Association of IL28B variation with viral diversity and disease outcomes: relevance to hepatitis C and allergy

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1 Association of IL28B variation with viral diversity and disease outcomes: relevance to hepatitis C and allergy Hiba Ghuloum Rustom Saleh Albloushi (BSc, GDipForSci) Centre for Forensic Science University of Western Australia This thesis is presented in partial fulfillment of the requirements for the Master of Forensic Science 2011

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3 DEDICATION To My beloved parents i

4 DECLARATION This thesis is submitted to the University of Western Australia in partial fulfillment (48 points) of the requirements for the Degree of Master of Forensic Science. This thesis has been composed by me from results of my own work, except where stated otherwise, and no part of it has been submitted for a degree at this, or at any other, University. Hiba Ghuloum Rustom Saleh Albloushi ii

5 TABLE OF CONTENTS DEDICATION... I DECLARATION... II TABLE OF CONTENTS... III ACKNOWLEDGMENTS... VII ABSTRACT... VIII LIST OF ABBREVIATIONS... XI LIST OF TABLES... XII LIST OF FIGURES... XIII GLOSSARY... XIV CHAPTER 1: LITERATURE REVIEW HEPATITIS C THE BIOLOGY OF HCV HCV Components The 5 and 3 UTRs HCV structural proteins HCV non-structural proteins HCV entry and life cycle HCV genotypes and subtypes DIAGNOSIS OF HEPATITIS C NATURAL HISTORY OF HCV INFECTION Acute infection Chronic HCV infection ANTI-VIRAL THERAPY FOR HCV iii

6 1.6 HOST IMMUNE RESPONSE AGAINST HCV AND GENETIC FACTORS ASSOCIATED WITH HCV OUTCOME Host immune response to HCV Innate immune response to HCV Adaptive immune response to HCV Host and viral genetic factors associated with HCV outcome Host factors that influence HCV evolution HCV DIVERSITY AND TREATMENT OUTCOME IL28B AND THE INTERFERON LAMBDA (IFN-λ) FAMILY IFN-λ family (IL29, IL28A, IL28B) IL28B and HCV treatment outcome IL28B and spontaneous HCV clearance IL28B and diseases: RESEARCH DIRECTIONS HYPOTHESES CHAPTER 2: MATERIALS AND METHODS HEPATITIS C COHORTS SAFETY PRECAUTIONS AND QUALITY CONTROL MEASURES Automation and documentation HCV GENOME SEQUENCING Viral RNA extraction RT-PCR for HCV 5 UTR First-round PCR amplification of HCV template Second-round PCR amplification of first-round HCV PCR template Electrophoresis Purification of HCV PCR products iv

7 2.3.7 HCV Sequencing Sequence editing Contamination check IL28B GENOTYPING Extraction of high molecular weight DNA from PBMCs Assessment of DNA Quantity and Quality for PCR-Based application DNA Quantification using the NanoDrop spectrophotometer DNA Quantification with picogreen assay Determining the rs genotype using the TaqMan assay Validation of the IL28B genotyping assay using BIORAD CFX ALLERGY COHORTS STATISTICAL ANALYSIS STUDY APPROVALS CHAPTER 3: RESULTS IL28B AND HCV HCV genotyping and contamination check of bulk HCV sequence HCV genotyping: comparison of clinical data with bulk HCV sequence HCV sequence contamination check Analysis of HCV polymorphism and IL28B variation in the three cohorts Phylogenetic analysis of cohort samples HCV sequence coverage IL28B genotyping Association between IL28B variation and HCV polymorphism Association between Treatment response and HCV polymorphism Association between gender and HCV polymorphism Viral clusters and IL28B genotype v

8 3.1.7 Joint analysis of factors associated with HCV outcome IL28B AND ALLERGIC DISEASE CHAPTER 4: DISCUSSION IL28B VARIATION AND HCV IL28B AND ALLERGIC DISEASE REFERENCES APPENDICES APPENDIX I APPENDIX II APPENDIX III vi

9 ACKNOWLEDGMENTS IN THE NAME OF GOD, THE MERCIFUL, THE CLEMENT! PRAISE BE TO GOD, Lord of the Worlds, and prayer and peace upon the Lord of the Prophets, Our Lord and Master Muhammad and upon his family and companions prayer and peace perpetually required until the Day of Judgment. I would like to thank my supervisor, Associate Professor Silvana Gaudieri, for the guidance, encouragement and advice she has provided throughout my time as her student. I have been extremely lucky to have a supervisor who cared so much about my work, and who responded to my questions and queries so promptly. I would also like to thank all the members at The Institute for Immunology and Infectious disease at Murdoch University. In particular I would like to thank Dr. Abha Chopra, Zina Zabaneh, Kiloshni Hahn, Dr. Emma Hammond, Dr. Monika Tschochner for their training on the variety of laboratory techniques and Prof Ian James for statistical support. Also, a great thanks for our collaborators for their contribution. I would like to thank United Arab Emirates Ministry of Higher Education for providing the Scholarship, which allowed me to undertake this research. I also thank my friends, Ashwaq Almaimmani and Habiba Alsafar for providing support and friendship that I needed. Finally, I would like to thank my family for their support, my parents for putting me through school and believing that I could get through this, my beloved sisters (Mona, Laila and Sawsan) and brothers (Mohammed, Isamil and Hussain) for their advice and encouragement while doing my thesis. vii

10 ABSTRACT Hepatitis C is one of the most common infections worldwide affecting around 170 million individuals 1. Approximately 30% of individuals that are infected with the Hepatitis C virus (HCV) will naturally resolve the infection but most develop chronic infection that often leads to liver cirrhosis and hepatocellular carcinoma 1 2. Current standard of care for HCV infection involves the use of interferon alpha (pegifn-α), an immunomodulatory molecule, and ribavirin (RBV). However, this treatment regime is only effective in about 50% of individuals. Treatment outcome is associated with HCV genotype, viral load decline during the initial phase of treatment and host genetic factors such as IL28B 3-6. IL28B encodes for interferon lambda 3 and is involved in the host s innate anti-viral response to viruses. To date, there is limited information regarding how IL28B affects viral evolution and in-turn clinical outcomes 7. IFN is likely to have a role in other diseases in which the host s innate immune response is important. In this study we examine the association between IL28B variation and HCV diversity and how this interaction may affect treatment outcome as well as the role of IL28B in allergic disease. IL28B typing and HCV sequencing was performed on three well-characterised HCV cohorts. Sixty eight samples were obtained from a cohort of chronic HCV-infected subjects in Western Australia and the Swiss HIV cohort study. These subjects were all treatment naïve at the time of sampling and had existing HCV sequence in the HCV NS5 region. DNA samples from the two cohorts were typed for the tagging SNP rs three kilobases upstream of IL28B. Ninety five samples were from a cohort of chronic genotype 1-infected subjects from Duke University, US. All subjects in this cohort had undergone pegifn-α/rbv therapy with known clinical outcomes. The Duke samples had all been typed for IL28B using the same tagging SNP as above and viral RNA from the pre-treatment plasma samples were sequenced for the HCV NS5 and viii

11 core regions. Initially, associations between IL28B variation and HCV polymorphism were tested. The next analysis examined the association between HCV polymorphism and treatment outcome with or without the IL28B risk allele associated with poor HCV outcome. Association between gender and HCV polymorphism was also examined given the known effect of gender on HCV outcome. Finally, sequence clusters within each subtype and protein were tested for association with IL28B variation and other variables (gender, ethnicity) to determine if specific host characteristics related to overall sequence variation. In addition, IL28B rs genotyping was performed on an allergy cohort (n=70) in order to determine the relationship between genetic variation at IL28B (rs ) and allergic disease. This relationship was also examined in a second cohort including children with clinically defined food allergy (n=30). After adjustment for founder effects (phylogenetic relatedness), significant associations were detected between HCV polymorphisms and IL28B variation including at positions 180 (p=0.03), 349 (p=0.015) of NS5A and 156 (p=0.017) and 421 (p=0.080) of NS5B. Variation at position 421 in NS5B was also associated with treatment non-response (p<0.05, unadjusted). An association with position 70 of core was found with treatment non-response but this was not significant following adjustment. In addition, the two main clusters of genotype 1a core sequences were associated with IL28B variation (p<0.01). For the genotype 1b core sequences, clusters were associated with ethnicity (p=0.02) and treatment non-response (p=0.05). For the allergy study, IL28B variation was associated with allergy in children (P=0.004). This relationship was confirmed in the second cohort. In conclusion, carriage of the IL28B rs T risk allele is associated with variation at specific sites within the HCV genome. These sites do not reside within the ix

12 interferon sensitivity determining region and future studies should test the variant sites in this study for IFN sensitivity. For the allergy cohort, carriage of the rs T risk allele is strongly associated with allergic phenotype. This is the first study to report the association of IL28B variation and allergic disease and highlights the role of the IFNs in allergic disease. x

13 LIST OF ABBREVIATIONS ALT DAA E EIA GAG GDD GWAS HBV HCC HCV HIV HLA IDU IFN IL28B IRES IRF ISDR ISG ISRE KIR LDL MHC NS PCR pegifn-α PKR RBV RDRP RLR RNA SNP SPT SVR TLR TRIF UTR Alanine aminotransferase Directly acting antiviral Envelope protein Enzyme immunoassay Glycoaminoglycan Gly-Asp-Asp Genome wide association study Hepatitis B virus Hepatocellular carcinoma Hepatitis C virus Human Immunodeficiency virus Human leukocyte antigen Intravenous drug use Interferon Interleukin 28B Internal ribosomal entry site IFN regulatory factor Interferon sensitivity determining region IFN stimulated gene Interferon-stimulated response element killer immunoglobulin-like receptor Low-density lipoprotein Major histocompatibility complex Non-structural Polymerase chain reaction Pegulated interferon alpha Protease Kinase R Ribavirin RNA-dependent-RNA polymerase RIG-I-like receptor Ribonucleic acid Single nucleotide polymorphism skin prick test Sustained virological response Toll-like receptor Toll-like receptor-3 adapter protein Untranslated region xi

14 LIST OF TABLES Table 1.1: Recent GWAS for HCV treatment outcome. Table 2.1: Demographic and clinical information on subjects in the Hepatitis C cohorts. Table 2.2: Primer combinations for RNA1, RNA2 and RNA3. Table 2.3: Thermal-cycling conditions for first round PCR covering the RNA1 region. Table 2.4: Thermal-cycling conditions for first round RNA2 and RNA3 PCR. Table 2.5: Second-round thermal-cycling programs for genotype-specific primers covering the core and NS5 regions. Table 2.6: Annealing temperatures for genotype-specific primer pairs covering the core and NS5 regions. Table 2.7: Thermal-cycling conditions for generic primers F7 (HCV5928M13F/HCV6823M13R) and F9 (HCV7498M13F/HCV8718M13R). Table 2.8: Thermal-cycling conditions for alternatives primers for core (HCV_gen_144F+ HCV1293R GEN) and F8-10 (HCVgen6628F+HCV9001). Table 3.1: Number of subtypes determined by bulk HCV sequence (5 UTR and NS5B) and from clinical data (Duke University collaborators). Table 3.2: Genetic distance within cohorts. Table 3.3: Genetic distance between cohorts. Table 3.4: HCV sequence coverage of Duke cohort samples. Table 3.5: Allele frequencies at rs for Duke, Swiss cohort samples. Table 3.6: Significant associations between i) IL28B genotype or ii) carriage of the T allele and HCV polymorphism. Table 3.7: Significant associations between HCV treatment response and HCV polymorphism. Table 3.8: Significant associations between gender and HCV polymorphism. Table 3.9: Allele frequencies at rs for Allergy cohort (1 and 2). xii

15 LIST OF FIGURES Figure 1.1: The HCV genome encodes a polyprotein that consists of structural (core, E1&E2) and non-structural components (NS2, NS3, NS4A, NS4B, NS5A and NS5B). Figure 1.2: Schematic representation of the HCV life cycle. Figure 1.3: Phylogentic tree of HCV genotypes and subtypes based on NS5B (DNASIS software). Figure 1.4: Geographic distribution of HCV genotypes. Figure 1.5: IFN signalling in response to HCV. Figure 1.6: Putative mechanisms of immune evasion by HCV. Figure 1.7: HLA footprints in HCV population sequences. Figure 1.8: Allele frequencies of rs among ethnic groups. Figure 2.1: Steps involved in obtaining viral sequence. Figure 2.2: First round HCV genome fragments. Figure 2.3: Generic and genotype specific primers used in second round amplification. Figure 2.4: Steps involved in the IL28B genotyping assay. Figure 2.5: Allelic discrimination results for the validation run generated from the BIORAD CFX manager. Figure 3.1: Phylogentic tree of NS5B region for the Duke cohort samples. Figure 3.2: Phylogenetic analysis of NS5B amino acid sequences. Figure3.3: Viral clustering based on consensus/non-consensus amino acid for a) 1A core and b) 1B NS5B. Figure 3.4: Allelic discrimination representation for allergy cohort 1. Figure 3.5: Variation at tagging SNP rs confers risk for allergic disease. Figure 3.6: Allelic discrimination representation for allergy cohort 2. xiii

16 GLOSSARY Allele Candidate gene Genome Haplotype HapMap Project Hardy Weinberg Equilibrium Linkage disequilibrium Minor allele frequency Phenotype Polymerase Chain Reaction Single Nucleotide Polymorphism An alternative form of a gene that is located at a specific position on a chromosome. A gene believed to influence expression of complex phenotypes due to known biological and/or physiological properties of its products, or to its location near a region of association or linkage. The entire complement of genetic material in a chromosome set. A group of specific alleles at neighboring genes or markers that tend to be inherited together. Genome-wide database of patterns of common human genetic sequence variation among multiple ancestral population samples. Population distribution of two alleles (with frequencies p and q) such that the distribution is stable from generation to generation and genotypes occur at frequencies of p 2, 2pq, and q 2 for the major allele homozygote, heterozygote, and minor allele homozygote, respectively. Association between two alleles located near each other on a chromosome, such that they are inherited together more frequently than expected by chance. Proportion of the less common of two alleles in a population (with two alleles carried by each person at each autosomal locus) ranging from 1% to less than 50%. The total characteristics displayed by an organism under a particular set of environmental factors, regardless of the actual genotype of the organism. A method for amplifying segments of DNA, by generating multiple copies using a DNA polymerase enzyme under controlled conditions. DNA sequence variations that occur when a single nucleotide (A, T, C, or G) in the genome sequence is altered. Each individual has many single nucleotide polymorphisms that together create a xiv

17 unique DNA pattern for that person. Genome-wide Association Study An examination of genetic variation across a given genome, designed to identify genetic associations with observable traits. xv

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19 CHAPTER 1: LITERATURE REVIEW 1

20 CHAPTER 1: LITERATURE REVIEW 1.1 HEPATITIS C Hepatitis C virus (HCV) infection is one of the most common blood-borne infections with an estimated 170 million infected individuals worldwide 1. Following acute HCV infection about 20-30% of individuals naturally resolves the infection but for the remainder of individuals the virus persists developing into chronic infection. Of those individuals with chronic infection a proportion will develop liver cirrhosis and hepatocellular carcinoma at a risk of about 4% per year 1 2. Consequently, HCV is the major cause of liver transplantations in Australia, Europe and the United States. Although it is not completely understood what determines outcome or disease progression in Hepatitis C, factors such as age, gender, alcohol consumption, coinfection with HIV or HBV and host genetic factors have been shown to influence outcome 8. The transmission of HCV occurs by direct contact with infected blood or blood products and in Australia intravenous drug use (IDU) is the most typical mode of transmission. Sexual transmission is rare but is known to occur 4. Due to the commonly asymptomatic nature of the acute phase of HCV infection and the protracted progression to disease in some individuals, many HCV infected subjects do not know their infection status and may unknowingly transmit their virus to another person. The silent stage is also a major obstacle to detect and treat HCV infection in early stages 1. HCV infection induces a series of innate and adaptive immune responses in the host that influence both spontaneous and treatment resolution 9. Not surprisingly, current treatment for HCV infection involves the use of an immunomodulatory drug interferon alpha (pegulated interferon alpha; pegifn-α) and ribavirin (RBV). However, this 2

21 treatment regime is only effective in about 50% of individuals 10. Treatment outcome is associated with HCV genotype, viral load, host and viral genetic variations 11. New specific anti-hcv drugs (DAA directly acting anti-virals) are in clinical trials and may improve outcome with HCV infection. There is currently no vaccine against HCV. 1.2 THE BIOLOGY OF HCV HCV is a single-stranded positive sense RNA virus and a member of the hepacivirus genus within the family Flaviviridae. The HCV genome is about 9.6 kilobases in length with an open reading frame (ORF) encoding a 3000 amino acid polyprotein. The polyprotein is flanked by 5 and 3 untranslated regions (UTRs) that are essential for regulating the replication and initiation of translation of the HCV RNA. The polyprotein is processed and cleaved by host and viral proteases in order to release structural (core, and envelope proteins E1 and E2) and non-structural (NS) proteins (P7,NS2, NS3, NS4A, NS4B, NS5A and NS5B) (Figure 1.1) Figure 1.1: The HCV genome encodes a polyprotein that consists of structural (core, E1&E2) and non-structural components (NS2, NS3, NS4A, NS4B, NS5A and NS5B) 1. There are six HCV genotypes and 52 subtypes reflecting the extensive HCV diversity observed worldwide. Genotype classification can be obtained using clinical assays that tend to target the 5 UTR region of the virus but classification can also be performed using phylogenetic analysis of complete or partial sequences of HCV isolates. 3

22 Genotype classification is used to determine the treatment regime for a patient. Individuals infected with HCV genotypes 2 or 3 undergo 24 weeks of combined therapy (pegifn-α/rbv) with a 80% sustained virological response (SVR) rate 12. Individuals infected with HCV genotypes 1 and 4 undergo 48 weeks of combination therapy with 50% and 55-69% SVR rates, respectively 13. SVR is defined by a HCV-specific PCR negative result 24 weeks following the cessation of treatment. Genotypes 5 and 6 are not well characterized and treatment regimes have not been tailored for these genotypes HCV Components The 5 and 3 UTRs The 5 UTR consists of approximately 340 nucleotides that reside upstream of the ORF translation initiation region. It contains four structured domains (I to IV) folded into several stem-loops and contains an internal ribosomal entry site (IRES). The IRES forms a pre-initiation complex that binds to the 40S ribosomal subunit to initiate translation of the RNA genome 1 2. The 3 UTR is nucleotides in length that comprises 3 major domains: a variable region (30 to 50 nucleotides), poly (U/UC) tract with an average of 80 nucleotides and the 3 region that contains the three stem-loop structures. The stem loop structure including SL2 and SL3 are essential for negativestrand RNA synthesis HCV structural proteins The structural proteins of the HCV genome include the core and two envelope proteins (E1 and E2). The core protein is processed by cellular proteases in the endoplasmic reticulum (ER) 15. After maturation of the core protein, it interacts with the HCV RNA in order to form the viral nucleocapsid 8. Core protein is a conserved region of the viral 4

23 genome. It is classified into three different elements based on molar mass 21kDa, 19kDa and 16kDa. The 21kDa and 19kDa elements attach to the membrane of the ER 16, while the 16kDa resides in the perinuclear space 17. The variability in the location of the core protein reflects its various functions during HCV replication and the course of infection. The core protein influences cell death mechanisms (apoptosis), lipid metabolism, transcription host cell transformation and the immune response of the infected cell 18. Also, the core protein is involved in encapsulation and regulates expression of certain viral proteins. In addition, the core protein plays a vital role in affecting the translational potential of the IRES that resides at the 5 end of the HCV viral genome 19. E1 and E2 are structural elements of the virion that are essential for cell entry via receptor binding. Both E1 and E2 are type I transmembrane proteins that are attached to the membrane by the amino acid transmembrane domain at the C-termini of each protein 2 8. The hypervariable domain in the E2 coding sequence is the most variable of the viral proteins resulting in the main differences between the amino acids among the HCV genotypes and within each subtype HCV non-structural proteins The P7 protein is a hydrophobic peptide consisting of two transmembrane domains that are embedded in the ER-membrane. The P7 protein forms a hexameric ion channel complex that plays a role in HCV replication during the viral life cycle 2. HCV NS2 is a transmembrane hydrophobic protein that interacts with itself and other HCV non-structural proteins. Active sites (H952, E972 and C99) within NS2 are 5

24 required for the catalytic activities of the NS2/3 cysteine protease 2. NS2 has zincdependent protease activity and is involved in autoclaving the NS2/3 junction 2 8. NS3 comprises a protease and a helicase. The helicase is part of the 2DExH/D-box helicase super-family that is involved in the unwinding of RNA-RNA duplexes during replication of the genome 2. The NS3 serine-type protease facilitates the cleavage of the non-structural proteins. The NS3 activities are improved with the cofactor NS4A that enhances helicase activity. Furthermore, the proteolytic activity of the NS3/4A complex is involved in IFN-α and -β cellular responses by cleaving components of the doublestranded RNA signaling pathway associated with a Toll-like receptor-3 adapter protein (TRIF) and Cardif 20. The HCV NS4A protein is a cofactor for NS3 and is involved in proteolytic activity. This non-structural protein is crucial for HCV replication and viral pathogenesis 2. The HCV NS4B protein consists of four transmembrane domains that are involved in the formation of the membranous web during the replication process 8. HCV N5A is a membrane bound phosphoprotein that exists in a phosphorylated (56kDa) and hyperphosphorylated (58kDa) form. NS5A has an amphipathic alpha helix at the amino acid terminus, which is anchored to the ER membrane that contributes to the replication complex 2. Thus, modulation of NS5A function by phosphorylation regulates the mechanism of replication. The amino acid sequence between NS5A 2209 and 2248 (position 237 to 276 in the NS5A protein) is known as the interferon sensitivity-determining region (ISDR). The NS5A inhibits the activity of the IFNinduced dsrna-dependent kinase PKR activity involved in host antiviral defence mechanisms. 6

25 HCV NS5B is a hydrophilic protein (molar mass 68kDa) containing an RNAdependent-RNA polymerase (RDRP) that contains a Gly-Asp-Asp (GDD) motif in its active site. NS5B initiates the negative-strand RNA synthesis using HCV genome as a template. The NS5B protein is anchored to the ER-derived membranous web HCV entry and life cycle HCV entry is a multi-step process that utilises various host cell molecules to gain access to the cell in order to initiate the infection. Viral entry is mediated by the binding of the viral surface proteins to several receptors on the host cell. The current hypothetical model consists of binding and entry, uncoating, translation and procession, genome replication, packaging and virus egress 8 14 as shown in Figure 1.2. HCV entry is achieved by the binding of HCV surface glycoproteins to the host receptors glycoaminoglycans (GAGs), low density lipoprotein (LDL) receptors, scavenger receptors B1, or CD Following that, the HCV virus is internalised via clathrin-dependent endocytosis. The acidification of the endosomes triggers the fusion of the HCV glycoprotein-dependent membrane leading to the release of the HCV genome into the cytoplasm 14. The HCV genomic RNA is translated into polyproteins by the IRES in the 5 UTR with the host 40S ribosomal subunit (Figure 1.2). 7

26 Figure 1.2: Schematic representation of the HCV life cycle. Host and viral encoded proteases cleave the polyprotein into the structural proteins (core, E1and E2) and the non-structural proteins (P7, NS2, NS3, NS4A, NS4B, NS5A and NS5B). The following steps are shown: 1-2) binding and entry, 3) uncoating, 4-5) translation and processing, 6-9) replication, 10) packaging and 11-12) virus egress 22. The initiation of HCV replication requires the assembly of the replication complex that comprises viral proteins, cellular components and the RNA strand. The HCV NS4B protein facilitates the formation of the membranous web that is essential for the replication complex assembly 22. The association of the replication complex components with the positive-strand genome RNA and NS5B at the catalytic core initiates the 8

27 synthesis of the negative-strand intermediate of replication. In the next step, the negative-strand acts as a template for the production of multiple copies of the HCV genome. Subsequently, a proportion of the newly synthesised genome will serve as the template for viral protein translation while others dimerise with core protein and produce core-protein-enriched nucleocapsids. The correlation between the core proteins and cytoplasmic lipid droplets is a crucial determinant of nucleocapsid and infectious viral particle assembly 22. Thus, the core-rna interaction plays a vital role in switching from replication to packaging. Finally, there is vesicle formation and release of the viral particles. The mechanism underlying viral egress is not yet understood HCV genotypes and subtypes Due to the lack of proof-reading ability of the RNA-dependent RNA polymerase, HCV exhibits high genetic diversity between infecting strains. A large proportion of the nucleotide diversity is observed between HCV genotypes. HCV genotypes are divided into six groups with each genotype further classified into subtypes (52 in total). Heterogeneity of the NS5B region has been used to classify HCV into the six major genotypes and series of subtypes by phylogenetic analysis. These genotypes sequences differ at the nucleotide level by 30-40% in the NS5B region. Each subtype exhibits differences of 20-25% with other subtypes from the same genotype sequence in the NS5B region (Figure 1.3). 9

28 Figure 1.3: Phylogentic tree of HCV genotype and subtype NS5B reference sequence (DNASIS software, GenBank). The numbers at the branches indicate the percentage of sequence similarity 16. The distribution of these genotypes and subtypes varies worldwide with genotypes 1, 2 and 3 the main circulating types in Western countries (genotype 3 more so in Europe and Australia than the US), genotype 4 is widely distributed in the Middle East, genotype 5 in Southern Africa and genotype 6 is present in most of South East Asia (Figure 1.4)

29 Figure 1.4: Geographic distribution of HCV genotypes. HCV genotypes 1, 2 and 3 have worldwide distribution. Each subtype is indicated with a colour in the pie chart within different regions and others indicate unclassified sequences DIAGNOSIS OF HEPATITIS C Diagnostic tests for HCV infection are divided into serological and molecular-based methods. The serological test is based on detecting virus specific antibodies using enzyme immunoassay (EIA) 24. In this test recombinant antigens or synthetic peptides are used to detect the presence of HCV-specific antibodies on a solid surface. Test samples containing HCV-specific antibodies will form antigen-antibody complexes that are detected by secondary antibodies raised against human immunoglobulin. In-turn, the secondary antibodies are linked with an enzyme that can catalyse the transformation of a substrate into a detectable compound 24. This type of method is considered a costeffective technique to screen for exposure to HCV, however, this method cannot detect active HCV infection. Molecular-based assays detect HCV RNA and can be both qualitative (the presence or the absence of the virus) and quantitative (viral load)

30 The molecular techniques are typically based on the polymerase chain reaction (PCR). The HCV RNA is extracted and reversed transcribed to produce cdna, which is processed to generate many detectable copies. Commercial assays are available for HCV RNA detection such as the Roche COBAS AMPLICOR HCV test (version 2.0) and Siemens VERSANT HCV RNA TMA. These assays can in most instances also be used to determine HCV viral load. Viral load is important for predicting treatment response but is not predictive for disease progression NATURAL HISTORY OF HCV INFECTION Acute infection The main characteristics of the acute phase of HCV infection is the occurrence of detectable viraemia from 2 to 4 weeks post-exposure and elevated levels of serum liver transaminase levels (ALT and AST). Anti-HCV antibodies develop at week 4 to This phase of the infection is typically asymptomatic, however some individuals (10-20%) exhibit acute symptoms between weeks About 20-30% of individuals manage to clear the virus within the first 12 weeks 27. There are several factors that are associated with viral clearance including age, gender, co-infection with HIV and/or HBV and host genetic factors Chronic HCV infection The development of chronic HCV infection is associated with several factors that include virus, host and external elements. HCV genotype 28, initial viral inoculum and viral diversity in quasi-species (mixture of closely related but genetically different species within a host) are likely to be involved in HCV progression 29. Also, gender, ethnicity, age and duration of infection can affect the acceleration of the course of 12

31 infection 28. Alcohol consumption and co-infection with HIV are external factors associated with the progression of liver disease ANTI-VIRAL THERAPY FOR HCV The main objectives for treating HCV infection are to prevent liver complications including cirrhosis, liver failure and hepatocellular carcinoma and reduce transmissions 8. Due to the lack of a prognostic test for HCV progression, anti-viral therapy is recommended for subjects at the greatest risk of developing advanced liver disease. Liver biopsy and histological examination provide a good indication of the stages of liver inflammation but biopsy is not longer a pre-requisite for treatment 8. Since IFNs are naturally occurring substances produced by a large array of cells in response to viral infection, IFN-based therapeutic approaches have been utilized for hepatitis C 31. Initially, it was shown that individuals undergoing IFN-based monotherapy achieved low levels of SVR. Consequently, therapy using a combination of RBV and IFN-α was introduced in order to increase the response in individuals with chronic HCV infection 32. To further increase efficacy, IFN was attached to polyethylene glycoprotein (PEG) that delays IFN metabolism leading to an increase in the duration of therapeutic activity. There are two formulas (pegifn-α-2a, pegifn-α-2b) available commercially for pegifn-α. PegIFN-α-2a is administrated as a fixed dose of 180 µg/week while pegifn-α-2b dosage is calculated according to an individual s weight (1.5µg/kg/week) 1 8. Both forms are administrated in combination with ribavirin, an antiviral drug that is involved in improving liver function 8. 13

32 The current treatment for chronic HCV involves the administration of a combination of RBV and pegifn-α for 48 weeks for genotype 1 (and 4) or 24 weeks for genotypes 2 and 3. Combined therapy treatment regime can lead to SVR. However, treatment is only effective in about 50% of individuals and results in a plethora of side-effects with many individuals unable to tolerate the treatment regime due to the high toxicity 8 9. Symptoms experienced by patients include fatigue, malaise, muscle aches, fever, diarrhoea, anorexia and haemolytic anaemia 8. Treatment response rates vary between the different HCV genotypes. For instance, 40-50% of genotype 1-infected individuals respond to the combined treatment and achieve SVR following 48 weeks of treatment compared to more than 70-80% of individuals infected with genotype 2 or 3 after only 24 weeks of treatment 8. Factors that are predictive of treatment outcome include viral load decline by week 4, gender, age, baseline viral load and ethnicity. Genetic variations in the virus itself may also influence treatment outcome as has been reported by several Japanese groups However, the effects of viral diversity on anti-viral therapy are not well understood. Recent studies in the last 18 months have shown an association between treatment outcome and genetic polymorphisms upstream of the IL28B gene that encodes the IFN lambda 3 protein 3-6. Consequently, more focus has been drawn to the function of the genes in the IFN pathway and how they may affect treatment outcome

33 1.6 HOST IMMUNE RESPONSE AGAINST HCV AND GENETIC FACTORS ASSOCIATED WITH HCV OUTCOME Host immune response to HCV Innate immunity to HCV is the initial response to control viral replication. Coordination between innate and adaptive immune responses occur in order to eradicate HCV Innate immune response to HCV The host s innate anti-viral activity occurs in two phases, initiation and effector 14. The initiation phase starts as the HCV RNA are recognized by a series of receptors including Toll-like receptors (TLRs) and retinoic acid-inducible gene I (RIG-I) receptors 37. TLR3 and RIG-I recognise viral material and initiate a signalling cascade through adapter proteins TRIF and Cardif in order to activate transcription factors such as IFN regulatory factor 3 (IRF-3) and nuclear factors κb (NF-κB) 38. The activated IRF3 and NF-κB translocate to the nucleus in order to activate the transcription of type I IFN 38. Secreted IFN can bind to their receptor on neighboring cells in order to initiate the effector phase. In the effector phase, IFNs (including IFN-λ and IFN-α) induce the signaling pathways that result in the upregulation of IFN stimulated genes (ISGs) that are involved in viral infection suppression 31. IFN-α/λ operate on the neighboring cells JAK-STAT pathway through different receptors. IFN-α binds to IFN-αR1 and IFN-αR2, whereas IFN-λ binds to IL-28Rα and IL-10Rβ. The binding of IFN-λ to the kinases triggers the phosphorylation of the STAT proteins. STAT-1 and STAT-2 proteins form a heterodimer that interacts with IRF-9 resulting in the interferon-stimulated response element (ISRE) 38. The ISRE binds to the promoter upstream of the ISGs in order to induce the regulation of the ISGs that are important in suppressing HCV 31 (Figure 1.5). 15

34 Figure 1.5: IFN signalling in response to HCV 31. The products of the ISG include enzymes, transcription factors, chemokines and cytokines that have direct anti-viral activity or induce and regulate the anti-viral immune response 39. Several mechanisms lead to the attenuation of ISG expression through four effector pathways of the IFN-mediated anti-viral response including Mx GTPase, 2 5 -oligoadenylate-synthetase-directed ribonuclease L (OAS), protein kinase R (PKR) and the ISG15 ubiquitin-like pathway 40. Despite the activation of the innate immune response at early stages of HCV infection, viral interference with innate immune responses occur and block the effect that contribute to the development of chronic hepatitis C infection 10. The anti-viral effects of several ISGs are weakened by HCV proteins through several mechanisms that block IFN signalling downstream of IFN-α/β receptors 38. HCV NS3/4 protease blocks the effector action of IRF NS5A and envelope interact and inhibit the PKR. Core 16

35 protein can suppress cytokine signalling by the induction of SOCS 3 proteins that repress phosphorylation of STAT1 by JAK. Not surprisingly, various genetic polymorphisms in innate immune genes are associated with hepatitis C clearance including ISGs MxA, OAS-1 and PKR 42, IRF-1 promoter 43, TLR 7 44 and SNPs near the IL28B gene 9. The IL28B gene is located on chromosome 19 and encodes for (IFN-λ3) 45. As discussed above, IFN-λ stimulates an intracellular cascade that turns on IFN-α/β-like anti-viral responses. In addition, IFN-λ plays a vital role in inhibiting HCV manifestations by interfering with virus replication 46. Another arm of the innate immune response involves Natural killer (NK) cells: a population of effector cells that are part of the innate immune response to viral infections. These cells are enriched in the liver (40 to 60%) compared to blood (5-15%). NK cells are able to exert anti-viral activity through cytotoxicity mechanisms and release immunoregulatory cytokines (eg. IFN-γ TNF-α, TGF-β, GM-CSF, IL-10) that destroy virus-infected target cells. The NK response against viral infection is regulated by its inhibitory and activation receptors that bind to a variety of ligands including human leucocyte Antigen (HLA) molecules 47. The interaction between NK killer immunoglobulin-like receptors (KIRs) and their HLA ligands appear to be important in the early immune response to HCV. Accordingly, HCV resolution has been associated with particular combinations of KIR and HLA ligands 48. The presence of the weak inhibitory KIR/HLA complex KIR2DL3-HLA-C1 is associated with HCV clearance 48 but KIR2DL3 alone with HCV persistence

36 Adaptive immune response to HCV The role of B and T cells in viral infection and control has been a major field of investigation in Hepatitis C research. However, the role of the humoral response against HCV is still obscure 50. In early stages of chronic infection neutralizing antibody responses can occur 51, however the high mutation rate of the hypervariable regions of the envelope glycoproteins, which are a key target of antibody responses, can change rapidly and viral mutational escape may impair an effective humoral immune response 52. The host s T helper (CD4 + ) and cytotoxic T cell (CD8 + ) response to HCV is a known correlate of infection outcome Decreases in viral titer overlap with the appearance of HCV-specific T cells suggesting that HCV clearance is partly a T cell mediated process 55. Immune responses in chronic infection are characterised by weak CD4 + and CD8 + T cell responses, reduced proliferative, cytokine and cytolytic capacity of HCVspecific T-cells and antigen recognition loss 56. Furthermore, reduced T cell priming 58 and low intrahepatic CD8 + T cell response to HCV have been shown to occur in chronic HCV infection. Recent studies have reported on functional signatures of T cell responses that are protective in models of human viral infections. These responses are characterised by the concurrence of three critical components, IFNγ and IL-2 production and proliferation of both CD4+ and CD8+ T-cells 59. Chronic HCV infection is correlated with reduced IL-2 production of CD4 + T cells as well as dysfunction of CD8 + T cells

37 T cell immune responses are regulated by the host s HLA repertoire. The HLA genes are the most diverse in humans and are contained within the major histocompatibility complex (MHC) on the short arm of chromosome six. The HLA genes encode the major proteins involved in antigen presentation to T cells. The variation within the HLA genes occurs mainly within exons 2 and 3 encoding the peptide binding regions. Accordingly, different HLA alleles can bind and present several viral epitopes. These polymorphic molecules present viral sequences (epitopes) to T cells in order to direct the host s immune response against the infecting pathogen. Hence, an effective T cell immune response to HCV epitopes, restricted by host HLA, makes an important contribution to adaptive immunity and disease outcome 61. Viral escape within these epitopes is used by HCV to subvert host immune control. The mechanisms by which HCV is hypothesized to escape the anti-viral immune response are summarised in Figure 1.6. In chronic HCV infected individuals the virus is capable of persisting even though detectable CD8 + T cell responses are present. Major proposed mechanisms of HCV immune evasion supported by with experimental evidence include mutational escape within epitopes, functional anergy and regulatory T cell activity

38 Figure 1.6: Putative mechanisms of immune evasion by HCV. Failure of HCV-specific CD4+and CD8+ T cell responses is fundamental to HCV persistence. HCV evasion of innate immune pathway disturbs innate signal and HCV specific immune cells as well as limits viral replication. Viral escape from HCV-specific T cells is also important Host and viral genetic factors associated with HCV outcome Given the importance of the host s immune response in HCV infection outcome, it is not surprising that various host genetic determinants of spontaneous HCV resolution include genetic variations of HLA, KIRs, chemokines, interleukins and IFN-stimulated genes 10 (some of which have already been mentioned). Better understanding of hostviral interactions involved in spontaneous HCV clearance has important implications in developing therapeutic and preventive strategies. The HLA repertoire of on individual, to some extent, regulates the host s T cell 62. A number of studies have shown significant associations between specific HLA alleles and HCV infection outcome 10. For example, HLA-A*1101, -B*57 and -Cw*0102 have 20

39 been associated with HCV resolution, whereas HLA-A*2301,-B*53 and -Cw *04 have been associated with chronic hepatitis C 63. However, a study of individuals from an Irish single source cohort of 227 women (141 chronic and 86 cleared) that were exposed to HCV contaminated immunoglobulin showed the association of HLA-B*27 with spontaneous resolution 64. This study highlights the contribution of the host s immune CD8+T cell response and HLA genes to HCV outcome by eliminating confounding factors such as gender, age and viral diversity known to influence outcome in the analysis. Studies have also reported the association of HLA class II alleles at the HLA-DRB1 and -DQ loci and spontaneous HCV clearance. The HLA alleles HLA-DRB1*11 and - DQB1*03 have been associated with spontaneous resolution of HCV in several studies. A meta-analysis of the effects of these alleles on HCV resolution report them to have an effect size of OR 3.0 (95% CI: ) and 2.5 (95% CI: ) respectively 65. Thus, the association of HLA class II alleles and control of HCV infection indicates the importance of CD4 + T cell responses in acute and chronic HCV infection Host factors that influence HCV evolution. As described previously, cellular immune responses are correlated to HCV outcome. HCV has a high mutation rate facilitating viral escape that involves modification of viral epitopes to escape from HLA-restricted T cell responses 61. As the range of viral epitopes presented by the host are restricted by the binding properties of the HLA repertoire of the individual, viral escape mutations from T cell responses can be considered characteristic for specific HLA types 10 or HLA footprints. Rauch et al 61 showed viral adaptation of HCV genotype 1 and 3 to HLA-restricted immune pressure. HLA footprints are characteristic changes in the virus that are associated with specific 21

40 HLA alleles at the population level. In this host-viral interaction, if a virus infects an individual with a particular HLA type, known escape mutations in the viral epitope sequence can be identified that are likely to abrogate presentation to the immune system 67. If this same virus then infects another individual with a different HLA type, then escape from the same epitope is not likely to be relevant for the new host s immune response and hence the mutation may revert to wildtype 67 (Figure 1.7). On the other hand, if the virus infects an individual with the same HLA type, the mutation is maintained and acts as a marker, or footprint, for that specific HLA type. The result of these footprints is the identification of HLA-specific viral polymorphisms at a population level. Figure 1.7: HLA footprints in HCV population sequences HCV DIVERSITY AND TREATMENT OUTCOME The complexity and diversity of HCV quasispecies in an individual has been suggested to predict treatment response 68. Moreau et al 68 showed the degree of HCV complexity in a SVR group was lower than for non-responders and the degree of HCV heterogeneity at baseline was predictive of treatment response. 22

41 Both E2 and NS5A proteins have been suggested to interact with IFN-induced cellular PKR activity that results in blocking the inhibitory activity of IFN on cellular and viral protein synthesis 69. Variation within the ISDR in NS5A has been investigated as a predictor for SVR 34. A study was conducted on patients with HCV genotype 2a who had undergone pegifn-α monotherapy and confirmed that the number of mutations in the ISDR was associated with response to IFN therapy. Two or more amino acid substitution within the ISDR region of NS5A was considered to be predictive for achieving SVR 35. The evolution of the HCV NS5A region during pegifn-α/rbv therapy has also been investigated by Yuan et al 70 in order to determine molecular changes in NS5A at various points of treatment. More mutations in the coding region of NS5A were found in SVR patients by week 12 of treatment 70. Several other studies investigated variations in the hypervariable regions, however the locus that defines the virological response difference between various HCV genotypes has not been determined Recent Japanese studies have reported associations between specific amino acid variations in HCV core and HCV treatment response SVR has been correlated with amino acid variation at position 70 (arginine replaced with glutamine or histidine) and 91 (leucine replaced with methionine) of HCV core IL28B AND THE INTERFERON LAMBDA (IFN-λ) FAMILY IFN-λ family (IL29, IL28A, IL28B) There are three types of IFNs; IFN-α/β (Type I), IFN-γ (Type II) and IFN-λ (Type III). IFN-λ contains three members IFN-λ1 (encoded by IL29), IFN-λ2 (encoded by IL28A) 23

42 and IFN-λ3 (encoded by IL28B). IFN-λ3 shares significant amino acid sequence homology with IFN-λ2 (96%) but less with IFN-λ (81%) 72. IFN-λ is primarily produced by plasmacytoid dendritic cells (pdc) and macrophages, whereas IFN-α is produced by all nucleated cells 36. The IFN-λ family is involved in the innate immune system as they have the ability to suppress viral replication including for HCV. The IFN-λ family may also be involved in modulating the differentiation and the maturation of the immune cells of the adaptive immune system IL28B and HCV treatment outcome The initial associations between IL28B variation and HCV treatment outcome were identified using genome-wide association studies (GWAS). This method is typically used to identify single nucleotide polymorphisms (SNPs) associated with disease outcome without a priori knowledge 14. The method screens a large number of host variants in hundreds or thousands of case/control subjects. The SNPs are pre-selected based on how well they tag certain areas or genes due to the linkage disequilibrium pattern across the genome. In that, not all SNPs need be sampled in each individual as although tagging SNPs may not necessarily be the causative variation they are likely to be near putative causative variations that can be investigated. Four independent groups utilised GWAS to evaluate the association between specific SNPs in the human genome and HCV infection outcome (spontaneous and treatmentinduced) (Table 1.1). The SNP rs was identified in all four studies as showing a significant association with HCV treatment outcome. This SNP resides 10kb upstream of the IL28B gene 4. For this SNP (rs ), the frequency of the G allele is associated with chronic HCV subjects and it is defined as the risk allele. The other SNP identified was rs by Ge and colleagues 3. This SNP is located 3kb upstream of 24

43 IL28B and is also associated with HCV treatment outcome. Subjects with genotype C/C at rs are more likely to respond to treatment compared to subjects who carried the T risk allele 3. The four studies included different ethnic groups but genotyping and analytical methods are similar, although the type of commercial SNP set used by the groups varied and may account for the lack of detection of rs as an important SNP in HCV treatment outcome in some of the studies 7. Furthermore, adherence to therapy was not included in the subject criteria for some studies and is known to influence treatment outcome. 25

44 Table 1.1: Recent GWAS for HCV treatment outcome 7. Characteristics Ge et al Tanaka et al Suppiah et al Rauch et al N Gender Male Female HCV genotype /2/3/4 Region Northern America Japan Ethnicity Methods Outcome Top SNPs associated with treatment response Caucasian, African- American, Hispanic Illumina Human610-quad BeadChip SVR vs. non- Responder rs (p= ²⁸) rs (p= ²⁷) rs (p= ) Northern Europe, Australia Switzerland Japanese Caucasian Caucasian Affymetrix SNP6.0 Array VR vs. non- Responder SVR vs. Non-responder rs (p= ) rs (p= ) rs (p= ) Illumina Infinium Human Hap300/ CNV370-Quad Bead- Chip SVR vs. non-responder rs (p= ) Illumina Human1 M-Duo, HumanHap550/ Human610W-Quad BeadChips SVR vs. nonresponder rs (p= ) rs (p= ) 26

45 Ge et al 3 detected a strong genetic association in the IDEAL study; a large randomized control trial comparing the effectiveness of different forms of pegifn-α. The study included 1137 patients from North America from three ethnics groups Caucasian, African American and Hispanic. All subjects were chronically infected with HCV genotype 1. The analysis definition compared treatment response and non-response based on SVR. The study was not replicated in an independent cohort. All patients included in this study showed >80% compliance of treatment. Seven SNPs were reported to be associated with treatment outcome. The SNP rs (P=1.21x10-28 ) had the strongest correlation to treatment outcome with the C/C genotype showing a two-fold greater rate of SVR than genotype T/T in all ethnic groups. In addition, there was a significant correlation between this SNP and treatment response between different ethnic groups. The C allele frequency is high in south East Asian populations and accordingly they achieve higher SVR with combined therapy than subjects from European background. The frequency of the protective C allele is significantly higher in individuals from European ancestry than African American and explains half of the difference in response between the two ethnic groups. Tanaka and colleagues 6 from Japan conducted a study including 142 infected individuals with genotype 1. This study was replicated on another cohort of 172 individuals in order to validate the association between specific SNPs and response to HCV treatment. The minor alleles of two SNPs rs and rs flanking the IL28B gene were correlated with treatment non-response (P=1.93x10-13, OR=20.3 and 3.11x10-15, OR=30.0, respectively). SNP rs was the strongest predictor for HCV treatment outcome. 27

46 The Suppiah et al 5 study investigated the correlation between SNPs and HCV therapy outcome in 293 HCV infected genotype 1 patients from an Australian population of northern European ancestry. A validation study was replicated on 555 individuals from Europe (UK, Germany, Italy) and Australia. In this study the strongest association detected was with rs The major allele of rs was significantly associated with treatment SVR (p=9.25x10-9, OR=1.98,95% Cl= ). Homozygous carriers of the rs G allele were associated with higher risk to fail treatment in comparison to homozygous T/T individuals. Fourteen other SNPs reached the threshold of significant association. Furthermore, a haplotype analysis of the IL28B, IL28A and IL29 gene cluster was conducted in order to further investigate the association of SNPs in this region with treatment outcome. The authors found that a haplotype associated with the responders is likely to include a regulatory region that affects the expression of both IL28A and IL28B. Rauch and colleagues 4 studied 465 Caucasian individuals infected with HCV genotype 1, 2, 3 or 4. Patients included in this study were from the Swiss hepatitis C and HIV cohort study groups and accordingly a subset of subjects were co-infected with HIV. This study compared SVR versus non-responders with at least 80% treatment adherence. Several SNPs were identified in the proximity of IL28B to be associated with HCV treatment outcome. The strongest association with treatment outcome was detected for SNP rs (P=6.07x10-9, OR=2.31, CI= ). Individuals carrying one or two copies of the minor G allele were more likely to fail HCV treatment. Also, the G allele was highly represented in chronically infected patients with HCV in comparison to the T allele (major allele) (OR=2.2, CI= heterozygote, OR=6.0, Cl= for G/G homozygous). Individuals with genotype 1 and 4 that carry the risk allele were less likely to respond to treatment in comparison to the 28

47 protective allele (SVR for G/G=28% and T/T=63%). For the favourable HCV genotypes 2 and 3 the difference was not statistically significant. In this study, the genetic variation flanking IL28B was shown to be the strongest predictor for HCV treatment as no SNPs outside the IL28B/A region achieved the genome-wide significant level. Furthermore, the authors of this study also showed that the association between IL28B variation and HCV treatment outcome was similar for mono-infected and coinfected subjects. Taken together the four GWAS studies support the association of IL28B variation with HCV therapy outcome supporting the view that IL28B variation is one of the strongest predictors of HCV treatment outcome IL28B and spontaneous HCV clearance The association between genetic variation in IL28B and spontaneous clearance of HCV has been investigated in two studies. Rauch et al 4 utilised a GWAS to identify host genetic factors associated with HCV spontaneous clearance. Several SNPs were identified and as for HCV treatment outcome the SNP rs was the strongest predictor for HCV clearance (OR=2.31, Cl= ). The second study by Thomas et al 9 also showed the same SNPs as for treatment outcome to be associated with spontaneous resolution of HCV in different ethnic groups (European OR=2.6,CI= and African OR=3.1,CI= ). Several studies examined the association between IL28B variation and different human populations and the correlation with known differences in spontaneous and treatmentinduced clearance. In these groups the C allele of rs and T allele of rs are significantly associated with viral clearance. These alleles are common in individuals of European descent and less frequent in individuals of African ancestry. 29

48 Thomas et al 9 genotyped more than 2000 individuals from 51 ethnic groups at the rs locus. The East Asian populations have the leading frequency for the allele associated with viral clearance (Figure 1.8). Differences in the allele frequency of the protective and risk alleles of IL28B likely reflect population differences in treatment and clearance rates. Figure 1.8: Allele frequencies at rs among ethnic groups. The allele frequency of C (green) associated with HCV clearance and the T (blue) associated with HCV persistence IL28B and diseases: IL28B and infectious diseases IFN-λ3 is an essential part of the host s immune response against viruses and the importance of IL28B variations in HCV infection and treatment outcome is now established. However, IL28B variations have recently been investigated for their role in controlling other viral infections including a study comparing 227 individuals with 30

49 HBV infection and 384 with HBV recovery 74. The C/C genotype of rs was not associated with HBV recovery. Furthermore, another study by Martin et al 74 examined subjects with, or at risk, of human immunodeficiency virus (HIV) infection. Again, the SNP rs was not associated with HIV persistence or HIV disease progression IL28B and immune-related diseases Allergic diseases including rhinitis, asthma and atopic dermatitis, are associated with inflammatory reactions triggered by immune responses against antigens (allergens) 75. The significant increase in these diseases over the last 50 years has drawn attention to investigate the early immune interactions, which form the basis of consequent development of allergic disease 76. Examination of newly identified common genetic variations known to influence the host s innate and, to some extent, adaptive immune response such as for IL28B should be performed on well-characterised allergic cohorts. Recently, the ontogeny of the innate immune response in allergic and non-allergic children was investigated as they are likely to affect allergic disease manifestation (via Toll-like receptors microbial identification pathway) during early childhood 77. Innate inflammatory cytokine responses to microbial products at birth and their development trajectory differed between allergic and non-allergic children This indicates the key role of the cytokine profile, particularly TNFα, IL-6, IL-1β and IL-12, during perinatal period and their effect on immune programming Furthermore, Tulic et al 77 reported significant increase in the expression of the pdc in allergic children at birth and one year of age and non-allergic control subjects exhibited constant expression over 5 years of age

50 The primary producers of IFN-λ are pdcs 80 and IFN-λ expression induces activation of Toll-like receptors (TLRs). In the previous study on allergic disease, TLR2- meditated cytokine responses were associated with high pdc TLR2 expression 79. This initial study on allergic disease and innate immune function suggests that variants in genes involved in innate immunity (such as IL28B given the role of pdcs) will be important in allergy. 1.9 RESEARCH DIRECTIONS This study aims to investigate the association between rs variation (tagging SNP 3kb upstream of IL28B) and HCV diversity in chronic HCV infected subjects including a subset that had undergone HCV treatment pegifn-α/rbv and to examine the role of IL28B variation in allergic disease. The specific aims of the project were: To determine the relationship between host genetic variation at IL28B and HCV diversity in the HCV proteins core, NS5A and NS5B. To determine the importance of the relationship between IL28B variation and HCV diversity in predicting treatment pegifn-α/rbv outcome for HCV-genotype 1 infected individuals. To determine if IL28B variation is associated with other immune-related diseases, specifically allergic disease in children. 32

51 1.10 HYPOTHESES IL28B variation correlates with specific variations in HCV proteins and this relationship, in part, determines IFN-treatment outcome in HCV genotype 1 infected individuals. IL28B variations are also important in other immune related diseases such as allergy. 33

52 CHAPTER 2: MATERIALS AND METHODS 34

53 CHAPTER 2: MATERIALS AND METHODS 2.1 HEPATITIS C COHORTS The first two cohorts comprised chronic HCV-infected subjects from Western Australia and Switzerland who already had existing viral sequence available for analysis. These individuals were all HCV treatment naïve at the time of sampling. The third cohort was from Duke University, North Carolina in the US. This cohort comprised chronic HCV genotype 1-infected subjects who had undergone pegifn-α/rbv treatment with known outcome (n=95). IL28B (rs ) typing had already been performed on DNA from these subjects by the Duke University collaborators (Dr Alex Thompson). Demographic and clinical details of the subjects in the Hepatitis C cohorts are shown in Table 2.1. Viral sequencing was performed on the Duke cohort plasma samples and IL28B typing (rs ) was performed on DNA samples from the Swiss and WA cohorts. As part of sample management all subject materials were registered on the Institute of Immunology and Infectious Diseases (IIID) database at Murdoch University. The registration process involved assigning a unique identification number in order to keep subjects anonymous. A barcode was produced for sample storage containers to track chain of custody as well as sample location. Clinical parameters and other details including viral load and subject identifications numbers were recorded in the database. 35

54 Table 2.1: Demographic and clinical information on subjects in the Hepatitis C cohorts. Cohort (n) Assay performed in study HCV Genotype n (%) HCV Treatment * Treatment response n (%) Gender n (%) Ethnicity n (%) Duke (95) WA (25) Swiss (53) Core and NS5 HCV sequencing IL28B genotyping IL28B genotyping GT1a 66 (69.5) GT1b 28 (29.5) ND 1 (1) GT1a 15 (60), GT1b 4 (16), GT3 6 (24) GT1 46 (86.8) and GT3 7 (13.2) Yes No No SVR 37 (38.9) NR 43 (45.3) Relapse 15 (15.8) N/A N/A Male 65 (68.4) Female 30 (31.6) N/A Male 30 (56.6) Female 23 (43.4) Caucasian 66 (69.5) African- American 27 (28.4) Hispanic 2 (2.1) N/A Caucasian 50 (94.3) Others 3 (5.7) ---- Not provided; N/A = not applicable; * Treatment = pegifn-α/rbv; SVR = sustained virological response; NR = non-responder; ND = subtype not determined SAFETY PRECAUTIONS AND QUALITY CONTROL MEASURES As samples were from subjects infected with HCV, appropriate safety controls were adhered to during processing. Specifically, all plasma samples were processed in a Class II Biosafety cabinet using Universal precautions. Negative controls (sterile water) were included in all experiments in order to detect contamination. A genotype 1a positive control sample (H77; Genbank accession number NC_ ) was used in each PCR and sequencing run in order to assess the success of the PCR and sequencing reactions. 36

55 As part of the quality control process for sample handling, each task that was performed was checked by a second individual. Furthermore, checklists were signed-off for robotic layout and sample orientation by a second individual AUTOMATION AND DOCUMENTATION Pre-PCR and post-pcr procedures were performed using the Biomek FX or Biomek NX robots. The IIID in house Elab software system was used to produce individual task proformas and files for the robots to allow the tracking of samples through the entire process. 2.3 HCV GENOME SEQUENCING Viral polymorphism was detected via direct sequencing of the virus extracted from plasma samples. RT-PCR and subsequent PCR rounds specific for the core and/or NS5 regions were used to obtain amplicons that were then sequenced. The sequences were edited using the Assign program (Conexio Genomics) and added to an in-house database (HCV sequences from multiple cohorts tested in laboratory) to check for contamination. The workflow to obtain HCV sequence from the plasma samples is shown in Figure

56 Figure 2.1: Steps involved in obtaining viral sequence. The virus was first extracted from a plasma sample, then a 5 UTR PCR was performed to confirm the success of the RNA extraction, check for possible contamination and determine viral genotype (or confirm genotype based on clinical data). If the initial 5 UTR PCR was successful, PCRs using specific primers were performed to obtain the core and/or NS5 regions. The resultant amplicons were sequenced and analysed using the software program Assign (Conexio Genomics) Viral RNA extraction The MagMax 96 viral isolation kit (Ambion) was used to extract viral RNA from plasma samples. This kit uses magnetic beads to isolate viral RNA and has the advantage of isolating higher RNA yield (IIID manual based on in-house comparisons with other methods), thereby facilitating subsequent amplification. For RNA isolation 100µl of plasma sample was used with 20µl of Bead mix and 195µl of lysis/binding solution. The bead mix was prepared by combining the RNA binding beads (10µl/per reaction) and lysis/binding enhancer (10µl/per reaction). The lysis/binding solution was prepared by mixing RNA Carrier (1µl/per reaction), lysis/binding solution concentrate (65µl/per reaction) and 100% isopropanol (130µl/per reaction). The sample plate was loaded with the appropriate solutions and processed in 38

57 the MagMAX deep-well instrument (Ambion). The sample plate was placed on a magnetic stand to capture the RNA binding beads. A series of washes were performed using wash solutions I and II. Samples in the processing plate were then eluted with 50µl of elution buffer. The purified RNA was collected from the elution plate and stored at -80 C in nuclease free-tubes RT-PCR for HCV 5 UTR The HCV 5 UTR RT-PCR is a one-step procedure performed in order to check the quality of the RNA extraction, the possibility of contamination and to determine the HCV virus genotype or confirm with genotype information provided from collaborators. In order to investigate contamination in RNA extraction and RT-PCR for HCV 5 UTR, a negative control was added in each step. The absence of amplicons in the negative control initially cleared the step from any possible contamination. Furthermore, phylogentic analysis was performed in order to determine the clustering of the correct genotypes for each sample (based on other laboratories or previous sequencing) and identify any contamination. The HCV 5 UTR RT-PCR assay utilizes the Superscript III one-step Reverse Transcription PCR Kit for the preparation of the master mix. The reaction mix consisted of 2x reaction mix (6.25µl/per reaction), RT III/Platinum Taq (0.5µl/per reaction), CSL water (4µl/per reaction) and primers (KY80 and KY78) at 25pmol/µl (0.25µl/per reaction). The KY80 and KY78 primers bind to a highly conserved region of the 5 UTR of the virus and produce an amplicon of approximately 240bp. Primer details are in Appendix I. The reactions were carried out in Axygen 96 full-skirted plates by adding 11.25µl of the reaction mix to 1.5µl of the RNA. The plate was spun down using a Sigma14-5 centrifuge and placed into the thermal-cycler (MJ Dyad/ BIO RAD). The PCR 39

58 conditions for the 5 UTR PCR is one cycle of 50 C for 30 minutes, 94 C for 2 minutes followed by 40 cycles of 94 C for 15 seconds and 61 C for 30 seconds and 68 C for 1 minute, with a final after cycle of 68 C for 5 minutes First-round PCR amplification of HCV template The characterization of the HCV sequence is determined by the conversion of the viral RNA into cdna using a reverse transcriptase enzyme. The procedure used in this study to sequence core and NS5 amplifies the HCV genome into fragments RNA1, RNA2 and RNA3 (Figure 2.2). However, the primer pairs and the thermal-cycler conditions were different for each fragment. These first-round PCRs had already been optimized in the laboratory using a panel of HCV positive samples including a positive control (as above). Figure 2.2: The first round HCV genome fragments. RNA1 extends from 144 bp in core to 2644bp in P7, RNA2 extends from 2412 in E2 to 6823 in NS5A and RNA3 starts at 6076bp in NS4B and ends at 9192bp in NS5B of the HCV genome. For each first-round PCR, HCV RNA (5µl) was mixed with 45µl of reaction mix. The reaction mix consisted of 2x reaction mix (25µl/per reaction), RT III/Platinum Taq (2µl/per reaction), CSL water (16µl/per reaction) and forward and reverse primers 25pmol/µl (1µl/per reaction). The primer pairs used to amplify the RNA1, RNA2 and 40

59 RNA3 regions are shown in Table 2.2. The PCR conditions used for the RNA1-3 regions (including alternative PCRs) are shown in Tables 2.3 and 2.4. Table 2.2: Primer combinations for RNA1, RNA2 and RNA3. Region Primer combination * RNA1 RNA2 RNA3 HCV-209F and HCV-2644R (genotype1) Alternative: HCV_gen_144F and HCV2412R HCV-2412F and HCV-6823R HCV-6076F and HCV-9192R * Primer sequences are listed in Appendix I. Table2.3: Thermal-cycling conditions for first round PCR covering the RNA1 region. Cycle N o Temperature ( C) Time (minutes) seconds (alternative)

60 Table 2.4: Thermal-cycling conditions for first-round RNA2 and RNA3 PCR. Cycle N o Temperature ( C) Time (minutes) seconds (RNA2) 60 (RNA3) (RNA2) 3.5 (RNA3) The first-round amplicon was transferred into sterile 1.5ml eppendorf tubes and stored at -20 C Second-round PCR amplification of first-round HCV PCR template After the completion of reverse transcription and first-round PCR amplification, secondround nested PCR amplification were performed using genotype-specific and generic (amplify genotype 1 and 3 genotypes) internal primers (Figure 2.3). Figure 2.3: Generic and genotype-specific primers used in second round amplification. Core primers (red) were used with the RNA1 fragment. Generic F7 and genotypespecific F8 primers (green) were used with the RNA2 fragment. Genotype-specific F9, F10 and generic F9 primers were used with the RNA3 fragment. 42

61 The reaction mix for second-round PCRs was composed of HCV second-round master mix (21µl/per reaction), Roche Taq DNA polymerase (0.1µl/per reaction), DMSO (1.25µl/per reaction) and forward and reverse primers at 25pmolµl (0.25µl/per reaction). The second-round master mix consisted of 131ml CSL, 20ml pooled 10x buffer, 14.1L CSL water (for dntp dilution), 400µl dntp and 1mL gelatine. The sample plates were placed in the thermal-cycler (MJ Dyad/BIO RAD) and were assayed using the following programs depending on the HCV fragments as shown in Tables 2.5 to 2.8. Mastermixes for second-round PCRs (10X PCR buffer, 100mMdNTPs, gelatine and CSL water) were made in bulk and then tested using a panel of HCV positive samples (including positive control) for a subset of specific PCRs. If successful, aliquots of the master mixes were made and then stored at -20 o C. Table 2.5: Second-round thermal-cycling programs for genotype-specific primers covering the core and NS5 regions. Cycle N o Temperature ( C) Time (minutes) seconds 20 AT1* 30 seconds seconds AT2* 30 seconds AT*= Annealing temperatures 1 and 2. 43

62 Table 2.6: Annealing temperatures for genotype-specific primer pairs covering the core and NS5 regions. Primer pairs AT1/AT2 ( C) core HCV269M13F/HCV1153M13R 58/56 F8 HCV6430M13F/ HCV7481M13R F10 HCV8268M13F/HCV9001M13R 56/54 F9 HCV7335M13F/HCV8356M13R 64/62 AT*= Annealing temperatures 1 and 2. Table 2.7: Thermal-cycling conditions for generic primers F7 (HCV5928M13F/HCV6823M13R) and F9 (HCV7498M13F/HCV8718M13R). Cycle N o Temperature ( C) Time (minutes) (F7) 55 (F9)

63 Table 2.8: Thermal-cycling conditions for alternative primers for core (HCV_gen_144F+ HCV1293R GEN) and F8-10 (HCVgen6628F+HCV9001). Cycle N o Temperature ( C) Time (minutes) seconds 35 53(core) 55 (F8-10) (core) 2.5 (F8-10) The completed plate was processed for electrophoresis in the Post-PCR laboratory. The remaining second round amplicon products were transferred into sterile 1.5ml eppendorf tubes and stored at -20 C Electrophoresis The presence of a successful amplicon was confirmed by electrophoresis. A volume of 10µl of each PCR product was mixed with 5µl of loading dye and then loaded into the sample lanes of an E-Gel 96 (Invitrogen). For the determination of the correct size of the PCR product 10µl of a 100bp ladder (0.1 µg/µl) was loaded into the marker lane. The E-gel was placed attached to an E-base integrated power supply that is designed for the E-Gel 96 system. The gels were run at 100 volt for 10 minutes and then the BIORAD ChemiDoc XRS was used to visualize the PCR products and obtain a digital image. E-editor Software 2.0 was used for the alignment of the sample lanes with the markers for comparison. 45

64 Products were scored based on correct size and intensity. Successful PCR products from the same subjects were pooled in a single microplate in order to maximize the efficiency of the purification. Samples reported as failed were subjected to a different primer combination where possible Purification of HCV PCR products The purification of HCV PCR products was performed using AMPure paramagnetic beads (Beckman Coulter). These particles bind to PCR amplicons and then a magnetic field is used to capture the beads/product complex. Seventy percent ethanol is used to wash the products to remove excess primers, nucleotides, salts and enzymes. An elution step using a magnetic field follows the washing procedure and removes the magnetic beads from the amplicons HCV Sequencing The sequencing reactions were performed using the ABI Big Dye Terminator Cycle Sequencing kit (v3.1). This kit uses fluorescently labeled dideoxynucleotide triphosphates that are attached to the DNA extension products according to the Sanger chain termination reaction. The purified PCR product (18µl), master mix (2µl) and primers (2µl) were added to a 96 well plate. The master mix from the ABI Big Dye Terminator Cycle Sequencing Kit includes ABI Big Dye Terminator Sequencing Buffer (1µl/per reaction). The sequencing reaction was set-up with PCR or M13 primers. For the 5 UTR PCR the amplicons were sequenced using the primers KY80 and KY78. After completion the plate was placed in the thermal cycler (MJ Dyad/ BIO RAD) and the reaction performed using PCR conditions of 25 cycles of 96 C for 10 seconds, 50 C for 5 seconds and 60 C for 4 minutes. 46

65 The purification of sequencing products was performed using CleanSEQ (Beckman Coulter). This magnetic bead buffer purifies the sequencing product by forming a bead/product complex and allowing the removal of unincorporated terminators, excess primers and contaminants by 85% ethanol. The elution step following the washing procedure separates the beads from the products using a magnetic field. The ABI 3130XL Genetic Analyzer was used in this project to capture the HCV sequence information. The ABI 3130XL sequencer is a 16 capillary genetic analyzer that detects the fluorescence from the four dyes that are assigned to each base A, G, C and T. Each dye passes through a capillary and emits a light when excited by an argon laser. All four bases can be distinguished in a single gel lane. All steps were fully automated including polymer loading, sample injection, separation, detection and data analysis Sequence editing Sequence electropherograms from the ABI 3130XL genetic analyzer were imported into the Assign editing software (Conexio Genomics). Assign is a DNA sequence-editing program designed for the analysis of sequences generated from viral and other organisms. The ABI sequences are aligned to a known reference and the bases at single positions are read as A, T, G, C or mixture based on IUPAC nomenclature. The initial base call made by the program can be manually edited Contamination check Edited HCV sequences were imported into the BioEdit program (Sequence Alignment) 81 containing other HCV sequences from other subjects sequenced within IIID and not included in this study. All sequences were aligned using the BioEdit 47

66 program and imported into MEGA v4 82. The nucleotide sequence aligned against the genotype reference sequence. Phylogenetic analysis was performed using the Neighbor- Joining method with the Kimura-2-parameter model for nucleotide or p-distance for amino acid alignments with 1000 bootstrap replications. 2.4 IL28B genotyping DNA extracted from stored peripheral blood mononuclear cells (PBMCs) from subjects in the Swiss and Western Australian cohort (n=68) were genotyped for the rs SNP using an allelic discrimination assay (Taqman). All of the DNA samples were diluted to the recommended concentration of 5ng/µl. The samples and the SNP genotyping master mix were transferred to an optical 384 well plate format in order to perform PCR amplification. The SNP genotyping master mix included the forward and the reverse primers that were designed for the rs SNP and fluorescence based reporter dyes (VIC and FAM). Both negative and positive control samples were added in duplicate to evaluate genotyping results (Figure 2.4). Furthermore, statistical calculations were conducted to evaluate allele frequencies (Hardy-Weinberg formula). The initial work-up of this method was performed by Dr Emma Hammond at IIID. Figure 2.4: Steps involved in the IL28B genotyping assay. 48

67 2.4.1 Extraction of high molecular weight DNA from PBMCs QIAGEN extraction of DNA from PBMCs was performed on spin columns in a microcentrifuge. The samples underwent a lysis step in order to remove all PCR inhibitors including proteins. Following this initial step, the samples were centrifuged and the DNA absorbed onto a silica-gel membrane. The DNA was then washed twice and the samples collected from the membrane with elution buffer Assessment of DNA Quantity and Quality for PCR-Based application The assessment of the quantity and the quality of the extracted DNA is an essential step in obtaining successful PCR products. Two different approaches were performed to determine the DNA quantity including the use of the NanoDrop ND1000 spectrophotometer and the picogreen assay. The quality of the extracted DNA was determined by electrophoresis on 1% agarose gel DNA Quantification using the NanoDrop spectrophotometer Measuring the sample optical density at 260nm and 280nm assesses the DNA quantity using the NanoDrop ND1000 spectrophotometer. Samples were loaded between two fibre optic cables and a pulse of xenon light was passed through the sample absorbance values collected into a linear CCD array. The data collected by the NanoDrop software was used to calculate the concentration of DNA (260nm) and purity (260/280) DNA Quantification with picogreen assay The picogreen assay is another accurate approach for quantifying double-stranded (ds) DNA. The Picogreen dsdna Quantification Reagent (Invitrogen) is an ultra sensitive fluorescent nucleic acid stain for DNA quantification. The assay includes a lambda 49

68 DNA standard. The assay was performed according to the user manual provided with the kit. Briefly, stock (20x) TE buffer was diluted to make 1xTE to make a series of dilutions of the Lambda standard (100µg/ml) for the standard curve (1µl standard to 49µl 1xTE buffer). A six end-point standard curve was generated up to 200ng/µl. The picogreen solution was diluted by adding 60µl picogreen concentrate to 12ml 1xTE buffer. A picogreen mixture (48µl) was dispensed into a 96 well plate followed by the addition of the 1xTE buffer (50µl). Then, DNA samples (2µl) were pipetted into the plate and the standards were added into the last two columns. The samples were excited at 485nm (standard filter) and emission was measured at 535 nm (standard filter). The analysis of the results was conducted using Multimode analysis software Determining the rs genotype using the TaqMan assay In this project, we tested the SNP rs using the ABI 7900 Real Time Thermocycler and BIORAD CFX. DNA samples (2.2µl) were transferred into 96 full skirt well plate and controls were added in duplicate. The reaction mix (2.8µl) was dispensed into the appropriate wells. The SNP genotyping master mix was prepared using the TaqMan SNP genotyping reagents 2x TaqMan Genotyping master mix (2.5µl/per reaction), primers and the reporters VIC and FAM (0.25µl/per reaction) (see Appendix II for specific primer details). The plate was sealed with optical adhesive seal and centrifuged. The plate was then placed in the ABI 7900 Real Time Thermocycler or BIORAD CFX. The conditions of the reaction were one cycle of 95 C for 10 minutes, and 92 C for 15 seconds followed by 40 cycles of 60 C for 1 minute. 50

69 The protocol on each instrument was developed for the rs SNP. The reporter dyes selected for this method were VIC and FAM. Reporter dyes are attached to probes that are specific for each allele. The VIC dye is linked to the probe that is specific for the T allele and the FAM dye is linked to the C allele specific probe. Upon completion the results were analysed using either sequence detection system (SDS) or BIORAD CFX manager. The relative fluorescence unit (RFU) cut-off level that was used in this project was determined by the CFX-BIORAD system. Furthermore, the positive controls used in the assay with a known genotype were used to confirm the cut-off levels Validation of the IL28B genotyping assay using BIORAD CFX The IL28B assay was validated on the BIORAD CFX by using samples that had previously been genotyped by the ABI 7900 Real-time Thermocycler. The samples were transferred to a 384 well plate in duplicate. The reaction mixes were prepared as mentioned above and added to the samples. The plate was placed in the BIORAD CFX 384 platform using the thermal-cycling conditions as described above. The results were analysed using the BIORAD CFX manager software using VIC and FAM detectors. The results obtained for the BIORAD matched the previous results obtained from the ABI machine (Figure 2.5). 51

70 Figure 2.5: Allelic discrimination results for the validation run generated from the BIORAD CFX manager. The clustering of allele 1 on the FAM axis is the genotype C/C while the allele 2 cluster on the VIC axis is the genotype T/T. The diagonal cluster corresponds to the genotype C/T. Samples clustering in the lower left part of the figure represented by diamonds correspond to negative controls and undetermined samples. 2.5 ALLERGY COHORTS The allergic children examined in this study were recruited ante-natally from healthy pregnant mothers from private obstructions in Perth, Australia. Children involved in this study were selected from 739 children enrolled in a birth cohort designed to investigate the pathogenesis of allergy. The first cohort (Cohort 1) consisted of 35 allergic and 35 non-allergic infants. This cohort follows the children over the first five years in order to characterize the development of the innate and adaptive immune system 77. Non-allergic children had no history of allergic disease or sensitization at any stage. Allergic children had been diagnosed with atopic dermatitis, allergic rhinitis, food allergy or asthma and certain IgE to allergens detected by skin-prick test (SPT). The second cohort consisted 52

71 of similar group size cohort with clinically-defined food allergy (n=30) from the same prospective birth cohorts as Cohort 1. For this study food allergy was defined as previous history of immediate symptoms after contact with food, ingestion of food, or both and a positive SPT to that food. Food allergy symptoms were characterized by skin reactions (hives, rash, or swelling) and/or respiratory tract symptoms (cough or wheeze) and/or gastrointestinal symptoms (abdominal pain, vomiting, or loose stools) and/or cardiovascular symptoms (collapse). In this cohort, 12/30 (40%) had severe food allergy (resulting in anaphylaxis). 27/30 (90%) had allergy to eggs, 13/30 (43%) allergy to nuts, 7/30 (23%) were allergic to house dust mite, 5/30 (17%) to cat dander and 20/30 (67%) reacted to multiple foods. All subjects in cohort 1 and 2 were all of Caucasian background. Allergy cohort was genotyped for IL28B (rs ). 2.6 STATISTICAL ANALYSIS Initially, consensus HCV sequences were obtained for each subtype and cohort and then for combined cohorts. The association between the presence or absence of the minor allele at rs and amino acid distribution at each residue of the HCV Core, and NS5A proteins were assessed via Fisher s exact tests for overall distributions and classification as consensus vs. non-consensus amino acid. False discovery rate and associated q-values were also generated. Statistical significance was set at a threshold of p<0.05. Associations between polymorphisms at each amino acid residue and carriage of the risk allele (T) of rs in the population were adjusted for founder effect. Partitioning around mediods method of Kaufman and Roussecuw 83 were used in order to determine clusters based on binary presence or absence of consensus at each residue. For the allergy study, the presence or absence of allergic disease and rs variation was examined by Fisher s exact test (two-tailed) and logistic regression 53

72 analysis. Odds ratios were determined using GraphPrism. Statistical consultation was obtained from Professor Ian James and Dr Elizabeth McKinnon from IIID at Murdoch University. 2.7 Study Approvals. Ethical approval for HCV research was obtained from the Royal Perth Hospital Ethics Committee (EC2004/005). Ethical approval for the allergy study was obtained from Princess Margret hospital for children Ethics Committee (EC07-74). The research is conducted according to the Declaration of Helsinki and International Conference on Harmonization Good Clinical Practice (ICH/GCP) guidelines. 54

73 CHAPTER 3: RESULTS 55

74 CHAPTER 3: RESULTS 3.1 IL28B AND HCV HCV genotyping and contamination check of bulk HCV sequence A total of 95 plasma samples from Duke University were processed for HCV bulk sequencing. Each sample was tested to obtain the 5 UTR, core, NS5A and NS5B regions. Each successful amplicon was bulk sequenced and electropherograms edited using the program Assign as described in Materials and Methods HCV genotyping: comparison of clinical data with bulk HCV sequence All plasma samples from the Duke cohort were initially assessed for genotype/subtype based on the 5 UTR sequence by comparing the sequences against HCV genotype/subtype references. All samples from the cohort were identified as HCV genotype 1a or 1b (Table 3.1). The genotyping results from the HCV 5 UTR sequence were compared to the clinical genotype results obtained as part of the clinical assessment of subjects (from the Duke cohort investigators). There were four discrepancies between the clinical and the 5 UTR sequence dataset, in three cases the clinical typing was 1b and HCV 5 UTR sequence determined the sample as 1a and one sample that had clinical typing as 1a and HCV 5 UTR sequence determined the sample as 1b. We cannot exclude mixed infection in these cases. The initial genotyping results were checked by examining the HCV NS5B region as this region is more variable than the 5 UTR and accordingly has greater discriminatory power to differentiate between subtypes. Genotype/subtype assessment via the NS5B region was made using phylogenetic analysis (Figure 3.1). There were two samples identified as 1b using the 5 UTR but were 1a based on the NS5B region (Table 3.1). These two samples were also classified as 1b based on clinical data. Where there was a 56

75 discrepancy between the 5 UTR sequence and the clinical data, the NS5B region gave the same subtype as the 5 UTR. Not all sequences had NS5B sequence, most likely due to variations in the priming sites affecting the PCR. Where available, genotyping results from the NS5B region were utilized in subsequent analyses. Table 3.1: Number of subtypes determined by bulk HCV sequence (5 UTR and NS5B) and from clinical data (Duke University collaborators). HCV subtype Clinical 5 UTR NS5B 1a b * 14 NA * Not classified into subtypes. NA= not able to be determined HCV sequence contamination check Phylogenetic analysis of HCV NS5B was used to trace potential contamination between samples from the Duke cohort (Figure 3.1). Bootstrap replications (1000) were performed on the tree with clusters corresponding to subtypes and some additional clusters within subtypes supported by bootstrap values >70% (Figure 3.1). No two sequences were identical and each pair-wise comparison showed several sites of variation between sequences suggesting no contamination was present. 57

76 HCV1a HCV1b Figure 3.1: Phylogentic tree of NS5B region for the Duke cohort samples. Phylogenetic tree was constructed using the Neighbor-Joining method with the Kimura-2-parameter model. Reference sequences for genotype 1a (black circle) and 1b (grey circle) are indicated. Bar indicates substitutions/site. Numbers at internal nodes refer to bootstrap replications. 58

77 3.1.2 Analysis of HCV polymorphism and IL28B variation in the three cohorts Phylogenetic analysis of cohort samples Samples from two other cohorts were added to the study: the Swiss HIV cohort and the Western Australian cohort. Figure 3.2 shows the phylogenetic analysis of the HCV NS5B sequences for samples in all three cohorts. The sequences tend to intermingle and do not cluster separately according to cohort. Genotype 3 sequences were only within the Swiss and WA cohorts. This analysis supports the approach to combine the datasets for each subtype/genotype to increase sample number to examine IL28B variation and HCV polymorphism. In addition, genetic distances were calculated within and between the three cohorts shown in Tables 3.2 and 3.3. The results show that the level of genetic similarity within any one cohort is similar to the inter-cohort values. All genetic distances were calculated using the distance method with pair-wise deletion (Mega v4). Table 3.2: Genetic distance within cohorts Cohort Genotypes 1a 1b 3a DUKE SWISS WA Table 3.3: Genetic distance between cohorts Cohort SWISS WA Genotype DUKE 1a b SWISS 1a b a

78 0.02 3a 1b 1a Figure 3.2: Phylogenetic analysis of HCV NS5B amino acid sequences from Duke (open triangles), Swiss (black triangles) and WA (grey triangles) cohorts. Genotype 1a (black circle) and 1b (grey circle) reference sequences are indicated. Distance bar indicates substitutions per site. Neighbor-Joining tree constructed using pair-wise deletion and p-distance model (Mega v4). Only sequences with >50% coverage were included. 60

79 HCV sequence coverage Table 3.4 shows the HCV sequence coverage obtained for cohort samples for the Core, NS5A and NS5B regions. Not all samples had complete sequence, most likely due to sequence variations within the primer sites utilized in the PCR reactions, however all samples had sequence coverage in at least one protein. Viral sequences for the NS5A and NS5B regions for the Swiss and WA cohorts had previously been obtained using similar PCR methods as described As the analysis in this study examined the HCV proteins residue by residue, incomplete sequences could be included. Table 3.4: HCV sequence coverage of cohort samples. Cohort Core NS5A NS5B Duke (mean) 97.14% 85.67% 78.79% Swiss (mean) NA 69.13% 90.87% WA (mean) NA 85.12% 81.12% * NA- no core sequences in Swiss and WA cohort IL28B genotyping All Duke cohort samples had been typed for IL28B using the tagging SNP rs Genotyping for IL28B using rs was performed on available DNA samples from the Swiss and WA cohort. Table 3.5 shows the allele and genotype frequencies at rs for all typed samples in the three cohorts. The T allele frequency is higher in the Duke cohort compared to the Swiss (p=0.08; Fisher s exact test, two tailed). 61

80 Twenty-seven individuals from the Duke cohort are from African American ancestry and the frequency of the T allele is known to be higher among individuals from African American background compared to Caucasian 9. Hence, the Duke cohort is expected to have a greater frequency of the T allele compared to the Swiss cohorts, as the subjects in the Swiss cohort are Caucasian. As expected, the genotype proportions are also significantly different between the Duke and Swiss cohorts (p=0.02; Fisher exact test, two tailed). The frequency of the T allele was similar between the Duke and WA cohorts but ethnicity data for all WA subjects was not available to determine if the ethnic profile was similar. Furthermore, the number of subjects in the WA cohort is small relative to the other cohorts. Table 3.5: rs allele and genotype frequencies for Duke, Swiss and WA cohort samples Allele and genotype Duke (n=95) Swiss (n=53) WA (n=25) frequencies for rs C T CC CT TT Association between IL28B variation and HCV polymorphism In the initial analysis, HCV sequences in core, NS5A and NS5B were correlated to IL28B (rs ) genotype in order to investigate the association between IL28B variation and viral diversity. A consensus sequence was generated for each genotype/subtype for each cohort and also combined. A residue by residue analysis was performed using Fisher s exact test to find an association between IL28B genotype or carriage of the T allele (known risk allele for HCV infection outcome) and presence 62

81 or absence of the consensus amino acid at each residue. As this was an exploratory analysis, the final p values were not corrected for multiple comparisons. Furthermore, given the genetic diversity between genotypes and subtypes, they were analysed separately. Significant associations (p<0.05) were detected between HCV polymorphisms in the NS5 regions and IL28B genotype or carriage of the T risk allele at position 180 in NS5A and 421 in NS5B (p<0.05) for genotype 1a and position 349 in NS5A for genotype 1b for the Duke cohort alone (Table 3.6). No associations were found between IL28B genotype or carriage of the T allele and Core. 63

82 Table 3.6: Significant associations between i) IL28B (rs ) genotype or ii) carriage of the T allele at rs with HCV polymorphism at NS5A and NS5B. Cohort Duke Swiss Duke and Swiss Duke, Swiss and WA i ii ii ii ii HCV genotypes Proteins NS5A NS5B 1a Ib a b a b 98 3a a b a b a Residues in bold indicate p<0.05 with adjustment. Residues underlined indicate unadjusted p<0.05 but p~0.1 with adjustment. The analysis was repeated for the Swiss cohort and then for all cohorts combined (Table 3.6). Common associations were found between IL28B variation and HCV polymorphism for genotype 1a at positions 367, 368 in NS5A and 421 in NS5B and position 349 in NS5A in genotype 1b. The combined analysis identified several new associations between rs variation and positions in both NS5A and NS5B but not core. 64

83 3.1.4 Association between Treatment response and HCV polymorphism The significant associations found between treatment response and HCV polymorphism are shown in Table 3.7. Variation at position 368 in NS5A in genotype 1a is strongly associated with non-response to treatment for HCV (p<0.001). Variation at position 70 in Core for genotype 1b has a p-value of 0.008, but the effect is weakened when adjusted for phylogenetic relatedness. However, given the low levels of variation in Core, accounting for clustering in this protein may be a conservative approach. Table 3.7: Significant associations between HCV treatment non-responders and HCV polymorphism Cohort HCV genotype Protein Core NS5A NS5B 421 Duke 1a b 90 Residues in bold indicate p<0.05 with adjustment. Residues underlined indicate unadjusted p<0.05 but p~0.1 with adjustment. Another variation at position 90 in Core for genotype 1b was associated with treatment outcome with unadjusted p<0.05. Variation at position 421 in NS5B for genotype 1a was also associated with non-response (p<0.05), the same position as indicated for IL28B genotype or carriage of the T allele. Similarly, position 368 in NS5A for genotype 1a was also found to be associated with carriage of the T allele of rs

84 3.1.5 Association between gender and HCV polymorphism Other factors known to influence outcomes were also tested to determine if they affected HCV diversity. Association between variation from consensus amino acid and male/female gender was investigated. Several amino acid positions were identified as shown in Table 3.8. Table 3.8: Significant associations between gender and HCV polymorphism. Cohort Genotypes Proteins NS5A NS5B Duke 1a Ib 246 Residues in bold indicate p<0.05 with adjustment. Residues underlined indicate unadjusted p<0.05 but p~0.1 with adjustment. There was no overlap between the associations found for gender and HCV polymorphism and treatment response or IL28B genotype and HCV polymorphism Viral clusters and IL28B genotype Analysis of the core and the NS5 sequences suggested some clustering within the sequences. Partition around medoids statistical approach was used to analyse the clustering effect (Figure 3.3). 66

85 Component Component Component 1 a) These two components explain % of the point variability Component 1 b) These two components explain % of the point variability. Figure 3.3: Viral clustering based on consensus/non-consensus amino acid for a) 1a core and b) 1b NS5B. The analysis of sequences suggested that the clusters for genotype 1a core were associated with the IL28B rs SNP (p=0.0013). There were no significant associations for gender, ethnicity or non-responders within the 1a core clusters (P>0.38). For the genotype 1b core sequences, clusters were associated with ethnicity (p=0.02) and non-response (p=0.05) Joint analysis of factors associated with HCV outcome When considered jointly with adjustment for other covariates, carriage of the T allele of rs and ethnicity were associated with non-response in the Duke cohort (p=0.001). 67

86 3.2 IL28B AND ALLERGIC DISEASE All children were genotyped for the IL28B tagging SNP rs by TaqMan allelic discrimination in order to determine the relationship between genetic variation at IL28B and allergic disease. The data represented in Figure 3.4 shows the distribution of the alleles using a unique pair of fluorescent dye detectors. FAM detector is a match for allele 1 (C) and the other fluorescent dye VIC is a complete match for allele 2 (T). The detection of both fluorescent dyes is classified as heterozygote C/T. Figure 3.4: Allelic discrimination representation for allergy cohort 1. VIC detect Allele 1 T risk allele, FAM detect Allele 2 C protective allele. The analysis of the results obtained from the TaqMan allelic discrimination assay indicated that carriage of the risk allele (T in either homozygous T/T or heterozygous C/T form) is significantly associated with allergic phenotype (Fisher's exact test, p=0.003) (Figure3.5). 68

87 In order to confirm these results, a second cohort was obtained including children from the 739 children who had evidence of severe food allergy (allergy cohort 2). Allergy cohort 2 was genotyped for the IL28B tag SNP rs as for the other cohort. The allelic discrimination assay results for cohort 2 are shown in Figure 3.6. Carriage of the T allele at rs was again associated with allergic phenotype (food allergy) (P=0.04) (Figure 3.5). Figure 3.5: Variation at tagging SNP rs confers risk for allergic disease. A. Carriage of the T allele of rs is over-represented in children with allergic disease (cohort 1) (p=0.003). This relationship is also observed for children with IgEmediated food allergy (cohort 2) (p=0.04 dominant model). For both cohorts, the frequency of the different genotypes varies between disease and control subjects (p=0.02; cohort 1 and cohort 2). B. Odds ratio (OR; 95% CI) for carriage of T allele of rs and allergic disease and for HCV persistence. Odds ratio values for HCV cohorts are from (di Iulio et al, 2011) 85. OR for allergy adjusted for gender. ORs for HCV cohorts adjusted for HBV co-infection in all cohorts and gender in multiple source cohort. 69