1 Effects of HIV/HCV co-infection on health

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dementia. There is therefore evidence that HCV-infected leukocytes can carry the virus into the central nervous system where viral replication may be sustained in an independent compartment (Santiago et al., 2006).

With the advent of highly active combined antiretroviral therapy (cART), HIV-associated morbidity and mortality has declined dramatically, in some countries. With longer survival and fewer opportunistic infections, liver disease because of HCV infection has emerged as a leading cause of non-AIDS-related death (Baker et al., 2011).

HAART regimens do not suppress HCV replication. Instead, they are associated with transient flares of HCV replication. The latter may increase the liver damage in chronic hepatitis C. Moreover, many antiretroviral drugs commonly used in HAART combinations are hepatotoxic. Hepatotoxic effects of antiretroviral therapy are more likely to develop in patients with underlying HCV infection. For these reasons, HAART could be associated with more severe liver damage and, as a consequence, with progression of liver fibrosis (Castellano et al., 2004; Koziel et al. 2007). Castellano et al found in their study in 2004 that use of HAART regimens including nevirapine is associated with an increased degree of liver fibrosis in HIV-infected patients with chronic hepatitis C. This complication could lead to changes in ARV drug regimens or even treatment discontinuation (Fuping et al., 2009). Thus, there seems to be some reservation about offering HAART to HIV/HCV co-infected patients, probably because HAART is more difficult to manage in these particular patients (Spengler et al., 2004).

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prevalence of HCV among HIV infected patients as compared to HIV negative patients. They also found that patients with co-infection had a statistically significant increase in mortality as compared to HIV mono-infected patients. Grakoui et al also mention in their review done in 2009 that there is an increased risk of death in people with HIV/HCV co-infection. Lalloo et al in their study found that age-gender distribution of HIV and HCV bore remarkable similarity. These findings led them to suggest that HCV was predominantly a sexually transmitted infection in their study population, which contrasts findings of other studies which regard sexual transmission of HCV to be relatively inefficient and not important in the epidemiology of HCV as IVDU, transfusion and other parenteral routes (Koziel et al., 2007; Santiago et al., 2006).

2.4.2 Epidemiology of HIV/HCV co-infection globally and in Kenya

HCV infection is often prevalent among HIV infected populations, with one-third of HIV-infected Americans, and 7 million worldwide being co- infected. The prevalence of HCV co- infection varies, depending on the mode of HIV transmission (Mayer et al., 2012). The principal route of HCV spread is injection drug use (IDU). HCV co-infection rates often exceed 90% among HIV infected individuals who use injection drugs. Increasingly, incident HCV among HIV infected men who have sex with men (MSM) is associated with sexual risk behaviour (Mayer et al., 2012).

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found. This confirms that in HIV/HCV co-infected patients, as in HCV mono-infected persons, parenteral transmission of HCV is very common, especially in IDU, but sexual transmission is rare. In two large US HIV trials (N = 1687), the overall rate of HIV/HCV co-infection was 16% (Brau, 2003).

Currently, there are few nation-wide studies, which demonstrate the prevalence of HIV/HCV co-infection in Kenya. In a study carried out at Aga khan university hospital, Nairobi in 2008, the prevalence of co-infection with HIV and HCV was found to be 1% among 378 patients (Harania et al., 2008). Among 458 HIV/AIDS medical in patients at Kenyatta national hospital, Nairobi, 3.7% were found to be co-infected with HCV and HIV (Anzala et al., 2005). 22% of 333 drug users tested positive for HCV in a study carried out between the year 2000 and 2008 amongst a cohort of drug users in Nairobi (Fukuda et al 2008). Among 300 HIV positive patients from nine Nairobi based health centres, 10% were found to be co-infected with HIV and HCV (Gicheru et al., 2013). These statistics show that the prevalence of HCV and HIV co-infection in Kenya is not static. A study from Tanzania revealed a HIV/HCV co-infection rate of 1.51%, while 1.2% was reported for women in Abidjan, Cote d’Ivoire. In Cameroon a HIV/HCV co infection rate of 6.7% has been reported. A much higher HIV/HCV co infection rate of 30% and 64.3% was reported in a drug cohort of American and Spanish women (Okonufua et al., 2009).

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2.4.3 Immune responses in HIV/HCV co- infected individuals

Both innate and cell mediated immune responses are crucial in the early control of viral infections (Lakew et al., 2013). HIV/HCV co- infected individuals usually have a depressed antibody and cellular immune responses.

Infection with HIV is characterized by depletion of CD4+ T-helper cell populations leading to immune deficiency and occurrence of opportunistic infections. Cell-mediated immunity plays an important role in the clearance of HCV infection. Vigorous responses from both CD4+ and CD8+ arms of T cells are necessary for the successful control of HCV replication. While it is generally assumed that direct infection by HIV represents the dominant source of CD4+ depletion among infected patients, it is also recognized that liver fibrosis, associated with development of portal hypertension may also lead to decreased cell populations (lymphocytes, thrombocytes and erythrocytes) via a mechanism of splenic enlargement with increased splenic sequestration of cellular elements. (Benko et al., 2010; Good man

et al., 2009).

Next to generalized T-cell activation, chronic viral infection is associated with loss of effector and proliferative functions of CD8+ T cells, leading to ineffective viral control. Reduced HCV-specific T cell responses have been demonstrated in co infected patients in the chronic stage of HCV Infection due to HCV specific T cells from HIV co-infected individuals being more exhausted than those from HIV mono-infected individuals. Attenuation of viral specific T- cell responses in chronic viral infections have been related to a phenomenon known as T- cell exhaustion (Arends

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individuals than in HIV-2/HCV infected individuals. Similarly the rate of decline was higher in co-infected individuals than in persons infected with HIV or HCV alone.

Liver disease due to chronic HCV infection is becoming a leading cause of death among persons with HIV infection worldwide, and the risk of death related to liver disease is inversely related to the CD4+ cell count (Koziel et al., 2007). The liver plays a role in lipopolysaccharide (LPS) detoxification, with kupfer cells and hepatocytes recognizing bacterial components via toll receptor 4 (TLR4). However to prevent liver injury due to excessive immune responses and release of pro-inflammatory cytokines, these cells display a degree of bacterial LPS tolerance. HCV infection appears to increase the sensitivity to LPS, resulting in chronic activation of monocytes and macrophages residing in the liver. Hyper responsive monocytes and macrophages contribute to persistent liver inflammation. Thus impaired LPS detoxification in the liver could contribute to the extraordinarily high levels of immune activation observed in HIV/HCV co- infected subjects Increased immune activation has been proposed as one of the underlying mechanisms of poor clinical outcome of HCV in HIV/HCV co infected patients (Arends et al., 2013; Gonzales et al., 2010).

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influenced by the presence of more severe immunodeficiency as determined by low CD4+ count.

Dendritic cells (DCs) are professional antigen presenting cells (APCs) that play a role in the initiation and regulation of immune responses. They are able to capture and present peptides as well as lipids and glycolipids to T cells, either through MHC class I and II molecules. Functional impairment and depletion of professional myeloid plasmacytoid DCs are associated with HIV disease progression. A decrease in circulating DC was also observed in HCV infected and HIV/HCV co-infected subjects (Abbate et al., 2011).

There are a number of conflicting findings. Some studies have demonstrated that HIV/HCV co-infection was associated with impaired CD4+ T cells recovery and lower viral suppression. These include studies carried out by Good man et al (2009), Berenguer et al (2009) and Benko et al (2010). However, other cohort studies have not found such an association. A study carried out by Castano et al (1999), found a transitory clearance from plasma of HIV RNA after HCV super infection (a new infection occurring in a patient having a pre existing infection) in a patient previously infected with HIV.

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CHAPTER THREE

3.0METHODOLOGY

3.1 Study Site

The study was carried out at the Clinical Trials Research Laboratory (CTRL), department of Obstetrics and Gynaecology, Kenyatta National Hospital between May 2012 and October 2012.

3.2 Study Design

The study was a retrospective cross sectional study.

3.3 Sample Size

To determine the minimum sample size, the formula (Cochran, 1977) below was used. Assuming 6.5% prevalence from literature review of similar work (Lakew et al., 2013), the minimum sample size was calculated.

N= Z2 X P X (1-P) C2

Where:

N= the sample size Z= 1.96 at 95% interval P= the estimated prevalence

C= Confidence interval expressed as a decimal N= (1.96)2X0.065 X0.935 = 94

(0.05)2

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3.4 Study Samples

HIV positive and negative plasma samples from HIV serodiscordant couples that had been randomly collected over a period of 2 years (2006-2008) and stored at -20° C were used. These samples were collected from inhabitants of Thika, Kiambu County that had been enrolled in the Partners in Prevention HSV/HIV Transmission Study (Celum et al., 2009). Participant demographics were obtained from already archived data. These included patients ID, age and sex (Appendix V & VI). Information on whether the participants were on ARVs or not when they were enrolled into the parent study was also obtained from already archived data (Appendix V). A total of 385 samples from serodiscordant couples were used in this study, 196 HIV positive samples and 189 HIV negative samples.

3.5 Study sampling technique

In the study, purposive sampling was used whereby all the plasma samples from the sample pool were used.

3.6 Study Population

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3.7 Murex anti- HCV ELISA for detection of antibodies to HCV in human serum and plasma

All the samples from both HIV negative and positive participants were tested for HCV virus antibody using Murex anti-HCV (version 4.0) microelisa kit, as per the manufacturer’s (Murex) instructions. Murex anti-HCV (version 4.0) is an enzyme

immunoassay for the detection of antibodies to hepatitis C virus (HCV) in human

serum or plasma. Briefly, the conjugate was reconstituted with the conjugate diluent,

at room temperature. For every plate constituting of 96 wells, substrate solution was

prepared by adding 6 ml of colourless substrate diluent to 6ml of pink substrate

concentrate. The wash fluid was prepared by mixing 125ml of wash fluid concentrate

containing glycine/borate with 2375ml of water. When diluted the wash fluid

contained 0.01% brondidox preservative. The working strength wash fluid was

stored at room temperature for the duration of the testing. All reagents and samples

were allowed to attain room temperature before use, but the left over samples were

immediately put into ice packs after use to ensure they maintained their stability and

retained integrity for future research.

180µl of sample diluents was pipetted into each well. 20 µl of samples was then

added into each well, leaving out 6 wells for the controls. 20µl of negative control

was then pipetted into 4 wells and 20µl of positive control added into 2 wells. The

wells were then covered with a lid and incubated for 1 hour at 37ºC (nüve EN 400

incubator, nüve, Turkey). At the end of the incubation period the well was washed 5

times using the working strength wash fluid in an automated microplate strip washer

(Biotek ELx50 microplate strip washer, Biotek, U.S.A). Immediately after washing

the plate, 100µl of conjugate was added into each well. The wells were then covered

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the wells were washed 5 times using the working strength wash fluid in an automated

microplate strip washer (Biotek ELx50 microplate strip washer, Biotek, U.S.A).

Immediately after washing the plate 100µl of substrate solution was added into each

well. The wells were then covered with a lid and incubated for 30 minutes at 37ºC,

while the colour developed. 50µl of stop solution (2M sulphuric acid) was then

added to each well. The absorbance of the plate was read at 450 using 650nm as the

reference wavelength (Biotek ELx800 absorbance microplate reader Biotek, U.S.A).

3.7.1 Results interpretation

The cut off value was calculated by adding 0.6 to the mean of the negative control replicates. Samples giving an absorbance less than the cut off value were considered negative in the assay. Samples giving an absorbance equal to or greater than the cut off value were considered initially reactive in the assay. Such samples were retested in duplicate using the original sample. Samples that were reactive in at least one of the duplicate retests were considered repeatedly reactive to contain antibody to the HCV antigens. The enzyme reaction was terminated with sulphuric acid to give an orange colour. The plate was read photometrically. The amount of conjugate bound and hence the colour in the wells was directly related to the concentration of antibody in the sample.

3.8 Data Analysis

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gender, HIV status, HCV infection and HIV/HCV co-infection. Correlation analysis was done using Pearson correlation and scatter plots used to display the relationships between HIV viral load and CD4+/CD8+ values. An association between HIV/HCV co-infection and gender was assessed using the Pearson Chi square test while the association between HIV and hepatitis C was done using McNemar chi square test considering the paired nature of the couples. Difference in HIV viral load, CD4+ and CD8+ was assessed using ranksum test considering they were skewed. However age difference was assessed using a t-test. Data was pesented in tables, pie charts, scatter plots and box plots. P < 0.05 were considered statistically significant.

3.9 Ethical Approval

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CHAPTER FOUR

4.0RESULTS

4.1 Demographic information

The available demographic characteristics of the study participants included the age and gender (Appendix V). None of the participants were on ARVs at enrolment of the original study (Appendix V).

4.1.1 Participants Age

The samples were from participants ranging from 19 to 70 years old. The participants had a mean age of 34.18 years (SD= 8.65). Patients aged between 30 to 34 years were the majority at 27% of the participants while participants aged between 19 to 24 years made the smallest proportion at 10.7% (Table 4.1 & figure 4.1).

Table 4.1: Age distribution of the participants

Age

groups Number Percentage

< 25 41 10.7

25-29 80 20.8

30-34 104 27.0

35-39 71 18.4

40-44 46 12.0

45+ 43 11.2

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Figure 4.1: Age distribution of the participants.

4.1.2 Participants Gender

192 of the participants were male (49.9%). 193 were female (50.1%) (Figure 4.2).

0

20

40

60

80

100

<25 25-29 30-34 35-39 40-44 45+

Age of the participants

F

re

q

u

en

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Figure 4.2: Participants Gender

4.2 Participants HIV status

The study population was equally distributed for HIV status at 50.9% HIV positive and 49.09% HIV negative.

4.3 Prevalence of HCV amongst all the participants

Overall, 13 (3.4%) were HCV positive (Table 4.2 & figure 4.3).

Table 4.2: Prevalence of HCV amongst all the participants Prevalence of HCV n (%)

Negative 372 (96.6)

Positive 13 (3.4)

50.13% 49.87%

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Figure 4.3: Prevalence of HCV amongst all the participants

4.3.1 Prevalence of HCV by HIV status

Results statistically significantly indicated that most of the HCV positive cases were HIV positive compared to HIV negative participants, 11(5.6%) vs. 2(1.1%), p= 0.013 (Table 4.3).

Table 4.3: Prevalence of HCV by HIV status

Prevalence of HCV by HIV status

HIV- HIV+ Test Stat, P value

Negative n(%)

187 (98.9)

185 (94.4)

ǂChi2(1) = 6.1163 , P = 0.013*

Positive n(%) 2 (1.1) 11 (5.6)

*Statistically significant ,p<0.05 , ǂ McNemar

96.6% 3.4%

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4.3.2 Prevalence of HCV by Gender

On assessment of HCV prevalence by gender there was no difference with respect to females or males, 7 (3.6%) vs. 6 (3.1%) (Table 4.4).

Table 4.4: Prevalence of HCV by Gender Prevalence of HCV by gender

Female Male

Negative n(%) 186 (96.4) 186 (96.9)

Positive n(%) 7 (3.6) 6 (3.1)

4.4 Prevalence of HIV/HCV co-infection

The overall prevalence of HCV was low at only 11(5.6%) among the HIV positive participants (Table 4.5).

Table 4.5: Prevalence of HIV/HCV co-infection HIV/HCV Co-infection n (%)

Negative 185 (94.4)

Positive 11 (5.6)

4.4.1 HIV/HCV co-infection by gender

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Table 4.6: HIV/HCV co-infection by gender

HIV/HCV Co-infection

Female Male

Negative n(%) 141 (95.3) 44 (91.7) Positive n(%) 7 (4.7) 4 (8.3)

4.4.2 HIV/HCV co-infection by age

There was no significant difference in mean age (SD) between those positive or negative for HIV/HCV co-infection, 33.73 (6.18) vs. 32.62 (8.24) (Table 4.7).

Table 4.7: HIV/HCV co-infection by age

Age (Years)

HIV/HCV Co-infection Mean(SD)

Negative 32.62 (8.24)

Positive 33.73 (6.18)

4.5 Correlation between HIV Viral load and CD4+ cell counts amongst HIV/HCV co- infected participants

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Figure 4.4: Correlation between HIV viral load and CD4+ count for HIV/HCV co-infected participants

4.6 Correlation between HIV Viral load and CD8+ cell counts amongst HIV/HCV co- infected participants

A positive correlation was observed between HIV Viral load and CD8+ cell counts amongst HIV/HCV co- infected participants. The positive correlation between HIV Viral load and CD8+ cell counts among HIV/HCV co- infected was however not statistically significant ; r= 0.4525, p= 0.162 (Figure 4.5).

0

10

00

00

20

00

00

30

00

00

40

00

00

HIV

V

ir

a

l L

oa

d

(

c

op

ies

/mL

)

200 400 600 800

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Figure 4.5: Correlation between HIV viral load and CD8+ count for HIV/HCV co- infected participants

4.7 HIV viral load count by the HIV/HCV co-infected versus HIV mono-infected participants

There was statistically significant higher median (IQR) HIV Viral load (Copies/mL) among the HIV/HCV co-infected participants than the HIV mono-infected participants, 89775 (2590, 335915) vs. 10695 (2725, 37435) , P= 0.0436 (Table 4.8 & Figure 4.6).

0

10

00

00

20

00

00

30

00

00

40

00

00

HIV

V

ir

a

l L

oa

d

(

c

op

ies

/mL

)

500 1000 1500 2000 2500

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Table 4.8: HIV Viral load by HIV/HCV co- infection

HIV Viral load (Copies/mL)

HIV/HCV Co-infection Mean(SD) Median (IQR) Test Stat, P value

Negative 43095.95 (91676) 10695 (2725 , 37435) z = -2.018, P = 0.0436*

Positive 140839.1 (148091.7) 89775 (2590 , 335915)

*Statistically significant ,p<0.05

Figure 4.6: Comparison of HIV viral load by HIV mono-infected participants and HIV/HCV co- infected participants

0

10

00

00

20

00

00

30

00

00

40

00

00

HI

V V

ira

l l

oa

d

(c

opies/

mL)

HIV Mono-Infected HIV/HCV

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4.8 CD4+ counts in HIV/HCV co-infected versus HIV mono-infected participants

Those positive for HIV/HCV co- infection had a lower median CD4+ cell count (IQR), compared to the HIV mono-infected participants. However there was no statistical significance, 383 (335,539) vs. 499 (376,658), p=0.0772. (Figure 4.7 and Table 4.9).

Figure 4.7: Comparison of CD4+ counts by HIV mono-infected participants and HIV/HCV co-infected participants

200

400

600

800

1,0

0

0

C

D4

+ count (c

ell

s/ul

)

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Table 4.9: CD4+ counts by HIV/HCV co-infection

CD4 Result (Cells/µL)

HIV/HCV co-infection Mean(SD) Median (IQR) Test Stat, P value

Negative 572.03 (289.94) 499 (376 , 658) z= 1.767 , p= 0.0772

Positive 434.18 (161.78) 383 (335 , 539)

4.9 CD8+ counts by HIV/HCV co-infected versus HIV mono-infected individuals

Those positive for HIV/HCV co-infection had a higher median CD8+ (IQR) than the HIV mono-infected participants, however without statistical significance, 1450 (1022 , 2001) vs. 1112 (867, 1640) (Table 4.10 & Figure 4.8).

Table 4.10: CD8+ counts by HIV/HCV Co- infection

CD8+ Result (Cells/µL)

HIV/HCV

Co-infection Mean(SD) Median (IQR) Negative 1228.95 (482.84) 1112 (867 , 1640) Positive 1427.46 (538.64) 1450 (1022 , 2001)

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Figure 4.8: Comparison of CD8+ counts by HIV mono-infected individuals and HIV/HCV Co- infected individuals

0

500

1,0

0

0

1,5

0

0

2,0

0

0

2,5

0

0

C

D8

+ C

ount (c

ell

s/ul

)

HIV Mono-infected HIV/HCV

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CHAPTER FIVE

5.0DISCUSSION,CONCLUSIONANDRECOMMENDATIONS

5.1 Demographic information

5.1.1 Participants Age

The participants mean age in this study was 34.18 (SD=8.65). This mean age is comparable to a similar study done in Kenya whose mean age of the participants was found to be 33.92 years (Gicheru et al., 2013). The mean age was slightly lower than that of a similar study done in Ethiopia that found the patients mean age to be 38.9 years (Lakew et al., 2013). This shows that majority of the participants were in their reproductive years.

5.1.2 Participants Gender

The number of males and females in the study was almost similar, as majority of the study samples were from discordant couples. 192 of the participants were male (49.9%). 193 were female (50.1%)

5.2 Prevalence of HCV among all the participants

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The findings from this study are consistent with prevalence estimates in Central Asia (Armenia, Azerbaijan, Georgia, Kazakhstan, Kyrgyzstan, Mongolia, Tajikistan, Turkmenistan, Uzbekistan) which was found to be 3.8%, East Asia (China, Hong Kong, Macau, North Korea, Taiwan) which was found to be 3.7% and South Asia (Afghanistan, Bangladesh, Bhutan, India, Nepal, Pakistan) which was found to be 3.4% (Flaxman et al., 2013). The findings are also consistent with Tanzanian’s

prevalence which was found to be 3.2%, Togo’s (3.9%) and Cote d’Ivoire (3.3%)

(Karoney et al., 2013).

The findings were lower than those of a cohort of drug users in Kenya whose prevalence was found to be 22.2% (Fukuda et al., 2008). They are also lower than 518 HIV negative in patients at Kenyatta National Hospital that were found to have a prevalence of 4.4% (Anzala et al., 2005). The findings were also lower than a cohort of patients with acute icetric hepatitis at Kenyatta national hospital that was found to be 7.1% (Atina et al., 2004). These study’s findings are relatively higher than the 2% prevalence reported in East Sub Saharan Africa (Flaxman et al., 2013), but lower than 22% that reported in Egypt (Alter et al., 2005). The highest HCV prevalence rates are reported in Africa and Asia (Alter et al., 2005). Currently, it is estimated that around 170 million people worldwide (about 2% of the population) are infected with HCV virus and some of the chronic carriers are not aware of their infection (Houghton et al., 2013).

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5.2.1 Prevalence of HCV by HIV status

Results statistically significantly indicated that most of the HCV positive cases were HIV positive compared to HIV negative participants, 11(5.6%) vs. 2(1.1%), p= 0.013. This observation was similar to previous studies conducted in Kenya (Gicheru et al., 2013) and one conducted in Ethiopia (Alem et al., 2013). This may be due to the fact that the mode of transmission for both HIV and HCV are similar. Both HIV and HCV are transmitted parenterally (Koizel et al., 2007). Co- infection with HIV and HCV is very common in certain populations such as intravenous drug users (IDUs) who often share contaminated needles/syringes for intravenous drug injection (Gicheru et al., 2013).

5.3 HIV/HCV co-infection

5.3.1 Prevalence of HIV/HCV co-infection

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This study’s findings were higher than a study carried out at Aga Khan Hospital, Nairobi that found the prevalence of co infection with HIV and HCV to be 1% among 378 patients tested (Harania et al., 2008). The findings are also high compared to 458 HIV medical in- patients at Kenyatta national hospital, amongst whom 3.7% were found to be co- infected with HCV and HIV (Anzala et al., 2005). A much higher HIV/HCV co- infection rate of 30% and 64.3% was reported in a drug cohort of American and Spanish women (Okonufua et al., 2009).

The findings were lower than 300 HIV positive patients from nine Nairobi based health centres amongst whom 10% were found to be co infected with HIV and HCV (Gicheru et al., 2013). The findings were also lower than 20,365 HIV positive patients in the UK that were tested for HCV antibody whose prevalence for co infection was found to be 8.9% and also lower than a cohort of hospital based patients in Addis Ababa, Ethiopia whose prevalence was found to be 6.5% (Anderson et al.,2010; Lakew et al., 2013).

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5.3.2 HIV/HCV co- infection by gender

There was a slightly higher proportion of the males than females who had HIV/HCV co- infection, however without statistical significance, 4(8.3%) vs. 7(4.7%), p= 0.346. These findings are consistent with a study carried out in Gambia (Fielder et al., 2009). The findings were also consistent with a study carried out in Kenya, with the males- 11.6% vs. females- 9.4% (Gicheru et al., 2013). The findings were also consistent with a study carried out in Addis Ababa, Ethiopia (60% vs 40%, p=0.06) (Lakew et al., 2013). The consistency observed above may be due to the fact that men are more likely to engage in behaviour leading to the transmission of HIV and HCV such as intravenous drug users (IDUs) who often share contaminated needles/syringes for intravenous drug injection.

5.3.3 Correlation between HIV Viral load and CD4+ counts amongst HIV/HCV co- infected participants

A negative correlation was observed between HIV Viral load and CD4+ amongst HIV/HCV co- infected participants. The negative correlation between HIV Viral load and CD4+ among HIV/HCV co- infected was high, however without reaching statistical significance; r= 0.600 ,p= 0.070. Other studies that had similar results to this study include a study done amongst a Swiss HIV cohort that found at baseline there were more patients with lower CD4+ cell counts and higher plasma viremia in the co- infected group (Horban et al., 2005).

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progressing to AIDS and for the determination of the commencement of antiretroviral therapy and for monitoring response to it (Fielder et al., 2009; Lakew et al., 2013). The CD4+ counts obtained in this study were therefore a good pointer of the immune status of the patients co- infected with HIV and HCV.

The study’s findings showed that CD4+

counts were depleted as HIV viral load increased. A possible explanation is that CD4+ T cell depletion induced by HIV is associated with loss of adaptive HCV-specific immune responses (Allen et al., 2006). CD4+ T cells play a vital role in viral clearance through the direct activation of macrophages, dendritic cells, and antigen-specific B cells and the cytokine-dependent activation of CD8+ T cells (Dore et al., 2012). CD4+ responses are critical to both the generation and maintenance of antiviral immune responses because they secrete cytokines such as IL-2 which are required for sustained expansion of CD8+ T cells. The cytokines also augment antibody production by B cells and prime CD8+ cells specific for virus-infected cells. Without CD4+ cells, induction of new immune responses is impaired as was seen in this study that CTL memory cannot be maintained in vivo (Dore et al., 2012; Koizel, 2006).

Figure

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