HEPATITIS C VIRUS GENOTYPES AND DETECTION OF VIRAL RNA BY PCR IN
SERUM SAMPLES FROM EAST AFRICA
BY
PAUL KATO KITANDWE BSc. (Mak)
REG.NO. 2006/HD17/6770U
A RESEARCH REPORT SUBMITTED IN PARTIAL FULFILMENT OF
THE REQUIREMENTS FOR THE AWARD OF
MASTERS IN BIOMEDICAL LABORATORY SCIENCE AND MANAGEMENT
DEGREE OF MAKERERE UNIVERSITY
DECEMBER 2011
i
DECLARATION
I Paul Kato Kitandwe do hereby declare that “Hepatitis C Virus Genotypes and Detection of
Viral RNA by PCR in Serum Samples from East Africa” is entirely my original work, except
where acknowledged, and that it has not been submitted before to any other University or
institution of higher learning for the award of a degree.
Signed…………………………………………
Date……………………………......
This research report has been submitted for examination with the approval of the following
supervisors:
1. Dr. Anne Nanteza
Faculty of Veterinary Medicine
Makerere University
Kampala, Uganda
Date:...............................................
2. Dr. Nicaise Ndembi
Genetic Sequencing Unit
Institute of Human Virology
Abuja, Nigeria
Date:...............................................
Signature:........................................
Signature:.......................................
ii
DEDICATION
I dedicate this research work to my wife Rose Nabatanzi Kitandwe for being supportive and
patient as I put in the extra time and effort necessary to complete this work.
iii
ACKNOWLEDGEMENTS
I would like to thank the following people who helped me to conduct this work. The
International AIDS Vaccine Initiative (IAVI) that funded the research work in particular I
thank Leslie Nielsen, Claudia Schmidt, Pat Fast and Helen Thomson. I also thank the Medical
Research Council (MRC) Uganda Research Unit on AIDS specifically the Basic Science
Section for providing the facilities from where I conducted the PCR and genotyping assays. I
would also like to thank Dr. Ann Nanteza and Dr. Nicaise Ndembi for supervising me. I also
thank Dr. Josephine Birungi for allowing me to conduct this research work as well as Dr.
Pontiano Kaleebu who encouraged me to complete it. I also thank the staff of MRC Uganda
Basic Sciences Section in particular Brian Magambo for training me in PCR, and Jamila
Nazziwa and Fred Lyagoba for training me in sequencing. I also thank Dr. Eduard Sanders of
Kilifi, Kenya, Dr. Anatoli Kamali of Uganda, and Dr. Etienne Karita of Kigali, Rwanda for
providing samples from the different sites for this study. Last but not least, I thank my family
especially my parents for the efforts they have made to support my education.
iv
TABLE OF CONTENTS
DECLARATION ........................................................................................................................ i
DEDICATION .......................................................................................................................... iii
ACKNOWLEDGEMENTS ...................................................................................................... iv
LIST OF TABLES ................................................................................................................... vii
LIST OF FIGURES ................................................................................................................ viii
LIST OF ABBREVIATIONS ................................................................................................... ix
ABSTRACT .............................................................................................................................. xi
CHAPTER ONE: INTRODUCTION ........................................................................................ 1
1.1 Background ................................................................................................................... 1
1.2 Statement of the problem .............................................................................................. 4
1.3 Aim of the study ........................................................................................................... 5
1.4 Specific objectives of the study .................................................................................... 6
1.6 Scope............................................................................................................................. 6
1.7 Justification and significance of the study .................................................................... 7
CHAPTER TWO: LITERATURE REVIEW ............................................................................ 9
2.1 The Hepatitis C virus infection ..................................................................................... 9
2.2 The Hepatitis C virus structure ................................................................................... 10
2.3 HCV genome variability ............................................................................................. 11
2.4 HCV genotype distribution ......................................................................................... 11
2.5 HCV genotyping methods .......................................................................................... 13
2.6 HCV diagnosis ............................................................................................................ 15
2.7 HCV nucleic acid testing ............................................................................................ 17
2.7.1 The COBAS Ampliprep/Cobas Taqman HCV Test ........................................... 17
2.7.2 RNA extraction ................................................................................................... 18
2.7.3 Reverse transcriptase PCR .................................................................................. 18
CHAPTER THREE: METHODOLOGY ................................................................................ 20
3.1 Research design .......................................................................................................... 20
3.2 Ethical considerations ................................................................................................. 20
3.3 Sample population ...................................................................................................... 20
3.4 Sampling procedure .................................................................................................... 22
3.5 Laboratory data collection .......................................................................................... 23
3.5.1 RNA extraction ................................................................................................... 23
3.5.2 Polymerase chain reaction analysis ..................................................................... 24
3.5.3 Visualisation of the PCR products ...................................................................... 27
3.5.4 Purification of PCR products .............................................................................. 27
v
3.5.5 DNA sequencing ................................................................................................. 28
3.5.6 Phylogenetic analysis .......................................................................................... 29
3.5.7 HCV viral load testing ........................................................................................ 30
3.6 Data quality control .................................................................................................... 30
CHAPTER FOUR: RESULTS ................................................................................................ 32
4.1 Comparison of anti-HCV EIA results with RT-PCR results ...................................... 32
4.2 Comparison of anti-HCV EIA results with the real-time PCR results ....................... 33
4.3 Types of HCV genotypes ............................................................................................ 34
CHAPTER FIVE: DISCUSSION ............................................................................................ 35
CHAPTER SIX: CONCLUSIONS AND RECOMENDATIONS .......................................... 41
6.1 Conclusions................................................................................................................. 41
6.2 Recommendations ....................................................................................................... 41
CHAPTER SEVEN: REFERENCES ...................................................................................... 43
vi
LIST OF TABLES
Table 1: Sample selection across the different sites…………………………………… 22
Table 2: Reaction components for RT, primary and secondary PCR…………………. 25
Table 3: Thermo cycling conditions used for RT, primary and secondary PCR………. 26
Table 4: Contingency table of anti-HCV EIA results against PCR results……………. 32
Table 5: HCV Viral loads of PCR positive samples by country of origin……………... 34
vii
LIST OF FIGURES
Fig. 1: Schematic representation of the Hepatitis C virus genome........................................ 10
Fig. 2: Global distribution of Hepatitis C virus genotypes.................................................... 11
Fig. 3: Agarose gel showing results of PCR products for samples from Rwanda................ 32
Fig. 4: Phylogenetic analysis of Hepatitis C virus non-structural region 5b sequences........ 33
viii
LIST OF ABBREVIATIONS
AIDS
Acquired Immune Deficiency Syndrome
ALT
Alanine Aminotransferase
Anti-HCV
Hepatitis C Virus Antibodies
bDNA
Branched Chain DNA Assay
CAP/CTM
Cobas Ampliprep/Cobas Taqman
cDNA
Complimentary DNA
ddNTP
Dideoxynuclelotide triphosphate
DNA
Deoxyribose nucleic acid
dNTP
Deoxyribonucleotide triphosphate
EIA
Enzyme Immunosorbent Assay
GCLP
Good Clinical Laboratory Practise
HCV
Hepatitis C Virus
IAVI
International AIDS Vaccine Initiative
ISO
International Standards Organisation
IU
International Units
MRC
Medical Research Council
NATs
Nucleic Acid Tests
ORF
Open Reading Frame
PCR
Polymerase Chain Reaction
QS
Quantitation Standard
RFLP
Restriction Fragment Length Polymorphism
RIBA
Recombinant Immunoblot Assay
ix
RNA
Ribonucleic acid
RT-PCR
Reverse Transcriptase Polymerase Chain Reaction
SANAS
South African National Accreditation Scheme
UGX
Uganda Shillings
USD
United States Dollar
UTR
Untranslated Region
UV
Ultra Violet Light
UVRI
Uganda Virus Research Institute
WHO
World Health Organisation
x
ABSTRACT
Over 170 million people worldwide are infected with the hepatitis C virus (HCV). Several
generations of Enzyme immunoassays (EIAs) have been developed to detect HCV antibodies
mostly using HCV genotype 1 antigens. In East Africa, there is limited information about the
circulating genotypes and EIA reactive results are rarely confirmed. Some studies suggested
that genotype differences affect serological reactivity while others have differed. This study
aimed to confirm EIA reactive serum samples from East Africa through the detection and
quantification of HCV RNA and to establish the HCV genotypes of these samples.
One hundred fifty one (151) EIA reactive and 16 randomly selected negative control samples
from Uganda, Kenya and Rwanda collected from clinically healthy participants of a
haematology and biochemistry laboratory reference range study were used in this study. An
in-house RT-PCR using non-structural region 5B genomic region targeting primers was
performed on the HCV RNA extracted from these samples. Viremia was measured using the
automated specimen extraction and real-time PCR. The HCV RNA positive samples were
sequenced using the Dye terminator cycle sequencing quick start kit. Generated sequences
were aligned with references from the Los Alamos HCV sequence database and phylogenetic
analysis done using the MEGA Version 4.0 software.
Nine samples (6%) had detectable HCV RNA by both the in-house RT-PCR and the
CAP/CTM HCV test. Viral loads ranged from 19 to 1,058,000IU/ml. All 16 anti-HCV EIA
negative control samples were HCV RNA negative. Only HCV genotype 4 was identified.
There was poor correlation between EIA reactivity and HCV RNA detection. Genotype 4 is
the most common HCV genotype of anti-HCV EIA reactive samples from East Africa.
xi
CHAPTER ONE
INTRODUCTION
1.1 Background
Hepatitis C virus (HCV) infection is a leading cause of chronic hepatitis and primary
hepatocellular carcinoma in most parts of the world (Lionis et al., 2000). Approximately 170
million people worldwide are believed to be infected with HCV with about 3-4 million
infections occurring annually (WHO and the Viral Hepatitis Prevention Board, 1999).
In Africa, HCV like many other chronic infections has been overshadowed by the HIV
pandemic. However, a critical review of the literature on HCV infection shows that this
disease is as prevalent in Africa as tuberculosis, malaria, and sexually transmitted infections.
The regions with high HCV prevalence are Asia, Middle-Orient, Africa, and South America.
Sub-Saharan Africa remains the highest endemic region with a seroprevalence of 5% to 15%
(Pawlotsky et al., 1998; Menendez et al., 1999; Laurent et al., 2001). However, these
estimates need to be clearly established through cohort studies. Studies in some other African
countries reported an HCV prevalence of 8.4% in Lagos, Nigeria (Ayolabi et al., 2006); and
1.2% in Madagascar (Ramarokoto et al., 2008). In Cameroon, a prevalence of 5.5% in
pregnant women in Yaoundé (Ndumbe and Skalsky, 1993) and 6.8% among pregnant women
in the rural zones of the Centre Province (Ndumbe et al., 1994) was reported. Also an HCV
prevalence of 1.9% was reported again among pregnant women in Yaoundé-Cameroon
(Njouom et al., 2003).
1
The screening for HCV infection depends primarily on serological assays that detect HCV
antibodies (anti-HCV) by enzyme immunoassays (EIAs). Like other viral infections during
the acute infection window period, HCV-specific antibodies are not detectable even though
the virus is present in the blood. For this reason, antibody tests are unable to detect the virus
in the early stages of infection. This seronegative period may last up to 2 months in
immunocompetent and from 6 to 12 months in immunodeficient patients (Van der Poel et al.,
1994; Schreiber et al., 1996, Muerhoff et al., 2002). To reduce the number of false negative
results therefore, a highly sensitive assay able to detect low levels of HCV antibodies must be
used for HCV screening during the window period when the risk of transmission through
blood transfusion is high.
Several generations of HCV EIAs have been developed to detect HCV infections. The first
generation anti-HCV EIAs (EIA-1) were developed using recombinant HCV C100-3 peptides
from the non-structural region 4 (NS4) genomic region of HCV (Kuo et al., 1989). The EIA-1
had relatively poor specificity and sensitivity (Alter, 1992) and the lengthy seronegative
window period in some blood donors resulted in HCV transmission. The second generation
EIA (EIA-2) which was introduced in 1991 incorporated recombinant antigens from nonstructural regions NS3 and NS4 and an antigen from the core region of HCV (Alter, 1992,
Nakagiri et al., 1993). The EIA-2 was more specific and sensitive than the EIA-1 and the
length of the seronegative window period was consequently reduced by an average of 5 weeks
(Majid & Gretch, 2002). The use of this kit in low risk populations such as blood donors,
however, resulted in a high number of false positive and false negative results (Courouce &
2
Janot, 1991; Hayashi et al., 1993). The third generation EIA (EIA-3) that added an NS5
epitope and reconfigured core antigens slightly improved the sensitivity and reliability of the
test (Courouce et al., 1994) but not as much as that observed between the change from EIA-1
to EIA-2. The EIA-3, however, did increase detection of HCV antibodies earlier in the course
of infection (Colin et al., 2001). The fourth generation HCV ELISA kit (EIA-4) incorporates
carefully selected antigens derived from the core, NS3, NS4A, NS4B, and NS5A regions of
the HCV genome.
Even though sensitivity increases as newer generations of EIAs are developed for diagnosis of
HCV infection, the specificity and sensitivity has varied between the different anti-HCV
generation kits (Callahan et al., 1993; Abdel-Hamid et al., 2002; Galel et al., 2002). For this
reason, supplemental tests like the recombinant immunoblot assay (RIBA) which possess high
specificity and are useful in identifying false-positive test results, have been used (Schroter et
al., 2001). However, the RIBA is an expensive test. Also, samples giving discordant results in
multiple EIAs of different generations are often indeterminate with the RIBA (Abel-Hamid et
al., 2002). As a result, quantitative HCV RNA methods have been used to detect active
infection (Lunel et al., 1996; Colin et al., 2001), thus confirming samples with positive or
indeterminate EIA results.
In East Africa, few studies have been done to evaluate the performance of anti-HCV EIAs.
During an HIV vaccine trial, IAVI 009, conducted in Entebbe Uganda in 2003, varied
sensitivities were observed between two EIAs used to screen for HCV infection namely the
fourth generation Innotest HCV Ab IV EIA kit (Innogenetics) and the second generation
3
Cobas Core anti-HCV EIA II kit (Roche). Out of 15 samples that were positive on the EIA-4,
only 3 were positive with the EIA-2 kit. Supplemental testing of the 15 positives by HCV
RNA branched chain DNA assay (bDNA) was not concordant with either of the EIA kit.
Similar findings were observed by Callahan et al., (1993) while working with samples from a
Ugandan population in which two EIA-2 kits and two supplemental assays, second generation
RIBA and line immunoassay (Innogenetics) exhibited a significant degree of discordance.
Most anti-HCV EIAs being used today are predominantly based on antigens derived from
HCV genotype 1. For EIA-4, HCV genotypes 1a, 1b, 2 and 3a were used. In Africa,
genotypes 4 and 5 are the most prevalent (Forns & Bukh, 1998; Zein, 2000) but in East
Africa, few studies have been done to determine the most prevalent genotypes. Nevertheless,
genotype 4 has been commonly identified in some selected populations in East Africa (Biggar
et al., 2006, Muasya et al., 2008). HCV genotype specific serological activity has been
previously reported (Dhaliwal et al., 1996; Neville et al., 1997), affecting the sensitivity of
HCV EIAs.
1.2 Statement of the problem
Infection with HCV is a public health problem with approximately 3% of the world’s
population infected with this virus (WHO, 1999). It is estimated that this infection accounts
for 27% of liver cirrhosis and 25% of primary hepatocellular carcinoma worldwide (Alter,
2007).
4
In East Africa, EIA reactive (EIA-positive) samples are rarely confirmed with more specific
tests (Biggar et al., 2006, Hladik et al., 2006). Furthermore, few countries in this region
routinely screen blood for HCV mainly because of the high costs involved (Madhava et al.,
2002). In Uganda for example, the cost of screening blood for HCV was estimated to be 112
times higher than that of hepatitis B screening, which is routinely done (Hladik et al., 2006).
Whereas immunoblot assays can be used as confirmatory HCV tests, they have major
limitations including not detecting HCV in the window period of infection and frequently
producing indeterminate results (Abdel-Hamid et al., 2002). The use of more specific antiHCV EIAs can therefore drastically reduce the cost of HCV screening in East Africa by
reducing the number of samples requiring confirmatory testing.
Most of the EIAs being used today were made using HCV genotype 1 antigens and to a lesser
extent genotypes 2 and 3. These genotypes (1-3) are the most prevalent ones in Europe and
North America. Studies done in some parts of Africa have identified genotypes 4 and 5 as the
most prevalent (Forns & Bukh, 1998; Zein, 2000). In East Africa, the few studies done so far
have reported genotype 4 (Biggar et al., 2006; Muasya et al., 2008). Some studies reported
that there exists differences in serological re-activities among the different HCV genotypes
(Neville et al., 1997, Dhaliwal et al., 1996). It is, therefore, possible that current generation
EIAs do not optimally detect the HCV genotypes found in East Africa.
1.3 Aim of the study
The purpose of this study was to verify the results of hepatitis C virus antibody reactive serum
samples from East Africa through viral RNA detection and to determine their genotypes.
5
1.4 Specific objectives of the study
1. To determine the percentage of anti-HCV EIA reactive samples with detectable HCV
RNA using an in-house RT-PCR.
2. To measure viral loads in the anti-HCV EIA reactive samples irrespective of the inhouse RT-PCR results.
3. To establish the HCV genotypes in the HCV RNA-positive samples.
1.5 Study questions
1. What is the correlation between anti-HCV EIA reactivity and the detection of HCV
RNA in serum samples from East Africa?
2. What are the HCV genotypes of anti-HCV EIA reactive samples from East Africa?
1.6 Scope
This study was conducted using archived serum samples from sites in three East African
countries i.e. Uganda (Masaka and Entebbe), Kenya (Kilifi), and Rwanda (Kigali). These
samples had been collected during the screening phase of a laboratory reference range study
conducted in 2005 to determine the normal haematology and biochemistry values of East and
Southern African populations. They were from clinically healthy adult volunteers screened for
HCV infection using two anti-HCV EIAs. All anti-HCV EIA positive samples identified
during this screening process and a few negative samples were shipped on dry ice from the
above mentioned countries to the Uganda Virus Research Institute (UVRI) where RNA
6
extraction, in-house RT-PCR and HCV genome sequencing were done. Samples were also
shipped to the National Health Laboratory Services (NHLS) in Johannesburg, South Africa
for HCV viral load measurement. This viral load testing was done by the NHLS staff
following established procedures.
1.7 Justification and significance of the study
This study will help in the development of a cost effective and reliable in-house RT-PCR that
can be used to confirm anti-HCV EIA-positive samples in East Africa. Two HCV RNA
detection methods namely, an in house RT-PCR and a commercial real time RT-PCR Cobas
Ampliprep/Cobas Taqman (CAP/CTM) were used in this study. Whereas both methods are
very sensitive and specific, the CAP/CTM HCV assay is more robust and reproducible
because it is fully automated (Majid and Gretch, 2002). On the other hand, the in-house RTPCR is less expensive costing about USD30 (UGX. 76,320) per test as opposed to the
USD150 (UGX. 381,600) required for the CAP/CTM HCV test. This makes the former
method more cost effective than the latter for use in the resource-limited countries of East
Africa.
With increasing access to antiretroviral therapy across Sub-Saharan Africa, HCV/HIV coinfection is an issue of concern. As HIV-infected individuals live longer, the effects of coinfection with chronic hepatitis C becomes more relevant. Indeed, HIV adversely affects the
natural history of HCV, both of which are endemic across the African continent (Apurva &
Jordan, 2007). Patients infected with both viruses have been reported to progress to cirrhosis
7
faster than those infected with HCV alone (Benhamou et al., 1999; Puoti et al., 2001).
Therefore, it is important that HCV infection be accurately confirmed especially in HIVpositive patients in order to better manage hepatotoxicity issues that are commonly associated
with highly active anti-retroviral treatment.
This study will also help determine the reliability of current generation anti-HCV EIAs in
detecting HCV in samples from East Africa. It will also ascertain whether HCV genotypes
found in East Africa are readily detected by the current anti-HCV EIAs that were designed
using antigens from genotypes commonly found in the developed world. Consequently, this
study will help to determine whether it is it is important to design anti-HCV EIAs using HCV
antigens from genotypes commonly found in their intended region of use.
8
CHAPTER TWO
LITERATURE REVIEW
2.1 The Hepatitis C virus infection
Hepatitis C is an infectious disease of the liver caused by the hepatitis C virus (Choo et al.,
1989). Acute infection is rarely detected because the majority of newly infected people
develop only mild or no clinical symptoms. Approximately 75% to 85% of those infected do
not clear the virus and develop chronic HCV infection marked by the persistence of serum
HCV antibodies for at least 6 months after the onset of acute HCV infection (Chen & Morgan,
2006). The rate of chronic infection is affected by a person’s age, gender, race and viral
immune response (Seef, 2002). An estimated 10% to 15% of infected persons advance to liver
cirrhosis within the first 20 years of infection (Chen & Morgan, 2006).
Transmission of HCV is mainly through direct contact with blood. Other routes of infection
are less efficient (Macdonald et al., 1996). In countries where routine screening of donated
blood is not done, blood transfusions are a major route of infection. For example, in Benin
where routine blood screening is not done, an HCV antibody prevalence of 17% was reported
in sickle cell patients who had at least three life-time transfusions verses 0% in those without
that history (Jeannel et al., 1998).
At present, there is no vaccine against HCV for a number of reasons. The virus is highly
mutable with escape mutations undermining vaccine-induced virus-specific immunity. Lack
of a small animal model and cell culture systems have also posed problems for vaccine
9
development and testing (Abrignani, et al., 1999). Due to the limited tissue tropism and host
selection, HCV could be generated in vitro in tissue culture systems only very recently
(Chevaliez & Pawlotsky, 2006). In the absence of tissue culture techniques, adequate number
of viruses could not be generated for vaccine antigen development.
2.2 The Hepatitis C virus structure
The hepatitis C virus is an enveloped positive-sense single-stranded RNA virus with a
diameter of about 50 nm (Choo et al., 1989). It is classified as a separate genus Hepacivirus
within the Flaviviridae family. The HCV genome contains approximately 9400 nucleotides
with a single open reading frame (ORF) flanked by 5’ and 3’ untranslated regions (UTR) that
are important for the translation and replication of the viral RNA. The polyprotein precursor
encoded by the open reading frame is cleaved by viral and host proteases into the core (C)
protein, envelope 1 and 2 (E1 and E2) glycoproteins, as well as 6 non-structural proteins
(NS2, NS3, NS4A, NS4B, NS5A and NS5B) (Choo et al., 1989). A seventh non-stuctrual
polyprotein, p7 was discovered later on (Lin et al, 1994; Mizushima et al., 1994). See figure 1
below.
Figure 1: Schematic representation of the HCV genome (Adapted from Chevaliez &
Pawlotsky, 2006)
10
2.3 HCV genome variability
Different isolates of HCV show substantial nucleotide sequence variability distributed
throughout the viral genome. Regions encoding the envelope proteins El, E2 and the
nonstructural protein NS-1 are the most variable (Weiner et al., 1991), whereas the 5' untranslated region (5'UTR) is the most conserved (Han et al., 1991; Okamoto et al., 1990).
Nucleotide sequence variability in the 5’UTR also differs from that found in the coding
regions in that there are no reliable sequence polymorphisms in this region to allow for the
differentiation of HCV subtypes. The HCV subtypes 1a, 1b and 1c show essentially the same
sequences in the 5’UTR as do subtypes 2a and 2c for example (Simmonds et al., 1993).
Variability of the sub genomic region of NS5 is generally representative of the virus as a
whole; therefore, sequencing larger pieces of the genome is not necessary in order to subtype
the virus (Mellor et al., 1995).
2.4 HCV genotype distribution
According to a WHO report of 2009, the global distribution of hepatitis C virus genotypes
indicates that the hepatitis C virus is genetically diverse (Figure 2). Several typing
methodologies have led to a consensus nomenclature of six major HCV genotypes and over
80 subtypes distributed across the world (Kuiken et al., 2005). Genotypes differ at more than
30% of nucleotides across the entire genome while subtypes vary at more than 20% of the
sites (Simmonds et al., 1995). Genotypes 1, 2 and 3 have a worldwide distribution
predominating in Northern Europe and North America, Southern and Eastern Europe and in
Japan (McOmish et al., 1994, Davidson et al., 1995, Zein, 2000). In Central and North
Africa, the most prevalent genotype is 4 (McOmish et al., 1994; Ndjoumu et al., 2003),
11
whereas in West Africa, genotypes 1, 2 and 4 have been isolated (Oni & Harrison, 1996;
Jeannel et al., 1998). Genotype 5 has been identified mostly in South Africa accounting for
about 40% of all infections whereas genotype 6 is found mainly in Eastern Asia (Smuts &
Kannemeyer, 1995).
Figure 2: Global distribution of Hepatitis C virus genotypes (WHO, 2009)
In East Africa, few studies have been conducted to identify the circulating genotypes. A study
that was done in Uganda among sickle cell children and their mothers identified only
genotype 4 (Biggar et al., 2006). Another study conducted in Kenya among a high-risk cohort
12
of illicit drug users identified both genotypes 1 and 4 (Muasya et al., 2008). More studies
using samples from the general population are required to confirm these findings.
The clinical significance of HCV genotyping is that it guides clinicians in determining the
course and duration of antiviral therapy when treating HCV infected patients. For example,
patients with genotype 2 or 3 require on average 24 weeks of treatment, while those with
genotype 1 require 48 weeks (Zuezem et al., 2009).
2.5 HCV genotyping methods
The gold standard of HCV genotyping is to amplify viral nucleic acid and perform direct
nucleic acid sequence analysis of the region of the viral genome to be classified (Majid &
Gretch, 2002). Most commercial methods target the 5′UTR because of its high degree of
conservation among different subtypes. However, this region does not allow sufficient
discrimination between closely related subtypes within the same genotype. As a result,
sequencing of an appropriate coding region enables better discrimination of HCV types and
subtypes.
The chain termination method introduced in 1975 by Sanger and co-workers became the
sequencing method of choice owing to its relative ease and reliability. In this method, PCR is
conducted in the presence of dideoxynucleotides (ddNTPs) which are the chain-terminating
nucleotides lacking a 3'-OH group required in the formation of a phosphodiester bond
between two nucleotides. This results in the termination of DNA elongation leading to the
formation of DNA strands of varying lengths. The newly synthesized and labelled DNA
13
fragments are heat denatured and separated by size using gel electrophoresis on a denaturing
polyacrylamide gel. The DNA bands are then visualized by autoradiography or ultraviolet
(UV) light and the DNA sequence can be directly read off the X-ray film or gel image (Sanger
et al., 1977).
Today, sequencing is frequently done using the dye-terminator sequencing method introduced
by Hood and co-workers (Smith et al., 1986). This method employs four ddNTP chain
terminators, tagged with dyes of different fluorescent emission wavelengths in a single
sequencing reaction. Detection is done using a laser fluorescence detector combined with a
computer. Using specialised software, generated sequences are cleaned up and then compared
to those in sequence databases to deduce phylogenetic relationships. The main disadvantage
of genotyping by direct nucleic acid sequencing is that it is very expensive and complex to be
used on a large scale or routine clinical basis. Its major advantage is its robustness and speed
(Majid & Gretch, 2002).
Another method that can be used to genotype HCV is by use of PCR using type-specific
oligonucleotide primers for core, NS5 and E1 regions of the HCV genome. This qualitative
PCR methodology is prone to technical issues related to conventional qualitative PCR namely
contamination, optimization for sensitivity, specificity and standardization. Development of
new automated real time PCR genotyping platforms using genotype/subtype specific probes
has greatly minimized the limitations of this method (Nakatani et al., 2010).
14
Restriction fragment length polymorphism (RFLP) analysis on the PCR products of 5'UTR
and NS5 has also been used to genotype HCV (Nakao et al., 1991). Specific restriction
endonucleases are used to cleave amplicons containing conserved mutations in these regions
relative to other HCV genotypes. Only certain genotypes are cleaved by specific restriction
enzymes and unique RFLP patterns are observed on ethidium bromide-stained gels. Whereas
this technique is useful in the high-throughput setting, its limitations include PCR dependency
and potential partial digestions of amplicons leading to unclear RFLP patterns (Majid &
Gretch, 2002).
Commercial methods are also available for genotyping HCV. These include the DNA
hybridization method INNO-LiPAHCV II (Innogenetics, Ghent, Belgium) and the direct
sequencing method using the TRUGENE HCV 5’NC genotyping kit (Visible Genetics,
Ontario, Canada). In the INNO-LiPAHCV II method, biotinylated PCR amplicons bind to
type-specific DNA probes immobilized on nitrocellulose strips. Positive reactions are then
identified using a streptavidin-colorimetric reaction. Although both methodologies are reliable
at genotyping HCV, the TRUGENE HCV 5’NC genotyping is more superior at the sub typing
level (Zekri, et al, 2007).
2.6 HCV diagnosis
The laboratory diagnosis of HCV infection is usually made on the basis of detection of HCV
antibodies using anti-HCV EIAs. Whereas these assays are useful in diagnosing exposure to
HCV, they neither provide evidence of active viremia nor identify persons in the window
period. In such circumstances, nucleic acid testing to detect HCV RNA is recommended.
15
Hepatitis C Virus RNA becomes detectable 7-14 days after exposure as opposed to the
antibodies which may take between 4-10 weeks to develop (Caruntu & Benea, 2006).
Serological tests used to detect HCV antibodies are generally classified as screening tests or
confirmatory tests. Screening tests provide the presumptive identification of antibody positive
specimens, while confirmatory tests are used to confirm that specimens found reactive with a
particular screening test contain antibodies specific to HCV. When several screening tests are
used in a testing algorithm to determine a final sero-status, these second and/or third line tests
are generally referred to as supplemental tests (WHO, 2001).
Confirmatory assays that are commercially available for the diagnosis of HCV include
line/strip immunoassays and assays using Nucleic acid tests (NATs). Line/strip immunoassays
have individual recombinant or synthetic antigens applied as separate lines to the solid phase.
In this way the different antigens to which antibodies in a specimen are reacting can be
distinguished. The application of established confirmation patterns of reactivity observed
permits greater specificity. Examples of line/strip immunoassays include RIBA HCV 3.0 SIA
(Chiron Corporation) and Inno-LIA HCV antibody III (Innogenetics).
For screening and supplemental tests to be used in an HCV confirmatory strategy, they must
be carefully selected to ensure that common false reactivity between these assays does not
occur. In developing countries, supplemental tests are often omitted because of their high cost
therefore, the reliability of the anti-HCV EIAs becomes very important (Abdel-Hamid et al,
2002).
16
2.7 HCV nucleic acid testing
Nucleic acid tests (NATs) that detect HCV RNA can also be used as supplemental tests for
anti-HCV EIAs. They are commonly used in clinical practice to confirm HCV diagnosis and
to assess viremia in patients undergoing antiviral treatment (Zuezem et al., 2009). Nucleic
acid tests are based on the PCR technique and can either be qualitative or quantitative.
2.7.1 The COBAS Ampliprep/Cobas Taqman HCV Test
The COBAS Ampliprep/Cobas Taqman (CAP/CTM) HCV test is a real time PCR test for the
quantification of HCV RNA in human serum or plasma. Specimen preparation, reverse
transcription, PCR amplification and detection are all automated. The method relies on
amplification of viral nucleic acids in the presence of a specific competitor molecule called
the Quantitation Standard (QS). The HCV QS contains HCV sequences with identical primer
binding sites as the HCV target RNA and a unique probe binding region that allows HCV QS
amplicon to be distinguished from HCV target amplicon. The quantity of HCV RNA is
measured by comparing the ratio of amplification products derived from the viral RNA and
the HCV QS. A known amount of QS RNA is titrated directly into the sample and is extracted
together with the target HCV RNA before analysis by competitive reverse transcription PCR.
Adding the QS directly into the clinical specimen allows the assay to be internally controlled
for variations in efficiency of RNA extraction, complementary DNA synthesis and PCR
because the QS is present at all steps. The CAP/CTM HCV test is very sensitive with a
reported lower limit of detection of 7.4 IU/ml and similar detection rates across all HCV
genotypes (Sarrazin et al, 2008; Vermehren et al., 2008).
17
2.7.2 RNA extraction
In order to successfully detect HCV RNA, an effective HCV RNA isolation method needs to
be used. Traditionally, RNA extraction utilised phenol chloroform separation of nucleic acids
from proteins. Whereas this method is very effective in RNA isolation, its major downside is
the use of hazardous chemicals in addition to being laborious.
As an alternative, isolation of viral RNA may be done using commercial RNA extraction kits
for example the QIAamp viral RNA mini kit (Qiagen, Hilden, Germany). This kit makes use
of microspin technology and the selective binding properties of silica-gel based membrane to
isolate RNA. Buffer is used to provide highly denaturing conditions to inactivate RNases.
Carrier RNA is also added to enhance binding of the RNA to the QIAamp mini membrane
and to reduce the chance of viral RNA degradation. This kit has been found to be very
efficient in the extraction of HCV RNA when compared to other kits of a similar nature
(Read, 2001).
2.7.3 Reverse transcriptase PCR
Reverse transciptase and primary PCR may be done using a OneStep PCR approach whereby
reverse transcription and amplification of the generated complimentary DNA (cDNA) are
carried out sequentially in the same tube. Reverse transcriptase and DNA polymerase
enzymes are used within the same reaction mix to enable reverse transcription and DNA
amplification to take place. During reverse transcription, chemically modified DNA
polymerase is completely inactive and does not interfere with the reverse transcription
reaction. After reverse transcription is complete, the reactions are heated to 950C for 15
18
minutes to activate the DNA polymerase and to simultaneously inactivate the reverse
transcriptase. This OneStep PCR method has been found to be superior to the two step PCR
approach where reverse transcription is done separately from cDNA amplification (Sergio, et
al, 2004).
The RT-PCR is capable of detecting RNA in samples of low level viremia with the most
sensitive and optimized PCR assays detecting HCV RNA in serum at levels of less than 100
copies per ml or 40IU/ml (Majid & Gretch, 2002). In order to increase the sensitivity and
specificity of the PCR, a nested approach is used. In this method, primary PCR is done
followed by secondary PCR using different primers inner to those of the primary PCR. The
new primers hybridise to a sequence internal to the first round (primary) PCR primer target
sequence. As a result, only specific first round RT-PCR products are amplified in the
secondary PCR (Alberts, 2007).
19
CHAPTER THREE
METHODOLOGY
3.1 Research design
This was a cross sectional study that utilised stored serum samples previously tested for HCV
antibodies using two anti-HCV EIAs.
3.2 Ethical considerations
Ethical approval for this study was obtained at various levels and stages of the study. Before
the start of the study, ethical approval was sought from the UVRI Science and Ethics
Committee where most of the analysis and data collection was done. In addition, approval
was sought and obtained and from the Uganda National Council of Science and Technology
(UNCST). In order to obtain samples from the various sites in East Africa, ethical approval
also was sought and obtained from the Science and Ethics Committees of each of these sites.
Informed consent had been previously obtained from participants allowing the conduct of
research on their samples.
3.3 Sample population
The serum samples used in this study were obtained from another study whose objective was
to establish the normal haematology and biochemistry laboratory reference ranges for East
and Southern African populations (Stevens et al., 2008). In the reference range study,
clinically asymptomatic volunteers were recruited from various sites namely; Masaka and
20
Entebbe (Uganda); Kilifi, Mtwpa, Kangemi, Nairobi (Kenya); Kigali (Rwanda) and Lusaka
(Zambia). Individuals who were acutely ill, pregnant, menstruating, or had significant clinical
findings were not included. Those enrolled were tested for various infections including HCV
and all had tested HIV negative within three months prior to screening. Below is a breakdown
of the characteristics of the population for those sites where samples were obtained for this
evaluation. Zambian samples and those from some Kenyan sites were not included because all
sample aliquots from these sites had been used up.
Masaka-Uganda. Eligible volunteers were selected from a rural general population cohort
enrolled into prospective HIV incidence studies in preparation for HIV vaccine trials. A total
of 52 samples from this area were obtained from individuals identified to have splenomegaly
and subsequently screened out. These 52 volunteers were later tested for anti-HCV and found
to be positive.
Entebbe-Uganda. Volunteers were drawn from community members who either had
expressed interest to participate in future clinical trials, or were pre-screened for a previous
HIV vaccine phase 1 clinical trial but were not enrolled because the trial had completed
enrollment.
Kilifi-Kenya. Half of this site’s study volunteers were from an HIV prevalence study in Kilifi
Town, and half were selected from individuals who were enrolled in HIV incidence studies in
preparation for HIV vaccine trials.
Kigali-Rwanda. Half of the volunteers were drawn from large prospective studies of longterm, stable sexually active couples of HIV discordant status (the volunteer’s partner was HIV
positive), and half were drawn from couples identified during couples’ voluntary counseling
and testing as concordant HIV-negative (both partners HIV negative).
21
3.4 Sampling procedure
Convenience sampling was used to arrive at the sample size used in this study. All samples
that were anti-HCV EIA-positive in the aforementioned laboratory reference range study and
a few negatives were used for this evaluation. The total sample size was 167 of which 151
were anti-HCV EIA positive and 16 were anti-HCV EIA negative (Table 1).
Table 1: Sample selection across the different sites
Site
EIA Used
Kigali, Rwanda
Murex anti HCV Version 4.0
(Abbot)
Entebbe, Uganda Innotest HCV Ab IV (Innogenetics)
Masaka, Uganda Innotest HCV Ab IV (Innogenetics)
Kilifi, Kenya
Innotest HCV Ab IV (Innogenetics)
Total
Number of
Positives
13
Number of
Negatives
2
Total
10
98
30
151
1
10
3
16
11
108
33
167
15
HCV antibody testing had been done using two anti HCV EIAs, namely, the Innotest HCV
Ab IV (Innogenetics NV, Gent, Belgium) and Murex anti-HCV Version 4.0 (Abbott
Laboratories, Chicago, IL) following the manufacturers’ instructions in the kit. Samples from
the Ugandan and Kenyan sites had been tested using the former EIA while those from
Rwanda were tested using the latter EIA. The testing was done from the site of origin of these
samples by the staff of these sites. Sample aliquots archived after completion of the laboratory
reference range study where later shipped on dry ice to UVRI to undergo evaluation for this
study.
The samples used for this study do not represent a true random sample of the local population
because volunteers had been selected from participants of ongoing research, or those with a
22
previous interest in participating in research studies. The Masaka site was an exception
because volunteers from there were recruited from the general population after the entire adult
population of three villages had been informed of upcoming research activities.
3.5 Laboratory data collection
3.5.1 RNA extraction
All serum samples were extracted using the QIAamp Viral RNA extraction kit (Qiagen,
Hilden, Germany) following the manufacturer’s instructions. The spin protocol was used. In
summary, 140µl of serum sample was added to 560µl of viral lysis buffer dissolved with
5.6µl carrier RNA (1µg/ml). The mixture was then vortexed for 15 seconds. After 10-minute
incubation at room temperature to allow for viral particle lysis and inactivation of RNases,
560µl of 96% ethanol was added to the sample to facilitate the release of RNA. The solution
was then vortexed for a further 15 seconds and then applied onto the QIAamp mini spin
columns into two aliquots of 630µl each. A centrifugation at 6000g for 1 minute was done in
between the two aliquots with the filtrate being discarded. After centrifugation, two wash
buffers AW1 and AW2 (500µl each) were then added in succession with a 1-minute
centrifugation at 6000g and 20,000g, respectively, in between additions. Finally, the RNA
bound to the membrane was eluted into a clean 1.5ml micro centrifuge tube by addition of
80µl of elution buffer AVE (RNase free water containing 0.04% sodium azide) to the mini
spin column followed by a 1 minute centrifugation at 6000g. The extracted RNA was then
temporarily stored at -200C awaiting RT-PCR which was done within a week from extraction.
23
3.5.2 Polymerase chain reaction analysis
Primary and secondary PCR were performed on the extracted RNA following a nested PCR
approach. Reverse transcription and primary PCR were done in a ‘one step’ reaction using the
Qiagen Onestep RT-PCR Kit (Qiagen, Hilden, Germany) which uses specially formulated
reverse transcriptase and DNA polymerase enzymes for reverse transcription and PCR
amplification, respectively. Primers targeting the NS5B region of the HCV genome (See
figure 1) were used with the sequences 5’-TAT GAY ACC CGC TGY TTT GAC TC-3’ and
5’-GCN GAR TAY CTV GTC ATA GCC TC-3’ for reverse transcription and primary PCR
and 5’-CAT AGC CTC CGT GAA GRC TC-3’ and 5’-TAT GAY ACC CGC TGY TTT
GAC TC-3’ for the secondary PCR (Mejri et al., 2005). They were manufactured by
Eurogentec S.A, Belgium. Secondary PCR was done using the Qiagen Taq PCR master mix
kit (Qiagen, Hilden, Germany). Components for both primary and secondary PCR and the
thermocyling conditions that were used are outlined in tables 2 and 3. The thermo cycling
program recommended in the kit insert was used.
24
Table 2: Reaction components for RT, primary and secondary PCR mixtures
Volume/reaction (µl) Final concentration
Component
RT & Primary PCR
Water
5X Qiagen OneStep RT-PCR buffer
containing 12.5Mm MgCl2
dNTP mix (containing 10mM of each
dNTP)
Forward primer (50µM)
Reverse primer (50µM)
Qiagen OneStep RT-PCR Enzyme Mix
RNase inhibitor (5units/µl)
RNA template
Total Volume
Secondary PCR
Master Mix
Water
DNA template from 10 PCR
Forward primer (50µM)
Reverse primer (50µM)
Total Volume
8.3
-
10.0
1X
2.0
400µM of each dNTP
0.6
0.6
2.0
1.5
25.0
50.0
0.6 µM
0.6 µM
7.5units/reaction
-
50.0
43.0
5.0
1.0
1.0
100
0.5µM
0.5µM
-
25
Table 3: Thermo cycling conditions used for RT, primary and secondary PCR
Temperature (0C)
Process
Time
RT & Primary PCR
Reverse Transcription
50
30 minutes
Initial PCR activation step
95
15 minutes
3- Step Cycling 1 (5 cycles)
Denaturation
Annealing
Extension
3- Step Cycling 2 (30 cycles)
Denaturation
Annealing
Extension
3- Step Cycling 3 (5 cycles)
Denaturation
Annealing
Extension/Elongation
94
62
72
30 seconds
45 seconds
1 minute
94
55
72
30 seconds
45 seconds
1 minute
94
52
72
30 seconds
45 seconds
1 minute
Final Extension
Hold
72
4
10 minutes
1-16 hours
Secondary PCR
Denaturation
95
5 minutes
3-step cycling (35 cycles)
Denaturation
Annealing
Extension
95
55
72
30 seconds
30 seconds
30 seconds
Final extension/Elongation
Hold
72
4
10 minutes
1-16 hours
26
3.5.3 Visualisation of the PCR products
The PCR amplicons were visualised using a 1.5% agarose gel stained with 5µl ethidium
bromide. The gel was prepared by dissolving 1.5 grams of agarose powder in 100ml of 0.5X
Tris-Borate-EDTA buffer (pH8). The solution containing the partially dissolved powder was
heated in a microwave oven for 3 minutes to enable complete dissolution and then 5µl of
ethidium bromide (10mg/ml) added to it and gently swirled. The solution was then poured
onto an electrophoresis tray. Combs were then inserted into the liquid gel to create wells for
sample addition. After solidification of the gel, the combs were removed and approximately
100ml of the 0.5X Tris-Borate-EDTA buffer poured onto the electrophoresis tray completely
immersing the gel. A mixture of 8µl of sample and 2µl of gel loading buffer dye (5X) was
then loaded into the agarose gel wells using a micropipette. In addition to sample, positive and
negative control samples obtained from the WHO HCV reference laboratory were also added
in the same manner as the samples. A 100bp DNA molecular weight marker (New England
Biolabs) was added to an adjacent well to enable size estimation of the resolved bands. The
gel was left to run for 45 minutes at 100 volts. At the end of the 45 minutes, the gel was
placed on an ultra violet (UV) illuminator to visualise the bands and a digital image of the gel
captured.
3.5.4 Purification of PCR products
The PCR amplicons were purified using the QIAquick PCR Purification kit (Qiagen, Hilden,
Germany) following manufacturer’s instructions. In summary, 500µl of buffer PB was mixed
with approximately 92µl of amplicon left after electrophoresis. A QIAquick column was then
27
placed in a 2ml collection tube and to this was added the sample mixture followed by
centrifugation at 17,900g for 1 min. The flow through was discarded and the QIAquick
column placed back into the emptied collection tube. Buffer PE (750µl) was added to the
QIAquick column and centrifuged at 17,900g for one minute. The flow through was discarded
again and the QIAquick column placed in a 1.5ml centrifuge tube. Elution buffer EB (30µl),
provided in the kit insert, was then added to the center of the QIAquick column, incubated for
1 minute and then centrifuged at 17,900g for one minute. The purified product was then
sequenced.
3.5.5 DNA sequencing
Sequencing was done using the Beckman Coulter 8000 genetic analysis system machine and
sequences analysed using the sequencher software version 4.6. In summary, reaction mix was
made by mixing 1.0µl of the cleaned DNA template with 1.0µl of the secondary PCR primers
5’-CAT AGC CTC CGT GAA GRC TC-3’ and 5’-TAT GAY ACC CGC TGY TTT GAC
TC-3’(5µM) and 8.0µl of DTCS Quick start Master mix (Beckman Coulter, Fullerton, CA).
This mix was then placed in a PCR thermocyling machine. The program used was
denaturation at 96oC for 30 seconds, annealing at 50 oC for 15 seconds and extension at 60oC
for 4 minutes. This cycle was repeated 29 times cycles after which samples were held at 4oC
for up to 16 hours.
The PCR reaction mixture was cleaned by ethanol precipitation. In summary, the PCR
reaction was first stopped using a mixture of 2µl of 3M Sodium acetate (pH 5.2), 2µl of 100
28
mM Na2-EDTA (pH 8.0) and 1µl of 20 mg/ml of glycogen. This was followed by the addition
of 70µl of 95% ethanol. The plate containing the samples was sealed using aluminum foil lids
and vortexed for 5 seconds. It was then centrifuged at 3000g for 10 minutes after which the
plate was gently tapped on tissue paper to remove excess ethanol. While still inverted and
covered with tissue, the plate was centrifuged at 300g for 20 seconds. After this, 0.2ml of ice
cold 70% ethanol was added and the sample centrifuged at 3000g for 3 minutes at 40C to repellet the DNA. The plate was then inverted on tissue paper to remove excess supernatant.
The process of addition of 70% ethanol and centrifugation at 300g for 20 seconds was
repeated. The samples were then dried under a vacuum for 30 minutes. 40µl of sample
loading solution was then added to the pellet and mixed thoroughly for about 5 minutes. A
drop of mineral oil was then added to the sample which was thereafter loaded on to the
sequencing analyzer machine and the capillary electrophoresis program started. On
completion of the program, the generated sequences were exported to the sequencher software
version 4.6 from where they were edited.
3.5.6 Phylogenetic analysis
Using the Clustal W software, NS5B gene sequences were aligned together with reference
sequences obtained from the Los Alamos HCV sequence database. These sequences were
manually edited to remove gaps and trimmed to identical sequences using BioEdit Version
7.0.5.3. Phylogenetic analysis was performed using the MEGA Version 4.0 software. The
phylogenetic trees were estimated with the neighbour-joining methodology using the
Tamura’s 3-parameter model of evolution. This model was selected using the jModelTest
29
software. The robustness and reliability of the tree was determined using bootstrap analysis
with 1000 replicates.
3.5.7 HCV viral load testing
HCV viral load testing was done by the staff of the National Health Laboratory Services
(NHLS) in Johannesburg South Africa using the COBAS Ampliprep/Cobas Taqman analyser
(Roche Diagnostics, Pleasanton, USA). This is an automated HCV RNA extraction
instrument (COBAS AmpliprepTM) that is combined with a real time PCR machine, COBAS
TaqManTM 48 analyzer. The HCV RNA extraction and PCR amplification and detection using
the CAP/CTM HCV assay were done following manufacturer’s instructions. In brief, after
setting up the Cobas Ampliprep instrument, it was loaded with the reagent cassettes and
disposable items namely tips, sample processing units and sample tubes. The instrument was
then started to begin the RNA extraction process. After extraction, the tubes containing the
extracted RNA were transferred onto the Cobas Taqman 48 analyser to conduct the DNA
amplification and detection procedures. At the end of the detection process, results are
displayed on the computer in international units (IU).
3.6 Data quality control
In all the assays used in this study, negative and positive quality control samples were
included to validate the run. This applied to PCR, sequencing and viral load testing. Any runs
in which these controls failed were repeated.
30
Samples used in this study were stored, shipped and handled in a way that ensured their
integrity was not compromised at any stage. They were stored in -800C freezers that are
temperature controlled and continuously monitored. The same applied to the freezers and
fridges that stored the reagents and kits.
The laboratories that conducted EIA testing are accredited in Good Clinical Laboratory
practice (GCLP) by Qualogy Ltd, (UK) while the lab that conducted the viral load testing is
also accredited in the International Standards Organization Standards (ISO) by the South
African National Accreditation Scheme (SANAS). Extraction of RNA, PCR and sequencing
were conducted in a laboratory accredited by the World Health Organisation.
3.7 Data analysis
Enzyme immunoassay results were compared with both the PCR and HCV viral load results.
Results were tabulated in a 2x2 contingency table. The Fisher’s exact test of association was
used to compare antibody results to those of the in-house RT-PCR and the CAP/CTM HCV
test.
31
CHAPTER FOUR
RESULTS
4.1 Comparison of anti-HCV EIA results with RT-PCR results
The figure below shows the agarose gel image of one of the PCR runs.
Fig. 3: Agarose gel showing results for samples from Rwanda. The gel contained two rows
of wells. The first row contained the samples while the second row contained the controls.
Letters M, N and P represent the marker, negative control, and positive control, respectively.
The numbers 1-15 represent the different samples run on this gel. Samples 1-5, 11, and 12
were HCV RNA positive. The amplified band product was 384bp.
Out of the 151 anti-HCV EIA samples, only 9 samples (6%) were positive by the in-house
RT-PCR assay. All the 16 anti-HCV EIA negative samples were RT-PCR negative (Table 4).
Table 4. Contingency table of anti-HCV EIA results against PCR results
PCR Positive
PCR Negative
EIA Positive
9
142
EIA negative
0
16
Total
9
158
Total
151
16
167
32
Using Fisher’s exact test of association to measure the correlation between EIA reactivity and
in house RT-PCR positivity, the p-value at 5% level of significance was 0.603.
4.2 Comparison of anti-HCV EIA results with the real-time PCR results
The real-time PCR results were similar to those obtained from the in-house RT-PCR. Only 9
out of 152 anti-HCV EIA positive samples had detectable HCV viral loads. All the 16 antiHCV EIA negative samples had undetectable HCV viral loads. Samples that were positive by
the in-house RT PCR were those previously detected by the real-time PCR. The viral loads
ranged from 19 IU/ml to 1,058,000 IU/ml as shown in table 5 below. The majority (seven) of
the samples with detectable HCV RNA were from Rwanda.
Table 5. HCV Viral loads of PCR positive samples by country of origin
Agarose gel IDa
Viral load (IU/ml)
Sample Origin
b
Not applicable
19
Uganda
4
3,740
Rwanda
1
4,420
Rwanda
12
16,300
Rwanda
2
35,200
Rwanda
5
71,400
Rwanda
Not applicableb
102,400
Uganda
11
684,000
Rwanda
3
1,058,000
Rwanda
a
Represents position of the sample on the agarose gel shown in Figure 3
b
Samples from Uganda were run on two different gels
A total of 12 out of 167 samples were not tested by real-time PCR due to control failure.
Repeat testing was not possible due to lack of extra sample aliquots. All the failed 12 samples
were in-house RT-PCR negative.
33
4.3 Types of HCV genotypes
Sequencing and phylogenetic analysis of the PCR positive samples only identified HCV
genotype 4. The phylogenetic tree in Figure 4 below shows the subtypes identified.
Fig. 4: Phylogenetic analysis of HCV NS5b sequences. A neighbour-joining
phylogenetic tree was built from isolates and reference sequences for the various HCV
genotypes from the Los Alamos HCV sequence database. The Tamura 3-parameter
method was used to estimate the genetic distances. The samples that were genotyped
in this study are highlited in bold with the code_HCV. The Ugandan samples are
7449_HCV and 4211_HCV while the rest of the samples were from Rwanda
34
CHAPTER FIVE
DISCUSSION
Results from this study demonstrated a very poor correlation between EIA reactivity and the
detection of HCV RNA. Only 9 (6%) of the 151 EIA-positive samples were positive by both
the in-house RT-PCR and the CAP/CTM HCV real time PCR. Using Fisher’s exact test of
association, the p-value at 5% level of significance was 0.603, indicating a lack of association
between EIA reactivity and HCV RNA detection. These results are suggestive of a high false
positive rate of the anti-HCV EIAs within the study population that cannot not be fully
explained by other factors as discussed below.
The poor correlation between EIAs and confirmatory testing has previously been reported in
East Africa and this study provides further evidence of this. For example, a study conducted
in Uganda among hospital patients recently reported that out of 166 anti-HCV EIA-3 positive
samples, only 48 (29%) had detectable HCV RNA (Seremba et al., 2010). An earlier study
also done in Uganda amongst blood donors found that out of 107 EIA positive samples, only
15 (16%) were positive and 47 (50%) indeterminate on RIBA (Hladik et al., 2006). In
Tanzania, a positive predictive value of only 18.8% for the third generation anti-HCV EIA
was reported among the general population (Tess et al., 2000). In India, a false positive rate of
82.4% and 78.5% as confirmed by PCR and immunoblot respectively was reported (Thakur et
al., 2008; Raghuraman et al., 2003). These results contrast sharply with those in the
developed countries where the specificity anti-HCV EIAs is reported to be very high (greater
than 98%) (Colin et al., 2001; WHO, 2001).
35
False positive results in earlier generations of anti-HCV EIAs were attributed to non-specific
antibody binding or possibly to cross-reactivity with other tropical pathogens such as other
flaviviruses (McFarlane et al., 1990; Sonmez et al., 1997). Samples used in this study were
not tested for the presence of other flaviviruses. However, in one of the studies done in
Uganda, samples were tested for the West Nile Virus one of the most common flaviviruses in
tropical Africa. None of the samples were positive for the flavivirus suggesting that crossreacting antibodies at least to this virus were unlikely (Seremba et al., 2010) but suggested
that antibodies resulting from antigens unique to Uganda may be cross reacting with the
hepatitis C virus.
Another reason that was advanced for the high false positive rates of the anti-HCV EIAs was
the high levels of serum IgG that cross-react with the antigens used in the EIAs. This
hypergammaglobulinemia has been reported in tropical countries due to the endemic parasitic
and infectious diseases found in this region (Raghuraman et al., 2003). The study population
from which samples for this study were obtained had a high rate of infectious diseases. This
was characterised by the high number of clinically asymptomatic participants excluded due to
laboratory diagnosed infections (Stevens et al., 2008). These infections may have contributed
to the high number of anti-HCV EIA reactive samples that could not be confirmed by HCV
RNA tests in this study.
Another possibility is that these participants were originally infected with HCV but it was
eventually completely cleared from their blood. According to literature the HCV clearance
rates in the blood varies from 14% to 46% (Seef, 2002) and may go as high as 60% (Caruntu
& Benea, 2006). In Egypt, where HCV genotype 4 is the most dominant genotype by far,
36
HCV clearance rates were reported to be averaging 38.5% with more clearance being seen in
women (44.6%) as compared to the men (33.7%) (Bakr et al., 2006).
Although the hepatitis C virus may be cleared from the blood, it is almost always still present
in the hepatocytes (Hoare et al., 2008). In fact, non viremic patients exposed to HCV have
chronic low-level probably hepatic viral replication that is associated with a lower risk of
progressive liver injury (Hoare et al., 2008). The hepatitis C virus has also been detected in
the peripheral blood mononuclear cells of the majority of healthy patients who test positive
for anti-HCV antibodies and have normal alanine aminotransferase (ALT) levels but who do
not have HCV RNA detected in sera (Carreno et al., 2006).
Hepatitis C virus clearance rates vary depending on a number of factors including age at time
of infection, race, gender and development of symptoms at the time of infection (Chen &
Morgan, 2006). This study did not investigate the extent to which each of these factors could
have affected HCV clearance rates and subsequently EIA specificity.
Viremia levels of the 9 samples with detectable viral loads ranged from 19 IU/ml to 1,058,000
IU/ml. Majority (8 out of 9) of these samples may thus be categorized as having had ‘low’
viral loads because they were below 800, 000IU/ml the recommended threshold between low
and high viremia (Zeuzem et al., 2009). These viremia levels cannot be used to determine
whether the samples were from persons in the acute or in the chronic phase of infection. Both
phases can have similar viremia levels although the acute phase is characterised by large
fluctuations in viremia levels over time (Caruntu & Benea, 2006). In this study, samples were
37
collected from a single time point hence viremia level fluctuations overtime were not
measured.
It should be pointed out that viremia levels do not correlate with the severity of hepatitis or
with a poor prognosis (Seef, 2002). Viral load measurements are more commonly done to
help in the monitoring of response to anti-viral therapy (Majid & Gretch 2002). In East Africa
where treatment for HCV infection is rarely done, viral load measurement for clinical
management is still of little relevance.
This study demonstrated a 100% agreement between viral load testing (Real time PCR) and
RT-PCR. Samples that were RT-PCR positive also had detectable HCV RNA using viral load
testing. Much as the two methodologies are based on similar principles, improvements in real
time PCR have made this test very sensitive. Automation of RNA extraction and detection
clearly makes this test more robust and efficient when compared to the manual qualitative
RT-PCR. Nevertheless, results from this study showed that the qualitative RT-PCR which is
significantly cheaper than the real time PCR (USD30 vs. USD150) was adequately optimised
to detect HCV RNA even at very low concentrations. This is because the sample with the
lowest viral load of 19 IU/ml as reported by the real-time PCR test was readily detected by the
in-house RT-PCR. Qualitative in-house RT-PCR can therefore be used to confirm anti-HCV
EIA results in resource limited countries like those of East Africa instead of using the more
expensive real time PCR. The sample size used in this study was however too small to
provide conclusive results in this respect.
This study identified only genotype 4 in samples from Uganda and Rwanda. This finding is
consistent with previous studies (Biggar et al., 2006; Muasya et al., 2008). The two samples
38
from Uganda clustered in the same subgroup with four samples from Rwanda (Figure 4). The
remaining three Rwandese samples clustered in a different sub group. The identification of
similar HCV genotypes in these two countries is not surprising. This can be attributed to their
close proximity and substantial interaction amongst its people.
The HCV subtypes that were identified clustered with those that have been found in
Cameroon. Genotype 4 is commonly found in West and Central Africa where it is postulated
to have spread eastwards (Ndjomou et al., 2003). Failure to identify other genotypes notably
genotype 1 is also not suprising. This genotype which is prevalent in Europe was identified in
Kenya amongst drug users (Muasya et al., 2008), a population different in nature from that
used for this study. The small sample size used in this study might have been a factor that also
limited the chances of identifying this or any other HCV genotypes.
This study found that differences in the HCV genotype of the sample tested and the genotype
of anti-HCV antigens used in the EIAs does not affect EIA performance. The anti-HCV EIAs
that were used to screen these samples do not include antigens from genotype 4 whereas only
genotype 4 was identified. This result is important because some authors suggested that antiHCV EIA sensitivity is affected by the genotype diversity of the antigens used in the
immunoassays. Specifically, the core, NS3, NS4, and NS5 have been reported to show
antigenic variation among the different genotypes (Neville et al., 1997).
By comparing the serological reactivities of sera to type-homologous and type heterologous
antigens, significant type-specific component to the reactivity to NS3 and NS5 was detected
39
(Neville et al., 1997). A fivefold weaker reactivity of sera from HCV type 2- and HCV type
3-infected blood donors in the EIA-3 has been previously reported, suggesting that this EIA
was suboptimal for screening populations in which the predominant genotype is not type 1
(Dhaliwal et al., 1996). On the other hand, other studies have found that with the EIA-3,
genotype differences do not significantly affect EIA performance (Maggi et al., 1995;
Pawlotsky et al., 1995). The combination of core, NS3, NS4, and NS5 antigens in current
EIA-3 assays have enough cross-reacting epitopes for all genotypes (Sheiblauer et al., 2006).
In summary, this study has shown that the kits that were used to screen for HCV in the
samples used for this study are adequate in detecting this infection in samples from East
Africa even though giving a high number of potentially false positives. It is, therefore, not
necessary to design anti-HCV EIAs using antigens from HCV genotype 4 in areas where this
genotype is the most prevalent one.
40
CHAPTER SIX
CONCLUSIONS AND RECOMMENDATIONS
6.1 Conclusions
This study showed that there is a very poor correlation between anti-HCV EIA reactivity and
the detection of HCV RNA in serum samples from East Africa. Only 6% of anti-HCV EIA
reactive serum samples from East Africa contain detectable viral RNA.
Genotype 4 is the most common HCV genotype in anti-HCV EIA reactive serum samples in
East Africa. However, because of the small sample size of this study, (nine samples
genotyped), this finding is not definitive.
This study also suggested that HCV genotype 4 is readily detected by non-genotype 4 antigen
HCV EIAs although with a very high number of potentially false positives.
There is a perfect agreement between the in-house RT-PCR and real-time PCR. Either method
could be used to detect HCV RNA in serum samples. The small sample size of this study
however makes this conclusion not definitive.
6.2 Recommendations
A cost effective HCV testing algorithm should be developed for use in East Africa. Anti-HCV
positive samples should be confirmed with more specific tests like HCV RNA
detection/quantification assays. An in-house RT-PCR is a reliable confirmatory test that may
be used in place of the more robust but more expensive commercial real time PCR assays.
41
The anti-HCV EIAs that were used to screen samples used in this study may not be specific
enough to be recommended for use in this region. However, additional studies are required to
confirm these findings using a larger sample size.
Further investigations are required to examine the cause of the poor correlation between antiHCV EIA reactivity and HCV RNA detection in serum samples from East Africa.
42
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