HOST CYTOKINE GENE POLYMORPHISMS AND PARASITE GENETIC VARIABILITY IN DETERMINING THE DISEASE OUTCOME OF Plasmodium falciparum INFECTION Y By AR R SEGUN ISAAC, OYEDEJI B B.Tech. Biology [LAUTECH] I M.Sc. Zoology (Parasitology) [IbaYdan] L Matriculation Number: 1I1T3321 RS A Thesis in the DEepartment of Zoology, SubmittedI tVo the Faculty of Science In partial fulfiUlmeNnt of the requirements for the Degree of N DA DOCTOR OF PHILOSOPHY IB A of the UNIVERSITY OF IBADAN SEPTEMBER, 2012 ABSTRACT Malaria, the world‟s most important tropical parasitic disease is caused by Plasmodium species. Infection with Plasmodium falciparum can result in one of three possible disease outcomes: Asymptomatic (AS), Uncomplicated Malaria (UM) or Severe Malaria (SM). Information on host genetic factors and parasite genetic diversity can improve understanding of the disease pathogenesis. In this study, the genetic diversity of P. falciparum isolates as wYell as polymorphisms in host cytokine genes was investigated in relation to the outcoRme of P. falciparum infection. RA Four hundred and thirty-seven children recruited from the SpecBialist Hospital, Lafia, Nasarawa State were assigned into UM or SM based on malaria severityI, determined by clinical and laboratory diagnoses. Asymptomatic children recruited from pLrimary schools within the study location constituted the control group (AS). PlasmoYdium falciparum infection was confirmed by PCR-based assay of SSUrRNA genes. GIenTetic diversity of P. falciparum was analyzed by genotyping the polymorphic domains ofS the Merozoite Surface Protein 2 (MSP-2). Host cytokine genes investigated included InterleuRkin-18 (IL-18), IL-18 receptor alpha (IL-18Rα) and Tumour Necrosis Factor alpha (TNF-Eα). Sequencing of MSP-2 gene and of the pro- ® inflammatory cytokines was carried oIutV using ABI PRISM 3100. Sequences were analyzed using the BioEdit Sequence AlignmNent software. Genotype and allelic frequencies were analyzed by Chi-square test. The level oUf significance was set at P=0.05. All participants hNad P. falciparum infection. Polyclonality was significantly higher in the AS (61%) and UM (A60%) groups compared with the SM (34%) group. Mean multiple infections was 2.1 ±1.0 in DAS, 2.0 ±1.0 in UM and 1.3 ±0.6 in SM. A total of 32, 35 and 28 distinct MSP-2 alleles wereA found in the AS, UM and SM groups respectively. Frequency of the 3D7 allele type was siIgBnificantly higher in UM (51%) and SM (54%) groups compared to the AS group (38%). Sequence analysis of the central variable region of the MSP-2 gene showed that the FC27-type sequence was characterised by two unique subtypes and hybrid sharing sequence with the two subtypes. The 3D7-type sequence was characterised by three subtypes of repetitive domains: a GSA-rich repeat unit, a TPA repeat motif and a poly-Threonine stretch. Three single nucleotide polymorphisms (SNPs): -656G/T, -607C/A and -137G/C were identified at the promoter region ii of IL-18 gene. The -656G/T and -607C/A SNPs were found to be in complete linkage disequilibrium. The genotype frequency of -607AA was significantly higher in the AS group 2 compared to SM cases (χ =4.26, P<0.05). Likewise, four SNPs were identified at the promoter and Exon 1 of the IL-18Rα: -661T/C, -175G/A, -93C/T and Ex1 +21C/G but none was associated with disease outcome based on statistical level of significance. Exons 2 to 11 of IL-18Rα gene were relatively conserved. Furthermore, two SNPs: -308G/A and -238G/A were identified Yat the promoter region of TNF-α but none was associated with disease outcome. R Plasmodium falciparum was found to be genetically heterogeneous. HighAer carriage of Plasmodium falciparum 3D7 alleles indicates higher risk of developingB symRptomatic malaria. There was association between IL18 -607AA genotype and asympLtomIatic infection, probably indicating a protective role. Keywords: Plasmodium falciparum, Merozoite, Cytokine, PTolyYmorphism, Disease outcome. Word count: 498 RS I VEI UN AN AD IB iii ACKNOWLEDGEMENT I am deeply indebted to Dr. Henrietta Awobode, my supervisor, under whose guidance I have received both intellectual and technical skills needed for this work. I am most grateful for the relentless encouragement and the constant push that altogether gave me the courage to move on. I sincerely appreciate the frank advice, helpful comments and criticisms- all of whichY have helped to refine this work. Thank you for your understanding, thank you for your supRport. You are indeed one in a million! A I am also grateful to Prof. Jürgen Kun (of blessed memory) of the InRstitute of Tropical Medicine, Tübingen, Germany, for believing in me and granting me free IacBcess to all I needed to do my work in his lab in Germany. Thank you so very much. L I am also appreciative of my mentors who had impact oYn me at one point or the other. I appreciate Dr. P. Olumese who aroused my interest and exIpTosed me to the field of malariology. I thank Dr. A. Bakare and Dr. O. Amodu both of whoSm have been instrumental to my choice of research area. Special thanks to Prof. O. OdaiboR, Prof. P. Kremsner, Dr. C. Anumudu, Dr. R. Nwuba, Dr. R. Gbadegesin, Dr. A. Adeyemo, … the list is endless; all of whom have blessed my life in different ways. VE I am particularly grateful toN ProIf. I. Adeyemi, Dr. A. Adeoye, Prof. O. Ogunmoyela, Dr. O. Malomo, Prof. I. Fawole, DUr. T. Yekeen, Mr. O. Olaniyi, Mr. T. Ganiyu and all my friends for their support and encouragem ent all the way. Special thanks to all those whose name could not appear here, but have coNntributed in no small measure to the success of this work. I thankfuDlly Aacknowledge the financial support/scholarship received from the Deutscher AkademischAer Austausch Dienst (DAAD) that enabled me to carry out my bench work in GermanBy. I also wish to appreciate the MIM/TDR arm of the WHO for giving me a PhD ReseaIrch Training Fellowship. I acknowledge the Staff Research grant from Bells University of Technology, Ota. Special thanks to the children and their parents/guardian, who consented and participated in this study. I am also indebted to the clinicians, nurses and laboratory scientists of the Dalhatu Araf Specialist Hospital (DASH), Lafia, Nasarawa State, for their immense contributions and iv support. Many thanks to the Nasarawa State Ministry of Health and the Ethics Committee of DASH for giving me the required approval to carry out this study. Finally, to The One who has kept me thus far, The Giver of life, in whom I live, move and have my being, The only wise God, before whom we all shall defend the “Theses of our lives”, I give all Glory, Honour, Adoration and Praise forever and ever… Amen! RY BR A LI ITY RS IV E UN N AD A IB v CERTIFICATION I certify that this work was carried out by Mr. Segun I. OYEDEJI, Department of ZOOLOGY, University of Ibadan. AR Y R LI B ---------------------------------------------T----Y------- Supervisor I RS Henrietta O. AEwobode, B.Sc., M.IScV., (Jos), Ph.D (Ibadan) SenioNr Lecturer, DUepartment of Zoology, AN University of Ibadan, Ibadan AD IB vi DEDICATION To the loving memory of my late Dad, Dn. Isaac B. Oyedeji and my late older sister, Mrs Grace Onwuasoanya, as well as my late father-in-law, Mr. Chris Michael Ekwuribe. To my wife, Mrs Mayowa Ngozi Oyedeji and my sons, Ephraim and Obaloluwa forY their patience, love, sacrifices, prayers and support all through the period of this study. R To my mum, Dns Mary Oyedeji and my brothers Seyi-, Tunde- and SRamuAel Oyedeji for their prayers support and love shown throughout the trying period. B Y LI IT S VE R NI N U AD A IB vii TABLE OF CONTENTS Content Page number Title Page i Abstract ii Acknowledgement iv Y Certification vi R Dedication vAii Table of Contents Rviii List of Tables IB xii List of Figures L xiii List of Abbreviations Y xvi CHAPTER ONE: INTRODUCTION IT 1 1.1 Background to the study R S 1 1.2 Justification for the Study E 7 1.3 Aims and Objectives V 8 CHAPTER TWO: LITERATURE RIEVIEW 9 2.1 Historical Background of MNalaria 9 2.2 Global Malaria Situati onU 11 2.2.1 Socio-economNic Impact of Malaria 16 2.3 The Malaria PAarasite 17 2.3.1 ClasDsification 17 2.3.2 LAife Cycle of Human Malaria Parasites 18 2.4 I GBenetic Diversity of the Malaria Parasite 27 2.4.1 The merozoite surface protein-1 28 2.4.2 The merozoite surface protein-2 29 2.5 Pathogenesis of Malaria 32 2.6 Host Immune Response to Malaria 37 2.6.1 Innate (non-specific) Immunity to Malaria 37 viii 2.6.2 Acquired (Adaptive) Immunity to Malaria 39 2.7 Cytokines in Host Defence against Malaria 45 2.7.1 General features of cytokines and gene expression 46 2.7.2 Pro-inflammatory and anti-inflammatory cytokines 48 2.8 Genetic basis of Host Resistance to Malaria 54 2.8.1 Haemoglobin variants 55 Y 2.8.2 Variants of red cell enzyme 58 R 2.8.3 Immunogenetic variants 5A9 CHAPTER THREE: MATERIALS AND METHODS R64 3.1 Study Site IB 64 3.2 Study Population L 64 3.3 Ethical Considerations Y 66 3.4 Sample Collection IT 66 3.5 Microscopy S 67 3.6 Determination of Haemoglobin Level (PCRV) 67 3.7 Determination of Haemoglobin GenoEtypes 67 3.8 DNA Extraction V 68 3.9 Design and Synthesis of OligonIucleotide Primers 69 3.10 PCR Determination oUf PlNasmodium species 69 3.10.1 SSUrRNA gene PCR 70 3.10.2 Gel ElectroNphoresis 70 3.11 MolecularA Characterization of P. falciparum MSP-2 70 3.11.1 MDSP-2 Gene PCR 70 3.11.2A Gel Electrophoresis 71 3I.B11.3 DNA Purification 71 3.11.4 MSP-2 Sequencing PCR 72 3.11.5 Purification of Sequencing Products 72 3.11.6 MSP-2 Gene Sequencing 72 3.11.7 MSP-2 Gene Sequence Analysis 73 3.12 Determination of Genetic Polymorphisms in IL-18 Promoter Region 73 ix 3.12.1 IL-18 PCR 73 3.12.2 Gel Electrophoresis 73 3.12.3 DNA Purification 75 3.12.4 IL-18 Sequencing PCR 75 3.12.5 Purification of Sequencing Products 75 3.12.6 IL-18 Gene Sequencing 75 Y 3.12.7 IL-18 Gene Sequence Analysis 75 R 3.13 Determination of Genetic Polymorphisms in IL-18 Receptor-α Gene 7A6 3.13.1 IL-18 Receptor-α Promoter and Exon 1 PCR R76 3.13.2 IL-18 Receptor-α Exons 2, 3, 6 and 11 PCR B 76 3.13.3 IL-18 Receptor-α Exons 4, 5, 7, 8, 9 and 10 PCR LI 76 3.13.4 Gel Electrophoresis 77 3.13.5 DNA Purification Y 77 3.13.6 IL-18 Receptor-α Sequencing PCR IT 77 3.13.7 Purification of Sequencing ProductsR S 77 3.13.8 IL-18 Receptor-α Gene SequencEing 79 3.13.9 IL-18 Receptor-α Gene Sequence Analysis 79 3.14 Determination of Genetic PolIymVorphisms in TNF-α Promoter Region 79 3.14.1 TNF-α PCR N 79 3.14.2 Gel ElectrophoreUsis 79 3.14.3 DNA Purificati on 81 3.14.4 TNF-α SeqNuencing PCR 81 3.14.5 PuDrificAation of Sequencing Products 81 3.14.6A TNF-α Gene Sequencing 81 3.B14.7 TNF-α Gene Sequence Analysis 81 3.1I5 Statistical Analysis 82 CHAPTER FOUR: RESULTS 83 4.1 Microscopy and PCR-based Diagnosis of Mixed Infections 83 4.2 MSP-2 Genotyping of Parasite Population 90 4.3 MSP-2 Sequence Diversity 95 x 4.3.1 MSP-2 Sequence Diversity in the FC27 Allelic Type 95 4.3.2 MSP-2 Sequence Diversity in the 3D7 Allelic Type 98 4.4 IL-18 gene Promoter Polymorphisms 104 4.5 IL-18 Receptor-α gene and Promoter Polymorphisms 104 4.5.1 Distribution of genotype variants in IL-18 R-α gene promoter 105 4.5.2 Distribution of Promoter (AC)n repeats among the study groups 106 Y 4.5.3 Distribution of Exon 1 and Exon 7 genotypes 119 R 4.5.4 Report of conserved Exons 2-6, 8-11 1A19 4.6 TNF-α gene Promoter Polymorphisms R142 CHAPTER FIVE: DISCUSSION IB 147 5.1 Genetic polymorphisms of P. falciparum MSP-2 alleles L 147 5.2 Sequence diversity of P. falciparum MSP-2 gene Y 151 5.3 IL-18 promoter polymorphisms and disease outcomTe of malaria 155 5.4 IL-18Rα polymorphisms and disease outcomeS of Imalaria 157 CHAPTER SIX: CONCLUSION R 158 REFERENCES E 159 APPENDIX V 207 NI N U DA IB A xi LIST OF TABLES Title Page number Table 2.1: Hierarchical Taxonomy of Human Malaria Parasites 19 Table 4.1: Baseline characteristics of study participants 84 Y Table 4.2: Distribution of haemoglobin (Hb) genotype among the study participants 85R Table 4.3: Frequency of Plasmodium species infections in the study population A 89 Table 4.4: Genetic diversity of isolates using the P. falciparum MSP-2 as moleculaRr Marker IB 92 Table 4.5: Genotype and allele frequencies of IL18 -656G/T, -607 C/A, -1L37G/C polymorphisms. Y 108 Table 4.6: Genotype and allele frequencies of IL18Rα -661T/C,T -175G/A, -93C/T and (AC)n repeats. SI 109 Table 4.7: Genotype and allele frequencies of IL-18RRα Ex1 +21C/G and Ex7 +63C/T 120 Table 4.8: Genotype and allele frequencies ofV TNEFα -308G/A and -238G/A 143 NI N U DA IB A xii LIST OF FIGURES Figure 2.1: Global distribution of malaria showing risk of transmission. 12 Figure 2.2: Estimated percentage of malaria cases due to P. falciparum. 13 Figure 2.3: Global malaria burden showing regional relationship to morbidity and mortality. 14 Figure 2.4: Diagram of a merozoite, highlighting major organelles and cellular Y structures. R20 Figure 2.5: Four major species of the human malaria parasites. A 21 Figure 2.6: Life Cycle of the Human Malaria Parasite. R 23 Figure 2.7: Invasion of Red Blood Cell by Merozoite. IB 25 Figure 2.8: Schematic diagram of MSP-2 gene. L 31 Figure 2.9: Case fatality of major clinical syndromes of seveYre m alaria among African children. 36 Figure 3.1: Map of Nigeria showing Lafia, where the stIuTdy was conducted. 65 Figure 3.2: IL-18 gene showing location of promotSer polymorphisms. 74 Figure 3.3: IL-18Rα gene showing location of Rpromoter polymorphisms. 78 Figure 3.4: TNF-α gene showing location Eof promoter polymorphisms. 80 Figure 4.1: Plasmodium falciparum IpaVrasites on thick film of a study participant. 86 Figure 4.2: Plasmodium ovale parasites on thick blood film of a study participant. 87 Figure 4.3: Distribution PlasmoNdium species among the study groups. 88 Figure 4.4: ElectrophNoreti c Useparation of PCR products showing intra-allelic diversity. 93 Figure 4.5: ClonaAlity of P. falciparum infection amongst the three study groups. 94 Figure 4.6: CDentral region of the MSP-2 gene showing nucleotide sequence variations. 96 Figure 4.7: APortion of the MSP-2 gene showing nucleotide sequence diversity, non-synonymous polymorphisms and variation in repeat unit. 97 FigureI 4B.8: Multiple sequence alignment of the FC27 allelic type of the MSP-2 gene showing intra-allelic sequence variations 100 Figure 4.9: Central region of MSP-2 locus showing conserved amino acid sequences at the C-terminal region of the FC27-type allele. 101 Figure 4.10: Multiple sequence alignment of the 3D7 allelic type of the MSP-2 gene showing intra-allelic variations. 102 Figure 4.11: Central region of MSP-2 gene showing partially conserved sequences at the C-terminal region of the 3D7-type allele. 103 xiii Figure 4.12: Agarose gel electrophoresis of IL18 gene promoter region showing ~1370bp of PCR product. 110 Figure 4.13: DNA sequence electropherogram showing the IL18 -656 G/T promoter polymorphism. 111 Figure 4.14: DNA sequence electropherogram showing the IL18 -607 C/A promoter polymorphism. 112 Figure 4.15: DNA sequence electropherogram showing the IL18 -137 G/C promoter polymorphism. 11Y3 Figure 4.16: Agarose gel electrophoresis of IL18Rα Exon 1 showing ~1409bp of R PCR product. A 114 Figure 4.17: DNA sequence electropherogram showing IL18Rα -661T/C polRymorphism.115 Figure 4.18: DNA sequence electropherogram showing IL18Rα -175GI/AB polymorphism.116 Figure 4.19: DNA sequence electropherogram showing IL18Rα -9 3LC/T polymorphism. 117 Figure 4.20: DNA sequence electropherogram showing the IL18Rα -430 A/C microsatellite repeats. Y 118 Figure 4.21: DNA sequence electropherogram showing thTe IL18Rα Ex1 +21C/G polymorphism. I 121 Figure 4.22: Agarose gel electrophoresis of IL1R8Rα SExon 7 showing ~410bp of PCR product. 122 Figure 4.23: DNA sequence electropheVrogrEam showing the IL18Rα Ex7 +63C/T polymorphiIsm. 123 Figure 4.24: Agarose gel electropNhoresis of IL18Rα Exon 2 showing ~525bp of PCR product. 124 Figure 4.25: Multiple align mUent of Exon 2 sequences showing conservation to reference Nsequence when identities were plotted as dot to ref.standard. 125 Figure 4.26: AgaroAse gel electrophoresis of IL18Rα Exon 3 showing ~415bp of PCR pDroduct. 126 Figure 4.27:A Multiple alignment of Exon 3 sequences showing conservation to reference sequence when identities were plotted as dot to ref. standard. 127 FigureI 4B.28: Agarose gel electrophoresis of IL18Rα Exon 4 showing ~285bp of PCR product. 128 Figure 4.29: Multiple alignment of Exon 4 sequences showing conservation to reference sequence when identities were plotted as dot to ref. standard. 129 Figure 4.30: Agarose gel electrophoresis of IL18Rα Exon 5 showing ~350bp of PCR product. 130 xiv Figure 4.31: Multiple alignment of Exon 5 sequences showing conservation to reference sequence when identities were plotted as dot to ref. standard. 131 Figure 4.32: Agarose gel electrophoresis of IL18Rα Exon 6 showing ~240bp of PCR product. 132 Figure 4.33: Multiple alignment of Exon 6 sequences showing conservation to reference sequence when identities were plotted as dot to ref. standard. 1343 Figure 4.34: Agarose gel electrophoresis of IL18Rα Exon 8 showing ~280bp of PCR product. 1Y34 Figure 4.35: Multiple alignment of Exon 8 sequences showing conservation to R reference sequence when identities were plotted as dot to ref. standarAd. 135 Figure 4.36: Agarose gel electrophoresis of IL18Rα Exon 9 showing ~370bpR of PCR product. B 136 Figure 4.37: Multiple alignment of Exon 9 sequences showing conservIation to reference sequence when identities were plotted as do tL to ref. standard. 137 Figure 4.38: Agarose gel electrophoresis of IL18Rα ExonT 10 sYhowing ~402bp of PCR product. 138 Figure 4.39: Multiple alignment of Exon 10 sequencSes sIhowing conservation to reference sequence when identitiesR were plotted as dot to ref. standard. 139 Figure 4.40. Agarose gel electrophoresis ofE IL18Rα Exon 11 showing ~750bp of PCR product. 140 Figure 4.41. Multiple alignment of ExIoVn 11 sequences showing conservation to reference sequence when identities were plotted as dot to ref. standard. 141 Figure 4.42. Agarose gel electropNhoresis of TNF-α promoter region showing ~832bp of PCR product. 144 Figure 4.43 DNA sequenc e Uelectropherogram showing the TNFα -308G/A PolymorpNhism. 145 Figure 4.44 DNAA sequence electropherogram showing the TNFα -238G/A pDolymorphism. 146 BA I xv ABBREVIATIONS HWE: Hardy-Weinberg equilibrium: IL: Interleukin IL-18Rα: Interleukin-18 receptor alpha TNF-α: Tumour necrosis factor alpha Y IFN-γ: Interferon gamma R LD: Linkage disequilibrium A OR: Odd ratio R AM: Asymptomatic malaria IB UM: Uncomplicated malaria L SM: Severe malaria PCR: Polymerase chain reaction TY SNP: Single nucleotide polymorphism I dNTPs: 2'-deoxynucleoside-5'-triphosphate S HLA: Human Leukocyte Antigen R MHC: Major Histocompatibility ComEplex G6PD: Glucose-6-phosphate dehIyVdrogenase Hb: Haemoglobin N NK Cells: Natural killer ceUlls JAK-STAT: Janus-KinNase protein-signal transducers and activators of transcription factors Ig: ImmuAnoglobulin GPI: GDlycosyl-phosphatidyl-inositol µl: AMicrolitre MOI: Multiplicity of Infection kDa: IB Kilodalton mg: Milligram PCV: Packed cell volume (haematocrit) WBC: White blood cells WHO: World Health Organisation xvi DNA: Deoxyribonucleic acid AR Y LIB R ITY S VE R UN I AN BA D I xvii CHAPTER ONE INTRODUCTION 1.1 Background to the Study Malaria is the world‟s most prevalent and by far, the world‟s most important troYpical parasitic disease (Garcia et al., 1995; WHO, 2000b; Garcia, 2010). It is a globRal health problem and a threat to about 40% of the world‟s population (WHO, 20R03bA). It has been estimated that about 300-500 million clinical cases occur each year and more than one million people die from the disease annually, mostly infants, yoLunIg Bchildren and pregnant women (WHO, 2000b, 2009; Murray et al., 2012). Malaria exerts its heaviest toll in Africa, wIheTre Yaround 90% of the more than a million deaths from malaria occur each year (WHSO, 2003a; Snow et al., 2005). The largest population at risk of the disease in Africa is in Nigeria, where malaria is a major public health problem (WHO, 2008b), accountiEng fRor about 65% of hospital cases and resulting in the death of close to 300,000 childrenV annually (WHO/UNICEF, 2005; FMOH, 2008). Human malaria is tradNitionIally known to be caused by four species of plasmodial parasites: Plasmodium faUlciparum, P. vivax, P. ovale and P. malariae. A fifth species, Plasmodium knowlesi, previously known to infect rhesus monkeys has now been found to be widely distributeNd in human population in Malaysia with the potential to cause disease and deaths (CoxA-Singh et al., 2008, 2010). Malaria parasites are usually transmitted by the bites of infDected female Anopheles mosquitoes. Africa is home to three major malaria vecBtorsA: Anopheles gambiae, Anopheles funestus and Anopheles arabiensis (Collins et al., 20I00; Rizzo et al., 2011). P. falciparum is the most virulent species of human malaria parasites (Gupta et al., 1994; Chen et al., 2000). It has been estimated that about 2.37 billion people worldwide, are at risk of P. falciparum infection alone (Guerra et al., 2008). In sub-Saharan Africa, most malaria infections are caused by P. falciparum where it is one of the most common causes 1 of childhood morbidity and mortality (Snow et al., 2005; WHO, 2005). Infections with P. falciparum can lead to different degrees of illness which initially starts as symptomless or asymptomatic infection; but may progress to acute uncomplicated disease, or to life- threatening severe forms (Snow et al., 2005; WHO 2000). However, the vast majority of malaria cases still present as non-specific febrile illnesses that are relatively easily terminated by either antimalarial treatment or, eventually, by host responses. Only a small proportion of cases, approximately 1%, progress to severe life-threateningR diYsease (Mackintosh et al., 2004; WHO/UNICEF, 2005). The reasons for these differences are not fully understood. However, several studies have suggested that variability iAn the clinical outcome of P. falciparum infection may be a consequence of heterogReneity in parasite phenotypes and host factors (Craig et al., 2000; Migot-Nabias et alI.,B 2000; Conway, 2007; Olotu et al., 2012). Y L Several parasite factors have been shown toT influence the clinical outcome of malaria. High propagation capacity of parasites, Ileading to high parasite loads and subsequent depletion/destruction of erythrocyteSs is a key factor that contributes to the clinical features of malaria (Haldar et Eal.,R 2007). The unique ability of P. falciparum infected RBCs to adhere to vascIuVlar endothelium (cytoadherence) and to non-infected erythrocytes (rosetting) is also a major contributor to the clinical manifestations of malaria (Kyes et al., 2001; Doumbo etN al., 2009; Fatih et al., 2012). In addition, the malaria parasite has a notorious surviva l Umechanism- the ability to undergo almost unlimited antigenic variation through chNanging the antigens on the infected red cell surface (Chen et al., 2000; Moxon et al., 20A11; Merrick et al., 2012; Witmer et al., 2012). AFurtDhermore, there exists wide range of genetic polymorphisms in natural popBulations of malaria parasites. Specifically, studies have shown that infections with P. faIlciparum exhibit a wide range of genetic diversity (Ntoumi et al., 1995; Smith et al., 1999b; Amodu et al., 2008; Takala and Plowe, 2009; Auburn et al., 2012). Genetic diversity of P. falciparum infections have been found to be higher in areas of high transmission than in low transmission areas (Babiker et al., 1997; Farnert et al., 2001; Ghanchi et al., 2010; Atroosh et al., 2011) and, it is observed at any of the developmental stages of the parasite. Genetic diversity in the parasite population increases the likelihood of an individual being 2 infected with different parasite genotypes (Arnot, 2002). Such infections are generally described as multiple or complex infections (Bendixen et al., 2001; Mayengue et al., 2011). This is particularly indicated by the large pool of merozoite surface protein-1 (MSP-1) and MSP-2 alleles reported so far (Ntoumi et al., 1996; Robert et al., 1996; Beck et al., 1999; Hussain et al., 2011; Mayengue et al., 2011; Koukouikila-Koussounda et al., 2012). Genetic complexity of P. falciparum (Arnot, 2002) and especially polymorphism of its surface antigen (Kyes et al., 2001) have been associated with clinical malaria (Al-Yaman eYt al., 1997; Beck et al., 1997; Farnert et al., 1999) in disease endemic areas. In NigeriaR however, only few studies have been conducted on the genetic diversity of P. falciparuAm infections and most were in Southern Nigeria (May et al., 1999; Engelbrecht eIt Bal., 2 R000; Happi et al., 2004; Amodu et al., 2008; Ngoundou-Landji et al., 2010; Ojurongbe et al., 2011). The only available data in Northern Nigeria assessed genetic diversiYty in c Lhildren with asymptomatic P. falciparum infections (Engelbrecht et al., 2000). TheTre is therefore need to assess genetic diversity in clinical infections including uncomplicaIted malaria as well as severe malaria cases. Moreover, there is no available data onS the sequence diversity of P. falciparum isolates in Nigeria. These gaps in informatioRn are part of what this study is set out to fill in order to generate data that will be relevanEt for malaria control interventions. Apart from the role of genIeVtic constitution of the parasite in determining disease outcome, there is evidence aNlso that the genetic background of the host, influences the degree of protection an inUdividual develops against malaria (Hill, 1996; Hill, 1999; Knight and Kwiatkowski, N1999; Kwiatkowski, 2005). Host genetic factors may determine an individual‟s initAial resistance to malaria, their likelihood of developing severe complications once an infDection has occurred, or their prospect of acquiring effective long-term immunity (KwiatkAowski, 2000). One of the best examples of host genetic resistance to malaria came frIomB studies on genes encoding red blood cell proteins such as haemoglobin S (HbS), HbC, α-thalassaemia and glucose-6-phosphate dehydrogenase (G6PD), with the HbS allele regarded as the classic paradigm of balanced polymorphism (Haldane, 1949; Allison, 1954; Lederberg, 1999; Feng et al., 2004; Kwiatkowski, 2005; Cappellini and Fiorelli, 2008; Taylor et al., 2012). 3 Beside studies on variants of red cell genes, several other studies on immunity- related genes as well as genes encoding adhesion molecules have shown variation among individuals for disease resistance to malaria (Hill et al., 1991; Jepson et al., 1997). Analyses of the major histocompatibility complex (MHC) have shown strong evidence for associations between both HLA Class I and Class II alleles and susceptibility to P. falciparum malaria (Hill et al., 1991; Weatherall and Clegg, 2002). Variants of genes encoding adhesion molecules such as ICAM-1 and CD36 have also been suggested to aYffect the outcome of Plasmodium infections (Fernandez-Reyes et al., 1997; AitmanA et aRl., 2000). It is well established that host immune responses to malaria incluRde components of the innate and adaptive immune systems (Perlmann and Troye-BlomIbBerg, 2002). These two arms of the immune defence mechanism are pivotal in contro llLing parasite replication and clearance from parasitized host. Furthermore, there are indiYcations from both murine models and human studies suggesting that cytokines, along witTh T cells, NK cells and macrophages, contribute to the pathophysiology of either surSvivaIl or fatal outcome in P. falciparum infections (Winkler et al., 1999; HensmannR and Kwiatkowski, 2001; Torre et al., 2002b; Wroczynska et al., 2005). Cytokines are immuno-modulatory proteins produced by macrophages as well as lymphocytes or mEonocytes in the blood, to influence the function of other cells through specific recepItoVr binding (Plebanski et al., 2002). Although several studies have shown associatiNon between cytokine profile or concentration and disease pathology, data are also emUerging showing that differences in susceptibility to, and severity of malaria might weNll have their roots in genetically-defined differences in the host‟s ability to produce vitalA cytokines (McGuire et al., 1999; Kwiatkowski, 2000; Ubalee et al., 2005; Tchinda et aDl., 2007b; Israelsson et al., 2011). Consequently, many attempts have been made to elucAidate the contribution of polymorphisms in genes encoding proinflammatory mIeBdiators, amongst them the interferon-gamma (IFN-), tumour necrosis factor-alpha (TNF-α) and Interleukin-18 (IL-18) genes (Giedraitis et al., 2001; Claser et al., 2011; Santovito et al., 2012). TNF-α is a proinflammatory cytokine involved in the regulation of a wide spectrum of biological processes including cell proliferation, differentiation, apoptosis, and coagulation (Beutler and Grau, 1993). It is a potent pyrogen, causing fever by direct action 4 or by stimulation of interleukin-1 secretion. TNF-α is secreted mainly by macrophages. Studies have suggested that serum levels of TNF-α may impact on individual susceptibility to disease (Clark and Rockett, 1994; Wilson et al., 1997; Miller et al., 2002). TNF levels have been shown to be elevated in the serum of malaria subjects who have a poor disease outcome (Kwiatkowski et al., 1990). TNF is also raised in placental malaria and is associated with low birth weight (Fried et al., 1998; Moormann et al., 1999). Y Genetic variations in the TNF-α gene have been suggested to influencRe TNF-α production (Abraham and Kroeger, 1999; Knight, 2005; Sohail et al., 2008)A. A particular polymorphic form of the TNF promoter has been shown to be associated Rwith susceptibility to cerebral malaria (McGuire et al., 1994). A single nucleotide polyImBorphism from guanine (G) in the normal TNF 1 allele to adenine (A) in the TNF 2 a lleLlic variant at the position -308 (relative to the transcription start site of the TNF-Yα gene), has been found to be associated with increased TNF-α production (AidooI eTt al., 2001). In addition, the TNF 2 allele was found to be associated with higher parasitaemia, severe anaemia, pre-term birth and early childhood mortality. The presenRce Sof another polymorphism in the TNF-α promoter region (TNF -376A) was foEund to be associated with a four-fold increased susceptibility to cerebral malaria I(KVnight and Kwiatkowski, 1999; Knight et al., 1999). However, the pathophysiology of malaria appears to be more complex than the apparent centrality of TNF-α alone. So,N there are propositions that other cytokines are potentially as important (Clark and Co wUden, 2003). InterleukAin-1N8 (IL-18) is another proinflammatory mediator of innate and acquired immune responses which belongs to the IL-1 superfamily of cytokines (Okamura et al., 1998; GAracDie et al., 2003; Maxwell et al., 2006). IL-18 is an early inducer of the Th1 respBonse, and together with IL-12 or IL-15, it is a potent enhancer of IFN- expression on T ceIlls. In an inflammatory environment, it stimulates the production of TNF-α, granulocyte- macrophage colony stimulating factor and IL-2 (Okamura et al., 1995a; Nakanishi et al., 2001b; Singh et al., 2002). IL-18 is secreted by antigen-presenting cells (APCs) and signals through the IL-18 receptor (IL-18R) complex which is a heterodimer consisting of IL-18Rα subunit, responsible for extracellular IL-18 binding, and IL-18Rβ, responsible for signal transduction. 5 Though IL-18 was described less than two decades ago (Okamura et al., 1995a; Okamura et al., 1998), ample data referring to IL-18 plasma/serum levels in various infectious diseases including malaria, as well as autoimmune disorders, neoplastic and cardiovascular diseases are available (Cebeci et al., 2006; Corvino et al., 2007). In patients with uncomplicated P. falciparum malaria, a significant increase in IL-18 concentrations was noted during the acute and recovery phase of the disease compared to healthy controls, reflecting a proinflammatory role of IL-18 in these patients (Torre et al., 2001). SimilaYrly, a significant increase in serum levels of IL-18 was found in children with uncompRlicated P. falciparum malaria compared to children with severe malaria, iRn BAurkina Faso (Malaguarnera et al., 2002; Musumeci et al., 2003), although this was not confirmed in studies conducted in Bangkok, Thailand where higher levels of LIL-I18B was observed among severe malaria patients (Nagamine et al., 2003; Kojima et aYl., 2 004). Owing to accruing evidence suggesting that seTrum levels of IL-18 may impact on individual susceptibility to disease, and that IL-18 varIiation may influence IL-18 production (Arimitsu et al., 2006; Ueda et al., 2006; FraRylingS et al., 2007; Lotito et al., 2007), a number of investigators have looked for Eassociations between IL-18 single nucleotide polymorphisms (SNPs), or haplotyIpVes and disease (Gracie et al., 2005; Lee et al., 2006; Bossu et al., 2007; Dong et al., 2007; Lin et al., 2007; Thompson and Humphries, 2007). Indeed, there are observationsN that polymorphisms within the IL-18 promoter region may themselves affect the co nfUormation of binding sites for transcription factors, resulting in its differential expressiNon (Tiret et al., 2005). Three single nucleotide polymorphisms in the promoter of IL-1A8 gene at the position -656G/T, -607C/A, and -137G/C have been identified with influenDce on the expression of IL-18 and potentially also of IFN-gamma (Giedraitis et al., 200A1; Tiret et al., 2005). However, there is very little information on the genetic vaIrBiability of IL-18 or IL-18Rα and its association with malaria (Anyona et al., 2011). This study therefore, aimed at determining the role of host cytokine gene polymorphisms of IL-18, IL-18Rα and TNF-α, as well as parasite genetic variability (using the MSP-2 gene as molecular marker) in determining the disease outcome of P. falciparum infections in children in north-central Nigeria. 6 1.2 Justification for the Study The interaction between the malaria parasites and the human host leading to disease and death is not fully understood. Given the role of malaria in morbidity and mortality, an understanding of the molecular mechanisms of malaria pathogenesis is fundamental to developing novel intervention strategies. This study therefore, aimed at determining the contribution of parasite genetic diversity as well as polymorphisms of host cytokine genYes in determining the disease outcome of P. falciparum infection. AR Data generated from this study will help in defining the parasite pRopulation structure in the study area as well as possible genotypes associated with diseasBe outcome. It will also provide information on the association of genetic variants of so mLe hIost cytokine genes with the outcome of P. falciparum infection. Y This study is important because it could proviIdTe novel diagnostic markers of disease susceptibility as well as useful information for maSlaria vaccine development based on natural antigens in the study region. It may also Rhelp to identify potential immuno-genetic risk factors and consequently, facilitate the iEdentification of individuals who are at high risk of developing severe disease or otheIr Vcomplications as well as individuals who might need immuno-modulatory therapy; thus providing novel approach to disease management and prevention. Furthermore, iUt wiNll improve our understanding of the molecular mechanisms of malaria pathogenesis. DA N IB A 7 1.3 Aims and Objectives The aim of this study was to characterize the host cytokine gene polymorphisms of IL-18, IL-18Rα and TNF-α, as well as the parasite genetic diversity using the merozoite surface protein-2 as a molecular marker, and to determine the association between these host-parasite genetic factors and the disease outcome of P. falciparum infection. RY Specific Objectives A 1) To determine the parasite species population predominant in chRildren with severe malaria, uncomplicated malaria and asymptomatic infectioInB using the genus and species-specific PCR. Y L 2) To characterize the P. falciparum parasite populTation in children with severe malaria, uncomplicated malaria and asymptomatic infIection using the polymorphic MSP-2 antigen as gene marker. RS 3) To determine the pattern of sequEence diversity in the P. falciparum MSP-2 gene in the study population. IV N 4) To characterize aUnd compare the host genetic polymorphisms and genotype frequencies oNf the interleukin-18 Receptor alpha (IL-18Rα) gene and of the promoter region oAf the IL-18 gene between groups of children with severe malaria, uncoDmplicated malaria and asymptomatic infection. IB A 5) To characterize and compare the host genetic polymorphisms and genotype frequencies in the promoter region of the tumour necrosis factor-alpha (TNF-α) gene between groups of children with severe malaria, uncomplicated malaria and asymptomatic infection. 8 CHAPTER TWO LITERATURE REVIEW 2.1 Historical Background of Malaria Y Human malaria has been recognized since the earliest period of man‟sR recorded history, and occurrence of mosquitoes trapped in amber suggests its pArevalence in prehistoric times (Garnham, 1952; Manson-Bahr, 1961; Bellomo, 196R5). Recognizable descriptions of the disease were recorded in various Egyptian papIyBri. The Ebers papyrus (1550 BC) mentions fever, splenomegaly and the use of oil Lof the Balamites tree as a mosquito repellent (Griffith, 1893; Hallmann-Mikolajczak, 200 4). Hieroglyphs on the walls of the ancient temple of Denderah in Egypt describIeT anY intermittent fever following the flooding of the Nile (Halawani and Shawarby, 195S7). It was often thought that there was anR aetiological relationship between swamps and fever. Italians referred to the bad air Ein fever-producing areas as mal‟aria and it was commonly concluded that the diseaIseV was contacted by breathing “bad air”, hence the name malaria, meaning bad area (WNahlgren and Bejarano, 1999). In 1717, Giovanni Lancisi (1654-1720), physician to Uthe Pope and a professor at the Sapienzia in Rome, suggested that malaria is transmitted b y the bite of mosquitoes, whilst at the same time accepting the miasmatic theory foNr transmission of disease. In 1716, Lancisi demonstrated „grey-black pigment in malaAria tissue (Gillespie and Pearson, 2001). Progress was made in 1847 about the aetiologDy of malaria when Meckel observed black pigment granules in the blood and spleBen Aof a patient who died of the disease. It was not until 1880, that Alphonse Laveran (1I845-1922), recipient of the Nobel Prize for medicine in 1907 discovered and described the parasite as bodies within the human erythrocyte while working in Algeria (Bruce-Chwatt, 1985; Cook, 1993; Cox, 2010). He witnessed one of the most dramatic events in protozoology: the formation of male gametes by the process of exflagellation (Schmidt and Robert, 1989; Cox, 2010). By 1890, several scientists in different parts of the world had verified his findings. 9 The mode of malaria transmission was however still unknown, until Sir Roland Ross in the late 1890s discovered that the vector of transmission of the disease was the female Anopheles mosquito and demonstrated that the parasites pass through a stage in mosquitoes and are then inoculated into man (Schmidt and Robert, 1989). However, it was Bignami, Bastianelli and Grassi in Italy, who experimentally transmitted the malaria parasite from mosquito to man in 1893 (Cox, 2010). Manson in 1900, by experiments with human volunteers in the Roman Campagna and in London, confirmed the mosquito-mYalaria transmission theory (Manson, 1901a; Manson, 1901b). AR In 1938, James and Tate discovered the exoerythrocytic stagBes oRf P. gallinaceum. After this discovery, large-scale work began in order to find the eIxoerythrocytic stages of human malaria parasites. Finally, in 1948, Shortt and GLarnham demonstrated the exoerythrocytic stages of P. cynomolgi in monkeys and YP. vivax in humans (Shortt and Garnham, 2000). Worthy of mention however, is IthTe continuous in vitro culture of P. falciparum developed by Trager and Jensen in thSe USA in 1976, which opened the gate to diverse fields of malaria studies and has brightened our understanding especially about the parasite (Trager and Jensen, 1976; TragerE andR Jensen, 2005). Meanwhile, the first importIaVnt event in the history of malaria was the discovery of the Peruvian fever tree, from wNhich quinine and cinchonine were isolated. These were used thto treat and cure fevers inU the early 17 century by Jesuit missionaries in South America. Research in the tweNntieth century was devoted largely to malaria control with the discovery of various antiAmalarial agents such as chloroquine, proguanil and primaquine (Bruce-Chwatt, 198D5). Similarly, the discovery of relatively low cost synthetic compounds in the 1940s Asuch as dichloro-diphenyl-trichloroethane (DDT) and dieldrin among others intrBoduced the concept of malaria eradication (Desowitz, 2005). Fifteen years after this peIriod, malaria was eradicated in most parts of Europe, America, Middle East, parts of former Soviet Union and some countries in Asia. However, there are reports that malaria is gradually returning to some of the places where eradication had been successful due to human and environmental factors (Hay et al., 2004). 10 2.2 Global Malaria Situation Malaria is one of the most common and important parasitic diseases worldwide (Trigg and Kondrachine, 1998; WHO, 2003b). Malaria is distributed worldwide throughout the tropics and subtropics. Half of the world‟s population is said to be at risk of the disease (WHO, 2008a) and about 106 countries or territories in the world are considered malarious (Fig. 2.1), almost half of which are in Africa, south of the Sahara (WHO, 2011). AlthYough this number is considerably less than it was in the mid-1950s (140 countries or teRrritories), more than 2.4 billion of the world‟s population are still at risk of malarRia (WAHO, 2000b; Snow et al., 2005). An estimated 3.3 billion people were at risk of malaria in 2010 (WHO, 2011). Of this total, 1.2 billion are at high risk (>1 case per 1000 poIpBulation), living mostly in the WHO African region (49%) and South-East Asia region ( 3L7%). There were an estimated 247 million cases ofT maYlaria as at 2006 (WHO, 2008a) although the figure reduced to 225 million in 2009 (WIHO, 2010), owing to the impact of the global malaria control measures. Eighty-six perceSnt, or 212 million (152-287 million) cases, were in sub-Saharan African and were mainRly due to P. falciparum infections (Fig. 2.2). Eighty percent of the cases in AfricVa weEre reported in 13 countries, and over half of these were in Nigeria, Democratic RepubIlic of the Congo, Ethiopia, United Republic of Tanzania and Kenya (WHO, 2008b). About 1% of clinical cases of P. falciparum infections that occur globally each yea r have N been estimated to be complicated by severe manifestations leading to death. AvailablUe data showed an estimated 881 000 (610,000-1,212,000) malaria deaths as at 200A6, oNf which 91% (801 000, range 520,000-1,126,000) were in Africa (Fig. 2.3) and 85D% were of children under 5 years of age (WHO, 2008b). This figure has reduced to 781,A000 by 2009 due to the concerted effort at malaria control (WHO, 2010). However, thisB figure corresponds to one death in nearly every 30 seconds (Greenwood et al., 1987). CIonversely to the above data generated by the World Health Organisation, a recent study now suggests that the global malaria mortality burden is larger than previously estimated, with about 1.24 million deaths in 2010 (Murray et al., 2012). 11 Y R BR A LI ITY RS VE I U N N DA Figure A2.1: Global distribution of malaria showing risk of malaria transmission IB (WHO/UNICEF, 2005) 12 Y R RA LI B Y IT R SE IV U N AN D FigBureA 2.2: Estimated percentage of malaria cases due to P. falciparum (WHO, 2008b). I 13 RY BR A LI Y IT RS IV E U N AN Figure A2.3:D Global malaria burden showing regional relationship to morbidity and B mortality. (http://www.rollbackmalaria.org/worldmalariaday/ Accessed 15 I February, 2010). 14 Besides children, pregnant women (particularly primigravidae) and non-immune individuals such as travellers and foreign workers are at highest risk of severe disease. In addition to the overwhelming death toll, over 213 million malarial “attacks” lead to more than 800 million days of illness in Africa annually (Breman et al., 2004). In malarious areas, malaria transmission may be endemic, occurring predictably every year, or it may be epidemic, occurring sporadically when conditions are faRvouYrable. Endemic transmission of malaria may be year round or seasonal. However, aAll age groups may be at risk of severe disease during malaria epidemics, which occur either when changes in the physical environment (caused by climatic variation, agricultural pRrojects or mining) increase the capacity of mosquitoes to transmit the diseaseI Bor when population displacements through natural disasters or war expose non-imm uLne populations to infection (Suh et al., 2004). In some areas of Africa, 90 to 100 per Ycent of children less than 5 years old have malaria parasites circulating in their bloIodT at most times. Because naturally acquired immunity develops with increasing exposure, in endemic areas, malaria disease is primarily found in children. In epidemic RareaSs, on the other hand, naturally acquired immunity falls off between epidemics, aEnd malaria therefore affects all age groups during epidemics (Gilles, 1993). LikewiseI, Vthe epidemiological pattern of P. falciparum infection varies in different geographical locations. In regions of high malaria transmission, adults develop potent but non-sterile Nimmunity against malaria (Giha et al., 2000). In areas of low transmission, malaria in feUctions are infrequent and no age group has significant acquired immunity to malariaN. MalDaria Ais transmitted primarily by the bite of infected female Anopheles mosquito but conAgenital malaria and acquisition through infected blood transfusion have also been desBcribed in the literature (Zheng and Kafatos, 2005; Falade et al., 2007; Lesi et al., 2010; PIoespoprodjo et al., 2010). Anophelines feed at night and their breeding sites are primarily in rural areas. The greatest risk of malaria is therefore from dusk to dawn in rural areas. However, urban transmission is common in some parts of the world especially in Africa where the sanitary condition of the environment is generally poor. Temperature and humidity are the most important environmental factors favouring transmission of the 15 disease. The optimal conditions for the parasite and vector are a mean temperature of 20- o 30 C and a relative humidity of 60% (Schmidt and Robert, 1989; Gilles, 1993). In most parts of sub-Saharan Africa, there is a high endemicity of malaria in areas where transmission is stable; 80% of clinical malaria cases worldwide and 90% of mortality occur in these areas (Gilles, 1993; Snow et al., 2005). In Nigeria, malaria is endemic and stable with minimal seasonal fluctuations, but peak transmissions occur during the Yrainy season (Ekanem et al., 1990). Nigeria accounts for a quarter of all malaria cases in Rthe WHO African Region (WHO, 2008b). Transmission especially in southern Nigeria oAccurs all-year round. There is no evidence of a systematic decline in malaria burden; Restimated malaria cases in 2007 was in the range of 2.97-3.98 million (WHO, 20I0B8b). The predominant species of the parasite in this region is P. falciparum and almostL all cases are caused by this species of human parasite but most are unconfirmed (WHYO, 2 008). However, P. malariae accounts for about 5% of total infection (Salako et al.,T 1990). Two main species of vectors that are predominant in Nigeria are Anopheles SgamIbiae and A. funestus (Molineaux and Gramiccia, 1980; Awolola et al., 2005) althRough A. arabiensis and A. moucheti are also found (Awolola et al., 2002; Okwa et al.,E 2009). IV 2.2.1 Socio-economic imUpacNt of malaria Malaria is anN exc eptionally complex disease (WHO, 2003b). It is most serious in the poorest countrieAs, among underprivileged populations living under the most difficult and impecuniouDs conditions. The causes of malaria and the impediments to its control are rooted in the social, cultural, political, economic, and ecological conditions of endemic countries. TheB sitAuation is so dire that malaria is now recognized as both a disease of poverty and a caIuse of poverty (Gallup and Sachs, 2001). Malaria strikes the most vulnerable and impoverished communities, ensuring that those most in need of treatment are those least able to afford it. The disease disproportionately affects the poor, in whom higher morbidity and mortality can be attributed to lack of access to effective treatment; 60% of malaria deaths worldwide occur in the poorest 20% of the population (Suh et al., 2004). Malaria undermines the health and welfare of families, endangers the survival and education of 16 children, debilitates the active population, and strains the resources of countries and their inhabitants, thus limiting their ability to contribute to economic and social growth (Trigg and Kondrachine, 1998). Malaria is estimated to be responsible for an annual loss of 35.4 million Disability Adjusted Life Years (Meyrowitsch et al., 2011). In some rural villages, a family may spend up to 25% or more of its annual income on malaria prevention and treatment (WHO, 2003b). Malaria thus anchors people in perpetual poverty. Y Malaria causes substantial losses to households in the form of foregone inRcome and decreased agricultural production (Kiszewski and Teklehaimanot, 2004). AbleA-bodied men, who are the economically more productive family members, are attacked Rby malaria during planting and harvesting seasons, thereby shrinking productive capIaBcity when agricultural workers are in highest demand (Attanayake et al., 2000). T hLe concurrent infections of massive number of people usually overload health faYcilities; thereby degrading the effectiveness of health care. In addition to the immeInsTe human suffering it causes, malaria costs Africa more than US$ 12 billion annually. Malaria has slowed economic growth in African countries by 1.3% per year (WHO, 200S3b). In Nigeria, the financial loss due to malaria annually is estimated to be about RN132 billion in the form of treatment cost, prevention and loss of man-hours (IFMVOH E, 2009). Consequently, funding for malaria control have been increased from US$ 17 million in 2005 to US$ 60 million in 2007, provided by the government, the Global NFund and the World Bank (WHO, 2008b). Recent report suggests that commitmen tU towards malaria control from International sources has risen from US$200 million in 2N004 to US$2 billion in 2011 (WHO, 2011). A 2.3 The MDalaria Parasite 2.3B.1 A Classification I Malaria parasites belong to the Genus Plasmodium which includes over 125 species infecting reptiles, birds and mammals (Bruce-Chwatt, 1985). Plasmodium spp are intracellular, blood-dwelling parasitic protozoa that cause the disease malaria. These species are restricted to the Family Plasmodiidae which includes parasites which undergo asexual division (schizogony) and a single sexual multiplication (sporogony) in an invertebrate host. 17 They belong to the Order Haemosporidia and to the Class Sporozoea (Table 2.1). Many members of Haemosporidia live in the red blood cells of vertebrates. These groups of parasites belong to the Phylum Apicomplexa which are spore-forming unicellular organisms and belong to the Sub-Kingdom Protozoa in the Kingdom Protista (Levine et al., 1980). Important characteristic features of the Apicomplexans include the presence, at specific stages of the life-cycle of an apical complex consisting of a number of specialized organelles (Fig. 2.4), which may include a conoid, polar rings, rhoptries and micronemes (Gilles, Y1993; Cowman and Crabb, 2006). AR Of the four species of malaria parasites traditionally known tBo inRfect humans (Fig. 2.5), three (Plasmodium vivax, P. malariae and P. ovale) beIlong to the sub-genus Plasmodium , while the remaining one (P. falciparum ) belong s Lto the sub-genus Laverania (Garnham, 1988). ITY 2.3.2 Life cycle of human malaria parasites S Human malaria parasites underEgo aR complex cycle of development, alternating between two hosts: the mosquito vIeVctor (invertebrate host) and man (vertebrate host). The life cycle occurs in a sequencNe of four phases, which includes one sexual phase and three asexual phases. U Stages in vertebArateN host ExoeryAthrocDytic cycle IB Infection of the human host occurs when an infective female Anopheles mosquito injects saliva containing tiny elongate sporozoites into the bloodstream during blood meal 18 Table 2.1: Hierarchical Taxonomy of Human Malaria Parasites (Levine et al., 1980; Gilles, 1993). Taxonomic Group Name Domain Eukaryota (Eukarya) Y Kingdom Protista AR Sub-Kingdom Protozoa R Phylum Apicomplexa IB Class Sporozoae L Subclass Eucoccidia Y Order Haemosporidia IT Family PlasmodiidaeS Genus PlasmoRdium Species V P. fEalciparum N I P. vivax U P. malariae N P. ovale A BA D I 19 RY A R LIB TY SI VE R I N Figure 2.4: Diagram ofU a merozoite, highlighting major organelles and cellular structures (CowNman and Crabb, 2006). AD A IB 20 Y AR LIB R TY SI R E NI V U DA N FigBure A2.5: Four major species of the human malaria parasites. I (http://www.google.com/imgres?imgurl=http://www.bioon.com/Article/UploadFiles/200406/20040 603215831151.gif&imgrefurl=http://www.bioon.com/Article/Class741/40125.shtml&usg=__on8o e6ywiW4PSCOVUnPH9g1Seoc=&h=334&w=488&sz=47&hl=en&start=6&zoom=1&tbnid=DHJ JcHu_aKRXGM:&tbnh=89&tbnw=130&ei=Zx6sTuupM4mZOrWpvN8P&prev=/images%3Fq%3 DPlasmodium %2Bmalariae%26hl%3Den%26sa%3DX%26rls%3Dcom.microsoft:*:IE- SearchBox%26rlz%3D1I7ACAW_en%26tbm%3Disch&itbs=1. Accessed 15 February, 2010). 21 (Figure 2.6). Sporozoites are deposited through the skin, an organ comprising three characteristic layers. The epidermis provides a physical barrier, the underlying highly vascularized dermis harbours immune cells, such as macrophages and dendritic cells, and the subcutis contains larger blood vessels and lymphatics. While acquired immunity could interfere with crossing this natural barrier, sporozoites migrate extensively in the skin of naive individuals and eventually leave the site of the mosquito bite (Frevert, 2004). The sporozoites circulate round the body via the blood and within 1-30 min penetrate theY liver and then into the hepatocytes, initiating the pre-erythrocytic or exoerythrocyticA cycRle. In the hepatocyte the sporozoite undergoes drastic changes in morpRhology, losing its apical complex and surface coat and transforming into a round or ovIalB trophozoite (Shortt et al., 1951). Once established within a hepatocyte, the sporozoi teL undergoes a multiplicative process known as exoerythrocytic schizogony. DevelYopment takes place within a parasitophorous vacuole in the hepatocyte. The troIphTozoite increases in size and finally develops into a tissue schizont (meront) containing several thousand merozoites. P. vivax sporozoites take 6-8 days to mature and prodRuceS about 10,000 merozoites; P. ovale takes 9 days to produce about 15,000 merozoiteEs; P. malariae takes 12-16 days to produce 2,000 merozoites and P. falciparum 5I-7V days to produce 40,000 merozoites, from a single sporozoite. In 2006, it was shown that the parasite buds off the hepatocytes in merosomes containing hundreds or thousaNnds of merozoites (Sturm et al., 2006). These merosomes lodge in the pulmonary caUpillaries and slowly disintegrate there over 48-72 hours releasing merozoites (Baer etN al., 2007). Similarly, when distended by the parasite meront, the cell ruptures, releasing the merozoites into the bloodstream (Murphy et al., 1989). Erythrocyte invasion is DenhaAnced when blood flow is slow and the cells are tightly packed: both of these conditioAns are found in the alveolar capillaries. IB 22 RY BR A LI Y IT ER S V UN I AN D A FIigBure 2.6: Life Cycle of the Human Malaria Parasite 23 Erythrocytic cycle Merozoites rapidly attach to and invade erythrocytes to initiate the erythrocytic cycle. They attach to receptor sites located on red blood cells before invasion. They have distinctive features and are specialized to recognize and attach to specific molecules of the membrane of the erythrocyte for invasion (Fig. 2.4). The merozoite enters the cell by five stages: initial recognition and attachment, formation of a junction, creation of a vaYcuole membrane continuous with the red cell membrane, entry into the vacuole thrRough the moving junction (Fig. 2.7), and sealing of the erythrocyte after entry (AikawAa et al., 1978; Gilles, 1993; Gaur and Chitnis, 2011). After invading the erythrocyte, thRe parasite loses its specific invasion organelles and differentiates into a round trophIozBoite located within a parasitophorous vacuole in the red cell cytoplasm. Once inside anL erythrocyte, the merozoite develops into a feeding trophozoite. A parasitophorous vacYuole forms round the trophozoite and the trophozoite takes on a „signet-ring‟ shape, moIreT or less amoeboid and uninucleate. The young trophozoite grows substantSially before undergoing several nuclear divisions. This is soon followed by the divRision of cytoplasm forming a schizont, each containing merozoites in numbers chVaracEteristic of the parasite species (Bruce et al., 1990). The merozoites then invade freshI erythrocytes and the cycle continues (Fig. 2.6). The erythrocyte eventually bursts Nreleasing the merozoites into the circulation and these then invade non-infected red blood cells. The result is a dramatic increase in parasitaemia and, when the number of pa raUsites reaches a certain level, the process of schizogony and the subsequent liberatioNn of merozoites become synchronized and periodic. The length of the intraerythroDcyticA development is variable, being 48hr for P. falciparum , P. vivax and P. ovale, aAnd 72hr for P. malariae (Eichner et al., 2001). At the end of each cycle when the eryBthrocytes burst and release the merozoites into the bloodstream, „toxins‟ are released into thIe host. Each time there is the liberation of parasites into the bloodstream it has a pyrogenic effect upon the host, making the host to feel feverish. After a few erythrocytic cycles, some merozoites develop into a male or a female gametocyte. Whether this development is pre- determined genetically or as a response to some specific stimulus is unknown. 24 (a) (b) RY A (c) (d) R LI B SI TY ER NI V Figure 2.7: Invasion o fU Red Blood Cell by Merozoite. (a) ApNical attachment and junction formation. A merozoite has begun to invade a red bAlood cell. The apical complex is attached to the RBC. One of the rhoptries is visible Dclose to the apical complex. (b) The junctional complex is forming around the point where the erythrocyte membrane is invaginating. The junction is represented by the A dense area beneath the erythrocyte membrane. (c) The junctional complex area has now moved to the rear of the merozoite and further invagination has taken place, so that the B merozoite is now effectively inside the erythrocyte. (d) The red cell membrane I surrounding the merozoite is now complete, forming the parasitophorous vacuole (Aikawa et al., 1978). 25 Stages in invertebrate host During a blood meal from an infected human, the female Anopheles mosquito takes up gametocytes, which transform into gametes (Fig. 2.6). The maturation of the female gametocyte into a macrogamete takes place without major morphological changes. In the extracellular male gamete, the nucleus divides three times and each of the eight nuclei formed combines with cytoplasm to form 6-8 thread-like microgametes in exflRagellYation (Day et al., 1998). A Sporogony R Fertilization occurs in the stomach wall of the mosquiItoB by the fusion of a microgamete with a macrogamete, resulting in the formation o f La diploid zygote. This soon elongates to become a mobile ookinete. The slow motileY ookinete crosses the peritrophic membrane of the midgut (probably by means of a chIitiTnase), then passes through the single cell layer of the midgut epithelium and establishSes itself beneath the basal lamina, forming an oocyst (Gilles, 1993). The oocyst graduRally increases in size, enlarges and undergoes nuclear division forming sporoblasts. The sporoblasts in turn divide repeatedly to form thousands of sporozoites. Being motileE, the sporozoites burst through the weakened or ruptured wall of the oocyst and invIaVde the body cavity of the mosquito (Fig. 2.6). From the haemolymph, sporozoites UmigrNate to the salivary glands of the female Anopheles mosquito, which becomes infecti ve. When the mosquito feeds on blood meal, it then injects sporozoites into the Nbloodstream of the vertebrate host. DA A IB 26 2.4 Genetic Diversity of the Malaria Parasite Plasmodium falciparum exhibits great genetic variability which gives rise to a number of antigenically different parasite populations (Fenton et al., 1991). The inherent variability of P. falciparum provides multiple effective immune evasion and drug resistance mechanisms for the parasite. Particularly, the extensive diversity of malaria surface antigens has been suggested as one of the main reasons why clinical immunity develops onlyY after repeated infections with the same species over time (Day and Marsh, 1991)R. Genetic diversity is manifested in extensive allelic polymorphisms of many paArasite genes, especially those encoding antigens, and in the occurrence of mixtures of gRenetically distinct parasite clones in individual patients. Antigenic diversity has a duBal origin. One is the classical genetic mechanism of nucleotide replacement and recomLbinIation that creates allelic polymorphism or stable alternative forms of antigen-codiYng g enes (Ferreira et al., 2004). The second mechanism is antigenic variation, wherebIy Ta clonal lineage of parasite expresses successively alternative forms of an antigen without changes in genotype (Chen et al., 2000; Hoffmann et al., 2006). S Malaria endemic areas are generEallyR characterized by extensive parasite diversity. Genetic diversity of P. falciparumI V parasites usually leads to complex infections where infected individuals often carry multiple parasite genotypes (Paul et al., 1998; Arnot, 2002), and is an indicator of malaria Ntransmission intensity. Knowledge of the genetic structure of the parasites in natural pUopulations is critical to any intervention strategy in a particular region. Antigenic dNiversity of MSP-2 genotypes in clinical malaria have been reported in south-west NigeAria (Happi et al., 2004; Amodu et al., 2008; Ojurongbe et al., 2011), and some parts Dof northern Nigeria (Engelbrecht et al., 2000). However, little information is currentlAy available on the relationship between parasite genetic diversity and disease ouItBcome of P. falciparum infection as well as sequence variations in naturally circulating strains of P. falciparum parasites in Nigeria. These gaps in information are part of what this study was designed to bridge. 27 2.4.1 Merozoite surface protein-1 Merozoite surface protein-1 (MSP-1) is the most abundant protein on the surface of the blood stage of the parasite and it is thought to play a role in erythrocyte invasion (Holder et al., 1992). It is synthesized as a 190 kDa precursor, which undergoes proteolytic cleavage into four fragments that remain on the merozoite surface as a glycosylphosphatidylinositol (GPI)-anchored complex. Before erythrocyte invasion, the entire MSP-1 complex is Yshed, except for the C-terminal 19 kDa (MSP-119), which remains on the surface as the Rmerozoite enters the erythrocyte (Blackman et al., 1990). MSP-119 contains two epidAermal growth factor (EGF)-like domains, which are thought to have an important functRion in erythrocyte invasion (Holder et al., 1992). Naturally acquired antibodies to BMSP-119 can inhibit erythrocyte invasion by preventing the secondary processing thatL releIases this fragment from the rest of the MSP-1 complex (Blackman et al., 1990; Guevar a Patino et al., 1997; Nwuba et al., 2002), and are associated with protection fromI cTlinicYal malaria in field studies (Riley et al., 1992; Egan et al., 1996; Branch et al., 2000; John et al., 2004; Okech et al., 2004; Bisseye et al., 2011). RS The sequence of the MSP-1 gene Ecan be organized into 17 blocks based on sequence variability (Tanabe et al., 1987; MIillVer et al., 1993). The Block 2 region includes repetitive motifs of three amino acids, grouped into three allele-families: K1, MAD-20, and RO33 with high variability whenU comNparing the groups, but less variability within them. Alleles in K1 and MAD-20 contain antigenically unique, tripeptide repeats, with extensive diversity in the number of repeaNts (Miller et al., 1993). RO33 lacks the tripeptide repeats observed in the other two familAies; however, outside Block 2, this allele is similar to the MAD-20 type (Hughes, 19D92). Fragment size in the three Block 2 allele families has commonly been used as a moAlecular marker in studies of malaria transmission dynamics and host immunity in P. faIlcBiparum malaria (Konate et al., 1999; Branch et al., 2001; Ghanchi et al., 2010; Atroosh et al., 2011). Block 17 contains MSP-119, which has been the focus of malaria vaccine development because of its highly conserved sequence and hypothesized critical function. However, even this region contains at least six nonsynonymous single nucleotide polymorphisms (SNPs). Studies of populations naturally exposed to P. falciparum have 28 shown various degrees of association between anti-MSP-119 antibodies and protection from clinical malaria (Egan et al., 1996; Kitua et al., 1999). 2.4.2 Merozoite surface protein-2 The merozoite surface protein-2 (MSP-2) is a 45- to 50-kDa glycoprotein anchYored in the merozoite surface by a glycosylphosphatidylinositol anchor. MSP-2 iRs a very immunogenic antigen malaria antigen, and is a promising candidate for iAnclusion in a malaria subunit vaccine (Hill, 2011; McCarthy et al., 2011), as both inR vitro and in vivo studies have demonstrated the ability of immune responses to MSPB-2 to inhibit parasite multiplication (Saul et al., 1992; Saul et al., 1999; Genton et al.L, 20I02). The corresponding MSP-2 gene is characterized by highly conserved amino and carboxyl-termini flanking a variable central region (Figure 2.8). The central polymoYrphic region contains a central repetitive sequence flanked by non-repetitive regionIsT that have been used to define two major allelic families: the FC27 family andR the S3D7 family after the names of the strains from which they were first described (Smythe et al., 1991; Snewin et al., 1991). Two features make MSP-2V of Eimportance in the molecular genotyping of P. falciparum. First, it is a promisingI candidate for inclusion in a subunit vaccine against the asexual intraerythrocytic stageNs of P. falciparum (Saul et al., 1992; Genton et al., 2003), and second, MSP-2 has bUeen shown to be a good discriminatory marker for assessing the genetic profile of P. falciparum isolates (Prescott et al., 1994; Snounou et al., 1999; Basco and Ringwald, 2A001N). Due to its polymorphism, the MSP-2 gene has been extensively used to type natuDral isolates of P. falciparum (Prescott et al., 1994; Felger et al., 1999; Franks et al., 200A1; Ojurongbe et al., 2011; Koukouikila-Koussounda et al., 2012). Most studies exIaBmining the distribution and frequency of different allelic forms of MSP-2 have enumerated the presence of the allelic families (Felger et al., 1994; Engelbrecht et al., 1995; Kang et al., 2010; Atroosh et al., 2011). By typing the gene for this protein, some symptom-specific molecular characteristics have been delineated for P. falciparum isolates collected from asymptomatic, uncomplicated and severe malaria cases in Senegal (Robert et al., 1996), in Tanzania (Smith et al., 1999a; 29 Bendixen et al., 2001) and in Nigeria (Happi et al., 2004; Amodu et al., 2008) amongst other countries. This information has been useful in understanding the dynamics of transmission as well as in evaluating the impact of malaria-control interventions, such as the use of antimalarial drugs and prototype malaria vaccines, on parasite populations (Beck et al., 1997; Beck et al., 1999; Haywood et al., 1999; McCarthy et al., 2011). AR Y BR Y LI T SI VE R NIU N AD A IB 30 1 2 3 4 5 Y R RA Keys IB Conserve d Lregions Dimorphic InoTn-rYepeat regions PolySmorphic repeat regions VE R I N Figure 2.8: Schematic d iaUgram of MSP-2 gene AN D IB A 31 2.5 Pathogenesis of Malaria Of all the Plasmodium species that cause malaria in humans, P. falciparum is the most deadly and the major cause of severe disease and death. Infection with P. falciparum produces a clinical outcome that depends on a combination of parasite, host and environmental factors, including the age of the patient and the pattern of prior exposure of that individual to malaria (Miller et al., 2002). Infections range from being asymptomYatic, through mild or uncomplicated malaria, to life-threatening severe forms of thRe disease involving multiple organ systems and varied pathological processes, often withA case fatality. However, the most common clinical manifestation of malarial infecBtionR is a non-specific febrile illness with mild clinical symptoms such as fever, malaise, Iheadache, and lethargy. Only a small proportion of cases often result in severe dis eLase and in the worst case scenario, death. Y Severe malaria is frequently described aIs Tcomplicated malaria. Severe and complicated malaria includes clinical features abSove and beyond fever and malaise. These include prostration, impaired consciousnessR (coma), hypoglycaemia, respiratory distress, acidosis, severe anaemia, hyperparasVitaemEia, hyperlactataemia (WHO, 2000a; Weatherall et al., 2002; Perkins et al., 2011). SIevere malaria is a complex multi-system disorder that affects several tissues and orgaNns (Gay et al., 2012a; Renia et al., 2012). There are important differences in the clinic aUl spectrum of severe malaria with age. Inhabitants of malaria-endemic areas gradNually acquire immunity to these signs of severe malaria illness, while remaining susceAptible to malaria infection. For this reason, African children between the ages of sixD months and five years are the group at highest risk of developing severe and complicAated malaria. IBEfforts by the scientific community at understanding the pathogenesis of severe malaria have shown that development of severe malaria probably results from a combination of parasite-specific factors such as adhesion and sequestration to the vascular endothelium, the release of bioactive molecules, together with host inflammatory responses and metabolic acidosis (Manning et al., 2012). Indeed, adhesion of parasitized erythrocytes to these cells 32 could drive their activation, which could participate in the trigger of an immune response and haemostatic derangements (Gay et al., 2012a). The most common presentations of severe malaria in African children include cerebral malaria, severe anaemia and respiratory distress (Fig. 2.9), but combinations of these, especially with other syndromes result in high mortality rates (Schellenberg eYt al., 1999; Haldar et al., 2007; Santos et al., 2012; von Seidlein et al., 2012). However, metabolic acidosis is now being widely recognised as a principal pathophysiological feaAtureR that cuts across the classical syndromes of cerebral malaria and severe malaria anaemia (Krishna et al., 1994; Marsh et al., 1995). Although the underlying pathophysiolRogy of metabolic acidosis is likely to be complex, two factors seem to be of major imIpoBrtance: reduced blood circulating volume and reduced oxygen carrying capacity ( MLarsh, 2005). Undoubtedly, much remains to be found out about the pathogenesis of meYtabolic acidosis in severe malaria but the clinical implications of what is known are siImTple and important: acidotic children require immediate and rapid attention to circulatinSg volume and oxygen delivery. Anaemia is an inevitable consequeRnce of Plasmodium infection, particularly in children. Anaemia develops rapidly Vin thEe course of severe malaria and blood haematocrit drops greatly especially when the pIarasite load is high (>100,000/µl). A haematocrit <13% (Hb <4g/dl) has been shown Nto be associated with a significant increase in mortality in children presenting with malaria (WHO, 2000a). In areas of high and stable transmission, the presentation of sNever e Uanaemia is the most important manifestation of severe malaria and occurs predominantly in children less than 3 years of age (WHO, 2000a). Severe malarial anaemia caDusesA over half of all malaria-related morbidity and mortality in children under five yeAars of age in Africa and carries a case fatality rate of ~10% in endemic regions (MBurphy and Breman, 2001). There is increasing data showing that deaths associated with seIvere malarial anaemia can occur within the first 12hr of admission (Marsh et al., 1995; English, 2000). Severe malarial anaemia consists of a group of conditions with different causes, including direct destruction of parasitized red blood cells, indirect destruction of non- parasitized red blood cells by immune mechanisms, and bone-marrow suppression which is 33 associated with imbalances in cytokine concentrations (Weatherall and Abdalla, 1982; Ekvall, 2003). Clearance of uninfected erythrocytes from the periphery may be due to multiple factors, including deposition of parasite ligands on erythrocytes. Parasite antigens shed during invasion or released upon lyses of infected schizonts, may be present at high concentrations in plasma and may adhere to uninfected erythrocytes, possibly resulting in immunoglobulin G or complement binding and eventual clearance from the circulation (Waitumbi et al., 2000; Goka et al., 2001; Stoute et al., 2003). In addition to adhYesive parasite ligands, erythrocyte clearance may be linked to oxidative damage (GriffiRths et al., 2001), reduced deformability (Dondorp et al., 2002), and/or phosAphatidylserine externalization (Kiefer and Snyder, 2000). RIB In severe malarial anaemia, a major fall in haemoglobin cLorrespondingly represents a radical fall in oxygen carrying capacity. One consequence oYf a net failure in oxygen delivery to areas of greatest need is a shift from aerobic to anIaeTrobic metabolism in tissues with the production of lactate and associated acidosis (SEnglish, 2000). This invariably leads to respiratory distress characterised by sustained nasal flaring, indrawing of the bony structure of the lower chest wall on inspiration, aEnd dReep breathing (WHO, 2000a). The idea that a tissue oxygen debt plays an impIorVtant role in the generation of metabolic acidosis is supported by the demonstration that total oxygen consumption of children with severe malarial anaemia rises markedNly during the course of blood transfusion and in proportion to the lactate level on admi ssUion (English et al., 1997; Narsaria et al., 2012). CerebralA maNlaria (CM) is the best-known presentation of severe malaria (Grau and Craig, 2012D). The defining feature of the clinical syndrome of cerebral malaria is deep coma. This is Adefined by the inability to localise a painful stimulus or with a Blantyre Coma Score <2 Bin a patient with a P. falciparum parasitaemia in whom other causes of encephalopathy suIch as meningitis have been excluded (Molyneux et al., 1989; Warrell, 1992; WHO, 2000a). In most research settings, the case fatality rate for children meeting this standard clinical case definition of CM ranges between 15% and 30% (Snow et al., 1999; Murphy and Breman, 2001). Carefully undertaken post-mortem studies in children have shown that this disease is a heterogeneous syndrome in which sequestration probably has a major role in some cases but little in others (Crawley et al., 2001; Taylor et al., 2004; Gay et al., 2012b; 34 Ponsford et al., 2012). Metabolic derangement including hypoglycaemia and subclinical convulsions are important in many cases. Sequestration is probably more consistently the cause in adults than in children (Silamut and White, 1993). In around 70% of cases, the onset of coma is with a seizure (Marsh, 2005). Convulsions occur in around 80% of cases of cerebral malaria. Multiple or prolonged convulsions are associated with a worse outcome, particularly with neurological (Molyneux et al., 1989; Steele and Baffoe-Bonnie, 1995; van Hensbroek et al., 1997) and cognitive impairment. Around 40% of children with cerYebral malaria have one or more of four distinct abnormalities of respiratory pattern AwhicRh may be of prognostic significance (Crawley et al., 1998). Deep breathing is a sign of metabolic acidosis and is an indication of the need for urgent fluid resuscitationR. Some surviving patients have an increased risk of neurological and cognLitivIe Bdeficits, behavioural difficulties and epilepsy, making cerebral malaria a leaYding cause of childhood neuro-disability in malaria transmission areas (Gay et al., 2012Ta). Among malaria-exposed adults, pregnant wIomen are particularly susceptible to malaria, despite substantial immunity prior Rto pSregnancy, and the risk is highest in first pregnancies (Brabin, 1983; McGregor, 1984). The major complications of infection are maternal anaemia, which in turn inIcVrease Es maternal deaths, and reduced infant birth weight from a combination of intrauterine growth retardation and premature delivery leading to excess infant mortality (BrabNin, 1983; Granja et al., 1998; Desai et al., 2007). In some settings, maternal malar iaU may also cause spontaneous abortion or stillbirth (McGregor, 1984). AN AD IB 35 Impaired Severe consciousness: respiratory 7.3% 27.8% distress: 23.8% 34.7% Y 5.9% 16.3% R A Severe anaemia R 1.3% IB L ITY ER S V NI U N Figure 2.9: CAase fatality of major clinical syndromes of severe malaria among African Dchildren (Marsh et al., 1995) A IB 36 2.6 Host Immune Response to Malaria Malaria infection gives rise to a series of host immune responses which can be divided into two general categories: innate immune responses and adaptive immune responses, that are regulated by the innate and the adaptive immune system respectively (Perlmann and Troye-Blomberg, 2002; Good et al., 2004; Van Den Steen et al., 2011). Innate immune responses are those the body mounts immediately, without requYiring previous contact with the parasite and thus provides the body with a first linAe ofR defence. Effector agents of this response include: cells that kill or ingest infected or altered cells such as macrophages, dendritic cells, natural killer (NK) cells; and solubleB proRteins (complement and cytokines) that can neutralize, immobilize, agglutinate, kill orI activate other effector cells (Karp, 2010; Teirlinck et al., 2011). The adaptive immune rLesponses on the other hand, require a lag period of several days and are highly specifYic. T hey are broadly categorized into two: humoral responses which involve the produTction of antibodies (proteins called immunoglobulins); and cell-mediated responses wShicIh involve the production of specialized cells (Stevenson et al., 2011). However, boRth the innate and the adaptive immune system work closely together in order to destroy the parasite, since the same phagocytic cells and NK cells that carry out an immediaIteV inna Ete response are also involved in initiating the much slower, more specific adaptive immune response. Immunity to various stages of P. falciparum infection is thoughNt to contribute to host protection (Plebanski and Hill, 2000). U 2.6.1 Innate (non-Nspec ific) immunity to malaria InnaDte mAechanisms of parasite growth inhibition by the human host are probably the reason Afor the low parasitaemia seen in acute P. falciparum infection. Accumulating eviBdence support the concept that macrophages, dendritic cells, NK cells, γδ and NKT cells arIe important effectors of the innate immunity against malaria (Perlmann and Troye- Blomberg, 2002; Mauduit et al., 2012). In addition, there are indications that dendritic cells (DCs) may play a critical role in amplifying the innate immune response, in particular, by stimulating the activation of NK cells (Ferlazzo et al., 2002). 37 NK cells have been shown to be the first group of cells to respond to P. falciparum infection by increasing in number, and with the ability to lyse infected RBC in vitro (Orago and Facer, 1991). NK cells are lymphocytes of the innate immune system that are involved in the early defense against foreign cells and autologous cells infected with parasites. They are widespread throughout the body (Lanier et al., 1986; Stevenson and Riley, 2004), being present in both lymphoid organs and non-lymphoid peripheral tissues (Cooper and Caligiuri, 2004; Cooper et al., 2004; Ferlazzo et al., 2004). NK cells are cytotoxic, inducing RapopYtosis of cells recognized as targets. Observations of rapid and marked increases in NK cell cytotoxicity levels during infection with a variety of protozoan parasites andA Plasmodium suggest a role for NK cells in innate immunity against these pathogeInsB (Ko Rrbel et al., 2004). NK cells are also able to modulate the immune responLse through the secretion of cytokines, including interferon-γ (IFN-γ), tumor necroYsis factor, interleukin (IL)-13, granulocyte-macrophage colony-stimulating factor, Tand chemokines such as CCL3 (macrophage inflammatory protein 1α), CCL4 (mSacrIophage inflammatory protein 1β), and RANTES (Roetynck et al., 2006; McCall etR al., 2010; McCall and Sauerwein, 2010). NK cells identify their targets through a set oEf activating or inhibitory receptors that allow them to recognize pathogen-encoded moIleVcules, self-proteins whose expression is up-regulated in transformed or infected cells, or self proteins that are expressed by normal cells but down- regulated by infected or transNformed cells (Vivier and Biron, 2002; Moretta et al., 2004; Moretta and Moretta, 200U4; Raulet, 2004). NK cell activation is controlled by the dynamic balance between thNese activating and inhibitory signals (Vivier et al., 2004). NK cells represent an imAportant early source of IFN-γ during primary murine malaria infections and NK depletioDn leads to a more rapid increase in parasitemia and higher mortality (Roetynck et al., 2006). Studies in mice have earlier indicated that during infection with P. chabaudi, inInBate r Aesponses, involving IFN-γ production by NK cells, and IFN-γ-producing Th1 cells predominate, whereas induction of Th2 responses with IL-4-secreting Th cells predominate after the peak of parasitaemia (Langhorne et al., 1998; Stevenson and Riley, 2004). Another group of lymphocytes, the Natural killer T (NKT) cells have also been suggested to exhibit capacity to inhibit the liver-stage parasite replication in a murine model in vitro (Pied et al., 2000). NKT cells have been shown to determine the outcome of 38 experimental cerebral malaria caused by P. berghei ANKA (Engwerda and Good, 2005). These cells express NK and T cell receptors and recognize antigen presented by CD1 molecules on antigen-presenting cells. CD1-restricted NKT cells are known to recognize the glycosylphosphatidylinositol-anchor molecule of P. falciparum. NKT cells from susceptible C57BL/6 mice produce IFN-γ and promote pathology following P. berghei ANKA infection, whereas in BALB/c mice they promote Th2 polarization and resistance to experimental cerebral malaria (Hansen et al., 2003). A possible role of the NKT cells iYn the human malaria could be speculated from their simultaneous production of highR levels of both IFN-γ and IL-4 upon primary TCR stimulation (Harris et al., 2005). RA Besides, dendritic cells and macrophages have been suggesteIdB to be activated as one of the earliest events in the innate response to malaria (Engwer daL and Good, 2005). DCs are a heterogeneous antigen-presenting cell population with a Ycrucial role in both the initiation and regulation of cell-mediated immune responses IasT well as adaptive immune response (Mauduit et al., 2012). DCs drive the differentiaStion of naïve T cells into IFN-γ-secreting Th1 cells, IL-4- secreting Th2 cells, or other subsets, such as IL-10-secreting regulatory T cells. Plasmacytoid dendritic cells (PDC), a Runique subset of DC, have also been shown to have a key role in the innate immunity beEcause of their ability to produce high levels of IFN- α in response to viral (Cella Net aIl. V, 1999) or microbial DNA or CpG DNA stimulation (Kadowaki et al., 2001). MUacrophages on the other hand, have been shown to have a role in innate immunity as evide nt in their ability to phagocytose infected erythrocytes (Gyan et al., 1994; Serghides et aNl., 2003), and thus contributing to the reduction of initial parasitaemia in malaria. AD A 2.6.2 Acquired (adaptive) immunity to malaria IBAcquired immunity to malaria requires both humoral and cellular components of the adaptive immune system. Both types of acquired immunity are mediated by a special class of white blood cells known as lymphocytes. These cells express cell surface molecules capable of recognizing a wide variety of proteins. Lymphocytes are also comprised of two subsets: T lymphocytes and B lymphocytes. Studies have suggested that during blood-stage infection with Plasmodium species in mice and humans, both cell-mediated and antibody- 39 dependent responses are critical for the control of parasitaemia and parasite-induced pathology (Bouharoun-Tayoun et al., 1990; Day and Marsh, 1991; Marsh and Kinyanju, 2006). In malaria endemic areas, acquired immunity develops with repeated exposure to the malaria parasite and, as such, is neither sterile nor permanent. Likewise, infection by one strain of P. falciparum does not induce acquired immunity to all strains. Thus, immunity is species-, stage-, and strain-specific (Plebanski and Hill, 2000). Y Humoral (Antibody-mediated) immune responses to the malaria parasites AR Humoral immune response is mediated by B lymphocytes (B ceRlls). B cells have antigen receptors (BCR) on their surfaces which consist Bof membrane-bound immunoglobulins or antibodies that bind selectively to a portionL of Ian intact antigen. When B cells are appropriately activated, they differentiate into cells that secrete their receptors or antibodies into the blood. Within the first week of priYmary malaria infection, specific antibodies of several isotypes (IgG, IgA, and IgSM) cIa Tn be detected (Marsh and Kinyanju, 2006). Immunoglobulin G and IgM antibody levels may be long sustained and may form the basis of many serological reactions uEsefuRl in diagnosis and epidemiological surveys, although they give little correlation Vwith clinical immune status. It has been demonstrated that passive transfer of monocloInal antibodies against parasite antigens may confer protection in naive mice (NaruNm et al., 2000). In humans, treatment of Thai P. falciparum - infected patients with IgGU extracted from African immune adults resulted in reduction of parasitaemia and clNinica l symptoms in an antibody-dependent cellular inhibitory effect in cooperation with monocytes (Bouharoun-Tayoun et al., 1990). The most direct evidence that antibodies Dare iAmportant mediators of immunity to malaria comes from passive transfer studies Ain which antibodies from malaria-immune adults were successfully used to treat patBients with severe malaria (Cohen et al., 1961; Sabchareon et al., 1991). Studies in mice deIficient in Fc-γ receptors further support an important role for antibodies (Rotman et al., 1998). Initially after an infectious bite by the mosquito vector, sporozoites may either be eliminated by antibodies or may proceed to infect liver cells. Anti-sporozoite antibodies are specific to sporozoites and directed mostly to a repeat sequence within circumsporozoite 40 (CS) protein or sporozoite STARP protein (Doolan and Martinez-Alier, 2006). Antibodies that bind to the sporozoite are able to prevent hepatocyte infection (Plebanski and Hill, 2000), and numerous studies have correlated anti-CS protein antibodies with protection in humans. Immunity to blood stages is thought to be mediated by antibodies that block merozoites from entering RBCs, antibodies that agglutinate infected RBCs or antibodieYs that opsonize infected RBCs (Engwerda and Good, 2005). Antibodies are directed eithRer against a number of identified proteins on the parasite itself or against parasite-deArived proteins expressed on the surface of the infected erythrocyte during intra-eryBthroRcytic development of the parasite (Giha et al., 2000; Stanisic et al., 2009; Omosun et aIl., 2010; Khosravi et al., 2011). Although the potential of many antigens as targets for iLmmune responses has been suggested, little is known about the mechanisms of protecYtion in vivo. Several studies have suggested possible mechanisms by which antibody rTesponses may mediate immunity to asexual blood stage of malaria including: inhibition oIf merozoite invasion of the RBC, or by blocking merozoite release from schizonts ReitheSr by binding to surface exposed antigens (Green et al., 1981; Wahlin et al., 1984E; Bull and Marsh, 2002); opsonization of parasites and infected RBCs for enhancedI Vphagocytosis (Giribaldi et al., 2001); prevention of cytoadherence of infected RBNCs to the microvasculature endothelium, thereby allowing them to be removed by theU spleen (David et al., 1983); and inhibition of rosetting of infected RBCs to uninfected RB Cs (Carlson et al., 1990a; Carlson et al., 1990b). In collaboration with other effector iNmmune cells, parasite antigen-specific antibodies play an important role via antibody-deApendent cellular inhibition (ADCI), whereby binding of antibodies to phagocytes Dvia Fc receptors lead to inhibition of parasite growth (Aucan et al., 2000; Tebo et al., 2A001). IBSpecific antibody isotypes and subclasses may play diverse roles in malaria. The polarization of antibody responses towards IgG1 and IgG3 subclasses, which bind to Fcγ receptors (FcγR) on the surface of monocytes, macrophages, and neutrophils, is believed to play a key role in immunity to blood-stage Plasmodium falciparum infection (Bouharoun- Tayoun et al., 1990). Specifically, high levels of malaria-specific cytophilic antibodies, such 41 as IgG3, were found in malaria-exposed donors and suggested to be protective (Shi et al., 2001; Leoratti et al., 2008; Courtin et al., 2009). Once merozoites have been released from the schizonts, cytophylic antibodies may mediate parasite elimination through complement- dependent lysis or by cellular effector mechanisms (Kumaratilake et al., 1997; Ramasamy et al., 2001). An almost exclusive restriction of the humoral immune response of IgG3 subclass to MSP-2 blocking has been observed by several investigators (Taylor et al., 1995; Ferrante and Rzepczyk, 1997). Hence, these IgG3 antibodies are potentially effeYctive mediators of protection due to their cytophylic nature. In another study howRever, IgG subclass distribution of naturally acquired antibodies to P. falciparum meroAzoite surface proteins in adults exposed to low to moderate levels of malaria transmissioRn was found to be primarily epitope driven (Scopel et al., 2006). IgG3 polarization waIs Balso found to be more evident for polymorphic domains of MSP-1 than those of MS PL-2, being little affected by cumulative or current exposure to malaria and not affYected by the subject‟s age and FcγRIIA. In contrast, high levels of IgE have been iImTplicated in the pathology of malaria (Maeno et al., 2000; Perlmann et al., 2000). S ER Cellular (Cell-mediated) immune reIsVponses to the malaria parasites Cell-mediated immUuneN response is carried out by T lymphocytes (T cells) which, when activated, can spec ifically recognize and kill an infected or foreign cell. T cells have receptors on their surfaces, termed the T cell receptor or TCR (Marrack and Kappler, 1987). T cells may be AclassNified into three based on the type of TCR that they express. These are: Cytotoxic TD Lymphocytes (CTLs) distinguished by the presence of CD8 protein on their surfaceAs; Helper T Lymphocytes (TH cells) distinguished by the presence of CD4 protein on thIeBir surfaces; and Regulatory T Lymphocytes (TReg Cells) which are characterized by the + +possession of CD4 CD25 surface markers (Spellberg and Edwards, 2001; Karp, 2010). Helper T cells may be further sub-divided into three (TH1, TH2 and TH17), which can be distinguished by the cytokines they secrete (Hall, 2011). TH1 cells secrete IFN-γ, TH2 cells secrete IL-4, while TH17 cells secrete IL-17. For T cells to be activated, the TCR must recognize and interact with foreign peptide on the surface of an antigen presenting cell 42 + (APC) in association with a major histocompatibility complex (MHC) molecule. CD4 T + cells are activated by a foreign peptide bound to a class II MHC molecule, whereas CD8 T cells recognize antigens presented to it by MHC class I molecules (Spellberg and Edwards, 2001). Cell-mediated immune responses induced by malaria infection have been suggested to be protective against both pre-erythrocytic and erythrocytic parasite stages and thus play a critical role in the host defence system against malaria (Horowitz et al., 2010; Kimura et al., 2010). RY There are data showing that T cells play a major role in the acAquisition and maintenance of protective immune responses to malaria infection (Li eRt al., 2012). Mice with severe combined immunodeficiency (SCID) and reconstituIteBd with T cells from immune donors suppress parasite growth, suggesting a prote ctLive role of T cells against malaria parasites, while B cell-deficient mice were able to Ysuppress parasitaemia at the same rate as normal mice (van der Heyde et al., 1993). A IcoTrrelation between resistance to fever and high parasitaemia and in vitro T cell responses to P. falciparum blood stage antigens has also been reported (Riley et al., 1992), althoSugh this was not found in previous studies (Hviid et al., 1990; Riley et al., 1990). In huRmans, direct studies of the responding T cells during malarial infection are difficult, as Ethese cells may leave the peripheral circulation and sequester in the spleen or otherN tissuIe Vs (Hviid et al., 1991a; Hviid et al., 1991b). U + + CD4 and CD8 T CNells + Of tDhe mAajor T-cell subpopulations, CD4 T cells are essential for immune protection against Aasexual blood stages in both murine and human malaria systems (Spellberg and EdwBards, 2001). For experimental malaria, evidence for this was based on adoptive transfer +ofI protection by such cells and on increased susceptibility to infection of CD4 T-cell- depleted mice. For P. falciparum malaria in humans, the existence of functionally different + + CD4 T cells in naturally exposed donors has also been established experimentally. CD4 T cells play a central role in regulating the immune responses to the asexual blood stages of P. falciparum via cytokine production and B-cell help (Claser et al., 2011). These cells respond to malaria antigen by in vitro proliferation and/or secretion of cytokines, e.g. IFN-γ 43 or IL4 (Bouyou-Akotet and Mavoungou, 2009). In general, these in vitro responses are + poorly correlated with protection. Nevertheless, in vitro stimulation of CD4 T cells from malaria-exposed donors may result in the production of IL4 in concordance with the serum concentrations of antibodies specific for the antigens used for lymphocyte stimulation. It has + been shown that CD4 T cells from individuals naturally exposed to malaria respond to blood stage antigens of P. falciparum by proliferation, production of IFN-γ and is IL-2 dependent in animal model (Kimura et al., 2010). RY + Similarly, CD8 T cells have been shown to play important roleA in the pre- erythrocytic immunity to malaria (Tse et al., 2011), thereby contBribuRting to protection against severe forms of malaria (Nardin and Nussenzweig, 1993; AIidoo and Udhayakumar, + 2000). However, no available evidence for a protective role oLf CD8 T cells against P. falciparum blood stage has been reported (Schmidt et al.Y, 2009; Tse et al., 2011). This is supported by the fact that RBC do not express claIssTical MHC class I molecules, hence lacking the antigen processing machinery, suggesting that RBC do not represent a target for + CD8 T cells. In any case, since human erythrocyStes do not express MHC antigens, lysis of + infected erythrocytes by CD8 cytotoxicE T lRymphocytes has no role in the defence against blood-stage parasites. V NI U DA N A IB 44 2.7 Cytokines in Host Defence against Malaria Cytokines are a diverse group of small, secreted proteins or glycoproteins which mediate, regulate and help direct many critical aspects of an immunity, inflammation, and hematopoiesis (Karp, 2010). They are rapidly produced in response to foreign antigen exposure and can promote the expansion, activation, recruitment, and differentiation of the responding cell types (Clark et al., 2007; Bakir et al., 2011). Cytokines generally (althYough not always) act over short distances and short time spans and at very low concRentration. They may act on the cells that secrete them (autocrine action), or on nearbAy target cells which are in the immediate vicinity of the producer cells (paracrine actionR). However, some cytokines may also enter the blood stream and act on distant ceLlls IinB an endocrine fashion (Hill and Sarvetnick, 2002; Vandenbroeck et al., 2006). Cytokines are key molecules that interact witIh TothYer immune cells in the activation of immune response to malaria (Torre et al., 2002b). They can have a profound effect on the balance between cellular and humoral responseS as well as the isotype of immunoglobin produced (Khaled and Durum, 2002; BorishR and Steinke, 2003). Cytokines are the major inducers of Th1 and Th2 subset develoEpment, which are important for the eradication of malaria parasites. Development of IThV1 response is mediated by pro-inflammatory cytokines, such as TNF-α, IFN-γ, IL-12N and IL-18 but can be antagonised by anti-inflammatory cytokines, including IL-4 , UIL-10 and transforming growth factor (TGF) β (Malaguarnera and Musumeci, 2002; CNabantous et al., 2009). Cytokine release in malaria may be triggered by parasite antigenAs, pigments or toxins. The balance between Th1 and Th2 immune response and betweeDn pro-inflammatory and anti-inflammatory cytokines is important in determining the levAel of malaria parasitemia, disease outcome and rates of recovery (Winkler et al., 199B8; Riley, 1999; Sinha et al., 2010; Bakir et al., 2011), while the overproduction of both prIo-inflammatory and anti-inflammatory cytokines can as well be responsible for disease severity and mortality (Day et al., 1999; Cabantous et al., 2009). 45 2.7.1 General features of cytokines and gene expression Cytokines are made by many cell populations, but the predominant producers are helper T cells (Th) and macrophages (Dong and Flavell, 2001). They have been referred to by a number of names depending on the cell types that produce them or their functional properties. For example, cytokines that are derived primarily from mononuclear cellsY such as monocytes or macrophages have been referred to as monokines while the cytokines produced by activated T lymphocytes are termed lymphokines. Cytokines with chRemotactic activities, which specifically regulate the migration of other cells, are calledA chemokines. Historically however, cytokines are referred to as interleukins since in a Rgeneral sense they are being produced by leukocytes and acting on other leukocytes (KIhaBled and Durum, 2002; Wurster et al., 2002; Borish and Steinke, 2003; Mehta et al., 20 04L). The biology of cytokine is so complex. Most of thYem are pleiotropic, meaning that different cell types may secrete the same cytokine orI fTor a single cytokine to act on several different cell types within the immune system as wSell as on cell types outside of the immune system. They are also redundant in natuEre: mRany biological properties originally described for one cytokine can also be ascribVed to others, suggesting that the loss of a particular cytokine can be compensated forI by the action of another (Hill and Sarvetnick, 2002). Cytokines are often produced iNn a cascade, as one cytokine stimulates its target cells to make additional cytokines. TheUy can also act synergistically, where two or more cytokines act together; or antagonNistic ally, where cytokines cause opposing activities (Dong and Flavell, 2001). DACytokines mediate their biological effect through the binding of specific receptors on theB outAer surface of target cells, generating cytoplasmic signals that act on various inItracellular targets (Ihle, 1996; Karp, 2010). These signal transduction events usually result in gene expression, which occurs rapidly after an inducing stimulus. The rapid increase in cytokine gene mRNA results in an outburst of cytokine protein secretion into the surrounding environment and can act directly on the cell that produced it or on neighbouring cells. This rapid increase in transcription is usually transient and is turned off rapidly resulting in a self-limited event. Thus, cytokine expression and signalling is highly regulated 46 because dysregulated cytokine responses can lead to pathological conditions (Wurster et al., 2002; Mehta et al., 2004). Cytokine receptors are transmembrane proteins where binding of the cytokine occurs in the extracellular region and interaction with signalling proteins occurs in the cytoplasm (O'Shea et al., 2002). Cytokine receptors can be divided into two groups: those whose intracellular domains exhibit intrinsic protein-tyrosine kinase (PTK) activity and those wYhose intracellular domains are devoid of such activity. Many of the latter group of Rreceptors, however, activate intracellular soluble PTKs upon ligand binding. ProteiRn-tyrAosine kinases (PTKs) are enzymes that phosphorylate specific tyrosine residues on protein substrates: a mechanism for signal transduction (Karp, 2010). LIB Cytokines utilize a novel signal transduction pathway referred to as Janus kinase- signal transducers and activators of transcription (IJATK-SYTAT) pathway (Shuai and Liu, 2003; Hideshima et al., 2005). JAKs represent aS family of PTKs whose members become activated following the binding of a cytokine to a cell-surface receptor. They play a central role in mediating signal transduction of mEanyR cytokines (O'Shea et al., 2002). JAKs harbour two potential active sites and were thVus named after Janus, a two-faced Roman god. STAT is a family of transcription factors thaIt become activated when one of their tyrosine residues is phosphorylated by a JAK (NIhle, 1996; Marrero, 2005). Once phosphorylated, STAT molecules interact to fo rmU dimmers that translocate from the cytoplasm to the nucleus. In the nucleus, the dimNerized STAT proteins are able to bind to specific DNA sequences in the promoters of cyAtokine inducible genes and activate or repress the transcription of those genes direcDtly. The JAK-STAT signalling pathway provides a direct link between cytokine bindingA at the cell surface to changes in gene expression at the level of new gene tranBscription (Marrero, 2005; Rakesh and Agrawal, 2005). Different cytokine receptors bind toI unique JAK and STAT combinations resulting in specific outcomes to cytokine exposure. 47 2.7.2 Pro-inflammatory and anti-inflammatory cytokines Interferon gamma (IFN-γ) IFN-γ is a key Th1 cytokine involved in the innate immune response to malaria. It is mainly produced by NK cells, CD8+ and CD4+ T lymphocytes and antigen presenting cells (Frucht et al., 2001; Bouyou-Akotet and Mavoungou, 2009; Horowitz et al., 2010). TY cell secretion of IFN-γ may help to induce cytophilic IgG blood-stage-specific antibRodies and assist in antibody-dependent cellular inhibitory mechanisms (Bouharoun-TAayoun et al., 1990). P. falciparum blood stage antigen can induce IFN-γ production byR CD4+T cells and this has been shown to be associated with protection against malarIiaB re-infection in Africa (Luty et al., 1999). Likewise, sporozoites which are rapidly p roLcessed by the host cell and presented on the surface of infected hepatocytes in combination with MHC class I, leads to stimulation of NK and CD4+ T cells to produce IFINT-γ,Y which can trigger a cascade of immune reactions and can lead to the death of intracellular parasites (Malaguarnera and Musumeci, 2002; McCall and Sauerwein, 201R0). S IFN-γ activates macrophages to kEill parasites, exerting its effects through its receptor IFNGR1. Animal models have shoIwVn a critical role of IFN-γ in immunity against malaria parasites (Favre et al., 1997; ANngulo and Fresno, 2002). High IFN-γ production as part of a Th1-driven immune resp oUnse has been associated with a more favorable outcome in most animal models of malaria (Sedegah et al., 1994). This effect has been attributed to the monocyte-macroAphaNge activating capacity of IFN-γ, with rapid killing of the malarial blood-stage parasites by reactive oxygen and nitrogen intermediates (Taylor-Robinson and Looker, 1998). ATheD role of IFN-γ as a key molecule in human antimalarial host defence has been demBonstrated in patients with uncomplicated P. falciparum malaria (Winkler et al., 1998). I However, IFN-γ is also part of an inflammatory response that, if exacerbated, can be associated with adverse pathology (Claser et al., 2011). It can also contribute to the acute symptoms of malaria through the induction of TNF-α and IL-1 (Riley, 1999). 48 TNF-α The first characterized parasite-induced cytokine was TNF-α, induced in macrophages by Plasmodium -infected erythrocytes, malarial pigment (Pichyangkul et al., 1994), and certain glycolipids such as GPI moiety (Schofield and Hackett, 1993; Malaguarnera and Musumeci, 2002). TNF is one of the most important mediators of inflammation. It is produced primarily by macrophages and monocytes after activatioYn by foreign antigens. Antibodies directed against GPI blocked the stimulatory function Rof lysates from different strains of plasmodia infected erythrocytes to induRce ATNF-α from mononuclear cells (Bate and Kwiatkowski, 1994). TNF-α can incBrease the phagocytic capacity of monocytes or macrophages due to an increased expLresIsion of Fc receptors on them, or to the modulation of Fc-receptor signalling pathways by signals originating from the binding of TNF-α to its receptors (Muniz-Junqueira Yet al., 2001). However, different strains of P falciparum obtained from children with Tmild or cerebral malaria have been found to show marked variation in thSeir Iability to induce TNF-α from monocytes/macrophages (Allan et al., 1995).R TNF-α has also been suggeVstedE to play a similar role to that of IFN-γ in early responses against Plasmodium (RaIndall and Engwerda, 2010). In animal models, treatment with an anti-TNF-α monoclonNal antibody resulted in a tendency toward longer times for parasite clearance (Looa reUesuwan et al., 1999), while treatment with recombinant human tumour necrosis facNtor-α reduced parasitaemia and prevented Plasmodium berghei K173-induced experimAental cerebral malaria in mice (Postma et al., 1999; Depinay et al., 2011). Similarly, aDn association between the ability to produce high levels of TNF-α and an acceleraAted cure and improved prognosis has been reported in humans (Mordmuller et al., 199B7; Randall and Engwerda, 2010). I TNF-α also seems to have, in roughly 1% of individuals with malaria, detrimental properties such as fever, aches and pains correlated to acute illness, hypoglycaemia, shock, bleeding, and reversible coma (Beutler and Grau, 1993). Elevated concentrations of TNF alter the surface properties of vascular endothelial cells and results in the local accumulation of leukocytes. These sequestered leukocytes release more TNF, thus amplifying the 49 cytotoxic effect on endothelial cells, and resulting ultimately in vascular wall damage and haemorrhagic necrosis. In severe falciparum malaria, several studies have shown association between plasma concentrations of TNF-α as well as other pro-inflammatory cytokines and mortality (Grau et al., 1989; Kern et al., 1989; Kwiatkowski, 1990), although this relationship was not confirmed in other studies (Shaffer et al., 1991). In murine models, immunopathological damage was found to be associated with elevated concentrations of TNF-α, which can be prevented by the administration of anti-TNF polyclonal antibYodies (Grau et al., 1987). AR Several studies have suggested that TNF-α is the main mBediaRtor of secondary complications accompanying severe malaria caused by P. falcLipaIrum and that it could become fatal among people suffering from cerebral malaria, se vere anaemia, lactic acidosis and hypoglycaemia (Odeh, 2001). Likewise, a close assoYciation between the presence of severe anaemia, high TNF-α concentrations, and largTe numbers of circulating haemozoin containing monocytes has been reported (Luty Set aIl., 2000), suggesting that haemozoin-induced TNF-α-production plays a part in eiRther initiation or exacerbation of anaemia as a clinical outcome of chronic, uncontrolled parasitaemia. Likewise, several experimental studies have demonstrated this cyItoVkine E's role in pathogenic malarial anaemia, including severe disruption of erythropoiNesis and erythroid cell suppression and proliferation (Tchinda et al., 2007a). HoweverU, the production of TNF-α could be regulated by the anti-inflammatory effect of IL -10 (de Waal Malefyt et al., 1991). AN Interleukin D(IL) 10 BAIL-10 was initially characterized as „„cytokine synthesis inhibitory factor‟‟ produced byI Th2 cell clones that inhibited the production of IFN-γ by Th1 cells (Fiorentino et al., 1989; Niikura et al., 2011). IL-10 is produced by B cells, Th2 cells, monocytes and macrophages after antigen stimulation (Vandenbroeck et al., 2006). The major function of IL-10 is to serve as an anti-inflammatory and immunosuppressive cytokine (Sunder et al., 2012). It inhibits cytokine production in Th1 and CD8+ cells as well as the production of 50 pro-inflammatory cytokines like TNF and IL-1. It however, does not affect the proliferation of Th1 and CD8+ T cells, but induces B-cell proliferation, and immunoglobulin production, which is essential for the development and maturation of antimalarial antibodies (Malaguarnera and Musumeci, 2002). However, evidence is accumulating that Th1 and CD4+ T cells provide a crucial source of IL-10 (Freitas do Rosario et al., 2012; Freitas do Rosario and Langhorne, 2012). IL-10 down-regulates the expression of MHC class II molecules on macrophages and of co-stimulatory molecules such as CD80 and CYD86, leading to decreased antigen presentation (Akdis and Blaser, 1999), inhibits ROIR and NOI production, prevents Tcell priming and proliferation, and suppresses the Aproduction of interferon-γ, interleukin 6, TNF-α, and GM-CSF by T cells (Akdis aIndB Bl Raser, 1999). It also inhibits the ability of malaria antigens to induce or release tumouLr necrosis factor (Ho et al., 1995). Y IL-10 is a key cytokine that has been shown to hTave important regulatory function in establishing a balance between pro- and anti-inflammIatory responses in malaria (Freitas do Rosario and Langhorne, 2012). A prominent Rrole Sin switching from Th1 to Th2 responses is attributed to IL-10 (Angulo and Fresno, 2002). Therefore, it is probably involved in controlling the adequate timing of IanVtipa Erasitic responses (Li et al., 1999). Plasma levels of IL-10 have been reported in paNtients with acute malaria (Wenisch et al., 1995). Similarly, an anti-IL10 antibody used tUo treat C57BL/6 mice infected with P. yoelii 17XL in vivo was shown to increase survi val times with no detectable changes in parasitemia (Kobayashi et al., 2000). Early IL-N10 production has been associated with susceptibility to infection, and it is thought that tAhis cytokine has a prominent anti-inflammatory effect, limiting in some way the damageD inflicted on normal tissues by an excessive Th1 response (Kobayashi et al., 1996). BAI It has been shown that the increase of interleukin 10 is more pronounced and more specific than interleukin 6 and interleukin 8 in patients with malaria parasitaemia compared with other infections (Jason et al., 2001). A study of malaria-infected children and adults in Gabon recorded many interleukin-10-producing CD4+ and CD8+ T cells co-expressing interferon-γ (Winkler et al., 1999). These cells may provide a fertile ground for parasite- 51 driven immune modulation. However, it is not yet clear whether the increased concentrations of interleukin 10 have a beneficial role by reducing the parasite-induced inflammatory response, or a detrimental one by decreasing the cellular immune responses. Similarly, in severe malaria, particularly in fatal cases, it has been suggested that there is a relative failure of IL-10 production, and thus of control of pro-inflammatory cytokine release (Ho et al., 1998). Likewise, it has been shown that severe anaemYia is associated with reduced concentrations of circulating interleukin 10 (Kurtzhals et Ral., 1998) and, that an increased ratio between TNF-α and IL-10 contributes to thRe revAersible bone-marrow suppression seen in malaria patients (Othoro et al., 1999). The inhibition of interferon-γ and TNF-α secretion by IL-10 synthesis has been repoIrBted to be important to counteract the pathological role of macrophages in cerebral mal arLia (Kossodo et al., 1997). ITYInterleukin-18 S IL-18 is a pro-inflammatory cytokineR that enhances innate and specific Th1 immune responses. It was originally discoverVed aEs a factor that induces IFN-γ production from Th1 cells (Okamura et al., 1995b). ApaIrt from Th1 cells, IL-18 can act on nonpolarized T cells, NK cells, B cells, and dendriticN cells to produce IFN-γ in the presence of IL-12 (Okamura et al., 1995b; Okamura et aUl., 1998; Akira, 2000; Ajiki et al., 2003). IL-18 has also been shown to have a rolNe in inducing a proper Th2 response because of its capacity to directly induce IL-4 andA IL-13 secretion, as well as high IgE expression by B cells (Hoshino et al., 1999; YoshDimoto et al., 2000; Nakanishi et al., 2001a). The ability of IL-18 to induce a Th2 responsAe depends on CD4+ T cells, NK-T cells, and IL-4. IL-18-induced IgE production has alsoB been shown to be abrogated in CD4+ T cell-depleted mice (Yoshimoto et al., 2000). TIherefore, IL-18 has the capacity to stimulate innate immunity and both Th1- and Th2- mediated responses (Nakanishi et al., 2001b). IL-18 is produced by monocytes, macrophages, dendritic cells, epithelial cells, Kupffer cells, astrocytes, kerotinocytes and osteoblasts when activated by antigenic products, or in response to microbial 52 lipopolisaccharides (Staak et al., 1997; Stoll et al., 1998; Dinarello, 1999; Nakanishi et al., 2001a; Seki et al., 2001; Swain et al., 2001). Analysis of the amino acid sequence and structural motifs of IL-18 shows that it belongs to the IL-1 family of cytokines (Okamura et al., 1995b). Like IL-1, IL-18 is produced as an inactive precursor that is cleaved by the IL-1 converting enzyme (caspaYse 1) to generate an 18.3 kDa biologically active peptide (Ghayur et al., 1997; Liu et al., 2000) and the activity of mature IL-18 is closely related to that of IL-1β (Bazan et aRl., 1996). Proteinase-3, caspase-3, and cathepsin proteases can also cleave the precursoAr polypeptide but this sometimes results in inactive forms of IL-18 (Su et al., 1997; SBugaRwara et al., 2001). Mature IL-18 binds a heterodimeric surface receptor (IL-L18RI) which is comprised of an α chain (IL-18Rα) responsible for extracellular binding Yand a β chain (IL-18Rβ) which is a nonbinding, signal transducing chain (Kato et al.I, T2003). Both chains are required for functional IL-18 signaling (Born et al., 1998; BoaSsberg et al., 2006). IL-18R is expressed on a variety of cells including macrophages, neRutrophils, natural killer (NK) cells, endothelial, and smooth muscle cells (Leung et al., 2001; Afkarian et al., 2002; Gerdes et al., 2002). The interaction of IL18 and IL18R results Ein the recruitment of myeloid differentiation 88 (MyD88), an adaptor molecule IiVnvolved in IL-1 and Toll-like receptor signaling (Chandrasekar et al., 2004). NThe high affinity IL18R complex also recruits the IL-1R- associated kinase (IRAK)U to the receptor complex resulting in phosphorylation of NFκB- inducing kinase wiNth su bsequent translocation of NFκB to the nucleus (Sareneva et al., 2000). Similar to IL-1, a soluble IL-18 binding protein which is constitutively secreted exists, and Dhas Ahigh affinity for IL-18 and blocks its biological activity (Nakanishi et al., 2001b). IB A In terms of its biological effects, IL-18 is closely related to and acts synergistically with IL-12 (Malaguarnera and Musumeci, 2002). The combination of IL-18 plus IL-12 has been suggested to be more effective at inducing interferon-γ production by macrophages than IL-18 alone (Dinarello, 1999). In synergy with IFN-α or IL-12, IL-18 induces IFN-γ production in T cells and enhances Th1 cell development (Okamura et al., 1995b; Micallef et al., 1996; Robinson et al., 1997), but may also exert its effect independently of IL-12 53 (Kohno et al., 1997). IL-18 can also induce IFN-γ production from T cells independently of TCR activation, a property unique to IL-18 (Dinarello and Fantuzzi, 2003). IL-18 has been reported to play a protective role in malaria, particularly in early immunity against Plasmodium by enhancing IFN-γ production in vivo (Singh et al., 2002). In human malaria elevated levels of IL-18 in serum/plasma of patients with P. falciparum malaria have been reported in several studies from endemic areas (Malaguarnera eYt al., 2002; Chaisavaneeyakorn et al., 2003; Nagamine et al., 2003). Likewise, increasedR levels of IL-18 as well as IFN-γ were observed in symptomatic individuals comparAed with non- symptomatic or aparasitaemic individuals suggesting the induction of tRhese cytokines in response to active P. falciparum infection (Torre et al., 2001). AsI aB result of the positive correlation between IL-18 levels and disease severity as well as Lparasitemia, IL-18 has been suggested to be a marker for disease severity in malaria (ToYrre et al., 2001; Nagamine et al., 2003). MyD88-dependent signalling of IL-18 is howeIveTr important for early parasite control as suggested by studies using animal models (CraSmer et al., 2008). R 2.8 Genetic Basis of Host Resistance tEo Malaria The impression that va VNriatiIons in host response to infection might have a genetic basis is not new (HaldaneU, 1949; Allison, 1954; Cooke and Hill, 2001). Way back in 1949, Haldane proposed that genetic variation in globin genes gave a selective advantage for survival in malariaN-endemic areas, and that similar forces from other pathogens could maintain great Abiochemical diversity (Haldane, 1949). Malaria has exerted an almost unparalleledD selective pressure on humans, leading to the appearance of gene polymoArphisms at high frequency (Kwiatkowski, 2000; Driss et al., 2011). Malaria has been deIsBcribed as the strongest known selective pressure in the recent history of the human genome (Kwiatkowski, 2005). The greatest number of genes conferring differential susceptibility to any disease has been reported only for the various manifestations of malaria (Frodsham and Hill, 2004). Malaria is the evolutionary driving force behind sickle-cell disease, thalassaemia, glucose-6-phosphate dehydrogenase (G6PD) deficiency, and other erythrocyte defects. 54 A growing number of human genes have been related to malaria resistance or susceptibility and these can be broadly divided into: genes that are related to erythrocyte metabolism, such as Duffy antigen chemokine receptor (DARC), G6PD, and β-globin haemoglobin (HBB); genes that mediate cytoadherence by P. falciparum -infected erythrocytes, such as complement component receptor 1 (CR1), CD36 ligand, and intercellular adhesion molecule 1 (ICAM-1); and genes that are directly involved in immune responses, such as interferon-γ (IFN-γ), tumour necrosis factor-α (TNF-α), interleukinsY (IL), and HLA genes (Jenkins et al., 2005; Mackinnon et al., 2005; Barreiro and QuAintaRna-Murci, 2010; Lyke et al., 2011). R IB 2.8.1 Haemoglobin variants L The most well-known examples of erythrocyte vYariants conferring resistance to malaria are the haemoglobin gene variants. HaemoglIoTbin comprises of four globin chains: foetal haemoglobin (HbF) has two α and two Sγ chains (α2γ2), while adult haemoglobin (HbA) has two α and two β chains (α2β2). TRhe α-globin and β-globin genes are located on chromosomes 16 and 11 respectively, Eand they control the production of globin chain (Ashley-Koch et al., 2000; VoIsVkaridou et al., 2012). The most striking of the haemoglobinopathies is associNated with the β-globin gene (HBB), of which three different amino acid changes are Uobserved at polymorphic frequencies: HbS (β6Glu→Val), HbC (β6Glu→lys), HbE (β26 Glu→lys) and they confer different levels of malaria protection (Flint et al., 1998; WNeatherall and Clegg, 2001; Verra et al., 2007). TheD termA sickle-cell disease (SCD) or “sickle hemoglobin” refers to a group of symptoAmatic disorders associated with mutations on the HBB gene (Richer and Chudley, 200B5), which produce the hemoglobin form known as Hemoglobin S (HbS). HbS hoImozygotes suffer from sickle-cell disease, but heterozygotes have a tenfold reduced risk of severe malaria (Allison, 1954; Ackerman et al., 2005). The mechanism of protection in heterozygotes having the sickle cell trait (HBAS) has been suggested to be innate (Gong et al., 2012). HbS is widespread all over malaria endemic areas and common in sub-Saharan Africa with carriers reaching 15-20% in some areas (Weatherall and Clegg, 2001). Within this region however, it has been shown that the HbS allele occurs in four different 55 haplotypes (Lapoumeroulie et al., 1992; Flint et al., 1998). Distinct mechanisms conferring protection against severe and complicated malaria have been proposed for the different haemoglobinopathies such as sickle-cell trait and beta thalassemia trait (Ayi et al., 2004; Williams et al., 2005a; Ferreira et al., 2011). Among the most relevant mechanisms, reduced erythrocyte invasion by the parasite, decreased intra- erythrocytic parasite growth (Pasvol et al., 1992), enhanced phagocytosis of parYasite- infected erythrocytes (Cappadoro et al., 1998; Ayi et al., 2004) and increasedR immune response against parasite-infected erythrocytes have all been described (DufAfy and Fried, 2006). The HbS allele seems not to prevent the infection per se, but is Rprotective against death or severe disease (profound anaemia and cerebral malaria)B, probably owing to impaired entry and growth of the parasites during the erythr ocLytiIc stage of development (Chippaux et al., 1992a; Chippaux et al., 1992b; Pasvol et al., 1992; Shear, 1993; Shear et al., 1993). Friedman (Friedman, 1978) had earlier describeYd the mechanisms by which HbS- containing erythrocytes inhibit malaria parasite SgrowIt Th. He showed that HbS changes its nature in deoxygenating conditions and pRarasites become gravely affected, therefore showing that only erythrocyte mechanisms are sufficient for providing resistance “in vivo”. He also showed that 90% of young parEasites are eliminated in HbAS cell populations, of which only 60% are sickled or dIisVtorted and that the parasite contributes to conditions inducing sickling in its host celNl. Haemoglobin C (HUb C) results from a point mutation leading to the replacement of glutamate by lysineN in the β-globin's sixth amino-acid position (Agarwal et al., 2000; Fairhurst et al., A2005). Hb C is restricted to parts of West and North Africa (Modiano et al., 2001; MockDenhaupt et al., 2004a). Although HbAC is asymptomatic, HbCC can produce mild haAemolysis, splenomegally and gallstones (Mockenhaupt et al., 2004a). Similarly, the reIlaBtively high frequencies of HbC have also been suggested to be maintained by resistance to P. falciparum malaria in West Africa (Modiano et al., 2001). The study showed evidence both for heterozygote and homozygote resistance and suggested that, unlike the sickle cell mutation, HbC may be an example of transient polymorphism, based largely on the perceived lack of clinical disability or haematological changes of HbC homozygotes, although it is not absolutely clear whether homozygotes for this variant are completely 56 unaffected by the condition. However, there are indications that HbC reduces parasitaemia and confers protection against mild malaria attack (Rihet et al., 2004). Haemoglobin E (HbE) is produced when the glutamic acid in position 26 of the β- globin chain is replaced by a lysine (Nagel et al., 1981; Chotivanich et al., 2002; Ohashi et al., 2004). It has been observed that erythrocytes from people having HbE show reduced plasticity and deformability “in vitro”, thus impairing merozoite growth and reYlease (Bunyaratvej et al., 1992). Homozygous HbE erythrocytes (HbEE) are microcytiRc (having low mean corpuscular volume) at low haemoglobin concentration (Nagel et alA., 1981). Such haemoglobinopathy is very common in South-eastern Asia (Chotivanich Ret al., 2002). HbE is found in the eastern half of the Indian sub-continent and througBhout Southeast Asia, where, in some areas, carrier rates may exceed 60% of the pop ulLatioIn (Ohashi et al., 2004). Homozygotes generally have symptoms of anaemia. It hasY been observed that erythrocytes from HbE-heterozygous individuals are relatively resiIstTant to invasion by P. falciparum and presumable that HbE protects against severe malaria (Chotivanich et al., 2002; Kwiatkowski, 2005). S The thalassaemias are the most commRon haemoglobin variant with high prevalence and distribution in malaria endemic areaEs and provide one of the most compelling evidence of genetic factors controlling diseIaVse susceptibility in humans (Haldane, 1949; Allison, 1954; Weatherall and Clegg, 2N001; Verra et al., 2007). The thalassaemias comprise a group of clinical disorders tha t Uresult from defective production of α- or β-globin chains, which arise from deletionsN or other disruptions of the globin gene clusters on chromosomes 11 and 16 (Allen et alA., 1997; Vento et al., 2006). The α-globin is produced by two identical (linked) HDBA genes referred to as HBA1 and HBA2, with the genotype (αα/αα). oHomozAygous thalassaemia occurs when both genes are deleted, causing α -thalassaemia wIhBich results in severe disease or death, whereas heterozygotes only have mild anaemia (Kwiatkowski, 2005). However, if one of the pair of genes (HBA1 or HBA2) is deleted or + inactivated such that some α-globin synthesis is possible (α -thalassaemia), the homozygotes are only mildly anaemic with hypochromic erythrocytes, whereas the heterozygotes are + clinically normal. The distribution of α -thalassaemia appears to be highly correlated with 57 malaria endemicity (Flint et al., 1998) and it is suggested to confer protection against severe malaria (Mockenhaupt et al., 2004b; Williams et al., 2005b). 2.8.2 Variants of erythrocyte enzyme Glucose-6-phosphate dehydrogenase (G6PD) deficiency is the most common human enzyme defect, being present in more than 400 million people worldwide (CappellinYi and Fiorelli, 2008). The geographical distribution of G6PD deficiency is consisRtent with evolutionary selection by malaria (Ganczakowski et al., 1995; Sarkar Aet al., 2010; Millimono et al., 2012). G6PD is a cytoplasmic enzyme that catalyIsBes th Re first step in the hexose monophosphate pathway leading to synthesis of pentoseL phosphate (Ruwende and Hill, 1998). It also catalyses conversion of nicotinamideY ade nine dinucleotide phosphate (NADP) to its reduced form (NADPH), thus providiTng reducing power to all cells and protecting erythrocytes from oxidative damage (FraInk, 2005). NADPH enables cells to counterbalance oxidative stress that can be triggeSred by toxic by-products that results from the digestion of haemoglobin by the malaria Rparasites after erythrocyte invasion (Cappellini and Fiorelli, 2008). G6PD is encoded byE a 16.2kb gene located on chromosome Xq28, the telomeric region of the X chromosIoVme's long arm, and hence one of the two G6PD alleles present in females is subject tNo inactivation. This gene comprises 13 exons (Ruwende and Hill, 1998) and displays dUifferent mutations varying among different populations (Mehta et al., 2000). The G6PAD Ngene exhibits remarkable polymorphism in human populations and G6PD is Dknown to have over 400 variants (Beutler, 1994; Frank, 2005; Hue et al., 2009). MAany mutations reducing G6PD activity have been associated with protection against maBlaria (Clark et al., 2009) and might be beneficial by reducing parasite growth rate into the erIythrocytes or by causing a more efficient phagocytosis of infected red cells at an early stage of parasite maturation (Friedman, 1978; Cappadoro et al., 1998; Ruwende and Hill, 1998). In clinical field studies, fewer P. falciparum parasites were found in children heterozygous for G6PD deficiency than in children with normal copies of the gene (Bienzle et al., 1972). Furthermore, G6PD-deficient children were found to have fewer episodes of life-threatening malaria than did children in whom G6PD activity was normal (Ruwende et 58 al., 1995; Orimadegun and Sodeinde, 2011; Luzzatto, 2012). In vitro studies showed that P. falciparum is able to invade G6PD-deficient red blood cells but does not mature normally (Usanga and Luzzatto, 1985). Parasitized G6PD-deficient red blood cells are phagocytosed more readily by macrophages than parasitized red cells with normal G6PD activity (Cappadoro et al., 1998; Ayi et al., 2004). Y 2.8.3 Immunogenetic variants R Major Histocompatibility Complex/Human Leukocyte Antigen RA The human major histocompatibility complex (MHC) is onIe Bof the most important components of the immune system, which is located on chro mLosome 6 and encodes cell-surface antigen-presenting proteins and many other proteins related to immune system function (Matsumura et al., 1992; Babbitt et al., 2005I; TFalkY et al., 2006a; Ahn et al., 2011). T cells recognize proteolytic fragments of antigens that are presented to them on major histocompatibility complex (MHC) molecuRles (SDoytchinova et al., 2011). MHC class I molecules present primarily products of proteasomal proteolysis to CD8(+) T cells, while MHC class II molecules display maVinly Edegradation products of lysosomes for stimulation of CD4(+) T cells (Munz, 2012). IMHC in humans is denoted as human leukocyte antigen (HLA) for its predominant expNression in these cells (Costantino et al., 2012). Major histoc UNomp atibility complex is formed by multiple polymorphic genes which have been subdAivided into three main groups: Class I (HLA-A, B, C); Class II (DRB1 and DQB1) andD Class III genes. These genes encode proteins involved in the recognition of parasiteA-derived antigens (Radwan et al., 2012). The first two classes are membrane-bound moBlecules able to activate T-lymphocytes to initiate or enhance an acquired immune reIsponse (Dausset, 1981; Bjorkman et al., 1987; Stern and Wiley, 1994; Pieters, 1997), while class III genes encode soluble proteins such as the complement cascade proteins and some cytokines and heat shock proteins. Multiple different human class II loci have been identified. These have been named DP, DM, DO, DN, DQ and DR, and exhibit different degrees of allelic polymorphism (Bell et al., 1986; Bjorkman and Parham, 1990; Mason and Parham, 1998). 59 Susceptibility to malaria has been shown in people having certain HLA class I and class II alleles (Weatherall et al., 2002; Yamazaki et al., 2011). Studies have suggested that the HLA-DR system could play an important role in protection against malaria (Mehta et al., 2004). In other studies, carriers of the class I HLA antigen HLA-Bw53 (frequently occurring in sub-Saharan Africa) were shown to be protected against severe malaria and associated with 14.7% reduction in cases of severe anaemia as well as 16.1% reduction of cerebral malaria (Hill et al., 1991; Hill et al., 1992). These findings were also supported byY data reported by other authors (Wilkinson and Pasvol, 1997; Gilbert et al., 1998). AMorReover, the class II HLA haplotype, DRB1*1302-DQB1*0501, is associated with reduced susceptibility to severe malaria in the population of Gambia in western Africa. FurIthBerm Rore, a recent study in Mali identified the HLA-A*30:01 and A*33:01 as potential susceptibility factors for cerebral malaria (Lyke et al., 2011), thus providing further evid eLnce polymorphism of MHC genes results in altered malaria susceptibility. ITY Nitric oxide synthase 2 (NOS2) polymorphism S The nitric oxide synthase 2 (NOSE2) eRnzyme produces nitric oxide (NO), free radical mediating several physiological processes in immune-regulation (Hobbs et al., 2002), which is implicated in innate immunity agIaVinst malaria. It has been shown that GPI moiety induces NOS in macrophages (TachadNo et al., 1996) and activates endothelial cells by tyrosine- kinase-mediated signal t raUnsduction (Schofield et al., 1996). The NOS2 encoding gene is localized in chromosNome 17 and consists of 26 exons, its transcription site beginning in exon 2 and its stop coAdon in exon 26 (Chartrain et al., 1994; Coia et al., 2005). Even though the molecular Dmechanisms responsible for protection against severe malaria is yet to be elucidaAted, some studies have suggested that polymorphism in the NOS2 gene promoter reIgBion does increase NO production and could thus be an antimalarial resistance mechanism (Lopez et al., 2010). Perkins et al. (1999) measured NO production and NOS (NO synthase) activity in peripheral blood mononuclear cells (PBMCs) from Gabonese children having a history of prior mild malaria (PMM) or prior severe malaria (PSM) caused by P. falciparum (Perkins et al., 1999). The study showed that the PMM group had significantly higher levels of NOS activity in isolated PBMCs, high NO production and NOS activity in cultured 60 PBMCs (Perkins et al., 1999), contrary to earlier study (Kremsner et al., 1996) showing increased NO levels in plasma from patients suffering from severe P. falciparum malaria, thus suggesting association of high levels of NO production with the disease's severity. In animal models, NO has been shown to be associated with protection against cerebral malaria through impaired brain microcirculatory haemodynamics and decreased vascular pathology (Cabrales et al., 2011). Y Promoter polymorphisms in the NOS2 gene has been suggested to bAe inRvolved in antimalarial resistance, mainly in children, partly depending on their innate immune response in malaria-endemic areas (Kun et al., 1998). The promoter vBariaRnts were shown to protect heterozygous carriers against severe malaria (Kun et al., 20I01). Carriers of certain promoter variants were also found to have higher basal levels oLf nitric oxide (Coia et al., 2005). The promoter mutation has likewise been shown Yto b e associated with protection against cerebral malaria and severe malarial anaemia iTn Tanzania and Kenya (Hobbs et al., 2002). Recently, it was shown that the NOS2 genotyIpe protects against severe malaria by increasing NO production during episodes oRf uncSomplicated malaria (Planche et al., 2010). Moreover, promoter variants in the NOSE2 gene have also been found to be associated with severe megaloblastic anaemia in maIlVaria patients (Aggarwal et al., 2011). However, in another stNudy assessing the relation between NOS2 promoter SNPs and haplotypes with malaria Useverity in Tanzanian children, no consistent associations were found and it was conclu ded that the cause-effect relationship might be more complex than previously thought (NLevesque et al., 2010). A TumouAr necDrosis factor-α promoter polymorphism IBAs described earlier, tumour necrosis factor-α (TNF-α) is a cytokine presenting a broad range of pro-inflammatory activities. It plays an important role in inflammation (Bayley et al., 2004) and acts on several cell systems, regulating the expression of adhesion molecules (Tchinda et al., 2007a). The TNF-α gene is located within the major histocompatibility complex and contains within its promoter region, several single nucleotide polymorphisms at positions -863, -857, -376, -308, -244 and -238 relative to the 61 transcription start site (Wilson and Duff, 1995). These polymorphisms could modify DNA conformation at the promoter and thereby, the binding of transcription factors that may ultimately alter TNF-α gene expression. The polymorphism at position -308 has either a G in the TNF-α1 allele or an A in the TNF-α2 allele. TNF-α2 allele (TNFα -380A/A) has been found to be a stronger transcription factor activator than the TNF-α1 allele (TNFα -308G/G) and has been associatedY with malaria susceptibility (Wilson et al., 1997; Baseggio et al., 2004). HomozygousRity at the TNF-308A has been found to be associated with increased risk of cerebrAal malaria in Gambian and Kenyan children (McGuire et al., 1994) while a second polRymorphism (TNF- 238A) also showed association to severe anaemia in the Gambian paBtients (McGuire et al., 1999). The frequency of the heterozygous genotype (TNFα -3L80IA/G) has recently been found to be high in the malaria endemic area of Ivory CoasYt, suggesting a possible selective advantage of the heterozygote genomes (SantovIito et al., 2012). The TNF-376A polymorphism appears to recruit the transcriptionS facto Tr OCT-1 to the promoter, resulting in increasing gene expression in monocytes, and increased susceptibility to infection (Knight et al., 1999). In The Gambia, the TNEF-37R6A alleles were associated with increased susceptibility to developing cerebral Vmalaria (Kwiatkowski, 2000). I IL-18 and IL-18Rα gene aUnd pNromoter polymorphisms The human NIL-1 8 gene is located on chromosome 11q22.2-q22.3, and is composed of six exons andA five introns (Kruse et al., 2003). Its promoter is relatively unique in that it contains multiple transcription initiation sites. Studies have shown the presence of three SNPs aAt poDsition -656G/T, -607C/A and -137G/C in the promoter of IL-18 gene (Giedraitis etI aBl., 2001; Sugiura et al., 2002; Higa et al., 2003) although there are very few reports on the -656G/T SNP. The -607C/A and -137G/C are believed to be within a transcription initiation site. These promoter regions are predicted to be the binding sites for cyclic (Adenosine 30, 50-cyclic monophosphate) AMP-responsive element-binding protein [cAMP] (Haus-Seuffert and Meisterernst, 2000) and human histone H4 gene-specific transcription factor-1 [H4TF-1] (Giedraitis et al., 2001), respectively. A change from C to A 62 at position -607 disrupts a potential cAMP-responsive element-binding protein binding site and a change at position -137 from G to C changes the H4TF-1 nuclear factor binding site, thereby impacting on IL-18 gene activity and potentially also to IFN-γ (Giedraitis et al., 2001). Polymorphisms in the IL-18 gene promoter have been implicated in various diseases and disorders such as type I diabetes, Alzheimer‟s disease (Yu et al., 2009), CYancer (Palmieri et al., 2008; Khalili-Azad et al., 2009), HIV (Castelar et al., 2010; SoRbti et al., 2011), tuberculosis, asthma (Hollegaard and Bidwell, 2006), hepatitis B virus A(Migita et al., 2009), and rheumatoid arthritis (Thompson and Humphries, 2007). MeanwRhile, no data was available to my knowledge, on the relationships between IL-18 genIe Bvariants as well as IL- 18Rα gene variants and malaria disease outcome as at the ti mLe this study was designed. However, there is now evidence to show that IL-18 promYoter variants are associated with severe malaria anaemia (Anyona et al., 2011). SI T R IV E N N U AD A IB 63 CHAPTER THREE MATERIALS AND METHODS 3.1 Study site This study was conducted in Lafia (Latitude 8° 30′ N and Longitude 8° 31′ E), a city in the middle belt region of Nigeria. Lafia is the capital city of Nasarawa state, which sYhares boundaries at the North-West with Abuja (the Federal Capital Territory), at the NRorth-East with Plateau State, at the North with Kaduna State, at the South with BenueA State, at the South-West with Kogi State and at the South East with Taraba State (Fig.R 3.1). Lafia has an estimated population of 134,185 out of the estimated 1,863,275 peIoBple in Nasarawa state. Lafia is an agrarian town with a large percentage of its popu laLce engaged in farming and agro-allied activities. The town has rich fertile soils, good for cultivating crops such as cassava, rice, yams, cashew, mangoes, oranges, groundTnutsY, beans, melon, maize, millet and guinea corn (http://www.nasarawastate.org/data.htm.I Accessed 4th January, 2008). Lafia lies within the Guinea savanna ecoloSgical zone in north-central Nigeria. In this region, malaria transmission is describeEd asR stable and intense through most of the year (Bruce-Chwatt 1951; Molineaux anVd Gramiccia 1980). In Lafia, malaria is endemic and perennial with 7-12 months of tranIsmission season (Craig et al., 1999). Anopheles gambiae s.s., Anopheles arabiensis and NAnopheles funestus are the predominant vectors in this region (Bruce-Chwatt, 1951; Bo rUeham et al., 1979; Molineaux and Gramiccia, 1980). N 3.2 StudDy PAopulations AA total of four hundred and thirty seven unrelated children between 6 months and 8 yeaBrs of age were enrolled into the study between November, 2005 and December, 2006, afIter satisfying the inclusion criteria. Children were enrolled into three groups: uncomplicated malaria, severe malaria and asymptomatic infections (control group) based on clinical and laboratory diagnoses. Children who present with clinical symptoms of 64 RY A LIB R Y IT S ER IV N N U DA Study Site A FIigBure 3.1: Map of Nigeria showing Lafia, Nasarawa State where the study was conducted (indicated by the bold arrow) 65 malaria were enrolled at the Dalhatu Araf Specialist Hospital (DASH) Lafia. The control group comprised of non-symptomatic children infected by P. falciparum, residing within 3km radius of the hospital. Inclusion criteria for uncomplicated malaria was presentation with symptoms compatible with malaria which includes chills, history of fever within the preceding 48 hr or o pyrexia at presentation (axillary temperature >37.5 C), and the presence of asexual formYs of P. falciparum in peripheral blood smears without any indication of severeR malaria. Participants enrolled into the severe malaria group satisfied at least one of tAhe following: impaired consciousness assessed using the Blantyre coma scale of ≤2 (uRnrousable coma), hyperparasitaemia corresponding to >5% infected cells (>250,000B/µl), severe anaemia (haematocrit <15%), hypoglycaemia (serum glucose < 2.2 mmoLl/LI or <40 mg/dL) and the presence of asexual forms of P. falciparum in peripheral blo od smear according to WHO criteria (WHO, 2000). Non-symptomatic infection wIaTs deYfined as the presence of asexual forms of P. falciparum in peripheral blood smSear with a measured axillary temperature o<37.5 C and no history of febrile illness oRr of antimalarial drug use in the preceding 2 weeks. VE 3.3 Ethical Considerations I Ethical approval foUr th Ne study was granted by the Ethics Review Committees of the Nasarawa State MinNistry of Health and the Dalhatu Araf Specialist Hospital, Lafia before the commencement of the study (Appendix 6 and 7). The details of the study were explained to parents/DguarAdians of likely participants. Informed consent was then obtained from interestAed parent or guardian of each child prior to being included in the study. B 3.I4 Sample collection Blood (1ml) was collected by venepuncture from each child into EDTA bottles for molecular, parasitological and haematological analysis. Three drops of blood were spotted on labelled filter paper, air dried, individually sealed in plastic bags and stored at room temperature until DNA extraction. Thick and thin blood smears were made for microscopic 66 examination. The slides were labelled, allowed to dry and stored in a slide rack until microscopy. 3.5 Microscopy Slides were stained with freshly prepared Giemsa stain. Thick and thin blood films were examined for malaria parasites. Parasitaemia were quantified relative to 2R50 Ywhite blood cells (WBC) on thick films and estimated as parasites per µl assuming a mean WBC of 8,000 per µl of blood. Blood smears were labelled negative if no parasites wAere seen after examination of 200 oil immersion fields (x1,000) on a thick blood filmR. Thin films were used for screening and identification of species of malaria parasiLtes IotBher than P. falciparum . Y T 3.6 Determination of Blood haemoglobin (PSCV)I Blood haemoglobin levels were estiRmated by haematocrit measurement using the micro-haematocrit centrifuge. Briefly, blEood sample in the EDTA bottle was gently mixed and a plain capillary tube was usedI tVo draw blood by capillarity to about 70% of the length of the tube. Excess blood wasN wiped off from the tip of the tube and the ends of the tube were sealed with plasticine. The tube was then placed in a microhaematocrit centrifuge and spun at 3,000rpm for 5 m iUnutes. A microhaematocrit reader (Hawksley) was afterwards used to measure the packNed cell volume. Centrifugation step was performed at room temperature. A 3.7 ADeteDrmination of Haemoglobin genotypes IBHaemoglobin genotypes were determined by electrophoresis of blood lysate on cellulose acetate paper. Briefly, 200µl of blood was taken from the EDTA bottle and transferred to a 2 ml microfuge tube. Water, about 4 times the blood volume, was added to the blood and allowed to stand for 20 minutes to facilitate cell lysis. Meanwhile, the electrophoresis chamber was half-filled with Tris-EDTA/Borate buffer at pH 8.6 and TM chromatography papers (used as wicks) placed over the Perspex chamber shoulder. One 67 end of the chromatography paper on the chamber shoulder was totally immersed in the cathodic compartment, while another end at the opposite side of the chamber shoulder was immersed in the anodic compartment of the buffer solution. The cellulose acetate membrane was slowly impregnated with the buffer solution for 10 minutes prior to the run. The haemolysate was mixed and small volume of each diluted sample was transferred onto a tile. The buffer impregnated membrane was then blotteYd and an applicator used to transfer the haemolysate sample of test subjects and known Rstandards (Hb A, S, C) onto the cellulose acetate membrane. The membrane was then poAsitioned at the chamber shoulder with the chromatography paper. Current was suppliedR at 200-240 volts and allowed to run for 20 minutes or until adequate separation was oBbtained. Reading was made immediately after separation. The haemoglobin gen otLypeI of each sample was determined using the bands of the standards as references. Y IT 3.8 DNA Extraction S ® DNA was extracted from the dried bRlood spots on filter paper using the QIAamp DNA Mini Kit (Qiagen, Hilden, GermEany) following the manufacturer‟s protocol, and o stored at -20 C until further analyIsiVs. Briefly, 3-5 pieces of approximately 3x5mm blood spot from the filter paper wereN cut-out using razor blades or disposable surgical blades, one for each sample (to avo idU contamination). The cut-out parts were transferred into a 1.5 ml microcentrifuge tubNe and 180 µl of Buffer ATL added to it to enable cell lysis. This was incubated at 85A°C for 10 min and briefly centrifuged to remove drops from inside the lid. For deproteDination, 20 µl of proteinase K stock solution was added to the sample, mixed by vortexinAg, and incubated at 56°C for 1 hr. 200 µl of Buffer AL was afterwards added to the samBple, mixed thoroughly by vortexing, and incubated at 70°C for 10 min. 200 µl of abIsolute ethanol (98-100%) was added to the sample, mixed thoroughly by vortexing and briefly centrifuged to remove drops from inside the lid. The mixture was then carefully ® applied to a QIAamp Mini spin column and centrifuged at 8000 rpm for 1 min. The ® QIAamp Mini spin column was then placed in a clean 2 ml collection tube and the filtrate ® discarded. 500 µl of Buffer AW1 was carefully added to the QIAamp Mini spin column and centrifuged at 8000 rpm for 1 min. This step was repeated using Buffer AW2 and 68 ® centrifuged at full speed 14,000 rpm for 4 min. The QIAamp Mini spin column was afterwards placed in a clean 1.5 ml microcentrifuge tube while the collection tube containing the filtrate was discarded. To elute DNA, 150µl of distilled water was carefully added to the ® QIAamp Mini spin column, incubated at room temperature for 1 min, and then centrifuged at 8000 rpm for 1 min. All centrifugation steps were performed at room temperature. DNA amplifications were performed using a BIOMETRA TB1 thermal cYycler (Biotron, Göttingen Germany). R A 3.9 Design and Synthesis of Oligonucleotide Primers BR With the exception of primers used for the genus and s peLcieIs PCR, Oligonucleotide primers were specifically designed for all PCR and sequencing reactions in this study. Primers were designed with the aid of two software programYs that are freely available on the Internet, for use to the scientific community: PrimerI3 T(http://www-genome.wi.mit.edu/cgi- bin/primer/primer3www.cgi) and ExonPrimer (htStp://ihg.gsf.de /ihg/ExonPrimer.html). With respect to the host cytokine gene study, gene Rsequences and mRNA sequences for the primer design were taken from both the EVntrEez Gene cytogenetic band and the Ensembl gene cytogenetic band. Sequences for theI P. falciparum MSP-2 study were taken from the Entrez PubMed and PlasmoDB databaNses. Following design of primers, Oligonucleotide sequences were reconfirmed on the cUytogenetic bands and sent for synthesis at Operon Biotechnologies GmbH, Cologne, GeNrmany. Primers were shipped salt-free in dried state (lyophilized). Upon arrival, primers Awere spun at 1000 rpm for 5 min, resuspended in sterile TE buffer at pH 7.0, ovortexed thDoroughly and stored at -20 C until use. BA3.I10 PCR Determination of Plasmodium spp In addition to microscopy, the PCR technique was used for the identification of the Plasmodium species because of its high sensitivity and specificity. The genus and species- specific PCR-based assay used in this study was designed to amplify portions of the sequence coding for the small subunit ribosomal RNA (SSUrRNA) and has the added advantage of being able to detect all the four major species of human Plasmodium. 69 3.10.1 SSUrRNA gene PCR 2.0µl of DNA template were amplified in a final volume of 25µl containing 2.5µl x10 reaction buffer, 100µM of each dNTPs (dATP, dGTP, dTTP, and dCTP), 0.5pM of each primer (PLU5 / PLU6 for the primary reaction and FAL1 / FAL2; MAL1 / MAL2; OVA1 / OVA2 in the nested reaction for P. falciparum, P. malariae and P. ovale respectivelyY) and 0.75 units of Taq DNA polymerase (Qiagen, Hilden, Germany). Primer sRequences (Appendix 1) are based on the SSUrRNA sequences described by Snounou et aAl. (1993). The o PCR programme used was: denaturation at 95 C for 5 min followed by 25R cycles (30 cycles o o o in nested) of 1 min at 94 C, 2 min at 60 C and 2 min at 72 C andI aB final extension period oof 5 min at 72 C. L 3.10.2 Gel electrophoresis TY PCR products were subjected to electrophoresIis on 1.5% and 2% agarose gels for P. malariae/P. ovale and P. falciparum respectivelyS, and visualized by transillumination with ® ultraviolet light after staining with SYBRE GRreen. Fragment sizes were calculated relative to the standard size marker (100bpI VDNA ladder) using the BioDocAnalyze (Biometra, Göttingen, Germany) computeNr software package. 3.11 Molecular CNhar ac Uterization of P. falciparum MSP-2 The genAetic diversity of P. falciparum infections was investigated by genotyping one of the Dmajor vaccine candidate antigens, the merozoite surface protein 2 (MSP-2), suggestAed to be the most informative single marker for assessing the mean number of paIrBasite genotypes per infected individual, which is also known as the multiplicity of infection (Snounou et al., 1999; Farnert, 2001). 3.11.1 MSP-2 gene PCR The primary reaction was designed to amplify the entire coding region of the MSA-2 gene using the MSA2-1 and MSA2-4 primer pairs (Appendix 2). The reaction mixture was 70 performed in a final volume of 25µl containing 5.0µl of DNA template, 2.5µl x10 reaction buffer, 100µM of each dNTPs (dATP, dGTP, dTTP, and dCTP), 0.75 units of Taq DNA o polymerase and 0.5pM of each primer. The PCR programme was: denaturation at 94 C for o o o 5 min followed by 35 cycles of 10 sec at 94 C, 30 sec at 57 C and 40 sec at 72 C and a o final extension period of 3 min at 72 C. This was followed by two sets of nested reactions using allelic family-specific primers (FC27 and 3D7). A third reaction was performed to amplify the entire central variable region with the primer pairs MSA2-2 and MSYA2-3 (Appendix 2) in order to detect sequences that may not be allelic family-specific. ARll nested reactions were performed in a final volume of 25µl containing 2.0µl of PCRA product from the primary reaction, 2.5µl x10 reaction buffer, 100µM of each IdNBTP Rs, 0.5pM of each primer and 0.75 units of Taq DNA polymerase. The PCR progrLamme was: denaturation at o o o o94 C for 5 sec followed by 30 cycles of 10 sec at 94 C, 30Y sec at 57 C and 40 sec at 72 C oand a final extension period of 3 min at 72 C. IT 3.11.2 Gel electrophoresis S PCR products were subjected to EelecRtrophoresis on 2% agarose gels and visualized ®by transillumination with ultraviolet Vlight after staining with SYBR Green. Fragment sizes were calculated relative to the sItandard size marker (100bp DNA ladder) using the BioDocAnalyze (Biometra, GöNttingen, Germany) computer software package. N U A 3.11.3 DNAD purification APCR products that showed single band on gel electrophoresis were purified on a IB® ®HiBind DNA spin column using the E.Z.N.A. Cycle Pure Kit according to the manufacturer‟s instructions. Briefly, 20µl of XP1 Buffer was added to the PCR product and ® mixed thoroughly by vortexing. The sample was then applied to a HiBind DNA spin column which had been inserted into a 2 ml collection tube and centrifuged at 13,000 rpm for 1 min. 700µl of SPW Buffer diluted with absolute ethanol was added to the sample and centrifuged at 13,000 rpm for 1 min. The liquid in the collection tube was discarded and 71 another 700µl of SPW Buffer was added to wash the sample again. The liquid in the collection tube was again discarded and the empty column was centrifuged at 13,000 rpm ® for 1 min to dry the column matrix. The HiBind DNA spin column was afterward placed in a clean 1.5 ml Eppendorf tube. 30µl of sterile deionised water was then added to the centre of the column matrix and incubated at room temperature for 1 min. This was then centrifuged at 13,000 rpm for 1 min to elute DNA. All centrifugation steps were performed at room temperature. Y AR 3.11.4 MSP-2 sequencing PCR R The sequence reactions were performed using the Big Dye IteBrminator reaction mix (PE Biosystems, Weiterstadt, Germany). Each amplicon was Lsequenced in the forward direction. The forward primers of the family-specific primers (FC 27-1, 3D7-1) were used for the sequencing reactions of the PCR products earlier Ygenerated. Sequencing PCR was performed in a reaction volume of 10µl with 30ng of IteTmplate DNA, 4µl sequencing buffer, 1µl BigDye™ Terminator reaction mix and R0.5µSl of primer. Cycling conditions (Biometra, o oGöttingen, Germany) were as follows: E25 cycles of 96 C for 30 seconds, 50 C for 15 oseconds and 60 C for 4 minutes. IV 3.11.5 Purification of sequenNcing products TM Sequencing prod ucUts were cleaned by centrifugation through Sephadex G-50 DNA Grade Fine (GE HeaNlthcare Bio-Sciences, Sweden) in 96-well Millipore plates. One gram of Sephadex was aAdded to 15ml of sterile water and mixed gently for 30 minutes. 200µl of the mix was thDen added to each well of a 96-well Millipore purification column plate, spun at o 3,000rpAm for 2 minutes at 4 C. Samples were then added to the gelatinized Sephadex for puIrBification. A sterile microtitre plate was attached to the bottom of the purification column oplate to collect the purified product. It was then spun at 3,000rpm for 2 minutes at 4 C. 72 3.11.6 MSP-2 Gene sequencing Samples were separated by capillary electrophoresis in ABI PRISM® 3100 sequencers using the default sequencing protocol in 50-cm capillary arrays. 3.11.7 MSP-2 Gene sequence analysis The sequences were analyzed and compared with published sequences on the EYntrez PubMed and PlasmoDB, using the BioEdit sequence alignment software A(HaRll, 1999) [http://www.mbio.ncsu.edu/BioEdit/BioEdit.html]. Sequences were cleaned up by manual adjustment. Multiple Alignments were carried out with the ClustaRl W programme (Thompson et al., 1994). LI B 3.12 Determination of Genetic Polymorphisms in ITL-1Y8 Gene Promoter Region The promoter region of IL-18 gene evaluaSted iIn this study is shown in Figure 3.2. R 3.12.1 IL-18 PCR E PCR products were generatIedV in a reaction volume of 25µl containing 2.0µl of DNA extract, 2.5µl x10 reaction bufNfer, 100µM of each dNTPs (dATP, dGTP, dTTP, and dCTP), 0.25 units of Taq DNA Upolymerase and 0.5pM each of the forward (IL-18Pro -F) and oreverse (IL-18Pro -RN) primers (Appendix 3). The cycling conditions consisted of 94 C for 3 o o omin followed byA 35 cycles of 40 sec at 94 C, 40 sec at 62 C and 1 minute at 72 C and a D ofinal extension period of 3 min at 72 C. A 3.I1B2.2 Gel electrophoresis PCR products were subjected to electrophoresis on 1.5% agarose gels and visualized ® by transillumination with ultraviolet light after staining with SYBR Green. Fragment sizes were calculated relative to the standard size marker (100bp DNA ladder) using the BioDocAnalyze (Biometra, Göttingen, Germany) computer software package. 73 (a) Y R (b) RA 1 2 3 4 5 6 ATG IB 3' G-656T C-607A G-137C 5' Y L 20.86Kb SI T Figure 3.2: IL-18 gene showing locationE of pRromoter polymorphisms. (a) The human IL-18 gene is locatedV on chromosome 11q22.2-q22.3 on the Entrez Gene Cytogenetic band. (b) The gene is composed of six exIons and five introns. Promoter polymorphisms in the 5' region are numbered upstream ofU the trNanscription start site. N AD A IB 74 3.12.3 DNA Purification DNA purification was done as described earlier in section 3.11.3. 3.12.4 IL-18 Sequencing PCR The sequence reactions were performed using the Big Dye terminator reactionY mix (PE Biosystems, Weiterstadt, Germany). Each amplicon was sequenced in theR forward direction. A separate primer (IL-18Pro -Fb) was designed and used as internal Aprimer for the PCR products of the promoter region (Appendix 3). Sequencing PCR wRas performed in a reaction volume of 10µl with 40ng of template DNA, 4µl sequencingB buffer, 1µl BigDye™ Terminator reaction mix and 0.5µl of primer. Cycling cond itLionsI (Biometra, Göttingen, o o Germany) were as follows: 25 cycles of 96 C for 30 secoYnds, 50 C for 15 seconds and 60oC for 4 minutes. IT 3.12.5 Purification of sequencing products S Purification of sequencing producEt waRs done as described earlier in section 3.11.5. 3.12.6 IL-18 gene sequencing IV Samples were seUparaNted by capillary electrophoresis in ABI PRISM® 3100 sequencers using the def ault sequencing protocol in 50-cm capillary arrays. N 3.12.7 IL-18 gAene sequence analysis ATheD sequences were analyzed and compared with published sequences on the Entrez PubBMed using the BioEdit sequence alignment software (Hall, 1999) [hIttp://www.mbio.ncsu.edu/BioEdit/BioEdit.html]. Sequences were cleaned up by manual adjustment. Multiple Alignments were carried out with the Clustal W programme (Thompson et al., 1994). 75 3.13 Determination of Genetic Polymorphisms in IL-18 Receptor-α Gene The entire gene for IL-18 Receptor-α as well as the promoter region was screened in this study (Figure 3.3). Molecular screening of the regulatory and coding regions of the gene were performed on 40 samples, drawn at random, from the non-symptomatic control group in order to determine common polymorphisms in this gene that could be of importance in this region. Subsequently, the promoter region, Exon 1 and Exon 7 were screened for sYingle nucleotide polymorphisms in all the study participants. AR 3.13.1 IL-18 Receptor-α promoter and Exon 1 PCR R PCR products were generated in a reaction volume of 25µLl cIonBtaining 3.0µl of DNA template, 4.0µl x10 reaction buffer, 200µM of each dNTPs (dATP, dGTP, dTTP, and dCTP), 0.75 units of Taq DNA polymerase and 0.4pM Yeach of the forward and reverse o primers (Appendix 4). The cycling conditions consisteTd of 94 C for 3 min followed by 35 o o o cycles of 40 sec at 94 C, 40 sec at 62 C and 1 mSinutIe at 72 C and a final extension period oof 3 min at 72 C. ER 3.13.2 IL-18 Receptor-α Exons 2I, 3V, 6 and 11 PCR PCR products were genNerated in a reaction volume of 25µl containing 2.0µl of DNA template, 4.0µl x10 rea cUtion buffer, 200µM of each dNTPs (dATP, dGTP, dTTP, and dCTP), 0.75 units oNf Taq DNA polymerase and 0.25pM each of the forward and reverse oprimers (Appendix 4). The cycling conditions consisted of 94 C for 3 min followed by 35 o o o cycles of 40D secA at 94 C, 40 sec at 63 C and 1 minute at 72 C and a final extension period A oof 3 min at 72 C. IB3.13.3 IL-18 Receptor-α Exons 4, 5, 7, 8, 9 and 10 PCR PCR products were generated in a reaction volume of 25µl containing 2.0µl of DNA template, 2.5µl x10 reaction buffer, 200µM of each dNTPs (dATP, dGTP, dTTP, and dCTP), 0.75 units of Taq DNA polymerase and 0.25pM each of the forward and reverse o primers (Appendix 4). The cycling conditions consisted of 94 C for 3 min followed by 35 76 o o o cycles of 40 sec at 94 C, 40 sec at 64 C and 1 minute at 72 C and a final extension period o of 3 min at 72 C. 3.13.4 Gel electrophoresis PCR products were subjected to electrophoresis on 1.5-2% agarose gels and ® visualized by transillumination with ultraviolet light after staining with SYBR GYreen. Fragment sizes were calculated relative to the standard size marker (100bp DNRA ladder) using the BioDocAnalyze (Biometra, Göttingen, Germany) computer softwRare Apackage. B 3.13.5 DNA Purification LI DNA purification was done as described earlier in sYectio n 3.11.3. T 3.13.6 IL-18 Receptor-α sequencing PCR SI The sequence reactions were performRed using the Big Dye terminator reaction mix (PE Biosystems, Weiterstadt, GermanyE). Each amplicon was sequenced in the forward direction except for Exon 1 (whichV also included the promoter region), which was also sequenced in the reverse direction.I Separate primers (IL18R1 Ex1-Fb, IL18R1 Ex1-Rb and IL18R1 Ex1-Rc) were desUigneNd and used as internal primer for the PCR product of Exon 1 and the promoter region (Appendix 4). Same primers used in the primary reaction were used for sequencing ExoNns 2-11. Sequencing PCR was performed in a reaction volume of 10µl with 40ng of temAplate DNA, 4µl sequencing buffer, 1µl BigDye™ Terminator reaction mix and 0.5µl oDf primer. Cycling conditions (Biometra, Göttingen, Germany) were as follows: o o o 25 cyclAes of 96 C for 30 seconds, 50 C for 15 seconds and 60 C for 4 minutes. IB 3.13.7 Purification of sequencing products Purification of sequencing product was done as described earlier in section 3.11.5. 77 (a) Y A R R B Y LI (b) T 2 3 4 S5 I 6 7 8 9 10 11 1 ATG T-661C -430 (AC)n G-175A C-93T 3' 5' ER 36.9Kbp V NI U Figure 3.3: IL-1A8RαN gene showing location of promoter polymorphisms. (a) The Dhuman IL-18Rα gene is located on chromosome 2q12 on the Entrez Gene Cytogenetic band. (b) AThe gene is composed of 11 exons and 10 introns. Promoter polymorphisms in the 5' region are numbered upstream of the transcription start site. IB 78 3.13.8 IL-18 Receptor-α gene sequencing Samples were separated by capillary electrophoresis in ABI PRISM® 3100 sequencers using the default sequencing protocol in 50-cm capillary arrays. 3.13.9 IL-18 Receptor-α gene sequence analysis The sequences were analyzed and compared with published sequences on the EYntrez PubMed using the BioEdit sequence alignment software (Hall, 1999) [http://wRww.mbio. ncsu.edu/BioEdit/BioEdit.html]. Sequences were cleaned up by maRnuaAl adjustment. Multiple Alignments were carried out with the Clustal W programIBme (Thompson et al., 1994). L 3.14 Determination of Genetic Polymorphisms inI TTNFY-α Gene Promoter Region The promoter region of the TNF-α gene eSvaluated in this study is shown on Figure 3.4. 3.14.1 TNF-α PCR ER PCR products were generatIedV in a reaction volume of 25µl containing 2.0µl of DNA template, 2.5µl x10 reaction Nbuffer, 100µM of each dNTPs (dATP, dGTP, dTTP, and dCTP), 0.25 units of Taq UDNA polymerase and 0.5pM each of the forward (TNFPro-F) and oreverse (TNFPro-R) prim ers (Appendix 5). The cycling conditions consisted of 94 C for 3 o o o min followed by 3N5 cycles of 40 sec at 94 C, 40 sec at 62 C and 1 minute at 72 C and a o final extension pAeriod of 3 min at 72 C. D 3.1B4.2 A Gel electrophoresis I PCR products were subjected to electrophoresis on 1.5% agarose gels and visualized ® by transillumination with ultraviolet light after staining with SYBR Green. Fragment sizes were calculated relative to the standard size marker (100bp DNA ladder) using the BioDocAnalyze (Biometra, Göttingen, Germany) computer software package. 79 (a) RY BR A LI (b) Y T1 2 3 4 ATG SI 5' 3' G-308A G-238A 3.5E6Kb RV NI U N Figure 3.4:D TNFA-α gene showing location of promoter polymorphisms. (a) AThe human TNF-α gene is located on chromosome 6p21.3 on the Entrez Gene Cytogenetic band. IB(b) The gene is composed of four exons and three introns. Promoter polymorphisms in the 5' region are numbered upstream of the transcription start site. 80 3.14.3 DNA purification DNA purification was done as described earlier in section 3.11.3. 3.14.4 TNF-α sequencing PCR The sequence reactions were performed using the Big Dye terminator reactionY mix (PE Biosystems, Weiterstadt, Germany). Each amplicon was sequenced in theR forward direction. A separate primer (TNFPro-Fb) was designed and used as internal Aprimer for the PCR products of the promoter region (Appendix 5). Sequencing PCR wRas performed in a reaction volume of 10µl with 40ng of template DNA, 4µl sequencingB buffer, 1µl BigDye™ Terminator reaction mix and 0.5µl of primer. Cycling cond itionsI (Biometra, Göttingen, o o oGermany) were as follows: 25 cycles of 96 C for 30 secondYs, 50 LC for 15 seconds and 60 C for 4 minutes. IT 3.14.5 Purification of sequencing products S Purification of sequencing producEt waRs done as described earlier in section 3.11.5. V 3.14.6 TNF-α gene sequencinNg I Samples were s eUparated by capillary electrophoresis in ABI PRISM® 3100 sequencers using theN default sequencing protocol in 50-cm capillary arrays. A 3.14.7 SeqDuence analysis AThe sequences were analyzed and compared with published sequences on the Entrez PIubBMed using the BioEdit sequence alignment software (Hall, 1999) [http://www.mbio.ncsu.edu/BioEdit/BioEdit.html]. Sequences were cleaned up by manual adjustment. Multiple Alignments were carried out with the Clustal W programme (Thompson et al., 1994). 81 3.15 Statistical analysis Data were entered into Microsoft® Excel, 2002 (Microsoft Corporation). A test for deviation from Hardy-Weinberg equilibrium was performed on all groups. Data were analyzed using JMP Statistical Discovery Software version 5.0.1.2 (SAS Institute Inc.) and Stata version 9.2 (StataCorp, College Station, Texas). Gene frequencies were obtained by simple gene counting and tested with chi-square test for comparing observed and expYected 2 values. For each locus, the chi-square statistic (χ ) and Fisher‟s exact test (for smalRl cell size, n< 5) were used to compare allele and genotype frequencies between casesA and control. Odds ratios (OR) and 95% confidence intervals (CI) were estimated by Rlogistic regression (Moore et al., 2002). Differences in clinical features betweeBn asymptomatic and uncomplicated malaria group as well as between asymptomaticL anId severe malaria group was compared using Student‟s t-test. The level of statisticalY sign ificance was set at P=0.05. T SI VE R I U N DA N IB A 82 CHAPTER FOUR RESULTS To determine host cytokine gene polymorphisms and parasite genetic factors that could contribute to disease outcome, a total of 437 children with microscopically confirmed P. falciparum infection were enrolled into this study. The baseline characteristics oYf the study population are shown in Table 4.1. On average, children in the severe malaRria group were the youngest with mean age of 32.6 (±18.4) months. The ratios of male toA female were not statistically different in all groups. The levels of parasitaemia were sRignificantly higher in both the uncomplicated and severe malaria groups compared wBith the asymptomatic group (P<0.001). Children were of comparable height acros s LtheI group, but there were decreases in mean weight with increasing disease severity (YTable 4.1). The distribution of haemoglobin genotype inI tThe three study groups are shown in Table 4.2. The AS haemoglobin genotypes wSere distributed according to the Hardy-Weinberg equilibrium, although individuals wRho were known to carry the SS genotype were excluded from the study even if they Ehad Plasmodium falciparum infection. A higher percentage of children (13.7%) IwVho carried the sickle cell trait (AS) were in the asymptomatic control group cNompared to 10% and 6.9% in the uncomplicated and severe malaria groups respectivelUy (Table 4.2). There was a statistically significant difference in the distribution of the AS g enotype between the asymptomatic group and the severe malaria group (13.7% vs 6.9N%; P < 0.05). DA 4.1 AMicroscopy and PCR-based diagnosis of mixed infections. IBAll the children who participated in this study tested positive for P. falciparum species by microscopy. Results of the PCR-based determination of the SSUrRNA gene showed that out of the 437 malaria positive participants, seven were mixed Plasmodium species infection (Figure 4.1-4.3; Table 4.3). Five of the seven cases were mixed infections 83 Table 4.1. Baseline characteristics of study participants (n = 437) AS UM P-value SM P-value (n=161) (n=160) (AS vs UM) (n=116) (AS vs SM) Y * Mean age (months) 36.3 (±16.9) 38.5 (±18.8) P=0.344 32.6(±18.4) P=0.0R72 Sex (male/female) 83/78 77/83 60/56 A Mean temperature o( C) 36.6 (±0.6) 37.8 (±1.0) P=0.001 38.1 (±1.0) R P=0.001 Mean haematocrit (%) 33 (±5.2) 30 (±5.7) P=0.011 20 (±6.I6)B P=0.001 Mean weight (Kg) 13.0 (±4.4) 12.8 (±4.5) P=0.584 Y 11 .9 L (±3.3) P=0.018 Mean height (cm) 88.5 (±12.4) 90.2 (±16.4) P=0.351T 88.9(±15.6) P=0.647 Parasite density (µl) §893 (118-5720) 5,403 (120-160,000) SP=0.I001 64,751 (640-1,825,500) P=0.001 AS= Asymptomatic Group (Control) R UM= Uncomplicated Malaria Group SM= Severe Malaria Group E * ±Standard deviation in parentheses V § Geometric mean (range in parenthes UN es) I DA N BA I 84 Table 4.2: Distribution of haemoglobin (Hb) genotype among the study participants Asymptomatic Group Uncomplicated Malaria Severe Malaria Hb Genotype n= 161(%) n= 160(%) n= 116(%) Y AA 130(80.75) 130(81.25) 102(R87.93) AC 8(4.97) 14(8.75) R A 6(5.17) AS 22(13.66) 16(10.00) I B 8(6.90) SC 1(0.62) 0(0) L 0(0) CC 0(0) 0(0)Y 0(0) SS 0(0) I 0T(0) 0(0) S ER V UN I N DA IB A 85 Lymphocyte RY BR A LI Plasmodium falciparum Neutrophil Y IT RS E IV N N U DA BAFIigure 4.1: Plasmodium falciparum parasites on thick blood film of a study participant. Arrows show representative of cells present on the film at mg= x1000. 86 Lymphocyte RY RA LIB Y Plasmodium ovTale RS I VE I UN Figure 4.2: PAlasNmodium ovale parasites on thick blood film of a study participant. DArrows show representative of cells present on the film at mg= x1000. A IB 87 Y R RA B Y LI IT S ER IV N Figure 4.3: Distribut ioUn of Plasmodium species among the study groups N LASYM= AsymptoAmatic Group (Control) LUM= UncDomplicated Malaria LSM= A Severe Malaria IB 88 Table 4.3: Frequency of Plasmodium species infections in the study population Infection category Number of Individuals infected (Single) Mono-species infection Pf 430 Y Pm 0 R Po 0 A (Mixed) Multi-species infection R B Pf + Pm 5I Pf + Po L 2 Pm + Po Y 0 Pf + Pm + Po T 0 I S Pf= Plasmodium falciparum R Pm= Plasmodium malariae E Po= Plasmodium ovale NI V U AN BA D I 89 of P. falciparum and P. malariae, while the other two were mixed infections of P. falciparum and P. ovale. Infection with P. vivax was not determined in this study. Participants with P. malariae infection included three from the asymptomatic group and two from the uncomplicated malaria group. The two participants that had P. ovale infection were from the asymptomatic group. No relationship was found between multi- species infection and disease outcome. In this study, multi-species infections were not fYound in the severe malaria group. R RA 4.2 MSP-2 genotyping of parasite population LIB Isolates from all the 437 participants were genotyYped for allelic polymorphisms at the MSP-2 locus. A total of 32, 35 and 28 distinIcTt MSP-2 alleles were found in the asymptomatic group, uncomplicated malaria and severe malaria groups respectively (Table 4.4). The distribution of MSP-2 alleles in the diffSerent groups showed high genetic diversity of isolates in this study population (Table 4R.4, Figure 4.4). The allelic frequency of FC27 type was higher in the asymptomaticV groEup (59%) compared with the severe malaria group (43%), while 3D7 alleles, in thIe asymptomatic group had a lower frequency (37%) compared to the severe malarNia group (54%). A significant difference was found in the distribution of FC27 a lleUles and 3D7 alleles between the asymptomatic controls and uncomplicated malaNria (P < 0.05; P < 0.05) as well as between the asymptomatic controls and severe malaAria group (P < 0.05; P < 0.01). ClonDality of infection (the distinct number of clones detected per child) ranged from 1 to 4 Aamongst the three study groups (Figure 4.5). Majority of children from the three clIinBical groups had one or two clonal infections (Figure 4.5). Most of the children with four distinguishable clonal infections were from the asymptomatic group. Polyclonality (the presence of more than one distinct clone) was found to be higher in the asymptomatic (61%) and uncomplicated malaria (60%) groups than in the severe malaria group where most infections were monoclonal and only 34% of the study participants had polyclonal infections. 90 The multiplicity of infection (MOI), defined as the average number of distinct genotype per infected subject, was calculated as the mean number of fragments (on gel electrophoresis) per infected subject in each group. The multiplicity of infection in children with asymptomatic infection, uncomplicated malaria and severe malaria groups were 2.1 (95% CI 1.9-2.3), 2.0 (95% CI 1.8-2.4), and 1.3 (95% CI 1.2-1.6) respectively. There was no statistically significant difference in the MOI between the asymptomatic malaria group and the uncomplicated malaria group (P> 0.05). However, the multiplicity of infection betYween the asymptomatic malaria group or uncomplicated malaria group and the severRe malaria group were statistically significant (P<0.001). RA B LI SI TY ER IV U N N AD A IB 91 AR Y R Table 4.4: Genetic diversity of isolates using the P. falciparum MSP-2 aIs Bmolecular marker LY MSP-2 FC 27 Allelic family MSP-2 3D7 AlleIlicT family Total No. of alleles Non-specific in each group alleles No. of alleles % frequency No. of alleles % frequency Asymptomatic group 19 59 12R S 38 32 1 Uncomplicated 16 46 18 51 35 1 malaria E Severe malaria 12 43 IV 15 54 28 1 UN AN D 92 BAI RYA IB R L ITY Figure. 4.4: Electrophoretic separation of PCRR proSducts showing intra-allelic diversity in one of the MSP-2 allele type, as reflected both in the number of distinct clones and in length polymorphisms. VE Lane M: 100-bp ladder. Lanes 1-18: parasNite DINA from infected individuals showing mono- (lanes 5,6,7,11 and 5) and multiple infections (lanes 4,9,12,U13 and 18) as well as variation in number or repeat units. DA N IB A 93 AR Y 70 65 KERY 60 AsIymBptomatic group 50 LUncomplicated malaria group 42 39 40 35 Severe malaria group 30 28 30 SI TY 18 20 15 ER 11 10 10 6 0 V 1 1 Clone N2 CIlones 3 Clones 4 Clones Number of distinct clones per infected child U Figure 4.5: Clonality of PN. falciparum infection amongst the three study groups. DA 94 A IB Percentage frequency of distinct clones per infected child 4.3 MSP-2 sequence diversity In order to explore the sequence diversity at the MSP-2 locus in isolates from this population, a total of 97 monoclonal infections that showed single fragment on gel electrophoresis were investigated across the three study groups. Sequences for MSP-2 gene were analyzed for FC27 allelic family from 46 isolates of P. falciparum which do not show multiclonal infection by gel electrophoresis of PCR product, as well as for 3D7 allelic fYamily from 51 isolates of P. falciparum that do not show multiclonal infection by gel electropRhoresis of PCR product. Sequence data from multiple sequence alignment using ClustalWA programme showed high sequence diversity in the MSP-2 gene characterized by Rsingle nucleotide substitutions, insertions and deletions (Fig. 4.6). In addition, there werIe Bboth synonymous and non-synonymous single nucleotide polymorphisms and proliferatio nLs of repeat units along the DNA sequence at the MSP-2 locus (Fig. 4.7). Y 4.3.1 MSP-2 sequence diversity in the FC27 allelic typeI TS The FC27 allelic type in this population Rhas two distinct subtypes and a hybrid sharing amino acid sequences from the two subtypesE. Subtype 1 (S1) consists of a 32-amino acid motif (96-bp unit) V which is also present in subtype 2, followed by a 12-amino acidI motif (36-bp unit) that is present in 3-7 copies (Fig. 4.8). SubtyUpe 2N (S2) consists of a slightly different 32-amino acid (96-bp) repeat unit that may be present in 2-3 copies followed by one cNopy of a 32-mer sequence that is identical to the one in subtype 1 (Fig. 4.8). The hybrid of tAhese subtypes has one copy of the 32 amino acid repeat unit seen in subtype 2 followed by aD copy of the 32-mer motif present in both subtypes 1 and 2 and then one copy of the 12 aBminAo acid repeat unit that is present in subtype 1 (Fig. 4.8). IAnalysis and comparison of the FC27 allelic type sequence at the nucleotide level showed several non-synonymous polymorphisms (Figure 4.7, 4.9). A G→A SNP at the first amino acid position of the 12-mer repeat motif seen in subtype 1 results in the synthesis of 95 Y Substitution on R TAC TCC CGC Repeat units deletion A underlined R B Y LI T I S R E IV N U Figure 4.6: Central region Aof tNhe polymorphic MSP-2 gene showing nucleotide sequence variations resulting from base substitution, deletions and differences in the copy number of repeat units. D 96 IB A RY RA B Long stretch of the GAA AGT I AAT TCA CGT TCA CCA CCC ATC ACT ACT ACA repeatsL encoding ESNSRSPPITTT ITY S R E NI V A variant of the repeat above U with the sequence AAA AGT AAT TCA CCT TCA CCA CCC ATC ACT ACT ACA encodes the amino acid KSNSPSPPITTT Figure 4.7: Portion of MS variation in the AP-2 gNene sequence showing nucleotide sequence diversity, non-synonymous polymorphisms and number of repeat unit. D 97 IB A Lysine (K) instead of Glutamic acid (E). Another non-synonymous polymorphism (C→G) at the th 5 amino acid position of the same 12-amino acid repeat unit leads to the synthesis of Arginine (R) instead of Proline (P). Likewise in subtype 2, a non-synonymous SNP (G→A) was observed at the last amino acid position of the 32-amino acid repeat motif resulting in the synthesis of Arginine (A) instead of Glycine (G) at that codon (Fig. 4.8). Furthermore, the 32-amino acid motif present in both subtype 1 and 2 are not identical. In subtype 1, the codon AGT encYoded rd Serine (S) at the 3 amino acid position of this motif while in subtype 2, a variant of Rthe codon (AGG) encoded Arginine (R) at the same position of the motif. The C-terminal porAtion (block 4) as well as the N-terminal region of the MSP-2 FC27 allelic types in the isolaRtes were however found to be relatively conserved (Fig. 4.9). The sequence variants of FBC 27 were distributed across the three study variants and no particular sequence was fou nLd toI be unique to a disease type. Y 4.3.2 MSP-2 sequence diversity in the 3D7 allelic type IT Analysis of the 3D7-type allele showRed eSxtensive intra-allelic sequence diversity resulting from amino acid substitutions espeEcially non-synonymous substitutions, deletions and repeat sequences .There were three subtyVpes of repetitive domains. These include the GSA-rich repeat unit, a TPA repeat motif and a Ipoly-Threonine (poly-T) stretch (Fig. 4.10). At the GSA domain, the common haplotypes inNclude GGSA which was present in 22% of the isolates that were sequenced, GGAS whi chU was present in 11% of the isolates, and a GASGSA which was present in 61% of the isoNlates sequenced. The GGSA if present was found in 1 to 4 copies, while the GGAS was usuaAlly found in 4 copies in the isolates for which it was present. The GASGSA was found in onDly one copy (Fig. 4.10). BThe A3-amino acid repeat motif having the sequence TPA was present in 1 to 7 copies in the paIrasite isolates having the 3D7 allelic type, except in one clone in which two non-synonymous polymorphisms led to the synthesis of PPV instead of TPA (Fig. 4.10). Four distinct haplotypes were found immediately preceding the TPA repeat domain. These haplotypes which consist of a 4-amino acid sequence include: GGSS (present in 33% of the sequenced isolates), 98 GGSR (present in 5% of the isolates sequenced), KSPS (present in 11% of the isolates) and RSPS (present in 50% of the isolates). Interestingly, the RSPS haplotypes was found to be significantly associated with multiple TPA repeat units (r = 0.89, P<0.001). The poly-Threonine repeat unit consists of 8 to 14 copies of Threonine. There were th however, single copies of Lysine (K) at the 6 amino acid position along this stretch in some isolates. It is not clear whether this is as a result of a non-synonymous mutation or an inseYrtion. Furthermore, the amino acid domain immediately after the poly-Threonine was Rrelatively conserved but this was soon punctuated by a polymorphic domain with lots of nonA-synonymous SNPs (Figure 4.10, 4.11). Meanwhile, no association was found between a pRarticular sequence variant of 3D7 and a specific disease category as the sequence variantsI wBere distributed across the three study groups. L SI TY ER IV U N N AD A IB 99 Y R RA LIB Y IT S Subtype 1 ER NI V Hybrid Subtype 2 U Figure 4.8: Multiple sequenAce alNignment of the FC27 allelic type of the MSP-2 gene showing intra-allelic variations along the central repDeat region. Upper panel shows DNA sequence while the lower panel shows amino acid sequence. 100 BAI Y R BR A I L Y T I S R IV E N U Figure 4.9: Central region Aof MSNP-2 gene showing conserved amino acid sequences at the C-terminal region of the FC27-type allele. D 101 BAI Y R A R B LI GSA-rich repeat unit Y GGSA haplotype GGAS haplotype TPA repeats GASGSA T Poly-Threonine haplotype I repeats S R E NI V U Figure 4.10: Multiple sequence alNignment of the 3D7 allelic type of the MSP-2 gene showing intra-allelic sequence diversity along the centralD repeaAt region. Upper panel shows DNA sequence while the lower panel shows amino acid sequence. 102 IB A Y R RA IB L ITY RS E V I N Figure 4.11: Central region of MSP-2 ge neU showing partially conserved sequences at the C-terminal region of the 3D7-type allele. AND 103 BAI 4.4 IL-18 gene Promoter Polymorphisms Genetic polymorphisms at the promoter region of IL-18 gene were determined for three previously described positions: -656 G/T, -607 C/A and -137 G/C, relative to the transcription start site as shown in Figure 3.2. All the three single nucleotide polymorphisms (SNPs) were present in the study population. The distribution of the allele and genotype frequencies for the three SNPs in the three study groups are shown in Table 4.5. Y Chi-square test for compatibility with the Hardy-Weinberg equilibrium showeRd that the genotype frequencies did not deviate from the Hardy-Weinberg equilibrium (TaAble 4.5). The -656 G/T and -607 C/A loci were found to be in complete linkage disequiliRbrium in the three 2 study groups (r =1). The frequency of the -656 G/T and -607 C/A alLleleIsB were not significantly different between the asymptomatic control and the severe malaria g roup (P>0.05). However, the genotype frequency of -607AA was significantly higher in the YAS group compared to SM cases (P<0.05; OR=1.68, 95% CI=0.95-3.04). Likewise, there wIaTs a statistically significant difference in the distribution of genotype frequencies at the -S137 G/C loci between the asymptomatic control and severe malaria group (P=0.044), withR a higher prevalence of the CC genotype in the severe malaria group (Table 4.5). E The electrophoretic pattern of thIeV 1370bp PCR product for the IL-18 promoter is shown in Figure 4.12. The electropherogNram showing the genotype variants of the three SNPs are presented in Figures 4.13 - 4. 15U. N 4.5 IL-18RαD genAe and Promoter Polymorphisms BFortAy samples were selected at random from the asymptomatic group for DNA sequenIcing in order to determine polymorphic sites at the promoter region as well as the coding region of the IL-18Rα gene. The results showed the presence of conserved as well as polymorphic sequences across the length of the IL-18Rα gene, including sequences at the promoter region. Only variants in the promoter and coding regions of IL-18Rα gene, having 104 frequencies greater than 1 percent (0.01) were considered and genotyped in the three study groups. Three single nucleotide polymorphisms were identified at the promoter region: -661 T/C, -175 G/A and -93 C/T relative to the transcription start site as shown in Figure 4.13. A synonymous polymorphism, which is a silent mutation that does not result in amino acid substitution in the transcribed cDNA, was found in Exon 1 of the IL-18Rα gene. This YSNP consists of a C-to-G transition (CCC→CCG) that both results in the synthesis of ProlRine at the th 7 7 7 amino acid position [Pro →Pro (P7P)]. A Exons 2 to 11 were also investigated for sequence variants. Except forR Exon 7, all other Exons were highly conserved in the study population. A synonymousL SNIPB or silent mutation was found in Exon 7, which consists of a C-to-T transition (TTC→T TT) that both results in the st 21 21 synthesis of Phenylalanine at the 21 amino acid position [Phe Y→Phe (F21F)]. IT 4.5.1 Distribution of genotype variants in IL-18RRα Sgene promoter The allele and genotype frequencies Efor the -661 T/C, -175 G/A and -93 C/T SNPs are shown in Table 4.6. The distributionsI oVf the observed genotypes for the -175 G/A were in conformity with the expected disNtribution when tested for the Hardy-Weinberg equilibrium. Although the distributions of tUhe -661 T/C and -93 C/T genotypes showed no deviation from the Hardy-Weinberg equilibNrium in the asymptomatic and uncomplicated malaria group, the distributions in the Asevere malaria group displayed a significant departure from the Hardy-2 2Weinberg equilDibrium (χ = 8.21, P<0.01; χ = 5.94, P<0.05) for the -661 T/C and -93 C/T genotypes rAespectively. Furthermore, there were decreases in the observed genotypes for heterozyBgotes in the severe malaria group compared to the expected value for both the -661 T/C and -9I3 C/T polymorphic loci. Further analysis to compare the distribution of genotype frequencies at the -661 position of the IL-18Rα gene in severe malaria group with the asymptomatic group showed that both the 105 CC and TT homozygotes were significantly higher in the severe malaria group compared to the asymptomatic group (P<0.05 and P<0.05 respectively). There was however, a significantly lower frequency of heterozygotes (CT) in the severe malaria group compared to the asymptomatic group which suggests a protective role for the IL-18Rα -661CT genotype (OR=2.06, 95% CI: 1.02-4.16, P<0.01). However, allele frequencies were not statistically different among the three study groups (P>0.05). Y Similar trend was observed for the distribution of IL-18Rα -93C/T genotypeR where a significantly higher frequency of both homozygotes (CC and TT) were observedA in the severe malaria group compared to the asymptomatic group (P<0.05 and P<0.05 Rrespectively). The frequency of the heterozygotes (CT) was however, significantly lower Bin the severe malaria group compared to the asymptomatic control group (P=0.032). The eLlectIrophoretic separation of the 1409bp PCR products comprising the promoter region andY Exon 1 of the IL-18Rα gene is shown in Figures 4.16. Furthermore, the electropherogram showing the genotype variants of the three SNPs are shown in Figures 4.17-4.19. IT RS 4.5.2 Distribution of promoter (AC)n reVpeaEts among the study groups An adenine-cytosine (AC)n NrepeIat polymorphism was found in the promoter region at the -430 position upstream of thUe transcription start site of the IL-18Rα gene. The frequency distribution of the (AC)n rep eat among the three study groups are presented in Table 4.5. Chi- square test for conformitNy with the Hardy-Weinberg equilibrium showed that distributions of the observed genotypes Awere in conformity with the expected distribution across the three study groups. D IThe Adistribution of the number of AC repeats was trimodal, with one peak having seven (AC)7 rBepeats, the second peak having eight (AC)8 repeats and the third being heterozygous for (AC)7 and (AC)8. The common number of repeats was (AC)7 in all the three groups. However, the distribution of (AC)8 was higher in the asymptomatic group compared to the two clinical 106 cases though this did not reach a statistically significant level (P> 0.05). The electropherogram showing variants of the (AC)n repeats are shown in Figures 4.20. AR Y BR Y LI T RS I E IV U N DA N A IB 107 Table 4.5 Genotype and allele frequencies of IL-18 -656G/T, -607 C/A, -137G/C Asymptomatic Control Uncomplicated Malaria Severe Malaria Locus n= 161(%) n= 160(%) n= 116(%) IL18 -656G/T GG 75(46.58) 79(49.37) 63(54Y.31) TG 67(41.62) 66(41.25) 4R4(37.93) TT 19(11.80) 15(9.38) A 9(7.76) G allele 0.674 0.700 0.733 T allele 0.326 0.300 R 0.267 2 2 2 *HWE (χ = 0.28, P=0.59) (χ = 0.03, P=0.85) I B (χ = 0.11, P=0.74) L IL18 -607C/A Y AA 19(11.80) 15(9.38) T 9(7.76) AC 67(41.62) 66(4S1.25I) 44(37.93) CC 75(46.58) 79(49.37) 63(54.31) A allele 0.326 E R 0.300 0.267 C allele 0.674 I V 0.700 0.733 2 2 2 *HWE (χ = 0.28, P=0.5N9) (χ = 0.03, P=0.85) (χ = 0.11, P=0.74) IL18 -137G/C U CC N5(3.11) 4(2.50) 6(5.17) GC A 40(24.85) 43(26.88) 31(26.72) GG D 116(72.05) 113(70.63) 79(68.10) G alleleA 0.845 0.841 0.815 CI aBllele 0.155 0.159 0.185 2 2 2 *HWE (χ = 0.45, P=0.50) (χ = 0.01, P=0.97) (χ = 1.54, P=0.22) *HWE= Hardy-Weinberg equilibrium 108 Table 4.6 Genotype and allele frequencies of IL-18Rα -661T/C, -175G/A, -93C/T and (AC)n repeats. Asymptomatic Control Uncomplicated Malaria Severe Malaria Locus n= 161(%) n= 160(%) n= 116(%) IL18Rα -661T/C CC 8(4.97) 10(6.25) 14(12.07) CT 72(44.72) 63(39.38) 33(28.45) TT 81(50.31) 87(54.38) 69(59Y.48) C allele 0.273 0.259 0R.263 T allele 0.727 0.741 2 2 A 0.737 2 *HWE (χ = 2.55, P=0.11) (χ = 0.10, P=0.75) R (χ = 8.21, P=0.004) IL18Rα -175G/A IB AA 2(1.24) 0(0) L 0(0) AG 30(18.64) 20(12.50) Y 14(12.07) GG 129(80.12) 140(87.50) 102(87.93) A allele 0.106 0.063 T 0.060 G allele 0.894 0.937S I 0.940 2 2 2 *HWE (χ = 0.03, P=0.86) (χ =R 0.71, P=0.40) (χ = 0.48, P=0.49) IL18Rα -93C/T CC 93(57.76) 1E03(64.38) 78(67.24) CT 62(38.51) I V 51(31.88) 29(25.00) TT 6(3.73) 6(3.75) 9(7.76) C allele 0.770 U N 0.803 0.797 T allele 0.230 0.197 0.203 2 2 2 *HWE (χ = 1.24N, P=0.27) (χ = 0.01, P=0.92) (χ = 5.94, P=0.015) IL18Rα (AC)n A (AC)7 D 77(47.8) 95(59.4) 64(55.2) (AC)7/8 74(46.0) 55(34.4) 44(37.4) (AC)8B A 10(6.2) 10(6.3) 8(6.9) 2 2 2 *HWE I (χ = 2.012, P=0.156) (χ = 0.285, P=0.594) (χ = 0.014, P=0.907) *HWE= Hardy-Weinberg equilibrium 109 (a) M 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 M 1,500bp 600bp 200bp RY RA LIB M 2 3 4 5 6 7 8 9 10 11 12I 1T3 1Y4 15 16 17 M (b) 2,000bp 1,000bp 500bp RS E IV U N N Figure 4.12: AgaroAse gel electrophoresis of IL18 gene promoter region showing ~1370bp of P AD CR product. (a) PCR pBroduct before purification; Lane M: 100-bp ladder. Lanes 2-19: DNA fragment of study participants (b) PCRI product after purification for sequencing PCR; Lane M: 150-bp ladder. Lanes 2-17: DNA fragment of study participants. 110 (a) RY (b) A R LIB ITY (c) S E R IV U N N Figure 4.13: DDNAA sequence electropherogram showing the IL18 -656 G/T promoter Apolymorphism. The locIatBions of base substitution are highlighted in shaded boxes. (a) Homozygous IL18 -656 GG (b) Heterozygous IL18 -656 G/T (c) Homozygous IL18 -656 TT. Sequences were done using the forward primer. 111 (a) Y (b) R A R LIB ITY (c) S ER IV N U Figure 4.14: DNAA seNquence electropherogram showing the IL18 -607 C/A promoter pDolymorphism. The locatBions Aof base substitution are highlighted in shaded boxes. (a) Homozygous IL18 -607 CC (b) Heterozygous IL18 -6I07 C/A (c) Homozygous IL18 -607 AA. Sequences were done using the forward primer. 112 (a) Y (b) AR BR Y LI T SI (c) ER IV U N AN D Figure B4.15A: DNA sequence electropherogram showing the IL18 -137 G/C promoter I polymorphism. The locations of base substitution are highlighted in shaded boxes. (a) Homozygous IL18 -137 GG (b) Heterozygous IL18 -137 G/C (c) Homozygous IL18 -137 CC. Sequences were done using the forward primer. 113 (a) 1,500bp M 2 3 4 5 6 7 8 9 M 11 12 13 14 15 16 17 18 19 M 600bp RY A 100bp LIB R Y IT (b) S 1,500bp 1,200bp M 2 3 4 5 6 7 8 9E 10R 11 12 13 14 15 16 M 600bp IV N 200bp N U A Figure 4.16A: ADgarose gel electrophoresis of IL18Rα Exon 1 showing ~1409bp of PCR product. IB (a) PCR product before purification (b) PCR product after purification for sequencing PCR Lane M: 100-bp ladder. Lanes 2-19: DNA fragment of study participants 114 (a) Y (b) R BR A LI ITY (c) RS E IV N N U Figure 4.17: DDNAA sequence electropherogram showing the IL18Rα -661T/C polymorphism. The locationsA of base substitution are highlighted in shaded boxes (a) Homozygous IL18Rα -661TT (b) HeterozIyBgous IL18Rα -661T/C (c) Homozygous IL18Rα -661CC. Sequences were done using the forward primer. 115 (a) Y R A (b) BR LI SI TY (c) R IV E UN N Figure 4.18: DDNAA sequence electropherogram showing the IL18Rα -175G/A polymorphism. The locationsA of base substitution are highlighted in shaded boxes. (a) Homozygous IL18Rα -175GG (b) HeterozIyBgous IL18Rα -175G/A (c) Homozygous IL18Rα -175AA. Sequences were done using the reverse primer. 116 (a) (b) AR Y R LI B (c) ITY S ER IV UN Figure 4.19: DNA sequNenc e electropherogram showing the IL18Rα -93C/T polymorphism. The locations of base Asubstitution are highlighted in shaded boxes. (a) Homozygous IL18Rα -93CC (b) Heterozygous IL18DRα -93C/T (c) Homozygous IL18Rα -93TT. Sequences were done using the reverse primer. BA I 117 (a) Y R (b) A BR LI ITY RS (c) E IV U N N Figure 4.20: DDNAA sequence electropherogram showing the IL18Rα -430 A/C microsatellite Arepeats. The loIcaBtions of repeat variants are highlighted in shaded boxes (a) Homozygous IL18Rα -430 (AC)7 (b) Heterozygous IL18Rα -430 (AC)7/8 (c) Homozygous IL18Rα -430 (AC)8. Sequences were done using the forward primer. 118 4.5.3 Distribution of Exon 1 and Exon 7 genotypes The allele and genotype frequencies for Ex1 +21 C/G are presented in Table 4.7. Chi- square test for conformity with the Hardy-Weinberg equilibrium showed that the genotype frequencies did not deviate from the Hardy-Weinberg equilibrium. Distribution of the heterozygous genotype CG was higher in the severe malaria group (12%). There was no statistically significant difference in the distribution of the Ex1 +21 C/G genotypes betweeYn the three study groups. The electrophoretic separation of the 1409bp PCR products of ExoRn 1 which also included the promoter region is shown in Figure 4.16. The electropherogramA showing the genotype variants of the polymorphisms in Exon 1 are shown in Figure 4.21. R For the Exon 7 polymorphism, the allele and genotype freq uLencIie Bs of the Ex7 +63 C/T are presented in Table 4.7. The distributions of the observed genotypes for the Ex7 +63 C/T were in conformity with the expected distribution when tested for tYhe Hardy-Weinberg equilibrium. The CC genotype was higher in the severe malariaI Tgroup (87.1%) compared with the asymptomatic group (73.9%) or the uncomplicated mSalaria group (74.4%), though this was not statistically significant. There was however, Ra statistically significant difference in the distribution of the heterozygotes with signifEicantly lower CT genotypes in the severe malaria 2 group (OR=0.72, 95% CI: 0.51-1.02, χI=V 4.795, P<0.05). The electrophoretic separation of the 410bp PCR products of Exon 7 is shown in Figure 4.22, while the electropherogram showing the genotype variants of polymorpUhismNs in Exon 7 are shown in Figure 4.23. 4.5.4 Report of conserNved Exons 2-6, 8-11 Exons 2D-6, 8A-11 were found to be conserved in the study population as no SNP was discovered Ain those coding sequences. The electrophoretic separation of PCR products and multipleB alignments showing sequence conservation for Exons 2, 3, 4, 5, 6, 8, 9, 10 and 11 are shownI in Figures 4.24-4.41. 119 Table 4.7: Genotype and allele frequencies of IL-18Rα Ex1 +21C/G and Ex7 +63C/T Non-Symptomatic Control Uncomplicated Malaria Severe Malaria Locus n= 161(%) n= 160(%) n= 116(%) IL18Rα Ex1 +21C/G CC 144(89.44) 138(86.25) 101(87.07) CG 17(10.56) 19(11.88) 15(12.93) Y GG 0(0) 3(1.88) 0A(0) R G allele 0.053 0.078 0.065 C allele 0.947 0.922 0.935 2 2 2 *HWE (χ = 0.50, P=0.48) (χ = 4.93, P=0.03) I B(χ = R 0.55, P=0.46) IL18Rα Ex7 +63C/T L CC 119(73.9) 119(74.4) T Y 92(87.07) CT 40(24.9) 41(25.6)I 24(12.93) TT 2(1.2) 0(0) 0(0) C allele 0.863 0.8S72 0.897 T allele 0.137 R 0.128 0.103 2 2 2*HWE (χ = 0.452, P=0.501) E (χ = 3.455, P=0.06) (χ = 1.544, P=0.214) V *HWE= Hardy-Weinberg equilibrium I UN DA N A IB 120 (a) AR Y (b) LIB R Y I T (c) S ER NI V U Figure 4.21: DNA seNquence electropherogram showing the IL18Rα Ex1 +21C/G polymAorphism. D The locationsA of base substitution are highlighted in shaded boxes. (a) Homozygous IL18Rα +21CC (b) HeterozIyBgous IL18Rα+21G/C (c) Homozygous IL18Rα +21 GG. This synonymous polymorphism is a silent mutation that does not result in amino acid substitution in the transcribed cDNA. Sequences were done using the reverse primer. 121 (a) M 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 M 1,500bp 600bp 100bp RY BR A (b) I 1,500bp M 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 M L 1,200bp 600bp Y 200bp T RS I VE I Figure 4.22: Agarose gel electropNhoresis of IL18Rα Exon 7 showing ~410bp of PCR product. (a) PCR product beUfore purification (b) PCR product after purification for sequencing PCR Lane M: 10N0-bp ladder. Lanes 2-19: DNA fragment of study participants AD A IB 122 (a) RY (b) RA B LI ITY (c) S ER NI V U Figure 4.23: DNA seNquence electropherogram showing the IL18Rα Ex7 +63C/T polymAorphism. D The locationsA of base substitution are highlighted in shaded boxes. (a) Homozygous IL18Rα Ex7 +63CC (b) HeterozIyBgous IL18Rα Ex7 +63CT (c) Homozygous IL18Rα Ex7 +63TT. This synonymous polymorphism is a silent mutation that does not result in amino acid substitution in the transcribed cDNA. Sequences were done using the forward primer. 123 a) M 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 M 1,500bp 600bp 100bp Y R RA b) M 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16I B17 M 1,500bp 1,200bp L 600bp ITY 200bp S ER IV N U N A Figure 4.24A: ADgarose gel electrophoresis of IL18Rα Exon 2 showing ~525bp of PCR product. B (a) PCR product before purification (b) PCR product after purification for sequencing PCR I Lane M: 100-bp ladder. Lanes 2-18: DNA fragment of study participants 124 Y AR LIB R ITY ER S IV U N N AD A IB 125 a) M 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 M 1,500bp 600bp 100bp Y RA R B b) M 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 I 18 19 M 1,500bp 1,200bp L 600bp Y 200bp SI T VE R NI U AN Figure 4.26A: ADgarose gel electrophoresis of IL18Rα Exon 3 showing ~415bp of PCR product. B (a) PCR product before purification (b) PCR product after purification for sequencing PCR I Lane M: 100-bp ladder. Lanes 2-19: DNA fragment of study participants 126 Y AR LIB R ITY ER S IV U N N AD A IB 127 a) M 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 M 1,500bp 600bp AR Y 100bp R B b) I 1,500bp M 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 M L1,200bp 600bp Y IT 200bp RS E IV UN AN Figure 4.28A: ADgarose gel electrophoresis of IL18Rα Exon 4 showing ~285bp of PCR product. B (a) PCR product before purification (b) PCR product after purification for sequencing PCR I Lane M: 100-bp ladder. Lanes 2-19: DNA fragment of study participants 128 Y AR LIB R ITY ER S IV U N N AD A IB 129 a) M 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 M 1,500bp 600bp Y R 100bp A IB R b) M 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 M 1,500bp L1,200bp 600bp Y T 200bp I ER S NI V U N A Figure 4.30A: ADgarose gel electrophoresis of IL18Rα Exon 5 showing ~350bp of PCR product. B (a) PCR product before purification (b) PCR product after purification for sequencing PCR I Lane M: 100-bp ladder. Lanes 2-18: DNA fragment of study participants 130 Y AR LIB R ITY ER S IV U N N AD A IB 131 a) M 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 M 1,500bp 600bp Y 100bp R A IB R M 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 M 1,500bp b) L 1,200bp 600bp Y T 200bp I S ER IV N N U A Figure 4.32A: ADgarose gel electrophoresis of IL18Rα Exon 6 showing ~240bp of PCR product. B (a) PCR product before purification (b) PCR product after purification for sequencing PCR I Lane M: 100-bp ladder. Lanes 2-18: DNA fragment of study participants 132 Y AR LIB R ITY ER S IV U N N AD A IB 133 a) M 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 M 1,500bp 600bp 100bp AR Y R B I L b) M 2 3 4 5 6 7 8 9 10 11 12 13 14 15Y 16 17 M 1,500bp T I 600bp S 100bp VE R NI N U A D A FigurIe B4.34: Agarose gel electrophoresis of IL18Rα Exon 8 showing ~280bp of PCR product. (a) PCR product before purification (b) PCR product after purification for sequencing PCR Lane M: 100-bp ladder. Lanes 2-17: DNA fragment of study participants 134 Y RA R B Y LI IT RS VE UN I AN AD IB 135 a) M 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 M 1,500bp 600bp 100bp Y RA R b) B M 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 L 18 I19 M 1,500bp 1,200bp 600bp Y 200bp IT RS E IV U N Figure 4.36: AgaroANse gel electrophoresis of IL18Rα Exon 9 showing ~370bp of PCR product. (aD) PCR product before purification (b) PCR product after purification for sequencing PCR ALane M: 100-bp ladder. Lanes 2-19: DNA fragment of study participants IB 136 Y AR LIB R ITY ER S IV U N N AD A IB 137 a) M 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 M Y 1,500bp R 600bp A R 100bp B LI Y M 2 3 4 5 6 7 8 9 10 11 12I T13 14 15 16 17 M b) 1,500bp 1,200bp S 600bp R 200bp E IV UN AN D FigurIe B4.38 A: Agarose gel electrophoresis of IL18Rα Exon 10 showing ~402bp of PCR product. (a) PCR product before purification (b) PCR product after purification for sequencing PCR Lane M: 100-bp ladder. Lanes 2-18: DNA fragment of study participants 138 Y AR LIB R ITY ER S IV U N N AD A IB 139 a) M 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 M 1,500bp 600bp Y R 100bp RA B Y LI T SI M 2 3 4 5 6 7 8 9 10 R 11 12 13 14 15 16 17 18 19 M b) 1,500bp 1,200bp E 600bp IV 200bp U N DA N Figure B4.40AI : Agarose gel electrophoresis of IL18Rα Exon 11 showing ~750bp of PCR product. (a) PCR product before purification (b) PCR product after purification for sequencing PCR Lane M: 100-bp ladder. Lanes 2-19: DNA fragment of study participants 140 RY RA LI B TY RS I VE NI U AN AD B FigurIe 4.41: Multiple alignment of Exon 11 sequences showing conservation to reference standard (shaded in black) when identities were plotted as dot to the reference standard. 141 4.6 TNF-α gene Promoter Polymorphisms -308G/A and -238G/A Genetic polymorphisms at the promoter region of TNF-α gene were determined for two previously reported variants: -308G/A and -238G/A relative to the transcription start site. Variants at these loci were found in the study population. The distribution of the allele and genotype frequencies for the -308G/A and -238G/A SNPs are shown in Table 4.8. The electrophoretic pattern of the PCR product spanning 832bp upstream of the transcriptionY start site of TNF-α gene is shown in Figure 4.42. R The most common genotype in the study population for the TNFα -A308 locus is homozygote GG. The AA homozygote genotype was not found in any oIf Bthe s Rtudy groups. Chi- square test for compatibility with the Hardy-Weinberg equilibriumL showed that the genotype frequencies did not deviate from the Hardy-Weinberg equilibrium (T able 4.8). No difference was also found in the distribution of the heterozygotes GA withinY the study groups (P>0.05). The electropherogram showing the genotype variants of the TNIFTα -308 are presented in Figures 4.43 Similarly, the GG genotype was the most commSon amongst the three study groups for the TNFα -238 locus. When tested for conformity wiRth the Hardy-Weinberg equilibrium, Chi-square analysis showed that the observed genotVypesE were not statistically different from the expected genotypes. The homozygote AA genoItype was also not detected in the study population. No association was found between theN allele and genotype distribution and disease outcome. The electropherogram showing th e Ugenotype variants of the TNFα -238 are presented in Figures 4.44 DA N BAI 142 Table 4.8: Genotype and allele frequencies of TNFα -308G/A and -238G/A Asymptomatic Control Uncomplicated Malaria Severe Malaria Locus n= 161(%) n= 160(%) n= 116(%) TNFα -238G/A Y GG 133(82.61) 128(80.0) 90(77.59)R GA 28(17.39) 32(20.0) 26(22A.41) AA 0(0) 0(0) R 0(0) G allele 0.896 0.824 B 0.786 A allele 0.104 0.176 I 0.214 2 2 2 *HWE (χ = 1.46, P=0.23) (χ = 1.98, P=0.16) Y L (χ = 1.85, P=0.17) TNFα -308G/A IT GG 135(83.85) 130S(81.25) 87(75.0) GA 26(16.15) R 30(18.75) 29(25.0) AA 0(0.62) E 0(1.25) 0(3.45) G allele 0.904 V 0.894 0.836 A allele 0.096 I 0.106 0.164 2 2 2 *HWE (χ = 1.24, PU=0.2 N7) (χ = 1.71, P=0.19) (χ = 2.37, P=0.12) N *HWE= Hardy-DWeinAberg equilibrium BA I 143 M 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 M (a) 1,500bp 600bp 200bp Y R BR A I M 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 L M (b) 1,500bp 1,200bp 600bp ITY 200bp S R VE I U N N Figure 4.42: ADgaroAse gel electrophoresis of TNF-α promoter region showing ~832bp of PCR Aproduct. B (a) PCR product before purification (b) PCR product after purification for sequencing PCR I Lane M: 100-bp ladder. Lanes 2-19: DNA fragment of study participants 144 (a) RY BR A I (b) L ITY S VE R I N U N Figure 4.43: DDNAA sequence electropherogram showing the TNFα -308G/A polymorphism. The locatBions Aof base substitution are highlighted in shaded boxes (a) Homozygous TNFα -308GG (b) Heterozygous TNFα -I308GA. Sequences were done using the forward primer. 145 (a) Y R RA IB L (b) Y IT RS VE I UN Figure 4.44: DNAA sequNence electropherogram showing the TNFα -238G/A polymorphism. The locations of baDse substitution are highlighted in shaded boxes (a) Homozygous TNFα -238GG (b) Heterozygous TNFα -238GAA. Sequences were done using the forward primer. IB 146 CHAPTER FIVE DISCUSSION The clinical outcome of an asymptomatic infection leading to severe disease and death has been shown to depend upon complexity of “many parasite, host, geographic and social factors” (Miller et al., 2002; Rao et al., 2012). Host-parasite interactions in malaria have led to a host's relative resistance to the parasite and parasite strain-specific susceptibility or RviruYlence (Becker et al., 2004; Grech et al., 2006; Williams, 2009). Malarial parasites have co-evolved together with the human host for thousands of years (Kwiatkowski, 2005), which Ahave led them to constitute an important driving evolutionary force behind common erIythroc Ryte variants, such as sickle-cell disease, thalassaemia, and G6PD gluose-6-phosphateL defiBciency (Kwiatkowski, 2000; Koella and Boete, 2003; Kwiatkowski, 2005; Komba et a l., 2009; Driss et al., 2011; Ferreira et al., 2011). These genetic variants have been aTssocYiated with resistance to malaria. Similarly, the level of antigenic diversity of P. falciparuIm populations in an area is likely to affect acquisition of immunity to malaria (Farnert et Sal., 2009). Therefore, the understanding of the genetic structure of parasite population isR necessary for planning of malaria control interventions. E IV 5.1 Genetic Polymorphisms ofN P. falciparum MSP-2 alleles In malaria endemic r eUgions, it is now well established that infected individuals carry several complex mixtureN of parasite clones with different genetic and phenotypic characteristics (Babiker et al., 199A7; Missinou et al., 2000; Muller et al., 2001; Kang et al., 2010). This is particularly trueD in Africa especially south of the Sahara, where studies have shown that considerableA genetic diversity exists (Missinou et al., 2000; Auburn et al., 2012; Koukouikila- KoussIoBunda et al., 2012). This phenomenon appears to be important for the development of an efficient anti-malarial immunity which requires continuous exposure to a large number of parasite variants and malaria antigens. However, the parasites‟ genetic profile has not been systematically documented in several parts of Nigeria. This aspect of the study therefore, 147 investigated the genetic complexity and allelic diversity of P. falciparum parasites in children presenting with mild malaria, severe malaria and asymptomatic infection from north-central Nigeria. In this study, a high genetic diversity of P. falciparum isolates was observed in the study population. This was reflected in the number of alleles found in each group studied (32, 35 and 28 for asymptomatic, mild and severe malaria respectively). This is consistent with data Yfrom other areas with high malaria transmission such as in north-eastern Tanzania (MageRsa et al., 2002), in Papua New Guinea (Fluck et al., 2007), Ghana (Falk et al., 2006b), Côte Ad'Ivoire (Silue et al., 2006) and Congo Brazzaville (Mayengue et al., 2011). Analysis ofR allele prevalence revealed interesting trends. A higher prevalence of 3D7 allelic tyIpBe was found in the symptomatic groups, 51% for uncomplicated malaria and 54% for sLevere malaria compared to 38% found in the asymptomatic malaria group. Likewise, FC27 alle lic types were more frequent in the asymptomatic group compared to the symptomatic grouYps. This may probably indicate a higher risk of developing symptomatic malaria with iSncreIas Ting carriage of isolates belonging to the 3D7 allelic family. R This observation is consistent with Ereports concerning clinical isolates from Senegal (Robert et al., 1996) as well as south-wesVtern Nigeria (Amodu et al., 2008). Similarly, in eastern Sudan, the FC27 genotype was nNotedI to be over-represented in subjects with asymptomatic infections comparable to whUat was found in the present study (A-Elbasit et al., 2007). Conversely, reports from oth er studies including north-eastern Tanzania (Magesa et al., 2002), Benin (Issifou et al., 20N01) and Gabon (Aubouy et al., 2003; Issifou et al., 2003), showed no evidence for associaAtion between a particular genotype and clinical outcome. The present result also contrasts wDith the observations made in Papua New Guinea where MSP-2 FC27 alleles were found toB beA associated with clinical malaria (Engelbrecht et al., 1995). However, the FC27 data from tIhis study are compatible with the observation of a higher prevalence of FC27 allelic types in asymptomatic carriers in Senegal (Ntoumi et al., 1995). In eastern Sudan, the genetic diversity of the parasite population was very high with 51 different genotypes (A-Elbasit et al., 2007). 148 In the Sudan study, it was found that the ratio of the 3D7 to FC27 allele between SM and UM was comparable which is similar to what was found in the present study in Lafia. Furthermore, they noted that the FC27 genotype was overrepresented in subjects with asymptomatic infection (A-Elbasit et al., 2007) comparable to what was found in the present study. Moreover, in an earlier study conducted in south-west Nigeria, the absence of FC27 alleles was found to be significantly associated with a 3.58-fold (95% CI = 2.0-7.3) increased risk of developing uncomplicated malaria and a 5.9-fold (95% CI = 2.2-9.6) increased riYsk of developing severe malaria (Amodu et al., 2008). There is need therefore, for a largRer, multi- regional study to be conducted in order to ascertain whether the discrepaAncies reflect geographical differences in parasite populations or a genuine tendency for 3D7R allelic types to be associated with clinical malaria. LIB Data on monoclonal infections in this study showed thYat m ultiplicity of infections and polyclonality was generally high in the asymptomatic as IwTell as uncomplicated malaria group. Multiplicities of infections were 2.1 and 2.0 on thSe average per infected individual in the asymptomatic group and uncomplicated malaria group respectively. On the average, majority of participants in the asymptomatic as well as EuncRomplicated malaria group, were infected with more than one parasite genotype with polyclonality being 61% and 60% for asymptomatic and uncomplicated malaria respectively, whIilVe monoclonal infections were predominant in the severe malaria group as polyclonality wasN only 34%. A similarly high degree of multiple infections per infected individual with sym pUtomatic malaria has been demonstrated in other areas of Africa with high malaria transmNission such as in Senegal (Ntoumi et al., 1995), Tanzania (Beck et al., 1997), Cameroon (Basco and Ringwald, 2001) as well as the Republic of Congo (Mayengue et al., 2011). DA BOn Athe contrary, in regions of low intensity of malaria transmission such as Pahang, MalayIsia a low multiplicity of infection (average of 1.2 per infected individual) has been reported in uncomplicated malaria, probably reflecting the transmission intensity of the area (Atroosh et al., 2011). In the severe malaria group in the present study however, multiplicity of infection was significantly low (1.3). It is presumable that multiplicity of infections could be a 149 molecular marker for severe malaria since children in the severe malaria group had a very low, statistically significant multiplicity of infection (P<0.001) and polyclonality (P<0.001) compared to the asymptomatic or uncomplicated malaria groups. Moreover, limited parasite diversity in severe malaria subjects is consistent with data from other studies (Milner et al., 2012). Although the number of parasite types harboured was different between uncomplicated and severe malaria groups, there was a trend for reverse relationship between parasite deYnsity and complexity: severe malaria isolates had higher parasite density than mild malariaR samples, yet their multiplicity of infection was lower. It is possible that severe malaAria would be associated with high parasite density, resulting from overwhelming multiplicRation of a limited number of clones, while mild malaria would be caused by a large numbeBr of clones reaching a lower density, most of which were previously not exposed to. IndeeLd thIere are indications that the diversity of asymptomatic P. falciparum infections eviYdent in the high multiplicity of infection, contribute to protective malaria immunity in children in an area of perennial transmission (Bereczky et al., 2007). SI T It is obvious then that the genetic complexRity of P. falciparum and in particular its ability to generate mutant variants, makes it a succesEsful pathogen. Studies on the genetic complexity of P. falciparum infections therefore haveV wide variety of application including distinguishing between new infections and recruNdescIence in drug trials as well as the assessment of other control intervention studies suUch as vaccine trials and the use of insecticide treated bed nets. Genotyping of the MSP-2 gene is a widely used protocol for epidemiological surveys investigating the geneticN diversity of P. falciparum populations (Contamin et al., 1995; Babiker et al., 1998; Kang etA al., 2010; Mwingira et al., 2011) or the effect of interventions on surviving parasites (Beck Det al., 1997; Snounou and Beck, 1998; Takala and Plowe, 2009; McCarthy et al., 2011) bBecauAse it has been demonstrated that MSP-2 gene polymorphism is extensive within naturaIl parasite populations (Felger et al., 1994; Meyer et al., 2002; Happi et al., 2004; Ghanchi et al., 2010; Hussain et al., 2011). One factor that might potentially compromise a comparison of genotypic characters of isolates collected from patients experiencing a clinical episode is uncontrolled drug intake before 150 presentation to the hospital. In Africa, majority of malaria cases occur in rural areas with considerable variation in the treatment seeking pattern and over 50% are self treatment at home (Hamel et al., 2001; Muller et al., 2003). Likewise, pre-hospital antimalarial treatment of febrile children has been reported to be a common practice among child care-givers in Nigeria (Mockenhaupt et al., 2000; Ajayi and Falade, 2006; Orimadegun et al., 2008). Since most malaria cases are first treated at home as fevers, a plausible reason for the observed reduced genotypes in the severe malaria group might be the clearance of susceptible clones as a resYult of self medication. So the resistant strains that have survived the scourge of treatment, Rwith their high propagative ability probably became more virulent to cause severe diseasRe (OAlumese et al., 2002). B Other probable explanations for the reduced multiplicity of infLectiIon in the severe malaria group include: (i) the likelihood of an artefact caused by single dom inant clones diluting the PCR template of low-density co-infections (Smith et al., 1999b) sinYce at high ratios of template, rare clones are not amplified (Contamin et al., 1995); (iSi) liIk Tely consequence of the anti-parasite effect of the cytokines released during fever or oRf fever itself on the parasite populations (Smith et al., 1999c). VE 5.2 Sequence diversity of P. faNlcipaIrum MSP-2 gene Although results from Uthis study showed a high complexity of infection determined by gel electrophoresis of neNsted PCR product, the possibility that PCR product of a given size could compromise variantAs with subtle differences in DNA sequence or arrangement of their amino acids could not Dbe disregarded. To assess the pattern of sequence diversity in the P. falciparum MSP-2 geneA, nucleotide sequences of 97 PCR positive samples that show single band by gel electropBhoresis of PCR product were determined. Sequence analysis of the central region of MSP-2I gene showed a high allelic diversity even at the level of intra-allele type. Therefore, genetic diversity of alleles in this region might be far higher than that reported from the results of gel electrophoresis. 151 Data from this study showed that there were mixed infections that were as a result of double infections with an FC27 family and a 3D7 family parasite as well as those containing more than one allele from the same family in contrast to findings from the Oksibil region of Irian Jaya (Eisen et al., 1998). Two subtypes of FC27 alleles were found in this study based on the sequence of repeat units and a hybrid sharing sequences from the two subtypes. The 3D7 allele type on the other hand had three subtypes of repetitive domains including the GSA-rich, the TPA and the poly-threonine repeat units. There were no intermediate allele sharing sequences ofY both FC27 allele and 3D7 allele which is in conformity with a previous report (Tanabe eAt al.,R 2004). The sequences belonging to the FC27 family of P. falciparum isolatRes from the study region were relatively conserved with few synonymous and non-synonIyBmous polymorphisms, but with varied number of repeats. The 3D7 allele however displayeLd more extensive sequence diversity with lots of synonymous and non-synonymous amino a cid substitutions as well as variations in the type and number of repeat units. This iIs in cYonformity with previous reports from Africa and other parts of the world (Fenton et al.S, 1991 T; Eisen et al., 1998; Hoffmann et al., 2006; Ferreira and Hartl, 2007). A frameshift mutation in the FC27-type sequences which was reported for isolates in Brazil (Tonon et alE., 20R04) was not found in this study which is in agreement with findings from other parts Vof Africa (Ferreira and Hartl, 2007). This mutation was generated by two indels leading to a vaIriant form AAG TTC TGG CAA TCG ACA (encoding KFWQCT), instead of the wild-tyNpe sequence AGT TCT GGC AAT GCA CCA (encoding SSGNAP) at positions 164-1 69U on the lower panel of Figure 4.9. As evident in theN sequencing data, that there were significant nucleotide substitutions in the 3D7 allelic familAy compared to the FC27 allelic family which may further explain why in the clinical groups,D a predominance of 3D7-type were found compared to the non-symptomatic group wherAe infections were largely of the FC27 allele type. In a recent study on the genetic analysIisB of sequence polymorphisms in MSP-2 gene in Senegal and other African Countries, a predominance of 3D7 allele type were also found in isolates from patients (Ahouidi et al., 2010). This additionally strengthens the idea that carriage of parasites belonging to the 3D7 allelic family may lead to increased risk of developing clinical symptoms. However, the fact that the 152 different genetic variants observed were present in isolates from the three clinical groups as shown from the sequencing results also calls for caution in drawing at a conclusion. Analyses of sequence variants especially those involving insertions and deletions of repeat units within dimorphic families are of practical significance in determining whether such variants affect the immune recognition of MSP-2 and thus, favour immune evasion. Previous studies have shown that antigenic proteins, especially the merozoite surface antigens incluYding MSP-1, MSP-2 and MSP-3 though polymorphic, are recognized by the host‟s immunRe system and are targets for the development of vaccines against blood stage parasites (GAenton et al., 2002; Nwuba et al., 2002; Mahajan et al., 2005; Tanabe et al., 2012). NRaturally acquired antibodies to MSP-2 have been associated with clinical immunity to maIlaBria in Africa (Metzger et al., 2003; Polley et al., 2006) but sequence diversity in the MSP-2L hampers its recognition by naturally acquired (Taylor et al., 1995) and vaccine-induced (Fluck et al., 2004) antibodies. There are reports showing that antibody recognIitTion Yof MSP-2 comprise of a type-specific component, which discriminates between Sdimorphic types, and a variant-specific component, which discriminates among variants within each dimorphic group (Franks et al., 2003; Tonon et al., 2004). Furthermore, studEies hRave shown that: (i) deletions of 12-mer repeats in FC27 allelic type variants affect their Vrecognition by naturally acquired antibodies (Ranford-Cartwright et al., 1996; Franks et al., I2003), (ii) a murine monoclonal antibody discriminates between 3D7 allelic type antigens Ndiffering in the number of copies of the tetrapeptide GGSA (Fenton et al., 1991), and (i ii)U antibodies that discriminate between MSP-2 variants within the same allelic family are Nfound during acute P. falciparum infections (Weisman et al., 2001; Felger et al., 2003; AKanunfre et al., 2003; Tonon et al., 2004), although examples of extensive cross-reactivity Dto structurally different MSP-2 variants have been described in African children (Franks et aAl., 2003). IBStudies of naturally acquired antibodies to MSP2 performed in Papua New Guinea demonstrated that significant numbers of people in the study area have antibodies only to the repeat regions of MSP-2 and that antibodies to the conserved regions of this protein develop at later ages after more prolonged exposure to malaria (al-Yaman et al., 1995). Similarly, anti- 153 MSP2 response occurring in Gambian adults was shown to be directed almost exclusively to polymorphic regions of the protein which consisted of the family-specific regions and the repeats (Taylor et al., 1995). Thus, the repeat regions appear to be the immune-dominant regions of the protein. It is clear that anti-repeat regions antibodies may inhibit parasite growth (Epping et al., 1988), but such antibodies may be much less effective against variant repeats. The conserved region has been shown to have a low frequency of non-synonymous nucleotide substitutions and are also poorly recognized by naturally acquired (Taylor et al., 1995) and vaccine-elicited (FYluck et al., 2004) antibodies. These data suggest a role for naturally acquired immunity in mRaintaining sequence diversity in the non-repetitive domains of MSP-2 dimorphic groups. RA Since naturally acquired antibodies to MSP-2 which reIcoBgnize predominantly polymorphic epitopes, have been shown to be associated with cliLnical immunity to malaria (Metzger et al., 2003), sequence diversity in surface antigens of m alaria parasites populations will have implications in determining susceptibility to theI dTiseaYse as well as for adequate design of MSP-2 based immunization strategy. For examplSe, the GGSA motif present in 22% of the isolates sequenced in this study is a component of a 3D7-based malaria vaccine prototype used in clinical trials (Fluck et al., 2007) and has beeEn foRund to be relatively common in Africa (13.8% of 3D7-typed alleles), Asia (15.8%), anVd Oceania (11.5%), although it is substantially less prevalent in areas like Brazil (5.0%). AIccordingly, recombinant antigens containing GGSA-type repeats are poorly recognized by Nantibodies of malaria-exposed subjects in areas like Brazil, while locally prevalent 3D7- tyUpe variants were readily recognized (Kanunfre et al., 2003; Tonon et al., 2004). N Therefore, itA remains uncertain whether vaccines containing GGSA-type repeats may induce significaDnt protection in areas where this MSP-2 variant is infrequent. Thus if immunity conferreBd byA a monovalent vaccine is allele specific, a vaccine with high allele-specific efficacy wouldI have low overall efficacy in populations where the target allele is in the minority. Without an understanding of the distribution of vaccine target haplotypes, this scenario could result in the premature abandonment of a promising vaccine that could be modified (perhaps by including additional target alleles) to be more universally protective. This possibility highlights the need to 154 include molecular endpoints in addition to conventional efficacy endpoints in clinical trials of malaria vaccines. This is the first description of sequence diversity of field isolates of Plasmodium falciparum parasites in Lafia, north-central Nigeria and also to my knowledge, the first description in Nigeria. This information therefore, bridges an important gap in understanding the molecular characteristics of P. falciparum populations in Nigeria. AR Y 5.3 IL-18 promoter polymorphisms and disease outcome of malaria R Based on the historical presence of malaria, a large impact on IthBe human genome has been exerted by the disease such that potentially harmful variants a reL preserved, largely because of the advantage offered in heterozygous individuals that aYre often protected from severe, complicated, and fatal malaria (Koch et al., 2005; KwIiaTtkowski and Luoni, 2006; Hedrick, 2011). Polymorphic forms of a number of host genes Sinvolved in immunity have been associated with protection or susceptibility to malaria. It is thRus expected that cytokine genes that regulate a Th1 dominant pathway may be associated wiEth malaria. In recent years, increasing evidence has emerged from experimental and epidemIViological data that IL-18, a pro-inflammatory cytokine involved in both innate and acquired immune responses, plays an important immune-regulatory role in malaria (Torre et al., U2002Na; Chaisavaneeyakorn et al., 2003; Perkmann et al., 2005; Torre, 2009). Information o n the relationship between IL-18 polymorphisms and malaria is however limited. This stNudy therefore investigated three known promoter polymorphisms in IL- 18 at positions -656,A -607 and -137 relative to the transcription start site. All tAhe tDhree single nucleotide polymorphisms were detected among participants in the study IrBegion. The -656G/T and -607C/A loci were found to be in complete linkage disequilibrium. A higher frequency of the -607AA genotype was found among the asymptomatic group compared to participants in the severe malaria group. This is comparable to findings from south west England where AA genotypes were higher among controls compared to subjects with osteoarthritis (Hulin-Curtis et al., 2011). It is also similar to a report from an earlier study that 155 showed a higher frequency of the AA genotype among controls in comparison to subjects with rheumatoid arthritis (Gracie et al., 2005). In Kenya, the carriage of -607AA genotype was found to be associated with protection against severe malaria (Anyona et al., 2011). Likewise, a higher prevalence of -137CC genotype was found among participants in the severe malaria group compared to the asymptomatic group. This is contrary to findings from Kenya where no difference was found in the distributions of the -137CC genotype between participants presenting with severe malarial anaemia and those in the non-severe malarial anaemia group, althYough carriers of the -137G/-607C (CG) haplotype were found to have increased suscepRtibility to severe malarial anaemia (Anyona et al., 2011). RA Functional assays have previously demonstrated that the productioBn capacity of IL-18 by monocytes is significantly reduced in participants with -137C and -60L7AI alleles (Giedraitis et al., 2001; Arimitsu et al., 2006). The -607C/A and -137G/C areY bel ieved to be located within a transcription initiation site and have consistently beTen associated with altered IL-18 transcriptional activity. These promoter regions are pSrediIcted to be the binding sites for cyclic AMP-responsive element-binding protein [cAMP] and the human histone H4 gene-specific transcription factor-1 [H4TF-1] respectively (EHauRs-Seuffert and Meisterernst, 2000; Giedraitis et al., 2001). A change from G to C at posVition -137 changes the H4TF1 nuclear binding site into that for an unknown factor located withIin the granulocyte-macrophage colony-stimulating factor (GM-CSF) promoter, potentially Nreducing production of IL-18 (Giedraitis et al., 2001). Furthermore, the C-to-A ch anUge at the -607 loci mediates transcriptional activity activity in response to cAMP by dNisrupting the binding site, thereby down-regulating transcription which may result in lower IAL-18 production (Giedraitis et al., 2001). 5.4 IL-18RαD polymorphisms and disease outcome of malaria IBA to Atal of three single nucleotide polymorphic loci were investigated at the promoter region of the IL-18Rα gene: -93C/T, -175G/A and -661C/T. No association was found between the 175G/A locus and disease outcome and the genotype distributions were in conformity with the Hardy-Weinberg equilibrium. Interestingly, the distributions of -93C/T and -661C/T in the severe malaria group significantly deviated from the Hardy-Weinberg equilibrium, even though 156 there was conformity with the Hardy-Weinberg equilibrium in the asymptomatic and uncomplicated malaria groups. The result showed that there was significant decrease in the frequency of heterozygotes for the two polymorphic loci (-93C/T and -661C/T), while the frequency of homozygotes increased in the severe malaria group. This may indicate a protective role for the heterozygotes (-93CT and -661CT genotypes) at the two loci. To my knowledge, this is the first study to investigate the association of polymorphYisms in the IL-18Rα gene and malaria and as such bridges an important gap in our knowledRge of the contributions of host cytokine gene polymorphisms in malaria. BR A 5.4 TNF-α polymorphisms and disease outcome of malaria LI The TNF-308G/A and TNF-238G/A loci were investigaYted for associations with disease outcome in malaria in the study population. The genotypTe distributions were found to be in conformity with the Hardy-Weinberg equilibrium. STheI most common genotype at the two polymorphic sites was the GG genotypes. At botRh loci, the rare genotype AA was not found in the study population. No evidence was found for associations between the TNF-308G/A and TNF-238G/A polymorphisms in this study. TEhis is in contrast to report from Gambia where the homozygotes for the TNF-308A aNlleleI w Vere found to be at increased risk of cerebral malaria (McGuire et al., 1994). In anoUther study, Homozygousity for the TNF-308A allele was found to be a risk factor for pre-ter m birth and early childhood mortality and malaria morbidity in children in Western KNenya (Aidoo et al., 2001). However, in another study in Mali, no association was founAd in the TNF-308G/A polymorhism with malaria (Cabantous et al., 2006). Furthermore, asDsociations were not found between the TNF-308G/A and TNF-238G/A loci and mild malariAa or parasitaemia in Gabon (Migot-Nabias et al., 2000) contrary to findings from BurkinIaB Faso (Flori et al., 2005). 157 CHAPTER SIX CONCLUSION The host-parasite interaction in malaria that leads to variability in individual susceptibility or resistance to the disease has been suggested to involve several host and parasite genetic factors. This study characterized and determined cytokine gene polymorphisms of IL-18, IL-18Rα and TNF-α as well as genetic polymorphisms in the P. falciparum MSP-2 geYne in children in three categories: asymptomatic infection, uncomplicated malaria and sevAere Rmalaria. Data from this study showed that all cases of malaria among the stuRdy participants in Lafia were due to infection with P. falciparum. It was also found that ImBultiplicity of infection was significantly lower in severe malaria group compared with Luncomplicated malaria or asymptomatic infection; which probably suggests that in severe ma laria, proliferation of certain dominant clones which could be more virulent, may be assocYiated with disease pathology. In addition, the study showed a high allelic diversity of t TShe MISP-2 gene in the study region, with a significantly higher distribution of 3D7 alleles Rin uncomplicated and severe malaria groups; which may indicate a higher risk of developing symptomatic malaria with increasing carriage of the 3D7 allele type isolates. Further analVysisE of the MSP-2 gene by sequencing showed several synonymous and non-synonymous aminIo acid substitutions in isolates from the study region, and with extensive sequence diversity inN the 3D7 allele type. Likewise, analysis of hUost cytokine gene polymorphisms showed a significantly higher distribution of the IL1N8 -607AA genotype in the asymptomatic group compared to the symptomatic groupsA; probably suggesting association with disease protection. This study finds no association Dof the promoter polymorphisms of TNF-α with disease outcome. However, promoter poAlymorphisms of the IL18Rα showed a significant deviation from the HWE in the distribIuBtion of genotypes at the -93C/T and -661C/T loci in the severe malaria group, with significantly higher frequency of homozygotes. This may indicate a protective role for the heterozygotes at the two loci. Thus, this study supports the idea that certain host and parasite genetic factors may indeed be associated with variable sucessibility or resistance to malaria. 158 REFERENCES Abraham, L. J., and Kroeger, K. M. 1999. Impact of the -308 TNF promoter polymorphism on the transcriptional regulation of the TNF gene: relevance to disease. 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N U A BA D I 206 APPENDIX Appendix 1: Nucleotide sequence of primers used in Plasmodium spp characterization Primer Name Nucleotide sequence RY Fw PLU6 5'-TTA AAA TTG TTG CAG TTA AAA CG-3' RA Rv PLU5 5'-CCT GTT GTT GCC TTA AAC TTC-3' I B L Fw FAL 1 5'-TTA AAC TGG TTT GGG AAA ACCY AAA TAT ATT-3' Rv FAL 2 5'-ACA CAA TGA ACT CAA TCAI TTGA CTA CCC GTC-3' S Fw MAL 1 5'-ATA ACA TAG TTEG TRAC GTT AAG AAT AAC CGC-3' Rv MAL 2 5'-AAA ATT CCICV ATG CAT AAA AAA TTA TAC AAA-3' N Fw OVA 1 5'-AT CU TCT TTT GCT ATT TTT TAG TAT TGG AGA-3' Rv OVA 2 A 5N'-GGA AAA GGA CAC ATT AAT TGT ATC CTA ATG-3' AD IB 207 Appendix 2: Nucleotide sequence of primers used in MSA-2 genotyping study Primer Name Nucleotide sequence MSA 2-1 5'-ATG AAG GTA ATT AAA ACA TTG TCT ATT ATA-3' Y MSA 2-4 5'-TTA TAT GAA TAT GGC AAA AGA TAA AAC AAG-3' AR MSA 2-2 5'-ACA TTC ATA AAC AAT GCT TAT AAT ATG AGTB-3' R MSA 2-3 5'- GAT TAT TTC TAG AAC CAT GCA TAT GTC LCAIT -3' Y FC 27-1 5'-GCA AAT GAA GGT TCT AAT ACT IATAT AG-3' FC 27-2 5'-GCT TTG GGT CCT TCT TCAR GTST GAT TC-3' E 3D7-1 5'-GCA GAA AGT AAGIV CCT TCT ACT GGT GCT-3' 3D7-2 5'-GAT TTG TTT CNGG CAT TAT TAT GA -3' U DA N A IB 208 Appendix 3: Nucleotide sequence of primers used for IL-18 gene promoter study Primer Name Nucleotide sequence IL-18Pro -F 5'-GAC TTC CCG AAA TGA AAA CCC-3' Y IL-18Pro -R 5'-ATG CAC TGG GAG ACA ATT CC-3' R IL-18Pro -Fb 5'-TCA AAT ATT TTA GGT CAG TCT TTG-3' RA LI B SI TY R VE NI N U A BA D I 209 Appendix 4: Nucleotide sequence of primers used for IL-18Rα study Primer Name Nucleotide sequence IL18R1 Ex1-F 5'-AGC CCA GGT TTG TGT GTT TC-3' Y IL18R1 Ex1-Fb 5'-CCA CTG GGA CAC AGT CAA TG -3' R IL18R1 Ex1-R 5'- TCA GCA TCT TCA GTA GCC ACC-3' A IL18R1 Ex1-Rb 5'-ACA TTC TTC CTC AT TAC TCA TGA A -3' BR IL18R1 Ex1-R c 5'-GCC TGG TCT ACT AAA TCC TGC T -3' LI Y IL18R1 Ex2-F 5'- TGC TAA CCT TGC TTC TTC ACCI-T3' IL18R1 Ex2-R 5'- TTC AGA TTA CTG CAT ARTTS TGA GTT G-3' E IL18R1 Ex3-F 5'- AAG GGA AGA TIGVG GTG ATA TTT G-3' IL18R1 Ex3-R 5'- ATG GTA GCNT CTC AGC CCC TC-3' U IL18R1 Ex4-F 5'-A GANT CCG CAG CTG CAT TAG AC-3' IL18R1 Ex4-R D 5'- TTT GGG GAT GAT TCA GGC-3' A IL18RI1B Ex5-F 5'- GGA TCA CTG TAA TAT CAA TTT GGC-3' IL18R1 Ex5-R 5'- GTG TGG TCA CAA CCC CAA C-3' 210 IL18R1 Ex6-F 5'- GGA ATC TTT GTT ACA TGA AAT GAG C-3' IL18R1 Ex6-R 5'- TCA TAT TTA CGC TTG GAA GGC-3' IL18R1 Ex7-F 5'-GCA CCA CGT TTT GCT TTA GG -3' IL18R1 Ex7-R 5'-ATA CAC ATC AGC CAC CCA GTG -3' RY IL18R1 Ex8-F 5'- TGT GAA TTC CCC TCT CAA GG-3' A IL18R1 Ex8-R 5'- TGG CCA TCT TTG AAA TGT CTC-3' R LI B IL18R1 Ex9-F 5'- ACA AGC ACG TGA TGA TGG AC-3' Y IL18R1 Ex9-R 5'- CCA TAG AAA ACC TCT CCC ACIAT G-3' S IL18R1 Ex10-F 5'- TTG CTT GGT TAG CEAT RGGG AG-3' IL18R1 Ex10-R 5'- AAT GGG ATA GICVT CTC TGG GG-3' N IL18R1 Ex11-F 5'- TGA C TTU TTA TCT CAT GTT CCC C-3' IL18R1 Ex11-R 5'- CANT CAC GTC CAG CTT CAC AC-3' DA IB A 211 Appendix 5: Nucleotide sequence of primers used for TNF-α gene promoter study Primer Name Nucleotide sequence TNFPro-F 5'-CCT GCA TCC TGT CTG GAA GT-3' Y TNFPro-R 5'-CTC CCT ATC AGC GCA CAT CTT-3' R TNFPro-Fb 5'-ATC AGT CAG TGG CCC AGA AG-3' A LIB R SI TY R IV E N U AN AD IB 212 Appendix 6: Ethical clearance granted by the Nasarawa State Ministry of Health, Lafia. AR Y BR Y LI IT S ER V NI U AN BA D I 213 Appendix 7: Ethical clearance granted by the Dalhatu Araf Specialist Hospital, Lafia. AR Y R LI B SI TY ER IV U N AND A IB 214