"Medicine, Faculty of"@en . "Medicine, Department of"@en . "Experimental Medicine, Division of"@en . "DSpace"@en . "UBCV"@en . "Shaw, David M."@en . "2010-01-14T00:28:37Z"@en . "2006"@en . "Master of Science - MSc"@en . "University of British Columbia"@en . "Complex diseases such as critical illness and post-cardiopulmonary bypass inflammation are characterized by inappropriate activation of the inflammatory response. Polymorphisms of key inflammatory mediator genes can alter the amount of that mediator produced and the severity of response to the stimulus. Interleukin-I 0 is a key down-regulator of the inflammatory response, dampening pro-inflammatory cytokine production follow injury. In opposition, interleukin-18 is a key pro-inflammatory cytokine, up-regulating the type I T cell response following activation. We hypothesized that polymorphisms and haplotypes of these genes are likely to contribute to alterations among patients in the response to stimuli such as critical illness and cardiopulmonary bypass surgery. A haplotype-based approach, grounded in linkage disequilibrium, is used for selection of polymorphisms to genotype in our patient cohorts, allowing great flexibility in choice of haplotype tagging polymorphisms. Novel haplotypes and polymorphisms of the interleukin-l 0 gene and interleukin-l S pathway genes (including the interleukin-18 binding protein and the interleukin-18 receptors 1 and receptor-accessory protein) were found to be associated with altered outcomes from cardiopulmonary bypass surgery as well as altered serum cytokine levels, indicating biologic plausibility. Significant results with novel polymorphisms of the interleukin-18 pathway genes in the cardiopulmonary bypass surgery cohort were not replicated in the critical illness cohort. This failure to reproduce initial findings may represent a lack of functionality of the identified polymorphisms, or the fact that effects of polymorphisms of the interleukin-I S pathway genes are not strong enough to affect survival or organ dysfunction in critical illness. The strong effects of these novel haplotypes and polymorphisms in the interleukin-I 0 and interleukin-l S pathway genes, including altered outcomes and intermediate phenotypes, indicate that these are attractive targets for further investigation in inflammatory diseases. The use of linkage disequilibrium and haplotypes for selection of polymorphisms in disease association studies is shown to be a powerful method of identifying markers of altered outcomes from inflammatory diseases."@en . "https://circle.library.ubc.ca/rest/handle/2429/18148?expand=metadata"@en . "Novel Haplotypes and Polymorphisms of Interleukin-10 and Interleukin-18 Pathway Genes in Complex Inflammatory Diseases By David M Shaw BSc. University of Victoria, 2002 A THESIS S U B M I T T E D IN P A R T I A L F U L F I L M E N T OF T H E R E Q U I R E M E N T S F O R T H E D E G R E E OF / M A S T E R OF S C I E N C E In T H E F A C U L T Y OF G R A D U A T E STUDIES (Experimental Medicine) T H E U N I V E R S I T Y OF BRIT ISH C O L U M B I A May, 2006 \u00C2\u00A9David M Shaw, 2006 A B S T R A C T Complex diseases such as critical illness and post-cardiopulmonary bypass inflammation are characterized by inappropriate activation of the inflammatory response. Polymorphisms of key inflammatory mediator genes can alter the amount of that mediator produced and the severity of response to the stimulus. Interleukin-10 is a key down-regulator of the inflammatory response, dampening pro-inflammatory cytokine production follow injury. In opposition, interleukin-18 is a key pro-inflammatory cytokine, up-regulating the type I T cell response following activation. We hypothesized that polymorphisms and haplotypes of these genes are likely to contribute to alterations among patients in the response to stimuli such as critical illness and cardiopulmonary bypass surgery. A haplotype-based approach, grounded in linkage disequilibrium, is used for selection of polymorphisms to genotype in our patient cohorts, allowing great flexibility in choice of haplotype tagging polymorphisms. Novel haplotypes and polymorphisms of the interleukin-10 gene and interleukin-18 pathway genes (including the interleukin-18 binding protein and the interleukin-18 receptors 1 and receptor-accessory protein) were found to be associated with altered outcomes from cardiopulmonary bypass surgery as well as altered serum cytokine levels, indicating biologic plausibility. Significant results with novel polymorphisms of the interleukin-18 pathway genes in the cardiopulmonary bypass surgery cohort were not replicated in the critical illness cohort. This failure to reproduce initial findings may represent a lack of functionality of the identified polymorphisms, or the fact that effects of polymorphisms of the interleukin-18 pathway genes are not strong enough to affect survival or organ dysfunction in critical illness. The strong effects of these novel haplotypes and polymorphisms in the interleukin-10 and interleukin-18 pathway genes, including altered outcomes and intermediate phenotypes, indicate that these are attractive targets for further investigation in inflammatory diseases. The use of linkage disequilibrium and haplotypes for selection of polymorphisms in disease association studies is shown to be a powerful method of identifying markers of altered outcomes from inflammatory diseases. T A B L E O F C O N T E N T S Abstract i i Table of Contents iv List of Tables v i List of Figures v i i List of Abbreviations v i i i Acknowledgements i x Dedication x C H A P T E R 1: Introduction 1 1.1 Inflammatory Diseases 1 1.2 Polymorphisms and Haplotypes 4 1.3 Disease Association Studies 8 1.4 IL-10/IL-18 Pathway 12 1.4.1 IL-10 12 1.4.2 IL-18 14 1.4.3 IL-18 Receptors 15 1.4.4 IL-18 Binding Protein 16 1.5 Overview and Hypothesis 18 1.6 References 19 C H A P T E R 2: A Novel Interleukin-10 Haplotype in the C S I C U 32 2.1 Introduction : 32 2.2 Methods 34 2.3 Results 39 2.4 Discussion 41 2.5 Summary , 45 2.6 Tables and Figures 46 2.7 References 55 C H A P T E R 3: A Novel Interleukin-18 Polymorphism in the C S I C U 62 3.1 Introduction 62 3.2 Methods 64 3.3 Results 68 3.4 Discussion 71 3.5 Summary 76 3.6 Tables and Figures 77 3.7 References 87 iv C H A P T E R 4: A Novel Interleukin-18 Receptor-1 Polymorphism in the C S I C U 92 4.1 Introduction 92 4.2 Methods 94 4.3 Results 98 4.4 Discussion 100 4.5 Summary 105 4.6 Tables and Figures 106 4.6 References 115 C H A P T E R 5: Interleukin-18 Pathway Haplotypes and Polymorphisms in the ICU 120 5.1 Introduction 120 5.2 Methods 123 5.3 Results 127 5.4 Discussion 130 5.5 Summary 133 5.6 Tables and Figures 134 5.7 References 140 C H A P T E R 6: Summary and Future Directions 147 6.1 Summary of Completed Research 147 6.1.1 IL-10 in the C S I C U 147 6.1.2 IL-18 in the C S I C U 148 6.1.3 IL-18R1 in the C S I C U 150 6.1.4 IL-18 Pathway Genes in the ICU 151 6.2 Strengths of the Completed Research 153 6.3 Weaknesses of the Completed Research 155 6.4 Future Directions 156 6.4.1 Whole-Haplotype Transfections 157 6.4.2 Single SNP-Based Alteration of Mechanism 157 6.5 Summary 159 6.6 References 160 A P P E N D I X A : Sequence of P C R primers and allele-specific probes 165 A P P E N D I X B: Supplementary results for C H A P T E R 5 166 LIST OF TABLES T A B L E 2.1: Clarification of SNP locus numbering in the IL-10 gene 46 T A B L E 2.2: Summary of baseline characteristics of C S I C U patients by IL-10 haplotype 47 T A B L E 2.3: Summary of peri-operative variables of C S I C U patients by IL-10 haplotype 48 T A B L E 2.4: Summary of IL-10 SNP - and haplotype-based alterations in serum IL-10 levels and outcomes from inflammatory diseases 49 T A B L E 3.1: Summary of baseline demographics by IL-18 9545 T / G htSNP genotype in C S I C U patients 77 T A B L E 3.2: Binary logistic regression of low SVRI by IL-18 9545 T / G htSNP genotype in C S I C U patients 78 T A B L E 3.3: Summary of IL-18 SNP - and haplotype-based alterations in serum IL-18 levels and outcomes from inflammatory diseases 79 T A B L E 4.1: Summary of baseline characteristics by IL-18R1 6691 C /T htSNP genotype in C S I C U patients 106 T A B L E 4.2: Summary of peri-operative variables by IL-18R1 6691 C /T htSNP genotype in C S I C U patients 107 T A B L E 4.3: Binary logistic regression of low SVRI by IL-18R1 6691 C /T htSNP genotype in C S I C U patients 108 T A B L E 5.1: Brussels organ dysfunction scoring criteria 134 T A B L E 5.2: Summary of baseline characteristics of I C U patients by haplotype of the IL-18 (a), IL-18BP(b), IL -18Rl (c) and IL-18RAP(d) genes 135 L I S T O F F I G U R E S F I G U R E 2.1: Haplotpe diagram of the IL-10 gene 52 F I G U R E 2.2: Phylogenetic tree diagram indicating relationships of IL-10 haplotypes based on similarity 53 F I G U R E 2.3: Serum IL-10 measurements by IL-10 gene haplotype in C I S C U 54 F I G U R E 3.1: Haplotype diagram of the IL-18 gene 82 F I G U R E 3.2: Simplified haplotype diagram of IL-18 gene in C S I C U patients 83 F I G U R E 3.3: Need for prolonged I C U care by IL-18 gene haplotype 84 F I G U R E 3.4: Need for prolonged I C U care and prevalence of low S V R J by IL-18 9545 T / G htSNP in C S I C U patients 85 F I G U R E 3.5: Serum concentrations of IL-18, tumor necrosis factor-alpha and Interleukin-10 by IL-18 9545 T / G htSNP in C S I C U patients 86 F I G U R E 4.1: Genotype and linkage disequilibrium map of IL-18R1 gene in Caucasians 111 F I G U R E 4.2: Haplotype diagram of the IL-18R1 gene in C S I C U patients 112 F I G U R E 4.3: Occurrence of low SVRI by IL-18R1 gene haplotype in C S I C U patients 113 F I G U R E 4.4: Post-operative serum tumor necrosis factor-alpha levels by 6691 C /T Genotype in C S I C U patients 114 F I G U R E 5.1: Haplotype diagrams of the IL-18(a), IL-18BP(b), IL-18R1 (c) and IL -18RAP (d) genes in I C U patients 138 F I G U R E 5.2: Summary of survival and prevalence of septic shock by IL-18 (a), IL -18BP (b), IL-18R1 (c) and IL -18RAP (d) gene haplotypes 139 L I S T O F A B B R E V I A T I O N S C S I C U - cardiac surgery intensive care unit C P B - cardiopulmonary bypass C A R S - compensatory anti-inflammatory response syndrome D N A - deoxyribonucleic acid ICU - intensive care unit kb - kilobases R N A - ribonucleic acid SVRI - systemic vascular resistance index SIRS - systemic inflammatory response syndrome SNP - single nucleotide polymorphism IL - interleukin TNF - tumor necrosis factor IFN - interferon Th - helper T cell U T R - untranslated region \u00C2\u00B0 - degree A - adenosine C - cytosine G - guanine T - thymidine v i i i A C K N O W L E D G E M E N T S I would like to acknowledge and thank my wife for her tireless support. Her understanding, caring and capacity to proof-read has seen me through many challenges. I would like to acknowledge and thank my family for their understanding and compassion while I put my life on hold. Many missed birthdays were forgiven in order that I was able to complete my research. I would like to acknowledge and thank my supervisor, Dr Keith Walley, and the members of my supervisory committee, Dr James Russell and Dr Andrew Sandford. These mentors have provided invaluable guidance, amazing opportunities and seemingly unending support, and have believed in my abilities as a researcher even when I did not. I would like to acknowledge and thank the numerous members of the Walley/Russell/Dorscheid lab and the iCapture Centre, whose expertise and patience I took advantage of in order to further the my research. Specifically, Dr Gurpreet Singhera, Ainsley Sutherland, Dr John Boyd, Andrea Page, Marissa LeBlanc, Shelly Dai, Dr Jianqing He, Andy Sham, Sean Minnaker, Dorota Stefanowicz and countless others. D E D I C A T I O N To my wife, Aurora. Nihil facimus, sed bene facimus. C H A P T E R 1: I N T R O D U C T I O N 1 2 The publication of the draft sequence of the human genome in 2001 ' and the completed sequence in 2003 3 have introduced the science of genomics to the practice of medicine, and has the potential to revolutionize medicine. It is not possible to overstate the impact this information has had on the study of complex diseases. Programs are now in place through the National Centers for Biotechnology Information (NCBI) to co-ordinate whole-genome association studies, incorporating pre-existing programs by the National Heart, Lung and Blood Institute (NHLBI) , the Genetic Association Information Network (GAIN) and the Coriell /National Institute of Neurological Disorders and Stroke 4. In the relatively short time since the publication of the human genome sequence, interest in using the publicly available sequence information in the study of complex diseases has expanded exponentially. Following on the success of the human genome project have been efforts to identify common polymorphisms in the human genome, as well as haplotypes defined by those polymorphisms. 1.1 Inflammatory Diseases The body's reaction to an inflammatory stimulus, such as infection or surgery, is a necessary component to proper healing following such an event. Were the inflammatory system not engaged following injury, a systemic infection would quickly be established, leading rapidly to death. Critical components of the inflammatory system include those members of the innate and adaptive immune systems that interact with infectious agents, 1 with each other and with other components of the body's barriers to infections, including the complement system and wound healing machinery. The systemic inflammatory response syndrome (SIRS) is a body-wide inflammatory response to stimuli such as infection and surgery. SIRS is defined as possession of two of the following four criteria: 1) fever (temperature >38\u00C2\u00B0C) or hypothermia (temperature < 36\u00C2\u00B0C), 2) tachypnea (respiratory rate > 20 breaths/minute) or the need for mechanical ventilation, 3) tachycardia (heart rate > 90 beats/minute), and 4) leukocytosis (total leukocyte count > 12,000 cells/uL) or leukopenia (total leukocyte count < 4,000 cel ls /uL) 5 . The presence of a confirmed (culturable) or suspected infection and SIRS is defined as sepsis, and sepsis including low systolic blood pressure unresponsive to fluid treatment is defined as septic shock. Sepsis and septic shock have mortality rates of 30% and 55%-65%, respectively 5. A systemic inflammatory response can result not just from introduction of an infectious agent, but also from an invasive procedure such as cardiopulmonary bypass (CPB) surgery6. Induction of an overwhelming inflammatory response can arise from the surgical procedure itself 7 or from exposure of immune cells to the lining of the C P B pump machinery ' . The exposure of immune cells to the pump machinery can result in a \"post-pump syndrome\" 9, whereby activated cells such as macrophages and neutrophils interact with vascular endothelium through release of pro- and anti-inflammatory cytokines such as interleukin (IL)-6, IL-8, IL-18, tumor necrosis factor-alpha (TNF) -a , or IL-10 and transforming growth factor-beta (TGF-p) 9 . 2 The release of cytokines typically occurs in two phases, often referred to as the SIRS phase and the compensatory anti-inflammatory response syndrome (CARS) phase 1 0. Cytokine release in the SIRS phase tends toward hyper-responsiveness to stimuli and pro-inflammatory cytokines, such as IL-1, IL-6 and IL-18, though IL-10 levels can be elevated in this phase\". Cytokine release in the C A R S phase leans more toward an anti-inflammatory profile, characterized by hypo-responsiveness to stimuli an anti-inflammatory cytokine release (e.g. increased IL-10 and TGF-(3) 1 2 . Dysregulation of the timing or balance of these two phases can lead to inappropriately exaggerated inflammatory responses (SIRS phase) or systemic infections due to lack of necessary response ( C A R S phase) 1 3. Variation in the sequence and expression of these genes can contribute to their dysregulation, and to the resulting inflammatory diseases. 3 1.2 Polymorphisms and Haplotypes Genetic variation between individuals accounts for a large portion of the observed variance in response to inflammatory stimuli. The combination of genetic and environmental factors is thought to determine a large portion of the outcomes from inflammatory and non-inflammatory events such as cancer, cardiovascular disease, infectious diseases and other inflammatory diseases 1 4. Genetic variants of genomic D N A can take the form of microsatellites, insertion/deletion (InDel) polymorphisms, variable number of tandem repeat (VNTR) polymorphisms or single nucleotide polymorphisms (SNPs). SNPs are thought to be the most common form of polymorphisms at 90% of observed variation 1 5 . Approximately three mil l ion common polymorphisms (>5% minor allele frequency) exist within the human genome. However when uncommon SNPs are also considered (minor allele frequency 1 to 5%) as many as 10 mil l ion SNPs can be found 1 5 . Polymorphisms can be present in either the 5' or 3' untranslated regions (UTR) of a gene, in the coding sequence (where the alteration in sequence may or may not induce a change in amino acid sequence), in the gene introns or within intergenic regions of D N A . Polymorphisms that occur in the coding sequence of a gene can potentially change the amino acids of the protein product, and thus may be able to significantly alter the function of the protein, but these are not the only polymorphisms that are able to alter the effect of a protein. Polymorphisms in the promoter can alter the binding capacity of transcription factors and effectors/repressors, thereby altering transcriptional efficiency of the gene. For example, promoter polymorphisms often result in an increase in the amount protein synthesized in response to a given stimulus, such as endotoxin or D N A damage 1 6. Similarly, polymorphisms in the 3' untranslated region can alter the binding of 4 downstream effectors/repressors, and can also alter stop signals for transcription, polyadenylation signals for m R N A and AU - r i ch m R N A destabilizing signals 1 7 . Thus, polymorphisms in the 3' untranslated region can also increase or decrease the amount of protein synthesized in response to a given stimulus. Polymorphisms in intronic regions can alter the splicing capability or efficiency by masking splice sites or by altering binding sited for spliceosomes . These polymorphisms are likely to alter the amino acid sequence of a protein. Single nucleotide polymorphisms may occur throughout a gene spaced at seemingly random intervals. For example, i f the G allele of one G /C SNP and the A allele of another A / T SNP, possible several hundred or thousand bases away on the same strand of D N A , always occur together then it is only necessary to genotype one of these two SNPs in order to gather information about both. These two alleles are then said to be in complete linkage disequilibrium and form a haplotype. Now i f the number of alleles that occur together with this G - A combination increases, the result is a haplotype block. Haplotype blocks are important units of genetic information that are passed from generation to generation in evolution. Crossing over, recombination and mutations events disrupt linkage disequilibrium so haplotype blocks do not extend the full length of a chromosome - they typically are 5 to 100 kilobases (kb) in length. Within this haplotype block, the SNPs are related to one another by so-called linkage disequilibrium. A l l the SNPs may not be in complete linkage disequilibrium with each other, but there should be some degree of certainty regarding the identity of other SNPs given by genotyping one or more of the SNPs within this block. For example, using the SNPs listed above, the G 5 allele of the G /C SNP may only occur together with the A allele of the A / T SNP 85% of the time. B y genotyping the G /C SNP the identity of the allele at the A / T SNP locus is known with 85% certainty. SNPs may be used to tag or mark a whole haplotype because SNPs of a haplotype are in linkage disequilibrium. In other words, it is not necessary to genotype all the SNPs of a haplotype to determine the haplotype of an individual. These genotyped SNPs are referred to as haplotype tag SNPs (htSNPs). Since every individual carries two copies of each gene (disregarding the sex chromosomes), every individual has two (potentially different) copies of haplotype blocks at a given locus. The International HapMap Project l 9was initiated in 2002 in an effort to identify common haplotype blocks across the human genome and to identify the haplotype tag SNPs that could maximize the information output for these blocks. That is, to identify the SNPs that should be genotyped in order to determine the haplotype block possessed by an individual at that locus. The project used D N A from four populations to identify the known differences in haplotype structure of these ethnic groups: Northern/Western European (using the Centre d'Etude du Polmorphisme Humain (CEPH) registry samples), Yoruban (African), Han Chinese and Japanese. Phase I o f the HapMap project, with an average SNP density of 1 SNP per 5 kb of D N A , has recently been published 2 0 . These results indicate a general pattern of linkage disequilibrium over large physical distances on chromosomes (1-100 kb), with common haplotypes often overlapping with those from other ethnic groups. Thus, haplotypes and htSNPs appear to be somewhat generalizable among ethnic groups, allaying some of the fears regarding populations admixture contributing to type 1 error in haplotype-based disease association studies. 6 Length of haplotype blocks estimated from the HapMap data average between 56 kb on chromosome 1 (the largest chromosome) to 34 kb on chromosome 21 (the smallest autosomal chromosome) 2 0. The results of Phase I of the HapMap project have already been beneficial in the field of pharmacogenomics, helping delineate common haplotypes and easing the selection of htSNPs for use in clinical trials, as described above . The htSNPs selected by the HapMap project have been tested in empirical and simulated data sets and have proven their worth for SNPs with minor allele frequencies greater than 5%, though SNPs with minor allele frequency ( M A F ) less than this cutoff are of diminished value 2 2 . 7 1.3 Disease Association Studies The prospect of patient-tailored therapies based on genetic risk factors has been brought forward as a clinical use for disease association studies using polymorphisms 2 3 ' 2 4 . The understanding of the genetic factors influencing outcomes from inflammatory diseases such as critical illness and C P B surgery has grown dramatically in recent years. One use for genome-tailored therapies is the design of clinical trials. The N O R A S E P T I I trial, assaying the functionality of ant i -TNF-a antibodies in outcomes from critical illness, reported no significant results in reduction of all-cause 28 day mortality from critical illness. Thus, no product based on ant i -TNF-a antibodies exists as an option for treatment of critical illness today 2 5 . Numerous groups report differences in production of serum T N F - a based on promoter polymorphisms of the T N F - a gene 2 6 ' 2 7 . Had these SNP-based differences been used in the classification of high vs. low serum T N F - a producers been used in the design of the clinical trial, it is possible that the clinical trial could have reached a positive outcome with regard to reduction in all-cause 28 day mortality. This difference has been reported for another sets of patients at risk for excessive T N F - a production and ant i -TNF -a treatment2 8. Similarly, polymorphisms in the cytochrome P450 gene alter drug metabolism rates for drugs such as anti-coagulants 2 9 and 30 thalidomide , and these polymorphisms have been used to titre the amount of those drugs in affected patients. Thus, we see that SNP-based disease association studies can have a real, clinical effect on design of trials testing the efficacy of novel drugs to treat critical illness. With respect to C P B surgery, design of novel chemical lining the pump machinery in an effort 8 to reduce immune over-activation is a current research topic 3 1 \" 3 3 , but this has also been a field beset by difficulties due to contra-indications, risk of bleeding and genetic dispositions against certain chemicals, such as unfractionated heparin 3 4 ' 3 5 . The incorporation of polymorphisms affecting production and modifications of heparin 3 6 and other systemic anti-coagulants 2 9 into clinical trials testing novel pump linings could drastically improve not only the successes of these compounds in trials, but also their successes in clinical use. Disease association studies have proliferated in the field of inflammatory conditions, and two approaches have been taken in order to find polymorphisms affecting outcomes from these diseases. Genome-wide scans for causative polymorphisms in patients o f complex diseases are monumental tasks, both in terms o f cost and numbers required to produce statistical power . Regions of the genome that are statistically strongly associated with a particular complex disease must further be subject to intense genotyping and study. This approach can be effective when single polymorphisms have large effect sizes and high penetrance, such as in Mendelian diseases 3 8, but most complex diseases are thought to be influenced by numerous polymorphisms of modest effect sizes, and environmental effects are not taken into account using this model 3 9 . The second approach often taken to identify SNPs contributing to outcomes from complex diseases is a candidate gene approach. In this method, genes thought to participate in the pathophysiology of the disease of interest are selected, and then polymorphisms are selected through a particular method (discussed below). Genotyping 9 of cases (affected individuals) and well-matched controls (individuals not possessing the disease) follows, and statistical tests are used to determine whether a particular SNP allele is found more frequently in cases or controls, suggesting a genotype-phenotype association. A cohort study design can also be used, whereby all patients exposed to a particular stimulus are enrolled, and those with a pre-defined negative outcome are classified as 'affected' individuals, while those without the outcome phenotype are classified as 'unaffected.' Differences in SNP alleles between affected and unaffected individuals then suggest an association between that allele and the phenotype described. The majority o f published studies in complex diseases are single SNP studies derived using a candidate gene-based approach, as described above. However, another method is emerging that has the potential to increase the power to detect associations without the need to intensively study multiple polymorphisms for associations 4 0. Haplotypes represent a method to maximize the information generated for each SNP genotyped. Only selected htSNPs need to be genotyped initially, in order to resolve the underlying haplotype structure of a region of interest. Once a particular haplotype is associated with outcome from the disease of interest, further effort may be made to identify a causative SNP (or SNPs). This method of discovering novel haplotypes and SNPs associated with outcomes is subject to its own limitations. Inference of haplotype structure from unphased genotype data involves some uncertainty, unless prior known haplotypes (from family data) are incorporated into the study design. Thus, incorporation of some amount of error is implicit from the start of the study. Another limitation is the possibility of type I error (false positive associations) arising from multiple statistical 10 tests performed. Selection of a limited number of candidate genes and htSNPs from the outset of the study can restrict the number of tests necessary, and thus reduce the possibility of spurious associations. Numerous potentially causative polymorphisms may also be missed using the candidate gene approach, because functional polymorphisms contained within unselected genes wi l l not be assayed. Similarly, functional polymorphisms may lie outside any known genes and are very unlikely to be chosen using the candidate gene approach. Defining the beginning of regions of the genome containing genes is a controversial topic, and can affect the likelihood that a causative polymorphism is selected for genotyping using the candidate gene approach. Linkage disequilibrium can extend for large physical distances, and can extend beyond the defined borders of a gene of interest, thus increasing the chances that a haplotype-based approach may capture a functional SNP lying outside the gene. Nonetheless, the possibility that a functional SNP may not be captured or selected remains a risk of candidate gene-based approaches. 11 1.4 IL-10/IL-18 Pathway 1.4.1 Interleukin-10 lnterleukin-10 is a Th2-polarizing, anti-inflammatory cytokine that down-regulates the expression of other cytokines 4 1 . Initially labeled cytokine synthesis inhibiting factor 4 2, IL-10 was renamed an interleukin due to its pleiotropic effects 4 3. IL-10 is a 18.5 kilodalton (kDa) protein, produced in macrophages 4 4, T cel ls 4 2 , B cel ls 4 5 , mast ce l ls 4 6 and keratinocytes 4 7. The Epstein-Barr virus (EBV, also known as human herpesvirus 4), a member of the Herpesviridae family, possess an open reading frame with considerable homology to human IL-10, suggesting gene capture at some point in E B V evolution 4 5 . The E B V homologue of IL-10, while able to suppress the system's usual reaction to viral infection, is unable to stimulate many of the other responses to human IL-10 (hIL-10), a distinction mediated by subtle differences between the ability of h lL -10 and E B V IL-10 to bind the IL-10 receptor 4 8. IL-10 binds to its receptor components, IL-10R1 and IL-10R2, which form a heterotetramer 4 9' 5 0. Signaling though the IL-10 receptor activates a Janus tyrosine kinase (Jak)/signal transducer and activator of transcription (STAT) pathway 5 1\" 5 3 . IL-10 ligand binding leads to expression of suppressor of cytokine signaling (SOCS) 3, which goes on to target cytokine receptor subunits possessing a so-called \"SOCS box\" (including IL-6) for degradation via ubiquitin tagging and proteolysis. Thus, IL-10 can diminish a cell's capacity to respond to cytokine stimuli. The SOCS protein also inhibits macrophage activation following LPS stimulation by interfering with expression of TNF-ot and inducible nitric oxide synthase ( iNOS) 4 1 , indicating that IL-10 can directly down-regulate 12 the expression of T N F - a following inflammatory stimulus. Other potential mechanisms of suppression of pro-inflammatory cytokine expression following IL-10 ligand binding are controversial, but may include inhibition of N F - K B translocation to the nucleus (and thus prevention of expression of numerous pro-inflammatory cytokines containing N F -K B consensus sequences in their promoters, e.g. T N F - a ) 5 4 ' 5 5 and inhibition of p38 mitogen-activated protein kinase-mediated stabilization of pro-inflammatory cytokine m R N A s 5 5 . IL-10 additionally inhibits the phosphorylation of STAT1 , preventing monocytes from responding to interferon-gamma (IFN-y), and thus preventing T helper cell-type I (Th l ) polarization from occurring 5 6.Thus, reception of the IL-10 signal by a cell dampens its ability to signal via pro-inflammatory pathways in several ways. In these ways, IL-10 acts as a potent immune regulatory cytokine, critically reducing the expression of T h l , pro-inflammatory cytokines. The IL-10 gene is 5.2 kb in length, comprised of 5 exons 5 7 , located on CO chromosome lq31-32 . Polymorphisms in and haplotypes of the IL-10 gene have been known to alter expression of the gene and serum levels of the IL-10 protein, as well as outcomes from inflammatory diseases, for several years 5 9. Genetic control over variation in production of IL-10 following stimuli is estimated at between 50% and 7 0 % 6 0 ' 6 1 , indicating the large role for SNPs and haplotypes in outcomes from diseases involving serum IL-10. Three SNPs within the promoter region of the IL-10 gene have received considerable attention with respect to variation in serum IL-10 levels and outcomes from inflammatory diseases: -1117 A / G (often called -1082 A / G , see Appendix A) , -854 C /T (often called -819 C/T) and -627 C / A (often called -592 C / A ) . Individual genotypes and 13 haplotypes of these SNPs have been linked to alterations in serum IL-10 levels and outcomes from inflammatory stimuli such as C P B surgery and sepsis 6 2 \" 6 4 . 1.4.2 Interleukin-18 The IL-18 gene is 26 kb in length, located on chromosome 1 Iq22.2-22.3 6 S. The IL-18 gene is comprised of 7 exons, two of which are non- coding 6 6 . The IL-18 gene in humans has two promoters, one located upstream of exon 1 (i.e. further upstream from the start site of translation than the second promoter) possessing a recognition sequence for interferon-gamma consensus sequence binding protein (ICSBP sequence: T G C T T T C A C T T C T C ) and a second located in intron 1 (i.e. between the two non-coding exons) possessing a recognition sequence for the PU. 1 transcription factor (sequence: T T C C T C ) 6 6 6 7. Each promoter possesses some constitutive activity and some varying ability to respond to up-regulation by LPS signaling 6 6 . IL-18 is typically classified as a pro-inflammatory, Thl -polariz ing cytokine due to its ability to stimulate IFN-y production 6 8. IL-18 does, however, possess some Th2-polarizing ability based on its capacity as a co-inducer of IL-13 production along with IL-2 6 9 and its ability to induce IL-4 and IL-10 upon co-activation with anti-CD3 antibodies 7 0. Thus, it may be more appropriate to view IL-18 as a potentiator for either the T h l or Th2 pathways, depending on the pre-existing cytokine pattern. Functional effects of IL-18, aside from induction of cytokine production, include up-regulation of FasL expression on natural killer (NK) cells, increasing N K cell cytotoxicity 7 1 , and 14 increasing neutrophil activity, including synthesis of reactive oxygen species, cytokine 7 7 production and degranulation 7 ^ IL-18 is produced as an 24kDa pro-protein by immune cells such as monocytes , Kupffer ce l ls 7 4 and dendritic cel ls 7 5 , but also by non-immune cells including 1ft 11 1H 7 0 keratinocytes , osteoblasts , adrenal cortex cells and mucosal cells . Stimulation of the cells by lipopolysaccharide (LPS) 8 0 or Fas ligand (FasL) 8 1 initiates production of the mature, 18kDa form of IL-18. This occurs either via cleavage by caspase-1, also known as interleukin-1 beta-converting enzyme (ICE), after aspartate residue 35, or via a caspase-1 independent pathway . Serum levels of IL-18 in healthy individuals are typically in the range 200-400 pg/mL, but can peak at concentrations greater than 1000 pg/mL 24-48 hours following an inflammatory stimulus such as sepsis 8 2. A recent study suggests that urine levels of IL-18 upon admission to the intensive care unit (ICU) can be used as a diagnostic marker for renal dysfunction and a unique predictor of mortality , making IL-18 a potential target for therapeutic intervention in clinical treatment of inflammatory diseases. 1.4.3 IL-18 Receptors IL-18 signals through two membrane-bound receptor molecules, IL-18 receptor-1 (IL-18R1), also known as l L - 1 8 R a , and the IL-18 receptor-associated protein (IL-18RAP), also known as IL -18Rp 8 4 . While IL-18R1 is the ligand-binding subunit o f the receptor complex, IL -18RAP has a longer cytoplasmic tail and is necessary for O f intracellular transduction of the signal . Signaling follows from binding of IL-18 to its 15 receptor complex and involves a series of molecules that bear similarity to the Tol l - l ike receptors (TLRs) and IL-1 receptor signaling. The cytoplasmic tail of the IL -18RAP protein contains a motif known as the TIR (Toll-like/IL-1 receptor) domain, based on the sequence similarity to the T L R s and I L - I R s 8 6 . Intracellular signaling downstream of the IL-18 receptor involves intermediates myeloid differentiation factor-88 (MyD88), interleukin-1 receptor-associated kinases ( IRAK) 1 and 4, and tumor necrosis factor receptor-associated factor-6 (TRAF-6 ) 8 7 . Signaling after IL-18 binding to its receptor complex activates downstream gene transcription through either the AP-1 or N F - K B transcription factors, and initiates transcription of genes containing binding sequences of these transcription factors, including T N F - a and IL -10 8 7 \" 9 0 . IL-18 acts in synergy with IL-12 to induce expression of IFN-y, using both STAT -4 (from 1L-12 signaling) and A P -1 (from IL-18 signaling) to up-regulate IFN-y expression. The synergistic activities of IL-18 and IL-12 occur through mutual up-regulation of expression of receptor subunits: that is, binding of IL-12 to its receptor increases cell surface expression of the IL-18 receptor, and vice versa 9 1 . 1.4.4 IL-18 Binding Protein The interleukin-18 binding protein (IL-18BP) is a natural, soluble serum antagonist of IL-18, inhibiting the Thl-polarizing effects of IL-18 . The IL-18BP gene is 8.3 kb in length, located on chromosome 1 l q l3 9 3 . The 40-55kDa IL -18BP protein is not structurally related to either IL-18 receptor component 9 4 ' 9 5, but is instead homologous to proteins produced by the Poxvirus family that reduce T h l immunity in Poxvirus-infected hosts 9 6 . Interestingly, the Poxvirus homologues of the IL-18BP are thought to have 16 derived from the human IL-18BP gene earlier in Poxvirus evolution 9 7 . Altered serum levels of IL-18BP and dysregulated IL-18/IL-18BP balance can alter outcomes from inflammatory conditions such as graft-versus-host disease 9 8, sepsis 9 5 , hemophagocytic syndrome (a syndrome characterized by uncontrolled activation of Thl - type lymphocytes and macrophages) 9 9 and adult-onset Stil l 's disease 1 0 0 . IL-18BP expression is up-regulated by IL-18, IL-12 and IFN-y , but not other T h l cytokines such as IL - l a / | 3 or T N F - a , nor by Th2 cytokines such as IL-4 or IL -10 1 0 1 . 17 1.5 Overview and Hypothesis Given the importance of IL-10 and the IL-18 pathway in inflammatory diseases, we have focused on these genes in two cohorts related to inflammatory diseases: a cardiac surgical cohort and an intensive care unit cohort. These genes are key modulators of the systemic response to inflammatory insults, as detailed above. Variations within these genes have either been shown previously to have an effect on outcomes from these diseases, or logically could be postulated to have an effect. We designed our studies around a cohort design, and restricted our analyses to well-defined outcome measures in these cohorts. Our central hypothesis was that variation in the IL-10 and IL-18 pathway genes alter outcomes from cardiopulmonary bypass surgery and critical illness in Caucasians. We derived haplotypes from publicly available genotype data for the IL-10 and IL-18 pathway genes, from which we selected htSNPs using L D as a clustering tool. The selected htSNPs for each gene were genotyped in our cohorts of interest, and haplotypes were inferred for analysis. Analysis of primary clinical outcomes by haplotypes identified either haplotypes of interest, or pointed to unique htSNPs of interest. From there, analysis proceeded following the previously identified haplotype or htSNP, using a priori defined outcome variables (primary clinical, secondary clinical and intermediate) to test for associations. We first tested for significant associations in the cardiac surgery cohort (Chapters 2-4) as a derivation cohort, and then repeated the analyses in the intensive care unit cohort (Chapter 5) as a validation cohort. 18 1.6 References 1. Lander, E. S. et al. Initial sequencing and analysis of the human genome. Nature 409, 860-921 (2001). 2. Venter, J. C. et al. The sequence of the human genome. Science 291, 1304-51 (2001). 3. Finishing the euchromatic sequence of the human genome. Nature 431, 931 -45 (2004). 4. (National Centres for Biotechnology Information, 2006). 5. Bone, R. C. The sepsis syndrome. Definition and general approach to management. Clin Chest Med 17, 175-81 (1996). 6. Sharma, M . et al. Release of pro-inflammatory mediators during myocardial ischemia/reperfusion in coronary artery bypass graft surgery. Mol Cell Biochem 247, 23-30 (2003). 7. Gu, Y . J . , Mariani, M . A. , Boonstra, P. W., Grandjean, J . G. & van Oeveren, W. Complement activation in coronary artery bypass grafting patients without cardiopulmonary bypass: the role of tissue injury by surgical incision. Chest 116, 892-8 (1999). 8. L i , S., Price, R., Phiroz, D., Swan, K. & Crane, T. A . Systemic inflammatory response during cardiopulmonary bypass and strategies. J Extra Corpor Technol 37, 180-8 (2005). 9. Harig, F., Feyrer, R., Mahmoud, F. O., Blum, U. & von der Emde, J . Reducing the post-pump syndrome by using heparin-coated circuits, steroids, or aprotinin. Thorac Cardiovasc Surg 47, 111-8 (1999). 19 10. Bone, R. C , Grodzin, C. J . & Balk, R. A. Sepsis: a new hypothesis for pathogenesis of the disease process. Chest 112, 235-43 (1997). 11. Halter, J . et al. Evidence of systemic cytokine release in patients undergoing cardiopulmonary bypass. J Extra Corpor Technol 37, 272-7 (2005). 12. Bone, R. C. Sir Isaac Newton, sepsis, SIRS, and C A R S . Crit Care Med 24, 1125-8 (1996). 13. Weigand, M . A. , Horner, C , Bardenheuer, H. J . & Bouchon, A. The systemic inflammatory response syndrome. Best Pract Res Clin Anaesthesiol 18, 455-75 (2004). 14. Sorensen, T. I., Nielsen, G. G., Andersen, P. K. & Teasdale, T. W. Genetic and environmental influences on premature death in adult adoptees. N Engl J Med 318, 727-32 (1988). 15. Kruglyak, L. & Nickerson, D. A . Variation is the spice of life. Nat Genet 27, 234-6 (2001). 16. Tomso, D. J . et al. Functionally distinct polymorphic sequences in the human genome that are targets for p53 transactivation. Proc Natl Acad Sci USA 102, 6431-6 (2005). 17. Fritz, D. T., Jiang, S., X u , J . & Rogers, M . B. A Polymorphism in a Conserved Post-Transcriptional Regulatory Mot i f Alters Bmp2 Rna:Protein Interactions. Mol Endocrinol (2006). 18. Miyamoto, Y . , Nakashima, E., Hiraoka, H., Ohashi, H. & Ikegawa, S. A type II collagen mutation also results in oto-spondylo-megaepiphyseal dysplasia. Hum Genet 118, 175-8 (2005). 20 19. The International HapMap Project. Nature 426, 789-96 (2003). 20. Altshuler, D. et al. A haplotype map of the human genome. Nature 437, 1299-320 (2005). 21. Andrawiss, M . First phase of HapMap project already helping drug discovery. Nat Rev Drug Discov 4, 947 (2005). 22. Zeggini, E. et al. A n evaluation of HapMap sample size and tagging SNP performance in large-scale empirical and simulated data sets. Nat Genet 37, 1320-2 (2005). 23. Sakaeda, T., Nakamura, T. & Okumura, K. Pharmacogenetics of drug transporters and its impact on the pharmacotherapy. Curr Top Med Chem 4, 1385-98 (2004). 24. Cariou, A. , Chiche, J . D., Charpentier, J . , Dhainaut, J . F. & Mira, J. P. The era of genomics: impact on sepsis clinical trial design. Crit Care Med 30, S341-8 (2002). 25. Abraham, E. et al. Double-blind randomised controlled trial of monoclonal antibody to human tumour necrosis factor in treatment of septic shock. N O R A S E P T II Study Group. Lancet 351, 929-33 (1998). 26. Wilson, A . G., Symons, J. A. , McDowel l , T. L., McDevitt, H. O. & Duff, G. W. Effects of a polymorphism in the human tumor necrosis factor alpha promoter on transcriptional activation. Proc Natl Acad Sci USA 94, 3195-9 (1997). 27. Altarescu, G., Zimran, A. , Michelakakis, H. & Elstein, D. TNF-alpha levels and TNF-alpha gene polymorphism in type I Gaucher disease. Cytokine 31, 149-52 (2005). 21 28. Cuchacovich, M . et al. Tumour necrosis factor-alpha (TNF-alpha) levels and influence of -308 TNF-alpha promoter polymorphism on the responsiveness to infliximab in patients with rheumatoid arthritis. Scand J Rheumatol 33, 228-32 (2004). 29. Daly, A . K. & King, B. P. Pharmacogenetics of oral anticoagulants. Pharmacogenetics 13, 247-52 (2003). 30. Ando, Y . et al. Pharmacogenetic associations of C Y P 2 C 1 9 genotype with in vivo metabolisms and pharmacological effects of thalidomide. Cancer Biol Ther 1, 669-73 (2002). 31. Ueyama, K. et al. P M E A coating of pump circuit and oxygenator may attenuate the early systemic inflammatory response in cardiopulmonary bypass surgery. ^ 0 / 0 750 ,369 -72 (2004). 32. Jensen, E. et al. Influence of two different perfusion systems on inflammatory response in pediatric heart surgery. Ann Thorac Surg 75, 919-25 (2003). 33. L i , J . et al. Transient adhesion of platelets in pump-oxygenator systems: influence of S M A and nitric oxide treatments. JBiomater Sci Polym Ed 10, 235-46 (1999). 34. Merry, A . F. Bivalirudin, blood loss, and graft patency in coronary artery bypass surgery. Semin Thromb Hemost 30, 337-46 (2004). 35. Hazama, S. et al. Inflammatory response after coronary revascularization: off-pump versus on-pump (heparin-coated circuits and poly2methoxyethylacrylate-coated circuits). Ann Thorac Cardiovasc Surg 10, 90-6 (2004). 22 36. Chen, J . et al. Platelet FcgammaRIIA H i s l 31 A r g polymorphism and platelet function: antibodies to platelet-bound fibrinogen induce platelet activation. J Thromb Haemost 1, 355-62 (2003). 37. Knapp, M . & Becker, T. Family-based association analysis with tightly linked markers. Hum Hered 56, 2-9 (2003). 38. Ratjen, F. & Doring, G. Cystic fibrosis. Lancet 361, 681-9 (2003). 39. Newton-Cheh, C. & Hirschhom, J . N. Genetic association studies of complex traits: design and analysis issues. Mutat Res 573, 54-69 (2005). 40. de Bakker, P. I. et al. Efficiency and power in genetic association studies. Nat Genet 37, 1217-23 (2005). 41. Qasimi, P. et al. Divergent Mechanisms Utilized by SOCS3 to Mediate Interleukin-10 Inhibition of Tumor Necrosis Factor {alpha} and Nitric Oxide Production by Macrophages. J Biol Chem 281, 6316-24 (2006). 42. Fiorentino, D. F., Bond, M . W. & Mosmann, T. R. Two types of mouse T helper cell. IV. Th2 clones secrete a factor that inhibits cytokine production by T h l clones. J Exp Med 170, 2081-95 (1989). 43. Spits, H. & de Waal Malefyt, R. Functional characterization of human IL-10. Int Arch Allergy Immunol 99, 8-15 (1992). 44. de Waal Malefyt, R., Abrams, J . , Bennett, B., Figdor, C. G. & de Vries, J . E. Interleukin 10(IL-10) inhibits cytokine synthesis by human monocytes: an autoregulatory role of IL-10 produced by monocytes. J Exp Med 174, 1209-20 (1991). 23 45. Vieira, P. et al. Isolation and expression of human cytokine synthesis inhibitory factor c D N A clones: homology to Epstein-Barr virus open reading frame BCRF I . Proc Natl Acad Sci USA 88, 1172-6(1991). 46. L in , T. J . & Befus, A . D. Differential regulation of mast cell function by IL-10 and stem cell factor. J Immunol 159, 4015-23 (1997). 47. Grandjean-Laquerriere, A., Le Naour, R., Gangloff, S. C. & Guenounou, M . Differential regulation of TNF-alpha, IL-6 and IL-10 in UVB-irradiated human keratinocytes via cyclic AMP/protein kinase A pathway. Cytokine 23, 138-49 (2003). 48. Yoon, S. I., Jones, B. C., Logsdon, N. J . & Walter, M . R. Same structure, different function crystal structure of the Epstein-Barr virus IL-10 bound to the soluble IL-10R1 chain. Structure 13, 551-64 (2005). 49. L iu , Y . , Wei , S. H., Ho, A . S., de Waal Malefyt, R. & Moore, K. W. Expression cloning and characterization of a human IL-10 receptor. J Immunol 152, 1821-9 (1994). 50. Kotenko, S. V . et al. Identification and functional characterization of a second chain of the interleukin-10 receptor complex. Embo J 1 6 , 5894-903 (1997). 51. Karaghiosoff, M . et al. Partial impairment of cytokine responses in Tyk2-deficient mice. Immunity 13, 549-60 (2000). 52. Welte, T. et al. STAT3 deletion during hematopoiesis causes Crohn's disease-like pathogenesis and lethality: a critical role of STAT3 in innate immunity. Proc Natl Acad Sci USAXQQ, 1879-84 (2003). 24 53. Finbloom, D. S. & Winestock, K. D. IL-10 induces the tyrosine phosphorylation of tyk2 and Jak l and the differential assembly of S T A T 1 alpha and STAT3 complexes in human T cells and monocytes. J Immunol 155, 1079-90 (1995). 54. Shames, B. D. et al. Interleukin-10 stabilizes inhibitory kappaB-alpha in human monocytes. Shock 10, 389-94 (1998). 55. Schottelius, A . J . , Mayo, M . W., Sartor, R. B. & Baldwin, A. S., Jr. Interleukin-10 signaling blocks inhibitor of kappaB kinase activity and nuclear factor kappaB D N A binding. J Biol Chem 21 A, 31868-74 (1999). 56. Ito, S. et al. Interleukin-10 inhibits expression of both interferon alpha- and interferon gamma- induced genes by suppressing tyrosine phosphorylation of STAT1 . Blood 93, 1456-63 (1999). 57. K i m , J . M . et al. Structure of the mouse IL-10 gene and chromosomal localization of the mouse and human genes. J Immunol 148, 3618-23 (1992). 58. Eskdale, J . , Kube, D., Tesch, H. & Gallagher, G. Mapping of the human IL10 gene and further characterization of the 5' flanking sequence. Immunogenetics 46, 120-8 (1997). 59. Eskdale, J . et al. Interleukin 10 secretion in relation to human IL-10 locus haplotypes. Proc Natl Acad Sci USA 95, 9465-70 (1998). 60. Reuss, E. et al. Differential regulation of interleukin-10 production by genetic and environmental factors~a twin study. Genes Immun 3, 407-13 (2002). 61. Westendorp, R. G. et al. Genetic influence on cytokine production and fatal meningococcal disease. Lancet 349, 170-3. (1997). 25 Galley, H. F., Lowe, P. R., Carmichael, R. L. & Webster, N. R. Genotype and interleukin-10 responses after cardiopulmonary bypass. Br J Anaesth 91, 424-6 (2003). Cunningham, L. M. , Chapman, C , Dunstan, R., Bel l , M . C. & Joske, D. J . Polymorphisms in the interleukin 10 gene promoter are associated with susceptibility to aggressive non-Hodgkin's lymphoma. Leuk Lymphoma 44, 251-5 (2003). Suarez, A . , Castro, P., Alonso, R., Mozo, L. & Gutierrez, C. Interindividual variations in constitutive interleukin-10 messenger R N A and protein levels and their association with genetic polymorphisms. Transplantation 75, 711-7 (2003). Nolan, K. F., Greaves, D. R. & Waldmann, H. The human interleukin 18 gene IL18 maps to 1 Iq22.2-q22.3, closely linked to the DRD2 gene locus and distinct from mapped I D D M loci. Genomics 51,161-3 (1998). K i m , Y . M . et al. Roles of IFN consensus sequence binding protein and P U . l in regulating IL-18 gene expression. J Immunol 163, 2000-7 (1999). el Kares, R., Abdelhak, S. & Dellagi, K. Genomic structure and characterisation of the promoter region of the human IL-18 gene. Arch Inst Pasteur Tunis 11, 55-8 (2000). Okamura, H. et al. Cloning of a new cytokine that induces IFN-gamma production by T cells. Nature 378, 88-91 (1995). Hoshino, T., Wiltrout, R. H. & Young, H. A. IL-18 is a potent coinducer of IL-13 in N K and T cells: a new potential role for IL-18 in modulating the immune response. J Immunol 162, 5070-7 (1999). 26 70. Hoshino, T., Yagita, H., Ortaldo, J. R., Wiltrout, R. H. & Young, H. A. In vivo administration of IL-18 can induce IgE production through Th2 cytokine induction and up-regulation of CD40 ligand (CD154) expression on CD4+ T cells. Eur J Immunol 30, 1998-2006 (2000). 71. Dao, T., Ohashi, K., Kayano, T., Kurimoto, M . & Okamura, H. Interferon-gamma-inducing factor, a novel cytokine, enhances Fas ligand-mediated cytotoxicity o f murine T helper 1 cells. Cell Immunol 173, 230-5 (1996). 72. Leung, B. P. et al. A role for IL-18 in neutrophil activation. J Immunol 167, 2879-86 (2001). 73. Gu, Y . et al. Activation of interferon-gamma inducing factor mediated by interleukin-1 beta converting enzyme. Science 275, 206-9 (1997). 74. Matsui, K. et al. Propionibacterium acnes treatment diminishes CD4+ NK1.1+ T cells but induces type I T cells in the liver by induction of IL-12 and IL-18 production from Kupffer cells. J Immunol 159, 97-106 (1997). 75. Stoll, S. et al. Production of functional IL-18 by different subtypes of murine and human dendritic cells (DC): DC-derived IL-18 enhances IL-12-dependent T h l development. Eur J Immunol 28, 3231-9 (1998). 76. Stoll, S. et al. Production of IL-18 (IFN-gamma-inducing factor) messenger R N A and functional protein by murine keratinocytes. J Immunol 159, 298-302 (1997). 77. Udagawa, N. et al. Interleukin-18 (interferon-gamma-inducing factor) is produced by osteoblasts and acts via granulocyte/macrophage colony-stimulating factor and not via interferon-gamma to inhibit osteoclast formation. J Exp Med 185, 1005-12 (1997). 27 78. Conti, B., Jahng, J . W., Tinti, C , Son, J. H. & Joh, T. H. Induction of interferon-gamma inducing factor in the adrenal cortex. J Biol Chem 272, 2035-7 (1997). 79. Pizarro, T. T. et al. IL-18, a novel immunoregulatory cytokine, is up-regulated in Crohn's disease: expression and localization in intestinal mucosal cells. J Immunol 162,6829-35 (1999). 80. Seki, E. et al. Lipopolysaccharide-induced IL-18 secretion from murine Kupffer cells independently of myeloid differentiation factor 88 that is critically involved in induction of production of IL-12 and IL-1 beta. J Immunol 166, 2651-7 (2001). 81. Itoi, H. et al. Fas ligand-induced caspase-1-dependent accumulation of interleukin-18 in mice with acute graft-versus-host disease. Blood 98, 235-7 (2001). 82. Emmanuilidis, K. et al. Differential regulation of systemic IL-18 and IL-12 release during postoperative sepsis: high serum IL-18 as an early predictive indicator o f lethal outcome. Shock 18, 301-5 (2002). 83. Parikh, C. R., Abraham, E., Ancukiewicz, M . & Edelstein, C. L. Urine IL-18 is an early diagnostic marker for acute kidney injury and predicts mortality in the intensive care unit. J Am Soc Nephrol 16, 3046-52 (2005). 84. Sergi, B. & Penttila, I. Interleukin 18 receptor. J Biol Regul Homeost Agents 18, 55-61 (2004). 85. Azam, T. et al. Identification of a critical Ig-like domain in IL-18 receptor alpha and characterization of a functional IL-18 receptor complex. J Immunol 171, 6574-80 (2003). 28 86. Dunne, A. & O'Neil l , L. A . The interleukin-1 receptor/Toll-like receptor superfamily: signal transduction during inflammation and host defense. Sci STKE 2003, re3 (2003). 87. Chandrasekar, B. et al. The pro-atherogenic cytokine interleukin-18 induces C X C L 1 6 expression in rat aortic smooth muscle cells via MyD88, interleukin-1 receptor-associated kinase, tumor necrosis factor receptor-associated factor 6, c-Src, phosphatidylinositol 3-kinase, Akt, c-Jun N-terminal kinase, and activator protein-1 signaling. J Biol Chem 280, 26263-77 (2005). 88. Cho, M . L. et al. Interleukin-18 induces the production of vascular endothelial growth factor ( V E G F ) in rheumatoid arthritis synovial fibroblasts via A P - 1 -dependent pathways. Immunol Lett 103, 159-66 (2006). 89. Chandrasekar, B. et al. Activation of intrinsic and extrinsic proapoptotic signaling pathways in interleukin-18-mediated human cardiac endothelial cell death. J Biol Chem 279, 20221-33 (2004). 90. Takeuchi, D. et al. Interleukin 18 causes hepatic ischemia/reperfusion injury by suppressing anti-inflammatory cytokine expression in mice. Hepatology 39, 699-710(2004). 91. Nakahira, M . et al. Synergy of IL-12 and IL-18 for IFN-gamma gene expression: IL-12-induced STAT4 contributes to IFN-gamma promoter activation by up-regulating the binding activity of IL-18-induced activator protein 1. J Immunol 168, 1146-53 (2002). 29 92. Faggioni, R. et al. IL-18-binding protein protects against lipopolysaccharide-induced lethality and prevents the development of Fas/Fas ligand-mediated models of liver disease in mice. J Immunol 167, 5913-20 (2001). 93. Novick, D. et al. Interleukin-18 binding protein: a novel modulator of the T h l cytokine response. Immunity 10, 127-36 (1999). 94. Aizawa, Y . et al. Cloning and expression of interleukin-18 binding protein. FEBS Lett 445, 338-42 (1999). 95. Novick, D. et al. A novel IL-18BP EL ISA shows elevated serum IL-18BP in sepsis and extensive decrease of free IL-18. Cytokine 14, 334-42 (2001). 96. Reading, P. C. & Smith, G. L. Vaccinia virus interleukin-18-binding protein promotes virulence by reducing gamma interferon production and natural kil ler and T-cel l activity. J Virol 77, 9960-8 (2003). 97. Watanabe, M . et al. Evolution of interleukin-18 binding proteins and interleukin-1 receptor, type II proteins. IntJMolMed 15, 561-6 (2005). 98. Zecchina, G. et al. Interleukin-18 binding protein in acute graft versus host disease and engraftment following allogeneic peripheral blood stem cell transplants. J Hematother Stem Cell Res 10, 769-76 (2001). 99. Mazodier, K. et al. Severe imbalance of IL-18/IL-18BP in patients with secondary hemophagocytic syndrome. Blood 106, 3483-9 (2005). 100. Kawashima, M . et al. Levels of interleukin-18 and its binding inhibitors in the blood circulation of patients with adult-onset Still's disease. Arthritis Rheum 44, 550-60 (2001). 30 Veenstra, K. G., Jonak, Z. L., Trul l i , S. & Gollob, J . A . IL-12 induces monocyte IL-18 binding protein expression via IFN-gamma. J Immunol 168, 2282-7 (2002). 31 C H A P T E R 2\": Novel haplotype of the interleukin-10 gene associated with improved outcome following cardiopulmonary bypass surgery 2.1 Introduction Cardiopulmonary bypass surgery for coronary artery bypass grafting and valve replacement typically involves the extracorporeal circulation of blood using cardiopulmonary bypass (CPB). C P B 1 and the surgery itself 2 initiate an inflammatory response. Whi le an appropriate inflammatory response is a necessary component of wound healing, an inappropriate response with excessive inflammation can lead to organ dysfunction and prolonged hospital stay3. Variation in post-surgery inflammation is not wholly accounted for by classical risk factors such as age, pre-operative health and C P B or surgery time 4. Genetic variation among individuals explains a portion of the inter-individual responses to inflammatory stimuli 5 . Inflammatory mediator genes are o f particular relevance because variations in these mediators may be tightly linked to control o f inflammation. Interleukin-10, an anti-inflammatory cytokine, increases in response to surgery 6' 7 and in response to other inflammatory diseases such as sepsis 8, ischemia-reperfusion injury 1 and atherosclerosis9. The genetic component of the inter-individual variation in production of, and in serum levels of, IL-10 may be as high as 50%'\u00C2\u00B0. Three polymorphic loci within the promoter of the IL-10 gene (-1117A/G, -854C/T, -627C/A) have been studied to elucidate the link between genotype (or haplotype) and serum concentrations 'A version of this chapter has been submitted to the journal Anaesthesiology. 32 of IL-10 (intermediate phenotype), as well as between genotype (or haplotype) and clinical outcome (phenotype). Most studies show that the -1117A, -854T, -627A haplotype is associated with lower serum levels of IL-10, while the -1117G, 854C, -627C haplotype is associated with higher levels of I L - IO 1 ' 1 2 . In contrast, Galley et al. found that the -1117G allele was associated with lower serum levels of IL-10 and less organ dysfunction post -CPB 6 . Thus, the role that IL-10 genotype or haplotype plays in modulating inflammation, altering organ dysfunction, and altering clinical outcome after cardiopulmonary bypass is controversial. Accordingly, we assessed the relationship between polymorphisms and haplotypes of the IL-10 gene and clinical outcome (need for prolonged I C U care) and clinical measures that reflect systemic inflammation following cardiopulmonary bypass surgery. To test for a biologically plausible explanation for our results we also measured serum concentration of IL-10. We discovered that a novel haplotype within the group of haplotypes containing the -1117G, -854C and -627C alleles (previously associated with high serum levels of IL-10) was associated with improved clinical outcome, measured as less frequent need for prolonged ICU care, a less severe inflammatory response and less respiratory organ dysfunction following CPB . We confirmed that this haplotype was associated with greater serum IL-10 concentration post-CPB, thus providing a possible explanation for our results. 33 2.2 Methods The Research Ethics Board of Providence Health Care and the University of British Columbia approved this study. Patient cohort A l l patients admitted to the Cardiac Surgery Intensive Care Unit (CSICU) of St. Paul's Hospital following cardiopulmonary bypass surgery between February 2001 and May 2002 were eligible for entry into this study. We recruited 850 patients who had on-pump cardiopulmonary bypass surgery to this study. We restricted our analysis to Caucasian patients (87%) who were successfully genotyped (84%) to decrease the potential confounding influence of population admixture secondary to ethnic diversity on associations between genotype and phenotype. Thus, 603 patients made up our final patient cohort for analysis. Phenotypic data were collected via retrospective chart review. Clinical phenotype We chose need for prolonged I C U care (greater than 72 hours) as our primary outcome variable because it reflects organ dysfunction , is directly related to increased costs of hospital stay 1 4 and occurs with sufficient frequency to allow statistical power. Prolonged I C U care is a marker of adverse outcome used by several authors 1 5\" 1 9. Nakasuji et al found that an I C U stay of greater than or equal to 3 day(72 hours) was a sensitive and specific marker of adverse outcome which reflected pulmonary and cardiovascular organ dysfunction 1 5 , while Lawrence and colleagues found that the maximum predictive efficiency of the Parsonnet score - a score of 10 - was associated with a need for I C U 34 discharge patients from our post-CPB surgical ICU is protocol driven, making this measure a reasonable outcome variable. The lung is an organ where IL-10 plays particularly important role 7. Therefore, we assessed pulmonary dysfunction (PaCVFjC^ ratio immediately post-CPB) as a secondary outcome variable. Pa02/Fj02 is a measure of pulmonary dysfunction after cardiopulmonary bypass that is influenced by a systemic inflammatory response 2 0.As a clinical indicator reflecting the intensity of the post-CPB inflammatory response we chose leukocyte count measured immediately post-CPB as an further secondary outcome variable . We chose these measures because they were routinely collected as part o f post-operative care, are not as heavily confounded by common therapeutic intervention as other measures (e.g. blood pressure confounded by vasopressor 2 2 and inotrope 2 3 use) and have been extensively used as measures of intensity of the systemic inflammatory response and attendant pulmonary organ dysfunction 2 0 ' 2 1 . Intermediate Phenotype We measured serum concentrations of the IL-10 protein as an intermediate phenotype directly related to the IL-10 gene. Serum IL-10 concentrations were measured pre-operatively, and 4 and 24 hours post-operatively in Caucasian patients undergoing on-pump coronary artery bypass graft ( C A B G ) surgery using the Luminex bead-based bioassay system 2 4 (Luminex Corp., Austin, T X , USA) . 35 Tag SNP Selection To first determine IL-10 haplotypes we used unphased genotype data from the Seattle SNPs Program for Genomic Applications (http://pga.mbt.washington.edu) and from the University of Arizona Innate Immunity Program for Genomic Applications (http://innateimmunitv.net). Twelve haplotypes were then inferred from this data using the P H A S E , version 2.0 2 5 (Figure 2.1). P H A S E uses Bayesian methods to find the most likely haplotype pattern within a population from unphased genotype data. The resulting haplotypes were clustered into four clades according to similarity using the molecular evolutionary genetics analysis software package M E G A 2 2 6 (Figure 2.2). Three haplotype tag single nucleotide polymorphisms (htSNPs) (1. -627C/A, 2. 734G/T and 3. 3368G/A) identified 4 major haplotype clades; C G G , A G G , C T A , and C T G (Figure 2.1). Relationship between these htSNPs and previous literature Table 2.1 clarifies differences in position numbering between this sequence data, N C B I numbering, and numbering in a variety of relevant publications. We were unable to successfully genotype position -1117 of the IL-10 gene. Therefore we chose position 734 (Figure 2.1) as a SNP in complete linkage disequilibrium (D'=l) with position -1117. Position -854 has also been widely reported in the literature as potentially linked to serum levels of IL-10 and clinical outcomes and was not genotyped since -854 is in linkage disequilibrium with the polymorphism at position -627 (D'=l by VG2) (Figure 2.1). Figure 2.1 shows that the previously reported -1117G, 854C, -627C haplotype 36 subdivided into two distinct and novel clades by the tag SNP at position 3368. For this reason 3368 G / A was genotyped as a haplotype tag SNP. Genotyping D N A was extracted from peripheral blood samples using a QIAamp D N A Blood M i n i K i t (Qiagen Inc. Canada; Mississauga, ON). SNP genotypes were determined using the 5' nuclease, or TaqMan\u00C2\u00A9 polymerase chain reaction (PCR) method (Applied Biosystems; Foster City, C A ) 2 7 . These htSNPs were then genotyped in the 601 patients of our cohort undergoing CPB . Then we again used P H A S E to infer haplotypes for these 3 htSNPs in our patient cohort. The patient genotypes for these three htSNPs were in Hardy-Weinberg equilibrium, indicating that the cohort is a good sample of the relevant population. Sequences of the P C R primers and allele-specific probes used in genotyping for our htSNPs can be found in Appendix A . Statistics Work by Long and Langley 2 8 indicates that on the order of 500 individuals are sufficient to detect the presence of causative polymorphisms having small effect on outcomes. Thus, we have included 601 individuals in our study population. 37 Differences in continuous variables were assessed using Student's t-test for normally distributed data, and a Mann-Whitney U Test for non-normally distributed data. Logarithmic transformation was used to normalize IL-10 cytokine measurements where applicable, and differences in serum IL-10 concentrations 4 and 24 hours post-CPB were assessed using a repeated measure A N O V A model. Fisher's exact test was used to test for significant differences in discrete variables. A p-value less than or equal to 0.05 was taken to indicate a significant difference. Analysis was performed using SPSS v l 1.5 (SPSS, Chicago IL). Al le le frequencies were tested for Hardy-Weinberg equilibrium using the test of Guo and Thompson 2 9 . Using P H A S E , we inferred haplotypes for our patients based on unphased genotype data for the three htSNPs and performed further analyses based on patients' haplotype. We found one haplotype (the C T G haplotype) was distinct from the other three haplotype groups with respect to the primary clinical phenotype (need for prolonged ICU care) and found the C T G haplotype was associated with a lower frequency of the primary clinical outcome compared to all others. Therefore, for further analyses we compared patients possessing at least one copy of the C T G haplotype to all other patients. 38 2.3 Results Baseline Characteristics and Peri-Operative Markers There were no differences between patients with at least one copy of the C T G haplotype and all others in age, sex, body mass index (BMI), frequency of diabetes or smoking (Table 2.2). Similarly, there were no differences in pre-operative use of anti-hypertensives, angiotensin converting enzyme (ACE) inhibitors, beta-adrenergic receptor antagonists (beta-blockers) or aspirin (Table 2.2). There were no differences between patients with at least one copy of the C T G haplotype and all others in duration of surgery or bypass, or in cardioplegia temperature or use of hemostatic modifiers (Table 2.3). Primary Clinical Phenotype Patients possessing at least one copy of the C T G haplotype of the interleukin-10 gene had significantly lower need for prolonged ICU stay compared to all others (11 (3.4%) vs. 19 (6.9%); p=0.035). Markers of Inflammation Patients possessing at least one copy of the C T G haplotype of the IL-10 gene had higher PaCVFjCh ratio and lower post-operative neutrophil count after C P B surgery compared to all others. These patients had higher arterial partial pressure of oxygen to fraction of inhaled oxygen ratios immediately post-operatively compared to all others (mean (standard error) P a 0 2 / F j02 : 283 (6) vs. 264 (6); p=0.027).These patients also had 39 significantly lower peak neutrophil count immediately post-operatively (within 1 hour) compared to all others (9.7 (0.6) vs. 13.0 (1.6) X 10 9 /L, respectively; p-0.033). Intermediate Phenotype Patients possessing at least one copy of the C T G haplotype of the interleukin-10 gene had a significantly greater serum interleukin-10 protein concentration 4 and 24 hours post-operatively (p=0.01); approximately doubled in patients carrying the C T G haplotype compared to patients carrying all other haplotypes (Figure 2.3). There were no differences in serum IL-10 cytokine levels pre-operatively. Single SNP Analysis There were no significant differences among the primary clinical phenotype and markers of inflammation when analyzed for any of the haplotype tag SNPs individually (not shown). 40 2.4 Discussion Our key finding was that patients possessing at least one copy of the C T G haplotype had significantly less need for prolonged ICU care following C P B surgery. This favorable outcome is consistent with our observation of less clinical evidence of pulmonary organ dysfunction and inflammation post-CPB (better Pa02/Fj02 measurements, lower neutrophil count). Less clinical evidence of inflammation may be due to greater increases in serum IL-10 levels observed in patients carrying a C T G haplotype - an observation consistent with previous publications showing increased IL-10 production associated with SNP alleles within this haplotype haplotype\"' 1 2 . Need for prolonged ICU care following surgery is a marker of poor outcome following cardiac surgery 1 3 ' 1 4 ' 3 0 . Furthermore, need for prolonged ICU care is an important measure of increasing ICU bed requirements and costs 1 5 . Discharge from the cardiac surgery ICU following cardiopulmonary bypass surgery at our institution is protocol driven based on assessment of organ dysfunction. Therefore need for prolonged I C U care is a clinically relevant marker of the severity of organ dysfunction arising from the inflammatory response triggered by surgery and C P B . To support this hypothesis, we measured Pa02/Fj02 ratio and neutrophil count as clinical outcomes that directly reflect the degree of post-CPB inflammation. Patients possessing at least one copy of the C T G haplotype had decreased pulmonary dysfunction post-CPB compared to all others as measured by the Pa02/Fj02 ratio. Low ratio of arterial partial pressure of oxygen to fraction of inhaled oxygen is a 41 marker of pulmonary dysfunction following CPB 2 1 1 , therefore significantly increased PaCh/FjCb ratios observed in patients with at least one copy of the C T G haplotype are indicative of improved pulmonary function compared to all others. Patients possessing at least one copy of the C T G haplotype also experienced significantly lower post-operative circulating neutrophil levels, indicative of a less-active systemic inflammatory response compared to those without a copy of the C T G haplotype. Increase in circulating neutrophil count 3 1 is commonly associated with C P B surgery and may be associated with overactive complement activation and a poor recovery from C P B surgery 3 2. To understand the link between these clinical measures of inflammation and the IL-10 gene, we measured serum IL-10 levels before, 4 hours after and 24 hours after C P B surgery. The C T G haplotype of the IL-10 gene was associated with significantly greater serum IL-10 cytokine concentrations 4 and 24 hours post-operation compared to on-pump C A B G patients having all other haplotypes, despite no differences at baseline. Interleukin-10 is primarily an anti-inflammatory cytokine, leading to down-regulation of pro-inflammatory cytokines including IL-12 and tumor necrosis factor alpha 3 3 . Studies of IL-10 gene polymorphisms have found conflicting associations with serum IL-10 levels and clinical outcome following C P B likely due, in part, to differences in study design and patient population. The majority of studies are consistent with our current observations (Table 2.4): the A allele of the -1117 A / G SNP and the -1117A/-854T/-627A haplotype are associated with lower IL-10 production\"' 1 2 , while the G allele of the -1117 SNP and the -1117G/-854C/-627C haplotype are associated with increased 42 IL-10 production 1 2 ' 3 4 \" 3 7 . Figure 2.1 illustrates that our C T G haplotype of the IL-10 gene contains the G allele of the -1117 A / G S N P 1 2 , the C allele of the -854 C /T S N P 3 8 , the C allele of the -627 C / A S N P 3 9 , and has extensive overlap with the -1117G/-854C/-627C haplotype typically associated with greater production of IL- IO 1 1. Although the -1117 A / G polymorphism was not genotyped in our study, the 734 G/T polymorphism which is in linkage disequilibrium with the -1117 polymorphism was genotyped. No significant difference in serum IL-10 concentrations was observed for the 734 G/T SNP. The -1117A allele has been found to disrupt binding of the transcription factor P U . l to its consensus sequence ( G G A A ) , possibly accounting for the decreased production of IL -10 1 0 . We found no significant association between individual SNP alleles and our primary clinical outcome which emphasizes the importance of the haplotype-based analysis. We chose htSNPs based on the ability to differentiate haplotype clades and, when alternative SNP choices were present, we chose SNPs previously reported in the literature. Haplotypes represent a powerful method for utilizing the linkage disequilibrium between neighboring SNPs. Groups of SNPs appearing as haplotype blocks are thought to be present throughout the genome, extending as far as 170kb from the SNP of interest 4 0. Thus, choosing tag SNPs allows us to investigate the underlying haplotype structure using relatively few polymorphic loci. This strategy improves upon the traditional SNP-based approach to disease association studies, whereby polymorphic loci are chosen from the gene of interest, typically based on literature. While this may be an appropriate method for common Mendelian diseases, it is limited in its ability to poll the functionality o f other SNPs within the same gene, since these SNPs are essentially 43 'invisible'' from the perspective of the chosen SNPs. Thus it may be assumed that functionality is determined by alternate alleles at a given locus, while the true functional SNP may be located outside of the gene of interest, but linked to the genotyped SNPs through LD . While this marker-style approach to disease association is useful, it does not address mechanism or functionality of the polymorphism itself. A n important strength of our study design was a sample size that allowed for statistical power to detect associations of modest effect. We limited the analysis to Caucasians patients in order to reduce type I error due to population admixture. We included two common clinical measures which reflect the intensity of inflammation. Importantly, we included measurement of serum IL-10, the intermediate phenotype most directly related to the IL-10 gene. One of the main weaknesses of our study design is that we do not identify the causative SNP for improved clinical outcome following CPB . Linkage disequilibrium existing within and possibly beyond the IL-10 gene suggests that polymorphic loci in L D with any of the SNPs uniquely marking the C T G haplotype could contribute protective effects following C P B surgery. We have limited our study to a single cohort; therefore this arising hypothesis should be tested in other cohorts to ensure reproducibility. 44 2.5 Summary We have identified a novel haplotype of the interleukin-10 gene associated with improved outcome following cardiopulmonary bypass surgery. The -627C/734T/3368G haplotype is associated with significantly reduced need for prolonged ICU care following C P B surgery, as well as improved Pa02/Fj02 ratio and reduced circulating neutrophil count post-CPB. These varied markers indicated a reduction in the activation of the inflammatory system post-CPB. Additionally, the C T G haplotype was associated with increased serum IL-10 concentrations post-CPB, indicating a biologically plausible mechanism for the improved outcome from C P B surgery associated with this haplotype. 45 2.6 Tables and Figures T A B L E 2 .1 : Numbering of Polymorphic Loci Due to the overwhelming volume of literature regarding polymorphic loci within the IL-10 gene and the various points in the history of the gene at which these polymorphisms were discovered relative to the sequencing of the gene, some confusion has arisen regarding the numbering of these positions relative to the site of start o f transcription. Table 4 presents an account of the different positional markers used to identify these loci , and indicates the numbering used in this article. Position Genbank Position Reported Position Reference in This Position by Turner eta 141 Reported by from Paper Grove et at2 NCBI ' s dbSNP database -1117 -1117 -1082 -1117 rs 1800896 -854 -854 -819 -854 rs 1800871 -627 -627 -592 -627 rs 1800872 734 734 734 n/a rs3024491 3368 3367 3367 n/a rs3024495 46 TABLE 2.2. Summary of baseline characteristics between patients carrying at least on copy of the C T G haplotype and all others. Values are reported as mean (standard error), median (interquartile range [range]), or number (proportion). Baseline Variable CTG Haplotype All Others N (%) 328 (54%) 275 (46%) Age (years) 67(15 [25-88]) 66(15 [24-87]) Male Sex 243 (74%) 215 (78%) B M I (kg/m 2) 27.9 (0.3) 28.1 (0.3) Diabetes 84 (26%) 69 (21%) Smoking 100 (31%) 86 (31%) Anti-hypertensive Use 199 (61%) 171 (62%) A C E II Inhibitor Use 160 (49%) 146 (53%) Beta-blocker Use 199 (61%) 154 (56%) Aspirin Use 182 (56%) 174 (63%) 47 TABLE 2.3. Summary of peri-operative variables between patients possessing at least one copy of the C T G haplotype and all others. Values are reported as mean (standard error), median (interquartile range [range]), or number (proportion). Peri-Operative Variable CTG Haplotype All Others Duration of Surgery (Hours) 4.4(0.1) 4.4 (0.1) Duration of Bypass (Hours) 1.8(0.04) 1.7(0.05) Cardioplegia Temperature (\u00C2\u00B0C) 36 (27 [6-37]) 36 (27 [6-37]) Use of Aprotinin 49(15%) 39(14%) Use of Milrinone 59(18%) 44 (16% Use of Amicar 175 (53%) 128 (47%) Use of Protamine 33 (10%) 26(10%) 48 T A B L E 2.4. Summary of SNP- and haplotype-based alterations in serum IL-10 levels and outcomes from inflammatory diseases, incorporating the results of this study. Alternate alleles are presented as white text on black background to represent common alleles, or black text on white background to represent rare alleles (as in Figure 2.1). Clade -1117 -627 -1117/-854/-627 Haplotype -627/734/3368 Haplotype E A 0 T A ^ ^ ^ ^ H < ' < \u00E2\u0080\u00A2 \u00E2\u0080\u00A2 ! \u00E2\u0080\u00A2 \u00E2\u0080\u00A2 -decreased IL-10 transcriptional -decreased serum -decreased -decreased serum IL-10 act iv i ty 1 0 IL -10 4 4 serum IL-10 1 1 (this study) I -increased susceptibility to sepsis 3 4 -increased mortality -increased -increased mortality from from critical inflammatory meningococcemia 4 3 i l lness 4 4 -less severe graft-versus-host disease 4 5 cell activation 3 8 a -increased Th2 -decreased serum IL-10 2 46 immunity (this study) -increased pulmonary sepsis mortality 4 7 G SitS increased serum IL -10 3 4 \" 3 7 -increased serum IL-10 1 2 -increased serum IL-10 (this study) IB IIIIS -decreased stimulated serum IL-10 6 -decreased inflammation -increased incidence of severe post-CPB (this study) \u00E2\u0080\u00A2 48 sepsis 4 9 Figure Legends Figure 2.1: Haplotype diagram of the interleukin-10 gene. Each column represents a polymorphic locus in the IL-10 gene, and is coded as either black (common allele) or white (rare allele). The position of each polymorphic locus is indicated at the top of each column. Each row represents one distinct haplotype. Each clade is indicated by the (arbitrary) numbering in the left-most column. The clade delineations are indicated within the haplotype diagram by thick lines between haplotypes. The positions chosen for genotyping (-627, 734 and 3368) are indicated in the figure by bold text in the numbering. The frequencies of each haplotype observed within the Caucasian sample population is indicated in the right-most column, the total observed haplotype number being 46 (2 haplotypes per individual and 23 individuals). F igure 2.2: Phylogenetic tree-style representation of IL-10 gene haplotypes, clustered by M E G A 2 (see text). Lettered branches represent distinct haplotypes inferred from genotype data of 23 unrelated Caucasians. Haplotypes are clustered into clades (labeled ellipses) according to common alleles of tag SNPs, as indicated in the figure: clade 1 is uniquely identified by the A allele at position -627; clade 2 is identified by the C allele at position -627 and G allele at position 734; clade 3 is identified by the T allele at position 734 and the G allele at position 3368; clade 4 is uniquely identified by the presence of the A allele at position 3368. Distances between branch ends represent evolutionary distances between haplotypes, based on the number of sequence differences. 50 Figure 2.3: Serum IL-10 cytokine levels pre-CPB and at 4 and 24 hours post-CPB by possession of at least one copy of the IL-10 C T G haplotype. Patients possessing at least one copy of the C T G haplotype had significantly higher serum IL-10 levels 4 and 24 hours post-CPB despite no difference at baseline. 51 FIGURE 2.1. 52 F I G U R E 2.2. Clade 2 -627C&734G Clade 1 -627A Clade 3 734T&3368G X \ \"V K <2> Clade4 3368A F I G U R E 2.3. 54 2.1 References 1. Sharma, M . et al. Release of pro-inflammatory mediators during myocardial ischemia/reperfusion in coronary artery bypass graft surgery. Mol Cell Biochem 247, 23-30 (2003). 2. Gu, Y . J . , Mariani, M . A. , Boonstra, P. W., Grandjean, J . G. & van Oeveren, W. Complement activation in coronary artery bypass grafting patients without cardiopulmonary bypass: the role of tissue injury by surgical incision. Chest 116, 892-8 (1999). 3. Levy, M . M . et al. 2001 S C C M / E S I C M / A C C P / A T S / S I S International Sepsis Definitions Conference. Crit Care Med3\, 1250-6. (2003). 4. Charlesworth, D. C. et al. Development and validation of a prediction model for strokes after coronary artery bypass grafting. Ann Thorac Surg 76, 436-43 (2003). 5. L in , M . T. et al. Relation of an Interleukin-10 Promoter Polymorphism to Graft-versus-Host Disease and Survival after Hematopoietic-Cell Transplantation. N Engl J Med 349, 2201 -2210 (2003). 6. Galley, H. F., Lowe, P. R., Carmichael, R. L. & Webster, N. R. Genotype and interleukin-10 responses after cardiopulmonary bypass. Br J Anaesth 91, 424-6 (2003). 7. Giomarelli, P., Scolletta, S., Borrelli, E. & Biagiol i , B. Myocardial and lung injury after cardiopulmonary bypass: role of interleukin (IL)- l 0. Ann Thorac Surg 76, 117-23 (2003). 55 8. Holmes, C. L., Russell, J . A . & Walley, K. R. Genetic polymorphisms in sepsis and septic shock: role in prognosis and potential for therapy. Chest 124, 1103-15 (2003). 9. Caligiuri, G. et al. Interleukin-10 deficiency increases atherosclerosis, thrombosis, and low-density lipoproteins in apolipoprotein E knockout mice. Mol Med 9, 10-7 (2003). 10. Reuss, E. et al. Differential regulation of interleukin-10 production by genetic and environmental factors\u00E2\u0080\u0094a twin study. Genes Immun 3, 407-13 (2002). 11. Cunningham, L. M. , Chapman, C , Dunstan, R., Bel l , M . C. & Joske, D. J . Polymorphisms in the interleukin 10 gene promoter are associated with susceptibility to aggressive non-Hodgkin's lymphoma. Leuk Lymphoma 44, 251-5 (2003). 12. Suarez, A. , Castro, P., Alonso, R., Mozo, L. & Gutierrez, C. Interindividual variations in constitutive interleukin-10 messenger R N A and protein levels and their association with genetic polymorphisms. Transplantation 75, 711-7 (2003). 13. Wil l iams, M . R. et al. Long-term survival and quality of life in cardiac surgical patients with prolonged intensive care unit length of stay. Ann Thorac Surg 73, 1472-8 (2002). 14. Christakis, G. T. et al. Impact of preoperative risk and perioperative morbidity on ICU stay following coronary bypass surgery. Cardiovasc Surg 4, 29-35 (1996). 15. Nakasuji, M. , Matsushita, M . & Asada, A. Risk factors for prolonged ICU stay in patients following coronary artery bypass grafting with a long duration of cardiopulmonary bypass. J Anesth 19, 118-23 (2005). 56 16. Lawrence, D. R., Valencia, 0 . , Smith, E. E., Murday, A. & Treasure, T. Parsonnet score is a good predictor of the duration of intensive care unit stay following cardiac surgery. Heart 83, 429-32 (2000). 17. Michalopoulos, A. et al. Determinants of duration of ICU stay after coronary artery bypass graft surgery. Br J Anaesth 77, 208-12 (1996). 18. Wong, D. T. et al. Risk factors of delayed extubation, prolonged length of stay in the intensive care unit, and mortality in patients undergoing coronary artery bypass graft with fast-track cardiac anesthesia: a new cardiac risk score. Anesthesiology 91, 936-44 (1999). 19. Tu, J . V . , Mazer, C. D., Levinton, C , Armstrong, P. W. & Naylor, C. D. A predictive index for length of stay in the intensive care unit following cardiac surgery. Cmaj 151, 177-85 (1994). 20. Montes, F. R., Maldonado, J . D., Paez, S. & Ariza, F. Off-pump versus on-pump coronary artery bypass surgery and postoperative pulmonary dysfunction. J Cardiothorac Vase Anesth 18, 698-703 (2004). 21. Fabbri, A . et al. Systemic leukocyte filtration during cardiopulmonary bypass. Perfusion 16 Suppl, 11-8 (2001). 22. Morales, D. L. et al. A double-blind randomized trial: prophylactic vasopressin reduces hypotension after cardiopulmonary bypass. Ann Thorac Surg 75, 926-30 (2003). 23. Maslow, A. D., Regan, M. M. , Schwartz, C , Bert, A . & Singh, A . Inotropes improve right heart function in patients undergoing aortic valve replacement for aortic stenosis. Anesth Analg 98, 891-902, table of contents (2004). 57 24. Giavedoni, L. D. Simultaneous detection of multiple cytokines and chemokines from nonhuman primates using luminex technology. J Immunol Methods 301, 89-101 (2005). 25. Stephens, M . & Donnelly, P. A comparison of bayesian methods for haplotype reconstruction from population genotype data. Am J Hum Genet 73, 1162-9 (2003). 26. Kumar, S., Tamura, K., Jakobsen, I. B. & Nei , M . M E G A 2 : molecular evolutionary genetics analysis software. Bioinformatics 17, 1244-5 (2001). 27. Livak, K. J . A l le l ic discrimination using fluorogenic probes and the 5' nuclease assay. Genet Anal 14, 143-9(1999). 28. Long, A . D. & Langley, C. H. The power of association studies to detect the contribution of candidate genetic loci to variation in complex traits. Genome Res 9, 720-31 (1999). 29. Guo, S. W. & Thompson, E. A . Performing the exact test of Hardy-Weinberg proportion for multiple alleles. Biometrics 48, 361-72 (1992). 30. Bucerius, J . et al. Predictors of prolonged I C U stay after on-pump versus off-pump coronary artery bypass grafting. Intensive Care Med (2003). 31. Pavelkova, M . et al. Blood phagocyte activation during open heart surgery with cardiopulmonary bypass. Physiol Res (2005). 32. Rinder, C. S., Fontes, M. , Mathew, J . P., Rinder, H. M . & Smith, B. R. Neutrophil CD1 lb upregulation during cardiopulmonary bypass is associated with postoperative renal injury. Ann Thorac Surg 75, 899-905 (2003). 58 33. Joyce, D. A . et al. Two inhibitors of pro-inflammatory cytokine release, interleukin-10 and interleukin-4, have contrasting effects on release of soluble p75 tumor necrosis factor receptor by cultured monocytes. Eur J Immunol 24, 2699-705 (1994). 34. Kahraman, S. et al. IL-10 genotype predicts serum levels of adhesion molecules, inflammation and atherosclerosis in hemodialysis patients. J Nephrol 19, 50-6 (2006). 35. Marka, M. , Bessenyei, B., Zeher, M . & Semsei, 1.1L-10 promoter -1082 polymorphism is associated with elevated IL-10 levels in control subjects but does not explain elevated plasma IL-10 observed in Sjogren's syndrome in a Hungarian cohort. Scand J Immunol 62, 474-80 (2005). 36. Yi lmaz, V . , Yentur, S. P. & Saruhan-Direskeneli, G. IL-12 and IL-10 polymorphisms and their effects on cytokine production. Cytokine 30, 188-94 (2005). 37. Schaaf, B. M . et al. Pneumococcal septic shock is associated with the interleukin-10-1082 gene promoter polymorphism. Am JRespir Crit Care Med 168, 476-80. (2003). 38. Timmann, C. et al. Promoter haplotypes of the interleukin-10 gene influence proliferation of peripheral blood cells in response to helminth antigen. Genes Immun 5, 256-60 (2004). 39. Jourdan-Le Saux, C. et al. A base substitution in the interleukin-10 (IL-10) promoter between Sp l and ets-1 binding sites is not associated with variation of IL-10 levels. Cell Mol Biol (Noisy-le-grand) 49, 1109-15 (2003). 59 40. Tishkoff, S. A . & Verrell i , B. C. Role of evolutionary history on haplotype block structure in the human genome: implications for disease mapping. Curr Opin Genet Dev 13,569-75 (2003). 41. Turner, D. M . et al. A n investigation of polymorphism in the interleukin-10 gene promoter. Eur J Immunogenet 24, 1-8 (1997). 42. Grove, J . , Daly, A . K., Bassendine, M . F., Gilvarry, E. & Day, C. P. Interleukin 10 promoter region polymorphisms and susceptibility to advanced alcoholic liver disease. Gut 46, 540-5 (2000). 43. Balding, J. et al. Genomic polymorphic profiles in an Irish population with meningococcaemia: is it possible to predict severity and outcome of disease? Genes Immun 4, 533-40. (2003). 44. Lowe, P. R., Galley, H. F., Abdel-Fattah, A . & Webster, N. R. Influence of interleukin-10 polymorphisms on interleukin-10 expression and survival in critically i l l patients. Crit Care Med 31, 34-8. (2003). 45. L in , M . T. et al. Genetic variation in the IL-10 pathway modulates severity of acute graft-versus-host disease following hematopoietic cell transplantation: synergism between IL-10 genotype of patient and IL-10 receptor beta genotype of donor. Blood 106, 3995-4001 (2005). 46. Hohler, T., Reuss, E., Freitag, C. M . & Schneider, P. M . A functional polymorphism in the IL-10 promoter influences the response after vaccination with H B s A g and hepatitis A . Hepatology 42, 72-6 (2005). 47. Wattanathum, A. , Manocha, S., Groshaus, H., Russell, J . A . & Walley, K. R. Interleukin-10 haplotype associated with increased mortality in critically i l l 60 patients with sepsis from pneumonia but not in patients with extrapulmonary sepsis. Chest 128, 1690-8 (2005). 48. Shu, Q., Fang, X . , Chen, Q. & Stuber, F. IL-10 polymorphism is associated with increased incidence of severe sepsis. Chin Med J (Engl) 116, 1756-9 (2003). 61 C H A P T E R 3 b: Novel polymorphism of interleukin-18 associated with greater inflammation after cardiac surgery. 3.1 Introduction The balance of pro-inflammatory (e.g. tumor necrosis factor alpha, T N F - a ) and anti-inflammatory (e.g. interleukin-10, IL-10) cytokine gene expression is highly correlated with organ dysfunction and adverse outcome following cardiopulmonary bypass (CPB) 1 . Interleukin-18 (IL-18) is a key cytokine regulator of this balance that, among other clinical and cytokine measures, stands out as predictive of organ dysfunction and adverse outcomes following C P B 2 . IL-18 acts with IL-12 in a synergistic fashion to stimulate the release of interferon-gamma (IFN-y) from lymphocytes 3. High serum levels of IL-18 are associated with increased production of the pro-inflammatory cytokine T N F - a 4 and decreased production of the anti-inflammatory cytokine IL-10 5 . IL-18 is an regulatory inflammatory mediator that is involved in the polarization of immune cells in a T h l pathway 6. Serum levels of IL-18 increase in response to C P B surgery2 and in other inflammatory 7 8 conditions such as sepsis and type I diabetes . Inflammatory gene polymorphisms have been linked to the intensity of the post-operative inflammatory response and to clinical outcomes following cardiopulmonary bypass surgery9. Therefore we postulated that IL-18 gene single nucleotide A version of this chapter has been accepted for publication in the Journal of Thoracic and Cardiovascular Surgery. polymorphisms (SNPs) may be important in recovery from C P B surgery. Two polymorphic loci within the IL-18 gene have been investigated for associations between genotype and serum concentrations of IL-18 (intermediate phenotype) as well as associations between genotype and clinical outcome (phenotype). The -607 C / A and -137 G /C SNPs were initially discovered to influence promoter activity of the IL-18 gene 1 0. The -137 C allele has been associated with adverse outcomes and higher serum IL-18 cytokine levels while the -607 A allele has been associated with improved outcomes and lower serum IL-18 levels in type I diabetes3. Our study design was based on the above observation that increased serum IL-18 has been demonstrated to result in adverse outcome following C P B , including cardiovascular dysfunction 2, associated with increased serum T N F - a and decreased serum IL-10 1 ' .Therefore we tested the hypothesis that IL-18 gene polymorphisms are associated with adverse outcome, as measured by prolonged ICU stay (primary clinical outcome) and pulmonary and cardiovascular dysfunction (secondary clinical outcome). We then confirmed that the polymorphism is associated with increased serum concentrations of IL-18 and altered serum concentrations of T N F - a and IL-10 post-CPB, thus providing a possible explanation for our clinical results. 63 3.2 Methods The Research Ethics Board of Providence Health Care and the University of British Columbia approved this study. Patient Cohort A l l patients admitted to the Cardiac Surgery Intensive Care Unit (CSICU) of St Paul's Hospital following cardiopulmonary bypass surgery between February 2001 and December 2003 were eligible for entry into this study. Eight hundred and ninety patients were screened for inclusion of which 92% had cardiopulmonary bypass pump-driven circulation of blood during the surgery. We restricted our analyses to Caucasian patients who were successfully genotyped for four polymorphisms in the interleukin-18 gene in order to decrease the potentially confounding influence of population admixture secondary to ethnic diversity, on associations between genotype and phenotype. Thus, 658 patients made up our final cohort for analysis. Primary Clinical Phenotype Mortality from C P B is uncommon, particularly since this cohort was confined to coronary artery bypass surgery and excluded valve replacement and repair surgery. Many authors therefore use prolonged intensive care unit (ICU) stay as a measure of adverse outcome ' . Most recently, Nakasuji et al. found that prolonged ICU stay of more than 3 days was a sensitive and specific measure of adverse outcome which reflected measures of cardiovascular and pulmonary organ failure . Lawrence and colleagues found that the Parsonnet score with a maximum predictive efficiency was a score of 10: patients having 64 a Parsonnet score of 0-9 had a mean ICU stay of approximately 1.5 days while those having a score of >-10 had a mean ICU stay of approximately 3 days 1 3 . Therefore, we used the proportion of patient having a post-operative ICU stay of greater than 3 days (72 hours) as our primary outcome variable. Secondary Clinical Phenotype Kristof and Magder 1 4 identified low post-CPB systemic vascular resistance index (SVRI) as a clinical manifestation of systemic inflammation. This vasodilatory syndrome is associated with related parameters such as longer cross-clamp times and lower post-C P B platelet count 1 4 . We used Kristof and Magder's definition of two consecutive S V R I measurements less than 1800 dyne.s/cm 5 /m 2 (SVRI = [ (MAP-CVP)*80] /CI , where M A P is the mean arterial pressure, C V P is the central venous pressure and CI is the cardiac index) as a secondary clinical phenotype in the subset of patients who underwent on-pump coronary artery bypass graft surgery. Intermediate Phenotype Serum concentrations of cytokines are useful as an intermediate phenotype 1 5. Interleukin-18 is a pro-inflammatory cytokine involved in T helper cell T h l polarization and IFN-y production 6. T N F - a is a pro-inflammatory cytokine that mediates some of the effects of inflammation following C P B surgery 1 6 and is regulated in part by serum IL-18 levels 1 7 . Interleukin-10 is an anti-inflammatory cytokine that suppresses the expression of other cytokines, the expression of which has been observed to be related to IL-18 serum 65 expression5. Thus, we measured serum IL-18, T N F - a and IL-10 concentrations in a subset of patients. In our own preliminary time course experiments it was found that serum IL-18 concentrations peaked at 24 hours post-CPB. Therefore, we measured serum IL-18, T N F - a and IL-10 at this post-operative time point. Serum IL-18 and T N F - a were measured by enzyme-linked immunosorbent assay (ELISA) ( R & D Systems, Minneapolis, M N for IL-18; B D PharMingen, San Diego, C A for TNF -a ) . Serum IL-10 18 was measured using the Luminex bead-based bioassay system (Luminex Corp, Austin, TX) . Tag SNP Selection To determine IL-18 gene haplotypes we used unphased genotype data from the University of Arizona's Innate Immunity Program in Genomics Application website (http://www.innateimmunity.net). We used P H A S E v 2 .0 1 9 to infer haplotype from unphased genotype data. The resulting haplotypes were clustered into four groups of similar haplotypes (clades) using the molecular evolutionary genetic analysis software package M E G A 2 2 0 . The program LDSelect was used to select a set o f maximally informative haplotype tag SNPs with the restriction that the literature SNPs -607 C / A and -137 G /C be included. Four htSNPs were chosen to differentiate the four haplotype clades: -607 C / A (rsl946518), -137 G /C (rsl87238), 8148 C /T (rs360722) and 9545 T / G (rs5744249) (Figure 3.1). 66 Genotyping D N A was extracted from peripheral blood samples using a QIAamp D N A Blood Maxi K i t (Qiagen Inc. Canada, Mississauga, O N , Canada). SNP genotypes were determined using the 5' nuclease, or Taqman polymerase chain reaction (PCR) method (Applied Biosystems; Foster City, C A , U S A ) 2 2 . These htSNPs were then genotyped in the 658 patients of our cohort undergoing CPB . Sequences of the P C R primers and allele-specific probes used in TaqMan-based genotyping of patients for the chosen htSNPs are given in Appendix A. Statistics Differences in continuous variables were assessed using Student's t-test for two groups or A N O V A for more than two for normally distributed data, and a Mann-Whitney U Test or Kruskal-Wall is H Test for non-normally distributed data. Fisher's exact test was used to test for significant differences in discrete variables. A p-value of 0.05 (or less) was taken to indicate a significant difference. Analysis was performed using SPSS v l 1.5 (SPSS, Chicago, IL, USA) . Al lele frequencies were tested for Hardy-Weinberg equilibrium using the test of Guo and Thompson and were all found to be in Hardy-Weinberg equilibrium. Work by Long and Langley 2 4 indicates that on the order of 500 individuals are sufficient to detect the presence of causative polymorphisms having small effect on outcomes. Thus, we have included 658 individuals in our study population. 67 3.3 Results Selection of the 9545 T/G SNP Using P H A S E , we found 4 main haplotypes occurring at a frequency greater than 5% in our patient cohort based on the four chosen htSNPs (Figure 3.2). We found clades 1 -3 were associated with greater need for prolonged ICU care (Figure 3.3). Since clades 1 -3 are uniquely tagged by the T allele of the 9545 T / G polymorphism we focused on the 9545 T / G genotype for further analyses. No significant associations between genotype and any clinical or intermediate phenotype were observed for any of the three other htSNPs (not shown). Baseline Characteristics There were no significant differences among patients with 0, 1 or 2 copies of the T allele of the IL-18 9545 T / G polymorphism in age, sex, frequency of diabetes or smoking, duration of bypass or surgery, and pre-operative use of anti-hypertensive drugs, use of angiotensin-converting enzyme (ACE) inhibitor drugs, use of beta-blockers, use of calcium channel blockers or use of aspirin (Table 3.1). There was a significant difference in body mass index (BMI) among the IL-18 9545 T / G genotype groups (28 for G G , 28 for GT, 26 for G G , p=0.022). Primary Clinical Phenotype In our cohort of Caucasian patients who had on-pump C P B surgery, patients possessing two copies of the T allele of the IL-18 9545 T / G SNP had increased need for 68 prolonged care in the intensive care unit (greater than 72 hours) following C P B surgery: 32 of 383 (8.4%) for TT vs. 10 of 275 (3.6%) for T G or G G ; p=0.015 (Figure 3.4). Secondary Clinical Phenotype In a subgroup of Caucasian patients undergoing on-pump coronary bypass graft surgery (CABG) , those patients homozygous for the T allele of the IL-18 9545 T / G SNP had increased frequency of 2 consecutive SVRI measurements less than 1800 dyne.s/cm 5 /m 2 . The TT genotype was associated with the increased frequency of 2 SVRI measurements less than 1800 (62%) compared to the G T and G G genotypes (53%) and (Figure 3.4). These differences were significant (p=0.045) upon binary logistic regression including covariates age, sex, B M I and duration of bypass (Table 3.2). Classic risk factors such as age and sex were not significant predictors of risk of low SVRI in this study. Intermediate Phenotype In a further subgroup of patients for whom serum cytokine measurements were available, a significant difference was found in the concentration of interleukin-18 24 hours post-CPB surgery by genotype of the IL-18 9545 T / G polymorphism. Patients carrying two copies of the T allele had a significantly greater mean serum IL-18 concentration (372.3 +/- 23.9 pg/mL) compared to those with the G T or G G genotypes (260.4 +/- 47.9 pg/mL); p=0.018 (Figure 3.5). 69 T N F - a at this time point (313.7 +/- 82.9 pg/mL) compared to all others (66.9 +/- 37.2 pg/mL); p=0.014 (Figure 3.5). A significant difference in serum IL-10 levels was observed at 24 hours post-CPB by IL-18 9545 T / G genotype. Those patients homozygous for the T allele had significantly lower serum IL-10 levels 24 hours post-CPB (2.4 +/- 1.0 pg/mL) compared to all others (9.1 +/- 2.8 pg/mL); p=0.018 (Figure 3.5). 70 3.4 Discussion We have identified an association between the TT genotype of the novel 9545 T /G polymorphism of the IL-18 gene and worse outcome following cardiopulmonary bypass surgery. The TT genotype was found to be associated with greater need of prolonged ICU care and higher prevalence of 2 consecutive SVRI measurements less than 1800 dyne.s/cm 5 /m 2 . A biologically plausible explanation for these findings is that the TT genotype of the 9545 T / G htSNP was also associated with higher serum concentration of IL-18, higher serum TNF - a concentration and lower serum concentration of IL-10 in our surgical population. Prolonged ICU care is a marker for poor outcome and greater inflammation following C P B surgery recognized in the 12 literature . Low systemic vascular resistance, defined as two consecutive SVRI measurements less that 1800 dyne.s/cm /m , is a marker of poor vascular tone following C P B , related to the systemic inflammatory response 1 4. Greater serum concentrations of 2 16 25 IL-18\" and TNF-a'\u00C2\u00B0and lower serum levels of IL-10 have been associated with increased prevalence of complications following C P B , and may be indicative of a prominent pro-inflammatory state. The IL-18 cytokine regulates the expression of the potent pro- and anti-inflammatory mediators TNF -a 4and IL -10 5 through intra-cellular signaling pathways. Activation of the N F -K B transcription factor by IL-18 binding to its receptor complex leads directly to production of TNF - a 4 . In the case of IL-10, cross-talk between signaling pathways provides reciprocal regulation of IL-18 and IL-10 such that increased serum IL-18 concentration leads to decreased expression of IL-10 5 . We found high serum IL-18 71 concentration associated with the TT genotype of the 9545 T / G htSNP at 24 hours post-CPB. Importantly, we also found increased serum T N F - a and decreased serum IL-10 in these patients at the same time point, as expected given our finding of increased serum IL-18 and the regulatory effects of IL-18 on these cytokines. The increased serum T N F - a and decreased serum IL-10 levels were associated with increased organ dysfunction as expected for a pro- versus anti-inflammatory cytokine balance of this nature\". Therefore, we believe that the mechanism of the IL-18 9545 TT genotype is: increased production of serum IL-18 leading to increased serum T N F - a and decreased serum IL-10, causing increased organ dysfunction and an increase in need for prolonged ICU stay. Polymorphisms in the IL-18 gene have been studied for association with inflammatory conditions such as type I diabetes3 and sepsis 2 6 . The -607 C / A and -137 G /C promoter SNPs have been found to be associated with susceptibility to type I diabetes such that the C allele of -137 was found to be a risk allele while the A allele o f -607 was found to be a protective allele 3. Polymorphisms in the IL-18 gene have also been associated with alterations in serum concentrations of the IL-18 cytokine 2 7 . None of the previous literature reports association between the 9545 T / G SNP and outcomes, or between this SNP and serum cytokine levels. The previous SNPs, -607 C / A and -137 G /C , are not in linkage disequilibrium with the 9545 T / G SNP (Figure 3.1). Neither of these previously reported SNPs were in association with our primary or secondary clinical or intermediate phenotypes. 72 The 9545 T / G SNP of the IL-18 gene is located within intron 2 and therefore may not be the causal SNP with regard to clinical outcomes or intermediate phenotypes. Strong linkage disequilibrium exists between the 9545 T / G SNP and several other SNPs within the IL-18 gene (Figure 3.1): -2163 C / A (rs5744222) in the promoter, 790 G/T (n/a) and 8936 A / G (rs4988359) in intron 1, 11024 G /C (rsl834481), 12003 T /C (rs5744256) and, 13084 G / C (rs5744258) in intron 3, and 17980 G / C (rs5744276) in intron 5. Promoter SNPs are likely to have an effect by disrupting or creating binding sites for transcription factors, thus altering levels of intracellular transcript and/or 9R extracellular protein . The -2163 C / A SNP, however, is not found to be located within a putative transcription factor binding site, nor does the rare allele create one, based upon a scan of the promoter region of the IL-18 gene using the TESS (transcriptional element search software) program 2 9 . Intronic SNPs can effect splicing of the pre -mRNA, resulting in alternative splice variants of proteins, however most intronic SNPs thought to have 30 these effects are observed to lie within approximately 20bp of intron/exon boundaries . The 9545 T / G SNP itself does not lie so close to such a boundary, nor do any of the SNPs in L D with 9545 mentioned above. Linkage disequilibrium can carry over the putative gene boundary, and may allow the 9545 T / G SNP to be tightly correlated with a causal SNP up- or downstream of the IL-18 gene, one which may have a causal effect on clinical and intermediate phenotypes. Haplotypes represent a powerful method of selecting SNPs for genotyping based on linkage disequilibrium. The interleukin-18 gene has 56 polymorphic loci in Caucasians according to sequencing data from the University of Arizona's Innate 73 Immunity Program in Genomic Applications website (http://www.innateimmunity.net). The SNPs at positions -607 and -137 relative to the start of translation are literature SNPs, and so make good choices for genotyping in an inflammatory-related population such as C P B patients. The positions 8148 and 9545 are not previously reported SNPs, however, and so would not have been chosen for genotyping without some method of selecting SNPs. B y selecting htSNPs so as to maximize information while minimizing the number of SNPs to be genotyped we have queried the underlying haplotype structure while using relatively few polymorphic loci. This strategy improves upon the traditional SNP-based approach to disease association studies, whereby polymorphic loci are chosen from the gene of interest, typically based on previous reports. While this may be an appropriate method for common Mendelian diseases, it is limited in its ability to poll the functionality of other SNPs within the same gene, since these SNPs are essentially 'invisible' from the perspective of the chosen SNPs. Thus it may be assumed that functionality is determined by alternate alleles at a given locus, while the true functional S N P may be located outside of the gene of interest, but linked to the genotyped SNPs through LD . Whi le this marker-style approach to disease association is useful, it does not address mechanism or functionality of the polymorphism itself. Our study has several strengths. The use of haplotypes to choose htSNPs has the benefit of not being restricted to literature SNPs for disease association studies. The large sample size allows for statistical power to detect associations of modest effect and the limitation of sampling to Caucasians patients reduces the likelihood of type I error due to population admixture. One of the main weaknesses of our study design is that we do not 74 identify the causative SNP for worse clinical outcome following C P B . Linkage disequilibrium existing within and possibly beyond the IL-18 gene suggests that polymorphic loci in L D with the T allele of the 9545 T / G SNP could contribute detrimental effects following C P B surgery. We have limited our study to a single cohort; therefore this arising hypothesis should be tested in other cohorts to ensure reproducibility. 75 3.5 Summary In the present study the TT genotype of a novel polymorphism of the IL-18 gene, 9545 T /G , was associated with greater need for prolonged ICU care following C P B surgery, greater frequency of low SVRI (2 consecutive SVRI measurements < 1800 dyne.s/cm 5 /m 2), higher serum concentrations of cytokine IL-18, higher serum concentrations of the cytokine T N F - a and lower serum concentrations of the anti-inflammatory cytokine IL-10. These widely varied markers of intensity of recovery post-C P B indicate this allele is potentially a risk allele for patients undergoing C P B surgery. 76 3.6 Tables and Figures TABLE 3.1. Baseline demographics by IL-18 9545 genotype. With the exception of body mass index, no significant differences were observed among patients with the TT, T G or G G genotype of IL-18 9545 T /G . A l l measurements were made pre-operatively on all patients within the cardiac cohort. Continuous variables are reported as mean +/-standard error of the mean. 9545 TT 9545 GT 9545 GG p Value N (%) 383 (58%) 225 (34%) 50 (8%) Age (years) 65 +/- 1 66 +/- 1 66 +/- 1 0.655 Male Sex (%) 77 77 70 0.544 B M I (kg/m^) 28 +/- 1 28 +/- 1 26 +/-1 0.022 Diabetes (%) 29 28 27 0.969 Smoking (%) 32 41 36 0.129 Anti-hypertensive Use (%) 65 61 58 0.495 A C E II Inhibitor Use (%) 48 54 50 0.447 Beta-blocker Use (%) 58 60 56 0.745 Aspirin Use (%) 59 59 60 0.992 Duration of Surgery (hours) 4.4 +/- 1 4.5 +/- 1 4.4 +/- 1 0.728 Duration of Bypass (hours) 1.8+/- 1 1.9+/- 1 1.8 +/- 1 0.544 77 TABLE 3.2. Relative risks, 95% confidence intervals and statistical significance of covariates in the binary logistic regression analysis of low SVRI in Caucasians patients who underwent on-pump C A B G surgery. The TT genotype of the 9545 T / G SNP was significantly associated with low SVRI when covariates duration of bypass, B M I , age and sex were included in the model. Covariate Relative Risk Of Low Post-CPB SVRI 95% Confidence Interval p Value IL-18 9545 T T vs. 1.57 1 .01-2 .44 0.045 T G / G G Genotype Duration of Bypass 1.03 0 .66 -1 .62 0.889 B M I 1.00 0 .95 -1 .05 0.918 Age 0.99 0 .97 -1 .02 0.480 Sex 0.70 0 .39 -1 .27 0.703 78 TABLE 3.3. Summary of SNP- and haplotype-based alterations in serum IL-18 levels and outcomes from inflammatory diseases, incorporating the results of this study. Alternate alleles are presented as white text on black background to represent common alleles, or black text on white background to represent rare alleles (as in Figure 3.1). Clade -607 -137 9545 -607/-137 Haplotype 1 s -increased serum IL-1 8 . 0 , 3 . s -increased serum IL-1810 \u00E2\u0080\u00A2 -increased serum IL-18 (this study) rara -increased sarcoidosis 3 2 -increased atopic -increased -increased type I \u00E2\u0080\u00A21-5 asthma inflammation diabetes 3 5 -increased following C P B inflammatory surgery (this study) bowl disease 3 4 C Sc 2 -increased type I diabetes3 -increased rheumatoid arthritis 3 6 A AC 1 -decreased rheumatoid arthritis 3 7 4 -decreased type I diabetes3 G 79 FIGURE LEGENDS Figure 3.1: Haplotype diagram of the interleukin-18 gene. Haplotypes were inferred from unphased genotype data of 23 unrelated healthy Caucasians by the P H A S E v2.0 program. Each column represents a polymorphic locus in the IL-18 gene, and is coded as either the common allele (black square) or the rare allele (white square). The position of each polymorphic locus relative to the start site of translation is indicated at the top of the diagram. Each row indicates a unique haplotype inferred from genotype data. The clustering of similar haplotypes into clades is done as per the phylogenetic relationship among haplotypes given by the M E G A 2 software package (described in M E T H O D S ) . The positions chosen for genotyping (-607, -137, 8148 and 9545) are indicated in the figure by bold numbering of the relative position and letter designations for the alleles within the diagram. Figure 3.2: Haplotype diagram of the interleukin-18 gene in patient population under study. Haplotypes were inferred from unphased genotype data of 658 unrelated Caucasians making up the study cohort using the P H A S E v2.0 program. Al lele and clade designations within the diagram are as in Figure 3.1. Haplotype frequency within the patient cohort is indicated to the right o f each haplotype. Only haplotype clades with frequency greater than 5% are represented in the figure. Figure 3.3: Need for prolonged ICU care following C P B by IL-18 haplotype clade in Caucasian patients who underwent on-pump C P B surgery. Percentage of patients 80 admitted to the ICU for prolonged care (greater than 72 hours) indicated on the Y-axis , IL-18 haplotype clade on the X-axis. Clades 1-3, marked by the T allele of the IL-18 9545 T /G SNP, were associated with greater need for prolonged ICU stay, compared to clade 4. Figure 3.4: Need for prolonged ICU care and low SVRI following C P B by IL-18 9545 T /G genotype in Caucasian patients who underwent on-pump C P B surgery. Percentage of patients admitted to the ICU for prolonged care (greater than 72 hours) indicated on the first Y-axis , percentage of patients having low SVRI following C A B G surgery are indicated on the second Y-axis . IL-18 9545 T /G genotypes are indicated on the X-axis . Patients possessing the TT genotype of the IL-18 9545 T / G SNP had significantly greater need for prolonged ICU care and significantly increased occurrence of low SVRI following C P B compared to all others (GT and G G genotypes). Figure 3.5: Serum concentrations of IL-18, T N F - a and IL-10 by IL-18 9545 T / G genotype in Caucasian patients who underwent on-pump C P B surgery. Serum concentrations of cytokines in pg/mL are indicated on the y-axes, with IL-18 9545 T / G genotype indicated in the legend. Serum cytokine measurements were made 24 hours post-CPB. Patients with the TT genotype of the IL-18 9545 T /G SNP had significantly higher serum IL-18 and T N F - a levels and significantly lower serum IL-10 measurements 24 hours post-CPB. 81 F I G U R E 3.1. R e l a t i v e P o s i t i o n 82 F I G U R E 3.2. Relative Position 2 C G C 3;:;:;:; A 1 c ^ K J B Frequency 7 2 2 \" 236 538 463 F I G U R E 3.3. F I G U R E 3.4. 10 ! 0> O O 6 \u00E2\u0080\u00A2a \u00C2\u00B0 R c o O 4 k> Q. \u00E2\u0080\u00A2o o N = 383 \u00E2\u0080\u00A2 IL-18 9545 TT \u00E2\u0080\u00A2 IL-18 9545GT/GG 70 n 60 p=0.015 50 a: > ^ 30 O 20 10 A N = 218 p=0.045 I N = 154 85 F I G U R E 3.5. 3.7 References 1. Wan, S. et al. Hepatic release of interleukin-10 during cardiopulmonary bypass in steroid-pretreated patients. Am Heart J 133, 335-9 (1997). 2. Sablotzki, A . et al. Different expression of cytokines in survivors and non-survivors from M O D S following cardiovascular surgery. Eur J Med Res 8, 71-6 (2003). 3. Kretowski, A . et al. Interleukin-18 promoter polymorphisms in type 1 diabetes. Diabetes 51, 3347-9 (2002). 4. Chandrasekar, B. et al. Activation of intrinsic and extrinsic proapoptotic signaling pathways in interleukin-18-mediated human cardiac endothelial cell death. J Biol Chem 279, 20221-33 (2004). 5. Takeuchi, D. et al. Interleukin 18 causes hepatic ischemia/reperfusion injury by suppressing anti-inflammatory cytokine expression in mice. Hepatology 39, 699-710(2004). 6. Tone, M. , Thompson, S. A. , Tone, Y . , Fairchild, P. J . & Waldmann, H. Regulation of IL-18 (IFN-gamma-inducing factor) gene expression. J Immunol 159,6156-63 (1997). 7. Oberholzer, A. , Steckholzer, U., Kurimoto, M. , Trentz, O. & Ertel, W. Interleukin-18 plasma levels are increased in patients with sepsis compared to severely injured patients. Shock 16, 411-4 (2001). 8. Hanifi-Moghaddam, P., Schloot, N. C , Kappler, S., Seissler, J . & Kolb, H. A n association of autoantibody status and serum cytokine levels in type 1 diabetes. Diabetes 52, 1137-42 (2003). 87 9. Schroeder, S. et al. A tumor necrosis factor gene polymorphism influences the inflammatory response after cardiac operation. Ann Thorac Surg 75, 534-7 (2003). 10. Giedraitis, V . , He, B., Huang, W. X . & Hillert, J . Cloning and mutation analysis of the human IL-18 promoter: a possible role of polymorphisms in expression regulation. J Neuroimmunol 112, 146-52 (2001). 11. Daemen, M . A. , van de Ven, M . W., Heineman, E. & Buurman, W. A . Involvement of endogenous interleukin-10 and tumor necrosis factor-alpha in renal ischemia-reperfusion injury. Transplantation 67, 792-800 (1999). 12. Nakasuji, M. , Matsushita, M . & Asada, A. Risk factors for prolonged ICU stay in patients following coronary artery bypass grafting with a long duration of cardiopulmonary bypass. J Anesth 19, 118-23 (2005). 13. Lawrence, D. R., Valencia, O., Smith, E. E., Murday, A . & Treasure, T. Parsonnet score is a good predictor of the duration of intensive care unit stay following cardiac surgery. Heart 83, 429-32 (2000). 14. Kristof, A . S. & Magder, S. Low systemic vascular resistance state in patients undergoing cardiopulmonary bypass. Crit Care Med 27, 1121-7 (1999). 15. Nadif, R. et al. Effect of T N F and L T A polymorphisms on biological markers of response to oxidative stimuli in coal miners: a model of gene-environment interaction. Tumour necrosis factor and lymphotoxin alpha. J Med Genet 40, 96-103 (2003). 88 Nakamura, K. et al. Relationship between cerebral injury and inflammatory responses in patients undergoing cardiac surgery with cardiopulmonary bypass. Cytokine 29, 95-104 (2005). Chandrasekar, B. et al. The pro-atherogenic cytokine interleukin-18 induces C X C L 1 6 expression in rat aortic smooth muscle cells via MyD88, interleukin-1 receptor-associated kinase, tumor necrosis factor receptor-associated factor 6, c-Src, phosphatidylinositol 3-kinase, Akt, c-Jun N-terminal kinase, and activator protein-1 signaling. J Biol Chem 280, 26263-77 (2005). Giavedoni, L. D. Simultaneous detection of multiple cytokines and chemokines from nonhuman primates using luminex technology. J Immunol Methods 301, 89-101 (2005). Stephens, M . & Donnelly, P. A comparison of bayesian methods for haplotype reconstruction from population genotype data. Am J Hum Genet 73, 1162-9 (2003). Kumar, S., Tamura, K., Jakobsen, I. B. & Nei , M . M E G A 2 : molecular evolutionary genetics analysis software. Bioinformatics 17, 1244-5 (2001). Carlson, C. S. et al. Selecting a maximally informative set of single-nucleotide polymorphisms for association analyses using linkage disequilibrium. Am J Hum Genet 74, 106-20(2004). Livak, K. J . A l le l ic discrimination using fluorogenic probes and the 5' nuclease assay. Genet Anal 14, 143-9(1999). Guo, S. W. & Thompson, E. A . Performing the exact test of Hardy-Weinberg proportion for multiple alleles. Biometrics 48, 361-72 (1992). Long, A . D. & Langley, C. H. The power of association studies to detect the contribution of candidate genetic loci to variation in complex traits. Genome Res 9,720-31 (1999). Nathan, N., Preux, P. M. , Feiss, P. & Denizot, Y . Plasma interleukin-4, interleukin-10, and interleukin-13 concentrations and complications after coronary artery bypass graft surgery. J Cardiothorac Vase Anesth 14, 156-60 (2000). Stassen, N. A. , Breit, C. M. , Norfleet, L. A . & Polk, H. C , Jr. IL-18 promoter polymorphisms correlate with the development of post-injury sepsis. Surgery 134, 351-6(2003). Kretowski, A . & Kinalska, I. Serum levels of interleukin-18~a potential marker of cardiovascular death\u00E2\u0080\u0094could be determined by genetic predisposition. Circulation 107, e206-7; author reply e206-7 (2003). Szalai, A . J . et al. Single-nucleotide polymorphisms in the C-reactive protein (CRP) gene promoter that affect transcription factor binding, alter transcriptional activity, and associate with differences in baseline serum C R P level. J Mol Med 83, 440-7 (2005). Schug, J . & Overton, G. C. TESS : Transcription Element Search Software. 2006 (1997). Majewski, J . & Ott, J . Distribution and characterization of regulatory elements in the human genome. Genome Res 12, 1827-36 (2002). 90 31. Zhou, Y . , Yamaguchi, E., Hizawa, N. & Nishimura, M . Roles of functional polymorphisms in the interleukin-18 gene promoter in sarcoidosis. Sarcoidosis Vase Diffuse Lung Dis 22, 105-13 (2005). 32. Kel ly , D. M . et al. Endotoxin Up-regulates Interleukin-18: Potential Role for Gram-Negative Colonization in Sarcoidosis. Am J Respir Crit Care Med 172, 1299-307 (2005). 33. Imboden, M . et al. The common G-allele of interleukin-18 single-nucleotide polymorphism is a genetic risk factor for atopic asthma. The S A P A L D I A Cohort Study. Clin Exp Allergy 36, 211 -8 (2006). 34. Haas, S. L. et al. -137 (G/C) IL-18 promoter polymorphism in patients with inflammatory bowel disease. Scand J Gastroenterol 40, 1438-43 (2005). 35. Ide, A . et al. Association between IL-18 gene promoter polymorphisms and C T L A - 4 gene 4 9 A / G polymorphism in Japanese patients with type 1 diabetes. J Autoimmun 22, 73-8 (2004). 36. Gracie, J . A . et al. Disease association of two distinct interleukin-18 promoter polymorphisms in Caucasian rheumatoid arthritis patients. Genes Immun 6, 211-6 (2005). 37. Sivalingam, S. P., Yoon, K. H., Koh, D. R. & Fong, K. Y . Single-nucleotide polymorphisms of the interleukin-18 gene promoter region in rheumatoid arthritis patients: protective effect of A A genotype. Tissue Antigens 62, 498-504 (2003). 91 CHAPTER 4C: A novel polymorphism of the interleukin-18 receptor 1 gene is associated with worse outcome following cardiopulmonary bypass surgery in Caucasians 4.1 Introduction Inappropriate activation of the inflammatory system following cardiopulmonary bypass (CPB) surgery can lead to the \"post-pump syndrome,\" evinced as increased organ dysfunction and prolonged hospital stay1. Inflammatory mediators, such as interleukin-18 (IL-18), play a key role in variation in the response to inflammatory events such C P B surgery. IL-18 is a key inflammatory mediator that acts in synergy with IL-12 to promote expression of interferon-gamma (IFN-y) and polarize T cells in a T h l pathway 2 ' 3. Increased serum concentrations of IL-18 have been associated with poor outcome in inflammatory conditions such as cardiac surgery4, sepsis 5, rheumatoid arthritis6 and type I diabetes7. Polymorphisms within the IL-18 gene have also been correlated with poor outcome in complex inflammatory diseases such as sepsis , rheumatoid arthritis and type I diabetes 1 0. IL-18 receptor-1 (IL-18R1) is one of two membrane-bound receptors for the T h l -polarizing IL-18 cytokine, and is necessary for ligand binding\". Downstream signaling from the IL-18 receptor complex (which also includes the IL-18 receptor-associated protein (IL-18RAP)) activates pro-inflammatory pathways, up-regulating cytokine responses such as tumor necrosis factor-alpha ( T N F - a ) 1 2 and interferon-gamma (IFN-y) 2. Natural soluble antagonists of cytokines, such as interleukin-1 receptor antagonist 1 3 and CA version of this chapter is in preparation for submission to the journal Shock. 92 the interleukin-18 binding protein 1 4 , indicate the effect that down-regulating the pro-inflammatory cytokine signal can have on inflammatory responses to C P B surgery. Blockade of receptors using antagonists is one approach to controlling inappropriate inflammatory responses following C P B surgery. Potential targets include the bradykinin b2 receptor 1 5 or the receptor for chemokine C C L 5 1 6 . Down-regulation of responsiveness of receptors to cytokine signals is another possible therapeutic action. Polymorphisms in receptor genes can affect the sensitivity of responses to inflammatory stimuli, indicating that hyper-sensitive receptors may be an attractive target for therapeutic blockade 1 7 . Polymorphisms in key inflammatory mediator genes and their respective receptor genes have been shown to have an effect in modulating the inflammatory response to C P B surgery 1 8 1 9 . With a look to this phenomenon and the previous literature attesting the role of IL-18 pathway genes in inflammation, we hypothesized that polymorphisms in the IL-18R1 gene are associated with adverse outcome from C P B surgery in Caucasians undergoing on-pump C P B surgery. 93 4.2 Methods The Research Ethics Board of Providence Health Care and the University of British Columbia approved this study. Inclusion Criteria A l l patients admitted to the Cardiac Surgery Intensive Care Unit (CSICU) of St Paul's Hospital following cardiopulmonary bypass surgery between February 2001 and December 2003 were eligible for entry into this study. Eight hundred and ninety patients were screened for inclusion of which 92% had cardiopulmonary bypass pump-driven circulation of blood during the surgery. We restricted our analyses to Caucasian patients who were successfully genotyped at four polymorphisms in the IL-18R1 gene in order to decrease the potentially confounding influence of population admixture secondary to ethnic diversity on associations between genotype and phenotype: Thus, 764 patients made up our final cohort for analysis. Primary Clinical Phenotype The systemic inflammatory response to C P B surgery manifests in part as low post-operative systemic vascular resistance index (SVRI). We used Kristof and Magder's definition of vasodilatory syndrome as 2 consecutive post-CPB SVRI measurements less than 1800 dyne.s/cm 5 /m 2 (SVRI = (mean arterial pressure - central venous pressure)*80/cardiac index ) as our primary clinical phenotype. This phenotypic measure is a composite measure of vascular resistance post-CPB used by many authors as a marker of post-CPB systemic inflammation 2 0\" 2 2 . We tested the effect of IL-18R1 6691 94 TT genotype on the prevalence of low SVRI by a multivariate linear regression model with covariates age, sex, BM1, smoking status and bypass duration. Secondary Clinical Phenotype Vasopressor agents influence the vascular resistance state post-CPB surgery, and are used to maintain vascular tone within normal l imits 2 3 . We measured use of vasopressors post-CPB and tested for differences according to IL-18R1 6691 C /T genotype. Intermediate Phenotype T N F - a is a pro-inflammatory cytokine that contributes to a vasodilatory state following C P B surgery 2 4. T N F - a expression lies downstream of the signaling cascade triggered by binding of IL-18 to its receptor complex 2 5 . Therefore, serum cytokine levels of T N F - a were measured pre-CPB, as well as 4 and 24 hours post-CPB as a relevant marker of inflammatory activation. Tag SNP Selection We used linkage disequilibrium (LD) to select a maximally informative set of haplotype tag SNPs (htSNPs) regarding the haplotype structure of the IL-18R1 gene while minimizing the number of genotyping assays. The SeattleSNPs Program in Genomics Applications (PGA) program Visual Genotype 2 (VG2, publicly available at http://pga.mbt.washington.edu/VG2.html) gives graphical representation of L D structure within a gene of interest, showing regions of L D clustered together and allowing 95 selection of htSNPs. We used unphased genotype data for the IL-18R1 gene in 23 unrelated Caucasians (part of the Coriell Registry), publicly available at the University of Arizona's Innate Immunity P G A website (http://www.innateimmunity.net/). The V G 2 program clusters SNPs by LD , allowing graphical representation of 'bins' of high L D from which htSNPs can be selected (Figure 4.1). We used the LDSelect software package to select htSNPs 2 6 . LDSelect tests pair-wise L D between SNPs (see Panels B and C of Figure 4.1) and groups them into bins of SNPs related by a threshold value of the r correlation coefficient for selection of htSNPs. With the r2 threshold set at 0.64 (i.e. SNPs within bins were related by a correlation coefficient of 64%), three htSNPs were selected to capture the underlying structure of the IL-18R1 gene: 5158 T /C (rsl420098), 6691 C /T (rs3771172)and 19158 G / A (rs3213732). Genotyping D N A was extracted from peripheral blood samples using the QIAamp D N A Blood Ma x i K i t (QIAgen Canada, Inc., Mississauga, O N , Canada). Genotypes for the htSNPs were determined using the 5' nuclease (Taqman) polymerase chain reaction technique (Applied Biosystems; Foster City, C A , U S A ) 2 7 . Primers for polymerase chain reaction (PCR) amplification of the genomic region of the IL-18R1 gene containing the htSNPs, and allele-specific probes for TaqMan-based determination of genotype are listed in Appendix A . 96 Statistics Differences in categorical variables (low SVRI , vasopressor use) were determined using Fisher's Exact Test for 2x2 tables, or the chi-squared test for larger tables. Differences in continuous variables were tested using the student's t test for 2 categories or A N O V A for more than 2 categories i f the variables were normally distributed; the Mann-Whitney U test was used for 2 categories and the Kruskal-Wall is U test was used for more than 2 categories when the variables were not normally distributed. Difference in serum T N F - a concentrations were tested using a repeated measures A N O V A model. A p value less than or equal to 0.05 was taken to indicate statistical significance. A l l analyses were performed using SPSS v l l . 5 (SPSS, Chicago, IL, USA) . Al le le frequencies were tested for Hardy-Weinberg equilibrium using the exact test o f Guo and Thompson and all were found to be in equilibrium. Previous work by Langley and Long indicates that a sample size of approximately 500 is sufficient to detect polymorphisms of modest effect s ize 2 9 . Therefore our cohort consists of 764 samples. 97 4.3 Results Selection of the 6691 C/T htSNP Patient genotype for the 5158, 6691 and 19158 htSNPs were used to infer haplotypes using the P H A S E v2.0 software package 3 0. We found 4 major haplotype clades occurring at a frequency greater than 5% within our patient population (Figure 4.2). Examining our primary clinical variable (low SVRI) by inferred haplotype clade, we found that clade B appeared to be associated with increased occurrence of low S V R I (Figure 4.3). Since this clade was uniquely tagged by the T allele of the 6691 C /T htSNP, we focused on this SNP for further analyses. No significant associations were found between genotype and phenotype for either of the other 2 htSNPs chosen (5158 T / C orl9158 G /A ) (not shown). Baseline Characteristics There were no statistically significant differences in pre-operative baseline characteristics such as age, sex, smoking status, or diabetic status among patients possessing 0, 1 or 2 copies of the T allele of the 6691 C /T htSNP (Table 4.1). There was a trend toward a difference in B M I among patients with 0, 1 or 2 copies of the T allele of the 6691 C /T htSNP, and this variable was included in multivariate regression analysis of the primary clinical phenotype. There were also no significant differences in peri-operative variables such as duration of bypass, duration of surgery, cardioplegia temperature or use of hemostatic modifiers among patients possessing 0, 1 or 2 copies of the T allele of the 6691 C /T htSNP (Table 4.2). 98 Primary Clincal Phenotype In our cohort of Caucasians who underwent on-pump C P B surgery, patients possessing two copies of the T allele of the 6691 C /T htSNP had significantly greater occurrence of low SVRI (40 of 61 patients, 66%) compared to all others (350 of 703 patients, 50%); p=0.022. This association remained significant upon multivariate linear regression with covariates age, sex, B M I , smoking status and bypass duration (p=0.034, Table 4.3), with classic risk factors age and sex also significant predictors of risk. Secondary Clinical Phenotype In our cohort of Caucasians who underwent on-pump C P B surgery, patients possessing the TT genotype of the 6691 C /T htSNP had significantly greater use of vasodilators post-CPB (11 of 61 patients, 18.0%) compared to all others (68 of 703 patients, 9.7%); p=0.048. Intermediate Phenotype In a subset o f patients who underwent on-pump C P B surgery and for whom serum cytokine values were available, patients homozygous for the T allele of the 6691 C /T htSNP had significantly greater serum T N F - a levels post-CPB compared to all others; p=0.034 (Figure 4.4). 99 4.4 Discussion We have identified an association between the T T genotype of the novel 6691 C /T polymorphism of the interleukin-18 receptor-1 gene and worse outcome in a cohort of Caucasians patients undergoing on-pump C P B surgery. The TT genotype was found to be associated with significantly greater occurrence of low SVRI post-CPB, which remained significant upon multivariate linear regression, and a significant increase in the need for vasopressor support post-CPB. The T T genotype was also found to be significantly associated with significantly increased serum T N F - a concentrations at 4 and 24 hours post-CPB, providing a biologically plausible explanation for this association. Low systemic vascular resistance index following C P B surgery is a recognized marker of poor vascular tone, and is considered a marker of systemic inflammation post-CPB\" . A previous report has indicated that an insertion/deletion (InDel) polymorphism within the IL-18R1 gene is associated with reduced capacity for IFN-y production and atopy in a Japanese population 3 1. This InDel polymorphism was found only to occur in the c D N A , not in the genomic D N A , and has been suggested to result from a splicing variation 3 1 . Thus, this polymorphism was not found in the sequences o f the IL-18R1 gene in the 23 Coriell Registry samples used to derive haplotypes. This polymorphism does not appear in L D with any of the SNPs reported in the IL-18R1 gene in our study. No other reports of polymorphisms within the IL-18R1 gene associated with diseases have been made to date, making our study the first to report an association between a genomic polymorphism in the IL-18R1 gene and disease. Cardoso and colleagues have reported two novel SNPs in the promoter of the IL-18R1 gene without any associated disease 100 study 3 2. These SNPs, reported at positions -69 and -638 with respect to the start of exon 1, correspond to SNPs at position -93 and -662 in our study (numbered with respect to the start site of translation, i.e. codon 1) (Figure 4.1). As these SNPs were not associated with altered outcome from any disease it is not necessary to use them as htSNPs, since their allele pattern is captured by our LD-based method of choosing htSNPs. Linkage disequilibrium exists between the 6691 C /T SNP and several other SNPs within the IL-18R1 gene (Figure 4.1): 6829 and 7033 in intron 2, 12958 in intron 3, 18612 in intron 4, 22281 in exon 6, 24144 in intron 6, 27266 in intron 7, 31409 and 31467 in intron 8 and 34841, 34842 and 35181 in the 3' untranslated region (UTR). The strong degree of L D between the T allele of the 6691 C /T htSNP and these SNPs means that the 6691 C /T SNP could be a marker for the effects of an alternative functional SNP, which could be any of the previously mentioned SNPs. The 6691 C /T SNP lies within intron 2 of the IL-18R1 gene. The functionality of intronic SNPs is an open question. Intronic SNPs can potentially affect the splicing of the pre -mRNA, thus producing splice variants and altered proteins, however most of these SNPs are thought to lie within 20 nucleotides of the intron/exon boundary in order to have any effect . The SNP associated with poor outcome in our study cohort, 6691 C/T, is not located within 20bp of an intron/exon boundary, nor are any of the intronic SNPs mentioned above that are in linkage disequilibrium with it. SNPs in the 3' U T R are able to alter the binding of regulatory elements 3 4. A scan of the IL-18R1 gene for transcriptional regulatory element binding sequences using the TESS (transcriptional element search software 3 5) program revealed no known human transcriptional element binding sites co-localized with the 101 SNPs reported above in the 3' UTR. Thus, the functionality of any of these SNPs is an open question. The IL-18R1 gene is located on chromosome 2ql2 in a cluster of similar receptor genes including four other members of the IL-1 receptor superfamily: interleukin-1 receptor 1(IL-1R1), IL-1R2, IL-1 receptor-like 2 ( IL-1RL2, also known as IL-1 receptor-related protein 2 (IL- lRrp2)) and IL-1RL1 (also known as T1 /ST2) 3 6 . The IL-18R1 receptor protein is the ligand-binding component of the IL-18 receptor complex, necessary for binding of IL-18 to the receptor complex and signal transduction, while the co-receptor protein, IL -18RAP ( IL -18RP) is the trans-membrane signaling component\". Binding o f IL-18 to its receptor complex signals an intracellular cascade, through intermediaries myeloid differentiation factor-88 (MyD88), interleukin-1 receptor-associated kinase ( IRAK) 1 and 4, tumor necrosis factor receptor-associated factor 6 (TRAF6) and eventually nuclear factor kappa-B ( N F - K B ) , leading to expression o f interferon-gamma (IFN-y) 3 7 and tumor necrosis factor-alpha (TNF -a ) 2 5 . Haplotype-based approaches to disease association studies are powerful methods for SNP-based disease association studies, incorporating underlying haplotype structure and individual SNP patterns. Since no previous reports of associations between SNPs and outcomes in the IL-18R1 gene are available traditional methods of choosing SNPs for disease association studies would not be appropriate. Our candidate gene-based approach allows us to narrow our examination of SNPs to genotype from the entire genome to regions of the genome associated with gene products reasonably thought to be in the 102 disease pathway. In this instance the IL-18R1 gene was chosen because it lies within the signal pathway of the pro-inflammatory cytokine IL-18, serum levels of which have been reported to be associated with altered outcomes from C P B surgery 3 8. The IL-18R1 gene has 101 polymorphic loci within the Coriell Caucasian population used to define haplotypes in our study, 74 of which occur with a minor allele frequency greater than 10% (Figure 4.1). Our method of choosing haplotype tag SNPs, using the P H A S E , M E G A 2 and LDSelect software packages, enabled maximization of information without an onerous genotyping burden - we genotyped 3 htSNPs to cover the majority of the haplotype structure. This approach is most effective in a case like the IL-18R1 gene, where there is no previous literature to aid in the selection of htSNPs. Any htSNPs that are associated with interesting outcomes may be tagging functional haplotypes. The haplotype structure may be assessed more fully upon finding a tagging SNP by genotyping more SNPs within the haplotype structure, thus giving a fuller picture of the structure. The drawback to this approach is the need for greater sample sizes in order to have enough power to discover clinically significant associations. Our study has several strengths, in addition to the use of htSNPs to improve association discovery for novel genes 3 9. The large sample size (greater than 500 patients) gives appropriate power to detect clinically relevant associations for variations of modest effect s ize 2 0 . We restricted our study to Caucasians in order to reduce the possibility o f spurious associations due to population admixture 4 0. In order to increase the homogeneity of the study sample, we restricted our analyses to patients undergoing on-pump C P B surgery, thus increasing the effect of the SNP of interest. One weakness of our study 103 design is the lack of functional investigation of the 6691 C /T SNP. The SNP of interest lies within an intron and may not possess a functional effect; rather, linkage disequilibrium may mean that the 6691 C /T SNP marks an alternative functional SNP through LD . Additionally, we have limited our study of this novel SNP to a single cohort; therefore this SNP should be assayed for disease association in other cohorts to ensure reproducibility. 104 4.5 Summary In the present study the TT genotype of the novel 6691 C /T polymorphism of the interleukin-18 receptor-1 gene was associated with significantly greater occurrence of low SVRI , despite significantly increased need for post-CPB vasopressor use. This genotype is also associated with significantly elevated serum T N F - a levels post-CPB, possibly establishing a biologically plausible explanation for our results. These widely varied and consistent markers of poor outcome from C P B surgery indicate that this allele is a potential risk allele for Caucasians undergoing on-pump C P B surgery. 105 4.6 Tables and Figures TABLE 4.1. Baseline characteristics of on-pump CPB surgery patients by IL-18R1 5591 C/T genotype. Values are reported as mean (standard error), median (interquartile range [range]), or number (percent). IL-18R1 6691 IL-18R1 6691 IL-18R1 6691 p Value TT CT CC N (%) 61 (8%) 294 (38%) 409 (54%) Age (Years) 67(15 [25-87]) 67 (14 [24-85]) 67(15 [24-88]) 0.937 Male Sex 49 (80%) 227 (77%) 306 (75%) 0.557 BMI (kg/m2) 26.5 (0.5) 28.1 (0.3) 27.9 (0.2) 0.064 Smoking 18(30%) 90 (31%) 122 (30%) 0.970 Diabetes 13 (21%) 78 (27%) 99 (24%) 0.624 Anti- 4 (7%) 25 (9%) 34 (8%) 0.879 hypertensive Use A C E II Inhibitor 30 (49%) 185 (63%) 252 (62%) 0.128 Use Beta-BIocker 35 (57%) 151 (51%) 199 (49%) 0.408 Use Aspirin Use 10(16%) 49(17%) 73 (18%) 0.903 106 TABLE 4.2. Summary of peri-operative variables of on-pump C P B surgery patients by IL-18R1 6691 C /T genotype. Values are reported as mean (standard error), median (interquartile range [range]), or number (percent). IL-18R1 6691 IL-18R1 6691 IL-18R1 6691 p Value TT CT CC Duration of 4.35 (0.14) 4.47 (0.07) 4.36 (0.06) 0.455 Surgery (Hours) Duration of 1.71 (0.11) 1.80 (0.05) 1.69 (0.04) 0.292 Bypass (Hours) Cardioplegia 36 (27 [6-37]) 36 (27 [6-37]) 36 (27 [6-37]) 0.263 Temperature (\u00C2\u00B0C) Use of Aprotinin 7(11%) 41 (14%) 69(17%) 0.390 Use of Milrinone 12 (20%) 59 (20%) 70(17%) 0.590 Use of Amicar 35 (57%) 160 (54%) 196 (48%) 0.141 Use of Protamine 14(23%) 51 (17%) 63 (15%) 0.318 107 TABLE 4.3. Details of multivariate binary linear regression on low S V R I with covariates IL-18R1 6691 TT genotype, sex, age, bypass duration, B M I and smoking status. IL-18R1 6691 TT genotype is an independent risk factor for low SVRI following C P B surgery, in addition to classic risk factors age and sex. Covariate Relative Risk of Low SVRI 95% Confidence Interval p Value IL-18R1 6691 TT 1.83 1 .05 -3 .19 0.034 Genotype Sex 1.63 1 .15 -2 .30 0.006 Age 0.98 0 .97 -0 .99 0.005 Bypass Duration 1.14 0 .96 -1 .36 0.129 BMI 0.99 0 . 9 6 - 1 . 0 2 0.539 Smoking Status 0.95 0 .69 -1 .31 0.765 108 F I G U R E L E G E N D S Figure 4.1: Genotype and linkage disequilibrium diagram ot'SNPs within the 1L-18R1 gene in 2 3 Caucasian Coriell samples. Only SNPs occurring at greater than or equal to 10% minor allele frequency were included in this diagram. Panel A shows the genotypes of SNPs of the IL-18R1 gene in 2 3 Caucasian Coriel l samples in physical order, with each column indicating a polymorphic locus and each row indicating the genotypes of one sample. Black fields indicate homozygous common genotypes, white fields indicate homozygous rare fields and grey fields indicate heterozygous genotypes (white fields with a black line through them indicate missing genotype information). Positions of the polymorphic loci (relative to the start site of transcription) are indicated at the top of the diagram. Panel B shows the genotypes clustered by L D , in order to show L D blocks within the IL-18R1 gene. Samples, loci and genotypes are indicated by the same coloring and labeling schema as in Panel A. Panel C shows the linkage disequilibrium map of SNPs in the IL-18R1 gene, clustered by LD . Polymorphic loci are indicated along the right-hand side and along the bottom of the diagram. Intersections of SNP loci are color-coded to indicate the degree of L D between the loci, with black indicating an r 2 value of 1.0 and white indicating an r 2 value of 0. Figure 4.2: Haplotype diagram of the IL-18R1 gene in our C S I C U study cohort. Unique haplotypes with frequency greater than 5% inferred from unphased patient genotype data are shown, with htSNPs indicated above. Dark fields represent common alleles, while light fields represent rare alleles. Frequency of each haplotype within our cohort are 109 indicated to the right of each haplotype. Relative positions of the loci are indicated above the diagram. Figure 4.3: Occurrence of low SVRI (primary clinical phenotype) by 1L-18R1 haplotype clade in our C S I C U study cohort. Percentage of patients possessing this phenotype is indicated on the Y -ax is , with IL-18R1 haplotype clade designations on the X-axis. Clade B was found to have greater occurrence of low SVRI , and is uniquely tagged by the T allele of the 6691 C /T htSNP. Figure 4.4: Serum T N F - a concentrations post-CPB by IL-18R1 6691 C /T genotype. Patients homozygous for the T allele had significantly greater serum T N F - a concentrations post-CPB compared to all others. 110 FIGURE 4.1. i l i i s f i i u l i i i i f i l i f t i s i i i mm aaaaaa i i i i . i t \u00E2\u0080\u00A2\u00E2\u0080\u00A2\u00E2\u0080\u00A2\u00E2\u0080\u00A2\u00E2\u0080\u00A2a aaa _\u00E2\u0080\u00A2\u00E2\u0080\u00A2 \u00C2\u00AB a a a a a a a * m \u00E2\u0080\u009E \u00E2\u0080\u009E \u00E2\u0080\u009E \u00E2\u0080\u009E -. \u00C2\u00AB . \" . \u00C2\u00BB \" \u00E2\u0080\u00A2 \u00E2\u0080\u00A2 . \" \" a . aa a \u00C2\u00BBa a a a_ <\u00E2\u0080\u00A2\u00E2\u0080\u00A2 aaaa \u00E2\u0080\u00A2 a e a a a a B B B B O B\u00C2\u00AB \u00C2\u00BB \u00E2\u0080\u00A2 \u00E2\u0080\u00A2\u00E2\u0080\u00A2 \u00E2\u0080\u00A2\u00E2\u0080\u00A2 a aaaa aa * aa aa mm I B I I * w mmmm mm a aw I Q I mm aaaa m a aaaa mm \u00E2\u0080\u00A2\u00C2\u00BB aa \u00E2\u0080\u00A2 aa n)Sa \u00E2\u0080\u00A2 \u00E2\u0080\u00A2\u00C2\u00AB a aa \u00E2\u0080\u00A2 . sin aaa \u00E2\u0080\u00A2 \u00E2\u0080\u00A2 I B \u00C2\u00ABB aa \u00C2\u00AB \u00C2\u00ABj a aaaa *a \u00C2\u00BB \u00C2\u00AB\u00C2\u00BB a ,? aaaaaat.\u00C2\u00BB* \u00C2\u00AB \u00E2\u0080\u00A2 >\u00E2\u0080\u00A2 a a \u00E2\u0080\u00A2 \u00E2\u0080\u00A2 \u00E2\u0080\u00A2 \u00E2\u0080\u00A2 \u00E2\u0080\u00A2 \u00E2\u0080\u00A2 \u00E2\u0080\u00A2 \u00C2\u00BB \u00C2\u00BB\u00E2\u0080\u00A2\u00E2\u0080\u00A2\u00E2\u0080\u00A2\u00C2\u00BB\u00E2\u0080\u00A2\u00C2\u00AB mmm ! \u00E2\u0080\u00A2 \u00E2\u0080\u00A2 \u00E2\u0080\u00A2 \u00E2\u0080\u00A2 \u00E2\u0080\u00A2 \u00E2\u0080\u00A2 .... \u00E2\u0080\u00A2 \u00E2\u0080\u00A2,\u00E2\u0080\u00A2\u00C2\u00AB-.. , , \u00C2\u00BB \u00C2\u00BB\u00C2\u00AB\u00E2\u0080\u00A2\u00C2\u00BB\u00E2\u0080\u00A2\u00E2\u0080\u00A2\u00E2\u0080\u00A2 a \u00E2\u0080\u00A2 \u00E2\u0080\u00A2 \u00E2\u0080\u00A2\u00C2\u00AB \u00E2\u0080\u00A2 \u00E2\u0080\u00A2 \u00E2\u0080\u00A2 aaaa aaa aaaa mm \u00C2\u00BBaaaaaa aaaa aaaaaa a aaaa \u00C2\u00BBa\u00C2\u00BBn aaa t \u00C2\u00AB n \u00C2\u00AB \u00E2\u0080\u00A2aaaaa aaaaaaa a an mmu \u00E2\u0080\u00A2 HH'Mvjsygote-CoirerK^ Al le le [jHfjmosygote-Rare Al le le 0 H e t e r o z y g o t e tZ] Undetermined 525ff977?5 a f^ a^ s^&s aaaaaa \u00E2\u0080\u00A2 \u00E2\u0080\u00A2 \u00C2\u00BB\u00E2\u0080\u00A2\u00E2\u0080\u00A2..<>\u00E2\u0080\u00A2 . J M a o . i u i i i a u a B a a a a a a a a a \u00E2\u0080\u00A2 \u00E2\u0080\u00A2 \u00E2\u0080\u00A2 \u00E2\u0080\u00A2 \u00E2\u0080\u00A2 \u00E2\u0080\u00A2 \u00E2\u0080\u00A2 \u00E2\u0080\u00A2 \u00E2\u0080\u00A2 \u00E2\u0080\u00A2 \u00E2\u0080\u00A2 \u00E2\u0080\u00A2 l l t t i i t i M i i a a . >a a a a a a a a a B a JSSSa'\" , r * ' ' ' 1 \" \u00E2\u0080\u00A2 . M M * * * - * . , . * \u00C2\u00BB.222\u00C2\u00A35!!!22a25 - s\u00C2\u00BB\u00C2\u00BBw\u00C2\u00ABa nviEissasavnwi aaaaaaaaaaaaaaaaaaaaaaaaa*aa.aa\u00C2\u00BB\u00C2\u00AB\u00C2\u00BB*\u00C2\u00ABa\u00C2\u00BB*\u00C2\u00BB a \u00E2\u0080\u00A2 a a a a a a a a a a a a a a a 2282!2222222222228I!!\"5!*\"\"\"\"\"\"\"\"\"*\"\"\u00C2\u00BB|\u00C2\u00BB\" \u00E2\u0080\u00A2\u00E2\u0080\u00A2\u00E2\u0080\u00A2 \u00E2\u0080\u00A2\u00E2\u0080\u00A2 San S22222222222!\"1*\"**** a,<\u00C2\u00BB\"> \u00E2\u0080\u00A2\u00E2\u0080\u00A2\u00E2\u0080\u00A2 aaa mm aaa! 5822222222222\"\"\"*1'0*''\"' 3<\u00C2\u00AB\u00C2\u00BBSS\u00C2\u00ABIfiSaie\u00C2\u00BB39ffl5* a a * 3 S \u00C2\u00AB S ! \u00C2\u00AB * 8 5 ! S 3 ; * * T a a a a a mmmatlW - I * * . ' \u00E2\u0080\u00A2 \u00E2\u0080\u00A2 \u00E2\u0080\u00A2 ' ' \" \u00E2\u0080\u00A2 \u00E2\u0080\u00A2 \u00E2\u0080\u00A2 \u00E2\u0080\u00A2 \u00C2\u00AB a a a a a a a \u00E2\u0080\u00A2 \u00E2\u0080\u00A2 aaa * > . \u00C2\u00BB w\u00C2\u00ABaa \u00E2\u0080\u00A2 a a a a a a a a a a a B a B a a a a a a a a a a a a a a a a a a a a a a a a i 15 \u00E2\u0080\u00A2\u00C2\u00BBaa\u00C2\u00BBaaaaa\u00C2\u00ABa.\u00C2\u00ABa\u00C2\u00AB \u00E2\u0080\u00A2 \u00E2\u0080\u00A2 \" \" . ! ! S S i n a \u00C2\u00BB \u00C2\u00BB \u00C2\u00BB i \" \" \u00C2\u00AB a \u00C2\u00BB \u00E2\u0080\u00A2aaaaaaaaaaaaaaaaaaiaaaaaaa < \u00C2\u00BB \u00C2\u00AB < a > \u00E2\u0080\u00A2 15 LD Method: r\"2 (min: 0 . 0 , 4? aaaa aaaa LD Min/Max Shading Scale \u00E2\u0080\u00A2Bin, ' \u00E2\u0080\u00A2 8 i s , 352 1 8 3 ' ; ' o o | 2 a 5 111 F I G U R E 4.2. Relative Position Clade 5158 6691 19158 Frequency c c T A A S l l l l l i l 112 FIGURE 4.3. N = 129 60 -i 58 56 54 E 5 2 > W 50 O _ l 48 46 44 42 40 Ciade A Clade B Clade C Clade D 113 F I G U R E 4.4. 800 700 600 g 500 ' 400 300 A $ 200 100 \u00E2\u0080\u00A2IL18R1 6691 CC/CT IL18R1 6691 TT p = 0 . 0 3 4 4Hr Post-CPB 24Hr Post-CPB 114 4.7 References 1. L i , S., Price, R., Phiroz, D., Swan, K. & Crane, T. A. Systemic inflammatory response during cardiopulmonary bypass and strategies. J Extra Corpor Technol 37, 180-8 (2005). 2. Rodriguez-Galan, M . C , Bream, J. H., Fair, A. & Young, H. A . Synergistic effect of IL-2, IL-12, and IL-18 on thymocyte apoptosis and Th l /Th2 cytokine expression. J Immunol 174, 2796-804 (2005). 3. Tone, M. , Thompson, S. A. , Tone, Y . , Fairchild, P. J . & Waldmann, H. Regulation of IL-18 (IFN-gamma-inducing factor) gene expression. J Immunol 159,6156-63 (1997). 4. Sablotzki, A . et al. The systemic inflammatory response syndrome following cardiac surgery: different expression of proinflammatory cytokines and procalcitonin in patients with and without multiorgan dysfunctions. Perfusion 17, 103-9 (2002). 5. Emmanuilidis, K. et al. Differential regulation of systemic IL-18 and IL-12 release during postoperative sepsis: high serum IL-18 as an early predictive indicator of lethal outcome. Shock 18, 301-5 (2002). 6. Rooney, T. et al. Synovial tissue interleukin-18 expression and the response to treatment in patients with inflammatory arthritis. Ann Rheum Dis 63, 1393-8 (2004). 7. Hanifi-Moghaddam, P., Schloot, N. C , Kappler, S., Seissler, J . & Kolb , H. A n association of autoantibody status and serum cytokine levels in type 1 diabetes. Diabetes 52, 1137-42 (2003). 115 8. Stassen, N. A. , Breit, C. M , Norfleet, L. A . & Polk, H. C , Jr. IL-18 promoter polymorphisms correlate with the development of post-injury sepsis. Surgery 134, 351-6 (2003). 9. Gracie, J . A . et al. Disease association of two distinct interleukin-18 promoter polymorphisms in Caucasian rheumatoid arthritis patients. Genes Immun 6, 211-6 (2005). 10. Kretowski, A . et al. Interleukin-18 promoter polymorphisms in type 1 diabetes. Diabetes 51, 3347-9 (2002). 11. Azam, T. et al. Identification of a critical Ig-like domain in IL-18 receptor alpha and characterization of a functional IL-18 receptor complex. J Immunol 171, 6574-80 (2003). 12. Chandrasekar, B. et al. Activation of intrinsic and extrinsic proapoptotic signaling pathways in interleukin- 18-mediated human cardiac endothelial cell death. J Biol Chem 279, 20221-33 (2004). 13. Marie, C , Muret, J . , Fitting, C , Payen, D. & Cavaillon, J . M . Interleukin-1 receptor antagonist production during infectious and noninfectious systemic inflammatory response syndrome. Crit Care Med 28, 2277-82 (2000). 14. Novick, D. et al. A novel IL -18BP E L I S A shows elevated serum IL-18BP in sepsis and extensive decrease of free IL-18. Cytokine 14, 334-42 (2001). 15. Pretorius, M. , Scholl, F. G., McFarlane, J . A., Murphey, L. J . & Brown, N. J . A pilot study indicating that bradykinin B2 receptor antagonism attenuates protamine-related hypotension after cardiopulmonary bypass. Clin Pharmacol Ther 78, 477-85 (2005). 116 16. Proudfoot, A . E. Chemokine receptors: multifaceted therapeutic targets. Nat Rev Immunol 2, 106-15 (2002). 17. Risma, K. A . et al. V75R576 IL-4 receptor alpha is associated with allergic asthma and enhanced IL-4 receptor function. J Immunol 169, 1604-10 (2002). 18. Schroeder, S. et al. A tumor necrosis factor gene polymorphism influences the inflammatory response after cardiac operation. Ann Thorac Surg 75, 534-7 (2003). 19. Lehmann, L. E. et al. A single nucleotide polymorphism of macrophage migration inhibitory factor is related to inflammatory response in coronary bypass surgery using cardiopulmonary bypass. Eur J Cardiothorac Surg (2006). 20. Kristof, A . S. & Magder, S. Low systemic vascular resistance state in patients undergoing cardiopulmonary bypass. Crit Care Med 27, 1121-7 (1999). 21. Cremer, J . et al. Systemic inflammatory response syndrome after cardiac operations. Ann Thorac Surg 61, 1714-20 (1996). 22. Oudemans-van Straaten, H. M . et al. Increased oxygen consumption after cardiac surgery is associated with the inflammatory response to endotoxemia. Intensive Care Med 22, 294-300 (1996). 23. Morales, D. L. et al. A double-blind randomized trial: prophylactic vasopressin reduces hypotension after cardiopulmonary bypass. Ann Thorac Surg 75, 926-30 (2003). 24. Sanders, D. B., Larson, D. F., Hunter, K., Gorman, M. & Yang, B. Comparison of tumor necrosis factor-alpha effect on the expression of iNOS in macrophage and cardiac myocytes. Perfusion 16, 67-74 (2001). 117 25. Chandrasekar, B. et al. The pro-atherogenic cytokine interleukin-18 induces C X C L 1 6 expression in rat aortic smooth muscle cells via MyD88, interleukin-1 receptor-associated kinase, tumor necrosis factor receptor-associated factor 6, c-Src, phosphatidylinositol 3-kinase, Akt, c-Jun N-terminal kinase, and activator protein-1 signaling. J Biol Chem 280, 26263-77 (2005). 26. Carlson, C. S. et al. Selecting a maximally informative set of single-nucleotide polymorphisms for association analyses using linkage disequilibrium. Am J Hum Genet 1'4, 106-20 (2004). 27. Livak, K. J . A l le l ic discrimination using fluorogenic probes and the 5' nuclease assay. Genet Anal 14, 143-9 (1999). 28. Guo, S. W. & Thompson, E. A. Performing the exact test of Hardy-Weinberg proportion for multiple alleles. Biometrics 48, 361-72 (1992). 29. Long, A . D. & Langley, C. H. The power o f association studies to detect the contribution of candidate genetic loci to variation in complex traits. Genome Res 9, 720-31 (1999). 30. Stephens, M . & Donnelly, P. A comparison of bayesian methods for haplotype reconstruction from population genotype data. Am J Hum Genet 73, 1162-9 (2003). 31. Watanabe, M . et al. Predominant expression of 950delCAG of IL-18R alpha chain c D N A is associated with reduced IFN-gamma production and high serum IgE levels in atopic Japanese children. J Allergy Clin Immunol 109, 669-75 (2002). 118 32. Cardoso, S. P., Keen, L. & Bidwel l , J . Identification of two novel single nucleotide polymorphisms in the promoter of the human interleukin-18 receptor alpha. Eur J Immune-genet 31, 27-9 (2004). 33. Majewski, J . & Ott, J . Distribution and characterization of regulatory elements in the human genome. Genome Res 12, 1827-36 (2002). 34. Mil ler , G. M . & Madras, B. K. Polymorphisms in the 3'-untranslated region of human and monkey dopamine transporter genes affect reporter gene expression. Mol Psychiatry 7, 44-55 (2002). 35. Schug, J . & Overton, G. C. TESS : Transcription Element Search Software. 2006 (1997). 36. Dale, M . & Nick l in , M . J. Interleukin-1 receptor cluster: gene organization of IL1R2, IL1R1, IL1RL2 ( IL- lRrp2) , IL1RL1 (T1/ST2), and IL18R1 ( IL - lRrp) on human chromosome 2q. Genomics 57, 177-9 (1999). 37. K i m , S. H. et al. Functional reconstitution and regulation of IL-18 activity by the IL-18R beta chain. J Immunol 166, 148-54 (2001). 38. Sablotzki, A . et al. Different expression of cytokines in survivors and non-survivors from M O D S following cardiovascular surgery. Eur J Med Res 8, 71-6 (2003). 39. Yende, S. et al. Impact of cytokine gene polymorphisms on outcomes of coronary artery bypass graft surgery. Chest 121, 86S (2002). 40. Cardon, L. R. & Bel l , J . I. Association study designs for complex diseases. Nat Rev Genet 2, 91-9 (2001). 119 CHAPTER 5 d: Interleukin-18 pathway gene haplotypes and polymorphisms are not associated with altered outcome in critically ill Caucasians 5.1 Introduction Inappropriate activation of the inflammatory system following septic stimulus can lead to increased mortality and organ dysfunction 1 ' 2. Inflammatory mediators, such as interleukin-18 (IL-18), play a key role in variation in the response to inflammatory events such as sepsis and C P B surgery. IL-18 is a key inflammatory mediator that acts in synergy with IL-12 to promote expression of interferon-gamma (IFN-y) and polarize T cells in a T h l pathway 3 ' 4. Increased serum concentrations of IL-18 have been associated with poor outcome in inflammatory conditions such as sepsis 5, cardiac surgery6, rheumatoid arthritis 7 and type I diabetes8. Polymorphisms within the IL-18 gene have also been correlated with poor outcome in complex inflammatory diseases such as sepsis 9, rheumatoid arthritis 1 0 and type I diabetes 1 1. For a summary of SNP and haplotype-based disease association studies, see TABLE 3.3 in CHAPTER 3. IL-18 signals through two membrane-bound receptor molecules, IL-18 receptor-1 (IL-18R1), also known as IL-18Roc, and the IL-18 receptor-associated protein (IL-18RAP), also known as IL-18Rp\ While IL-18R1 is the ligand-binding subunit of the 10 receptor complex , I L -18RAP has a longer cytoplasmic tail; both are necessary for intracellular transduction of the signal 1 3 . Signaling after IL-18 binding to its receptor complex activates downstream gene transcription through either the AP-1 or N F - K B transcription factors, and initiates transcription of genes such as vascular endothelial d A version o f this chapter is in preparation for submission to the journal Critical Care. 120 growth factor ( V E G F ) 1 4 , the chemokine C X C L 1 6 1 5 , tumor necrosis factor alpha 1 6 and 11 monocyte chemotactic protein-1 . Activation of N F - K B , an outcome of IL-18 receptor binding, causes several phenotypic results relevant to sepsis and inflammation, such as systemic inflammation and hypotension (though not fever) , making the IL-18 and IL-1 pathways distinct yet related. The interleukin-18 binding protein (IL-18BP) is a soluble serum protein that binds and inactivates IL-18 activity, thus acting as an IL-18 antagonist 1 9. IL -18BP is not a homologue of either IL-18 receptor component 2 0, but is related to proteins produced by the Poxvirus family that reduce T h l immunity in Poxvirus-infected hosts 2 1 . Altered serum levels of IL -18BP and dysregulated IL-18/ IL-18BP balance can alter outcomes from inflammatory conditions such as graft-versus-host disease 2 2, sepsis 2 0 , hemophagocytic syndrome (a syndrome characterized by uncontrolled activation of T h l -type lymphocytes and macrophages) 2 3 and adult-onset Stil l 's disease 2 4. IL -18BP expression is upregulated by IL-18, IL-12 and IFN-y 2 5 . Polymorphic loci within the IL-18 gene have previously been investigated for associations with serum levels of IL-18 as well as outcomes from diseases. Two promoter polymorphisms of the IL-18 gene in particular have received attention with regard to serum IL-18 levels and outcomes from inflammatory diseases: -607 C / A and -137 11 26 G/C ' . Similarly, two polymorphic loci have been found in the promoter of the IL-18R1 gene: -638 C /T and -69 C/T, though these have not been linked to outcome from 121 any disease state, nor to alterations in cell membrane receptor expression 2 7 . N o polymorphisms in the IL -18BP or the IL -18RAP genes have been discovered to date. Our study design is based on the proposed importance of IL-18 in the pathophysiology of critical illness. The inclusion of other members of the IL-18 pathway (IL-18BP, IL-18R1 and IL -18RAP) is a logical continuation of the investigation into IL-18 gene polymorphisms and haplotypes, given the importance polymorphisms of other cellular receptors (such as the toll - l ike receptors ' , Fcgamma receptor and the endothelial protein C receptor 3 1) and soluble binding proteins (such as the interleukin-1 receptor antagonist ) in the pathophysiology of critical illness. We tested the hypothesis that haplotypes and htSNP genotypes of IL-18 pathway genes are modulators of outcome from critical illness in Caucasians with sepsis. 122 5.2 Methods The Research Ethics Board of Providence Health Care and the University of British Columbia approved this study. Inclusion Criteria Critically i l l patients with sepsis admitted to the tertiary mixed medical-surgical intensive care unit ( ICU) of St Paul's Hospital were screened for inclusion into this study. O f those, 488 were Caucasian and were successfully genotyped at all 12 chosen haplotype tag SNPs (htSNPs). We limited the patients in our study to Caucasians to limit the potentially confounding effects of population admixture on genotype-phenotype associations 3 3. The systemic inflammatory response syndrome (SIRS) is defined as two of the following four criteria: 1) fever (temp > 38\u00C2\u00B0C) or hypothermia (<36\u00C2\u00B0C), 2) tachypnea (> 20 breaths/min), 3) tachycardia (> 90 beats/min) or paced, and 4)leukocytosis (total leukocyte count > 12,000/uL) or leukopenia (total leukocyte count < 4,000/u.L) 3 4.Sepsis is defined as having a proven or suspected infection in addition to 2 of the 4 SIRS criteria. Patients were included in this cohort on the day they met 2 of the 4 SIRS criteria, and were followed for 28 days or until death or discharge. Clinical Phenotype Our primary outcome variable was 28-day mortality. Secondary outcome variables were prevalence of septic shock and days alive and free (DAF) of organ dysfunction (cardiovascular, respiratory, renal, hematologic and hepatic organ systems). Significant organ dysfunction in a particular organ system was defined as present during 123 a 24-hour period i f there was evidence of at least moderate organ dysfunction in that system using the Brussels criteria (Table 5.1)35. To assess duration of organ dysfunction and SIRS corrected for the effects of death, we calculated days alive and free of organ dysfunction as follows: during each 24 hour period for each variable, a D A F score of 1 was given i f the patient was alive and free of significant organ dysfunction (normal or mild dysfunction). A D A F score of 0 was given i f the patient was not alive or had significant organ dysfunction (moderate or worse dysfunction). The D A F scores for each organ system were summed over the 28 day observation period (carrying forward where applicable 3 6) to give a total D A F score for each organ system. The lowest possible D A F score is 0, indicating greater organ dysfunction, and the highest is 28, indicating less organ dysfunction. Baseline demographics, including age, sex, Acute Physiology and Chronic Health ( A P A C H E ) II score and medical vs. surgical diagnosis (based on A P A C H E III diagnostic codes 3 7), were recorded on admission. Tag SNP Selection To determine IL-18 pathway (IL-18, IL -18BP, IL-18R1 and IL -18RAP) gene haplotypes, we used P H A S E v2.0 3 8 to infer haplotypes from unphased genotypes for each gene in the 23 Coriell Registry subjects, publicly available at the University of Arizona's Innate Immunity Programs in Genomic Applications website (http://www.innateimmunity.nef). The resulting haplotypes were clustered by similarity into groups of similar haplotypes (clades) using the M E G A 2 3 9 software package. A set of 124 maximally informative haplotype tag SNPs (htSNPs) were selected using the LDSelect with the r correlation coefficient threshold set at 0.64. The selected htSNPs were genotyped in our patient cohort, and unphased patient genotype data was used to infer haplotypes for the IL-18 (Figure 5.1a), IL -18BP (Figure 5.1b), IL-18R1 (Figure 5.1c) and IL -18RAP (Figure 5.1d) gene. Genotyping D N A was extracted from peripheral blood samples using the QIAamp D N A Blood Max i K i t (QIAgen Canada, Inc., Mississauga, O N , Canada). Genotypes for the htSNPs were determined using the 5' nuclease (TaqMan) polymerase chain reaction technique (Applied Biosystems; Foster City, C A , U S A ) 4 1 . Primer sequences for P C R amplification of the regions of interest and probe sequences used in TaqMan-based genotyping of patients are given in Appendix A for all SNP assays used in this study. Statistics Differences in categorical variables were determined using Fisher's Exact Test for 2x2 tables, or the chi-squared test for larger tables. Differences in 28-day survival were tested using the Kaplan-Meier test for survival. Differences in the non-normal days alive and free (DAF) of organ dysfunction variables were determined using the non-parametric Mann-Whitney U Test for 2 categories or Kruskal-Wall is H Test for more than 2 categories. A p value less than or equal to 0.05 was taken to indicate statistical 125 significance. A l l analyses were performed using SPSS v l 1.5 (SPSS, Chicago, IL, USA) . Allele frequencies were tested for Hardy-Weinberg equilibrium using the exact test of Guo and Thompson 4 2 and all were found to be in equilibrium. A power calculation for 28 day mortality, assuming a relative risk of mortality of 1.6 for the risk allele over the normal allele and a minimum minor allele frequency of 10% from our sample size of approximately 500 patients, gives a power to detect an association of 80%. 126 5.3 Results Haplotype and htSNP Analysis A . IL-18 Using P H A S E v2.0, we found four unique haplotypes occurring at a frequency greater than 5% in our study cohort based on unphased genotype of the four selected htSNPs (-607 C / A (rsl946518), -137 G /C (rsl87238), 8148 C /T (rs360722) and 9545 T / G (rs5744249)) (Figure 5.1a). These haplotypes constitute the analysis variable for the IL-18 gene, along with the individual htSNP genotypes. B. IL -18BP Three haplotypes of the IL -18BP gene were inferred from unphased patient genotype data of the two selected htSNPs (-1765 T /C (rs3814721) and 3 041 C /T (rsl541304)) in our study cohort (Figure 5.1b). These, along with genotypes of the two htSNPs, were used as the analysis variable for the IL -18BP gene. C. IL-18R1 Four IL-18R1 gene haplotypes occurring at a frequency greater than 5% were inferred from unphased patient genotype data of the three selected htSNPs (5158 T /C (rsl420098), 6691 C /T (rs3771172) and 19158 A / G (rs3213732)) (Figure 5.1c), and were the analysis variable for the IL-18R1 gene along with genotype of the three tSNPs. D. IL -18RAP 127 Five I L -18RAP gene haplotypes occurring at a frequency greater than 5% were inferred from unphased genotype data of the three selected htSNPs (14336 A / T (rs4479442), 20354 T / C (n/a) and 27120 A / G (n/a)) (Figure 5.1d), and along with the htSNP genotype data, made up the analysis variable. Baseline Characteristics There were no statistically significant differences in age, sex, A P A C H E II score or medical vs. surgical diagnosis among the inferred haplotypes of the IL-18 gene (Table 5.2a). There were no significant differences in age, A P A C H E II score or medical vs. surgical diagnosis among haplotypes of the IL-18BP gene, however a significant difference in sex among haplotypes was observed (Table 5.2b). There were no significant differences in age, sex or medical vs. surgical diagnosis among haplotypes of the IL-18R1 gene, however a trend toward a difference in A P A C H E II score by IL-18R1 haplotype was observed (Table 5.2c). There were no significant difference in age, sex, A P A C H E II score or medical vs. surgical diagnosis among haplotypes of the IL -18RAP gene (Table 5.2d). No significant differences were observed in age, sex, A P A C H E II score or medical vs. surgical diagnosis occurred among patients possessing 0, 1 or 2 copies of each allele of the htSNPs of those genes (not shown). Significant associations between haplotypes of IL-18 pathway genes and sex or A P A C H E II score were further tested for effects on clinical outcomes (see below). 128 Primary Clineal Phenotype There were no significant differences in 28 day mortality, our primary clinical phenotype, by haplotype of the IL-18 gene (Figure 5.2a), the IL -18BP gene (Figure 5.2b), the IL-18R1 gene (Figure 5.2c) or the IL -18RAP gene (Figure 5.2d). In order to test for effects of associations between haplotype and sex or A P A C H E II score observed in baseline characteristics, Cox proportional hazard regression analyses with covariates gene haplotype, age, sex, A P A C H E II score and medical vs. surgical were performed, with the result that the observed associations did not affect mortality in our cohort (not shown). There were also no significant differences in 28 day mortality by htSNP genotype for any of the htSNPs in the IL-18 gene, the IL -18BP gene, the IL-18R1 gene or the IL -18RAP gene (Appendix B). Secondary Clinical Phenotype Organ systems tested for significant differences were: cardiovascular, respiratory, renal, hematologic and hepatic. There were no significant differences in days alive and free of major organ dysfunction, our secondary clinical phenotype, by haplotype of the IL-18 gene, the IL -18BP gene, IL-18R1 gene or the IL -18RAP gene (Appendix B). There were also no significant differences in D A F organ dysfunction by genotype of htSNPs of any of the IL-18 pathway genes (not shown). There were no significant differences in prevalence of septic shock by haplotype of the IL-18 gene (Figure 5.1a), the IL -18BP gene (Figure 5.1b), the IL-18R1 gene (Figure 5.1c) or the IL -18RAP gene (Figure 5.1d). 129 5.4 Discussion We report a lack of significant associations between outcomes from critical illness and haplotypes or genotypes of genes in the interleukin-18 pathway, including IL-18, IL-18BP, IL-18R1 and IL -18RAP. Our primary clinical phenotype was 28 day mortality, with prevalence of sepsis and septic shock and days alive and free of organ dysfunction as our secondary clinical phenotype. While 28 day mortality is a fairly blunt endpoint, our secondary clinical phenotypes allow for more sensitive probes into the effects of IL-18 gene pathway haplotypes and htSNP genotypes on outcomes. Days alive and free of organ dysfunction serves as a numerical method of assaying organ dysfunction without ignoring effects of death. Prevalence of sepsis and septic shock also serve as meaningful secondary clinical outcomes because mortality from sepsis and septic shock stand at approximately 30% and 55-65%, respectively 3 4. The genetic contribution to outcomes from inflammatory diseases such as SIRS is estimated to be greater than that of cancer or cardiovascular disease 4 3. Alterations in cell signaling pathways is an important process in sepsis and inflammation 4 4 . Polymorphisms of key inflammatory mediator genes, such as IL-18 and its pathway members, can have an effect on pathway mechanics and outcomes from critical i l lness 4 5 . Two polymorphisms of the IL-18 gene, the -607 C / A and -137 G /C htSNPs used in this study, have been previously described as having an effect on development of sepsis following injury 9. Similarly, these two polymorphisms, separately or in a two-SNP haplotype, have been associated with altered outcomes from other inflammatory diseases, such as type I diabetes 1 1 ' 4 6, inflammatory bowl disease 4 7, rheumatoid arthritis 4 8 and atopic asthma 4 9. 130 Polymorphisms of the interleukin-18 binding protein have been identified as potential risk factors for type I diabetes, however minor allele frequencies were deemed to be too low to allow for noticeable effect size 5 0 . Our haplotype-based selection of htSNPs in the IL -18BP gene resulted in selection of two htSNPs: -1765 C /T and 3041 T /C (Figure 5.1b). Al le le frequencies of these two htSNPs, and the frequencies of rare haplotypes based on these htSNPs, were quite low in our cohort, resulting in lower power to detect differences in outcomes. The subsequent lack of significant findings is therefore not surprising for this gene. Interleukin-18 receptor subunits (IL-18R1 and IL -18RAP) play a key role in transduction of the signal following ligand binding at the cell surface. While polymorphisms of the IL-18R1 gene have previously been described in the literature 2 7, no association study has found these or any others to play a role in outcomes from critical illness. In a related study from our lab, a novel polymorphism of the IL-18R1 gene was found to be associated with altered outcome from cardiopulmonary bypass surgery (Chapter 4), but neither this polymorphism, nor other htSNPs nor resulting haplotypes were found to be associated with any alterations from critical illness in this study. Haplotype-based disease association studies have several advantages over traditional single SNP-based studies. Haplotype blocks depend on linkage disequilibrium between SNPs, and can therefore be used to capture information about more than one SNP simply by genotyping htSNPs. The statistical power to detect associations is 131 improved using inferred haplotypes over traditional single SNP analyses 5 1. This method provides a way to select SNPs for genotyping and haplotype construction that is not dependant on literature reports of SNP association studies to provide genotyping targets. Polymorphic loci associated with outcomes of interest in the literature, such as -607 C / A and -137 G /C of the IL-18 gene, can be incorporated into this design method, allowing flexibility in the design of SNP-based disease association studies. Another strength of our study lies in the fact that we used a large sample size and restricted our cohort to critically i l l Caucasians, generating a large, homogeneous cohort i in an effort to maximize the potential effects of SNPs and haplotypes and to reduce the potential of falsely positive associations due to population admixture 3 3 . Our large sample size decreases the likelihood of false negative associations, making our study likely a truly negative one for the genes tested. 132 5.5 Summary In this study we report a lack of significant associations between outcomes from critical illness, including mortality, organ dysfunction and prevalence of sepsis and septic shock, and haplotypes and htSNP genotypes of four genes in the interleukin-18 pathway: IL-18, IL -18BP, IL-18R1 and IL -18RAP. The lack of associations is l ikely not due to lack of statistical power, but seems to represent a lack of functional effect of these variations within IL-18 pathway genes and outcomes in critically i l l Caucasians. 133 5.6 Tables and Figures T A B L E 5.1. Brussels Organ Dysfunction Scoring Criteria. O R G A N S Free of Organ Dysfunction Clinically Significant Organ Dysfunction Normal M i l d Moderate Severe Extreme Cardiovascular >90 Systolic B P (mmHg) Pulmonary Pa0 2 /F|0 2 (mmHg) Renal >400 <1.5 Creatinine (mg/dL) Hepatic Bil irubin (mg/dL) Hematologic Platelets (xloVmm 3) Neurologic (Glasgow Score) <1.2 >120 15 <90 Responsive to fluid 400-301 1.5-1.9 1.2-1.9 120-81 14-13 <90 Unresponsive to fluid 300-201 Acute lung injury 2.0-3.4 2.0-5.9 80-51 12-10 <90 + p H <7.3 200-101 A R D S 3.5-4.9 6.0-11.9 50-21 9-6 <90 + pH <7.2 <100 Severe A R D S >5.0 >12 <20 <5 Round Table Conference on Cl inical Trials for the Treatment of Sepsis Brussels, March 12-14, 1994 3 5 134 TABLE 5.2a. Baseline Characteristics by IL-18 Gene Haplotypes. Values are reported as mean (standard error), median (interquartile range [range]), or number (percent). IL-18 Gene Haplotype A B C D p Value N (%) 451 (41%) 140 (13%) 282 (26%) 222 (20%) Age (Years) 59(26 59(28 60 (24 59 (25 0.543 [15-88]) [19-88]) [17-89]) [15-89]) Male Sex (%) 294 (65%) 83 (59%) 189 (67%) 145 (65%) 0.180 APACHE II Score 24.2 (0.4) 24.0 (0.8) 23.3 (0.5) 23.8 (0.6) 0.626 Surgical Diagnosis (%) 110(24%) 34 (24%) 71 (25%) 60 (27%) 0.766 TABLE 5.2b. Baseline Characteristics by IL -18BP Gene Haplotypes. Values are reported as mean (standard error), median (interquartile range [range]), or number (percent). IL-18BP Gene Haplotype A B C p Value N (%) 1013 40 (4%) 45 (4%) (92%) Age (Years) 59 (25 53.5 (24.5 58(20 0.132 [15-89]) [17-79]) [24-79]) Male Sex (%) 665 (66%) 19(48%) 26 (58%) 0.038 APACHE II Score 23.6 (0.3.) 25.3 (1.3) 25.7(1.2) 0.146 Surgical Diagnosis (%) 259 (26%) 6(16%) 7(15%) 0.108 135 TABLE 5.3c. Baseline Characteristics by IL-18R1 Gene Haplotypes. Values are reported as mean (standard error), median (interquartile range [range]), or number (percent). IL-18R1 Gene Haplotype A B C D p Value N (%) 104 290 298 405 Age (Years) 58.5 (27.75 60.5 (25.25 56 (25 60 (24.5 0.171 [17-85]) [15-85]) [19-89]) [15-89]) Male Sex (%) 66 (63%) 192 (66%) 179 (60%) 271 (70%) 0.261 APACHE II Score 23.0 (0.9) 23.9 (0.5) 24.8 (0.5) 23.3 (0.4) 0.086 Surgical Diagnosis (%) 22 (21%) 80 (28%) 68 (23%) 102 (25%) 0.456 TABLE 5.4d. Baseline Characteristics by IL -18RAP Gene Haplotypes. Values are reported as mean (standard error), median (interquartile range [range]), or number (percent). IL-18RAP Gene Haplotype A B C D E p Value N (%) 243 (22%) 347 (32%) 90 (8%) 287 (26%) 130(12%) Age (Years) 56(25 60 (26 63 (23 61 (27 58 (23.75 0.222 [19-88]) [15-89]) [21-83]) [15-89]) [17-85]) Male Sex (%) 147 (60%) 225 (65%) 61 (68%) 189 (66%) 85 (65%) 0.660 APACHE II Score 24.3 (0.6) 24.4 (0.5) 22.8 (0.9) 23.7 (0.5) 22.4 (0.8) 0.151 Surgical Diagnosis (%) 53 (22%) 97 (28%) 19 (21%) 73 (25%) 31 (24%) 0.436 136 FIGURE LEGENDS. Figure 5.1: Haplotype diagrams of the IL-18 (panel A), IL -18BP (panel B), IL-18R1 (panel C) and IL -18RAP (panel D) genes in our Caucasian I C U cohort. Haplotypes were inferred from unphased patient genotype (see Methods). Each column represents a polymorphic locus, and each row represents a unique haplotype in our cohort. Common alleles are colored black, while rare alleles are colored white. Relative positions of polymorphic loci (with respect to start of translation) are given above each column. Frequency of the haplotype in our cohort is given for each haplotype to the left. Figure 5.2: Summary of 28 day survival and prevalence of septic shock by haplotype of the IL-18 (panel A), IL -18BP (panel B), IL-18R1 (panel C) and IL -18RAP (panel D) genes in our cohort of critically i l l Caucasians. Within each panel, percent of patients (% survival or % with septic shock) is shown on the y-axis, while separate gene haplotypes are shown on the x-axis. Significance is given for each comparison within the panel. No significant differences in 28 day survival or prevalence of septic shock by gene haplotypes were present for any of the IL-18 pathway genes. 137 138 p-0,883 p*0.333 Swwu \u00E2\u0080\u00A2 ii-ttHkjwip* a rH,-l\u00C2\u00BBl\u00C2\u00BB,Mja t 0 p-0.628 F I G U R E 5.2. B. too \u00E2\u0080\u00A2 \u00C2\u00BB\u00E2\u0080\u00A2 \u00C2\u00BB 90 \u00C2\u00BB j \u00C2\u00BB Ml j \u00E2\u0080\u00A2I* p*0J33 Survival N * 45 in\u00C2\u00ABiiiiiii>i|\u00C2\u00BB.o SepiicSiwk : !L!aS\u00C2\u00AB>HB\u00C2\u00ABMw>C p\u00C2\u00BB\u00C2\u00A9,$43 U L i SUM Shock DMMW SulVKSf Se js fc S h o c k 139 5.7 References 1. Esmon, C. T. The interactions between inflammation and coagulation. Br J Haematol 131, 417-30 (2005). 2. Dixon, B., Santamaria, J . & Campbell, D. Coagulation activation and organ dysfunction following cardiac surgery. Chest 128, 229-36 (2005). 3. Rodriguez-Galan, M . C , Bream, J . H., Fair, A . & Young, H. A . Synergistic effect of IL-2, IL-12, and IL-18 on thymocyte apoptosis and Th l /Th2 cytokine expression. J Immunol 174, 2796-804 (2005). \. Tone, M. , Thompson, S. A. , Tone, Y. , Fairchild, P. J . & Waldmann, H. Regulation of IL-18 (IFN-gamma-inducing factor) gene expression. J Immunol 159,6156-63 (1997). >. Emmanuilidis, K. et al. Differential regulation of systemic IL-18 and IL-12 release during postoperative sepsis: high serum IL-18 as an early predictive indicator of lethal outcome. Shock 18, 301-5 (2002). i. Sablotzki, A . et al. The systemic inflammatory response syndrome following cardiac surgery: different expression of proinflammatory cytokines and procalcitonin in patients with and without multiorgan dysfunctions. Perfusion 17, 103-9(2002). Rooney, T. et al. Synovial tissue interleukin-18 expression and the response to treatment in patients with inflammatory arthritis. Ann Rheum Dis 63, 1393-8 (2004). 140 Hanifi-Moghaddam, P., Schloot, N . C , Kappler, S., Seissler, J . & Kolb , H. A n association of autoantibody status and serum cytokine levels in type 1 diabetes. Diabetes 52, 1137-42 (2003). Stassen, N . A . , Breit, C. M . , Norfleet, L. A . & Polk, H. C , Jr. IL-18 promoter polymorphisms correlate with the development of post-injury sepsis. Surgery 134, 351-6 (2003). Gracie, J . A . et al. Disease association of two distinct interleukin-18 promoter polymorphisms in Caucasian rheumatoid arthritis patients. Genes Immun 6, 211-6 (2005). Kretowski, A . et al. Interleukin-18 promoter polymorphisms in type 1 diabetes. Diabetes 51, 3347-9 (2002). Torigoe, K. et al. Purification and characterization of the human interleukin-18 receptor. J Biol Chem 272, 25737-42 (1997). Debets, R. et al. IL-18 receptors, their role in ligand binding and function: anti-IL-l R A c P L antibody, a potent antagonist of IL-18. J Immunol 165, 4950-6 (2000). Cho, M . L. et al. Interleukin-18 induces the production of vascular endothelial growth factor ( V E G F ) in rheumatoid arthritis synovial fibroblasts v ia A P - 1 -dependent pathways. Immunol Lett 103, 159-66 (2006). Chandrasekar, B. et al. The pro-atherogenic cytokine interleukin-18 induces C X C L 1 6 expression in rat aortic smooth muscle cells v ia MyD88 , interleukin-1 receptor-associated kinase, tumor necrosis factor receptor-associated factor 6, c-Src, phosphatidylinositol 3-kinase, Akt, c-Jun N-terminal kinase, and activator protein-1 signaling. J Biol Chem 280, 26263-77 (2005). 141 Chandrasekar, B. et al. Activation of intrinsic and extrinsic proapoptotic signaling pathways in interleukin-18-mediated human cardiac endothelial cell death. J Biol Chem 279, 20221-33 (2004). Yoo, J . K. et al. IL-18 induces monocyte chemotactic protein-1 production in macrophages through the phosphatidylinositol 3-kinase/Akt and M E K / E R K 1 / 2 pathways. J Immunol 175, 8280-6 (2005). L iu , S. F. & Mal ik , A . B. NF-{kappa}B activation as a pathological mechanism of septic shock and inflammation. Am J Physiol Lung Cell Mol Physiol 290, L622-45 (2006). Faggioni, R. et al. IL-18-binding protein protects against lipopolysaccharide-induced lethality and prevents the development of Fas/Fas ligand-mediated models of liver disease in mice. J Immunol 167, 5913-20 (2001). Novick, D. et al. A novel IL -18BP E L I S A shows elevated serum IL -18BP in sepsis and extensive decrease of free IL-18. Cytokine 14, 334-42 (2001). Reading, P. C. & Smith, G. L. Vaccinia virus interleukin-18-binding protein promotes virulence by reducing gamma interferon production and natural killer and T -cel l activity. J Virol 77,9960-8 (2003). Zecchina, G. et al. Interleukin-18 binding protein in acute graft versus host disease and engraftment following allogeneic peripheral blood stem cell transplants. J Hematother Stem Cell Res 10, 769-76 (2001). Mazodier, K. et al. Severe imbalance of IL-18/ IL-18BP in patients with secondary hemophagocytic syndrome. Blood 106, 3483-9 (2005). 142 Kawashima, M . et al. Levels of interleukin-18 and its binding inhibitors in the blood circulation of patients with adult-onset Still's disease. Arthritis Rheum 44, 550-60 (2001). Veenstra, K. G., Jonak, Z. L., Trull i , S. & Gollob, J . A . IL-12 induces monocyte IL-18 binding protein expression via IFN-gamma. J Immunol 168, 2282-7 (2002). Giedraitis, V . , He, B., Huang, W. X . & Hillert, J . Cloning and mutation analysis of the human IL-18 promoter: a possible role of polymorphisms in expression regulation. JNeuroimmunol 112, 146-52 (2001). Cardoso, S. P., Keen, L. & Bidwel l , J . Identification of two novel single nucleotide polymorphisms in the promoter of the human interleukin-18 receptor alpha. Eur J Immunogenet 31, 27-9 (2004). Sutherland, A . M . , Walley, K. R. & Russell, J . A . Polymorphisms in CD14, mannose-binding lectin, and Tol l - l ike receptor-2 are associated with increased prevalence of infection in critically i l l adults. Crit Care Med 33, 638-44 (2005). Lorenz, E., Mi ra , J . P., Cornish, K. L., Arbour, N . C. & Schwartz, D. A . A novel polymorphism in the toll - l ike receptor 2 gene and its potential association with staphylococcal infection. Infect Immun 68, 6398-401 (2000). Yuan, F. F. et al. FcgammaRIIA polymorphisms in Streptococcus pneumoniae infection. Immunol Cell Biol 81, 192-5 (2003). Saposnik, B. et al. A haplotype of the E P C R gene is associated with increased plasma levels of s E P C R and is a candidate risk factor for thrombosis. Blood 103, 1311-8 (2004). 143 32. Amal ich , F. et al. Interleukin-1 receptor antagonist gene polymorphism and mortality in patients with severe sepsis. Clin Exp Immunol 127, 331-6 (2002). 33. Cardon, L. R. & Be l l , J . I. Association study designs for complex diseases. Nat Rev Genet 2, 91-9(2001). 34. Bone, R. C. The sepsis syndrome. Definition and general approach to management. Clin Chest Med 17, 175-81 (1996). 35. Sibbald, W. J . & Vincent, J . L. Round table conference on clinical trials for the treatment of sepsis. Crit Care Med 23, 394-9 (1995). 36. Bernard, G. R. et al. A trial of antioxidants N-acetylcysteine and procysteine in A R D S . The Antioxidant in A R D S Study Group. Chest 112, 164-72 (1997). 37. Knaus, W. A . et al. The A P A C H E III prognostic system. Risk prediction of hospital mortality for critically i l l hospitalized adults. Chest 100, 1619-36. (1991). 38. Stephens, M . & Donnelly, P. A comparison of bayesian methods for haplotype reconstruction from population genotype data. Am J Hum Genet 73, 1162-9 (2003). 39. Kumar, S., Tamura, K., Jakobsen, I. B. & Ne i , M . M E G A 2 : molecular evolutionary genetics analysis software. Bioinformatics 17, 1244-5 (2001). 40. Carlson, C. S. et al. Selecting a maximally informative set of single-nucleotide polymorphisms for association analyses using linkage disequilibrium. Am J Hum Genet 74, 106-20 (2004). 41. Livak, K. J . A l le l ic discrimination using fluorogenic probes and the 5' nuclease assay. Genet Anal 14, 143-9 (1999). 144 42. Guo, S. W. & Thompson, E. A . Performing the exact test of Hardy-Weinberg proportion for multiple alleles. Biometrics 48, 361-72 (1992). 43. Sorensen, T. I., Nielsen, G. G., Andersen, P. K. & Teasdale, T. W. Genetic and environmental influences on premature death in adult adoptees. N EnglJ Med 318, 727-32 (1988). 44. Abraham, E. Alterations in cell signaling in sepsis. Clin Infect Dis 41 Suppl 7, S459-64 (2005). 45. Arcaroli , J . , Fessler, M . B. & Abraham, E. Genetic polymorphisms and sepsis. Shock 24, 300-12(2005). 46. Novota, P. et al. Interleukin IL-18 gene promoter polymorphisms in adult patients with type 1 diabetes mellitus and latent autoimmune diabetes in adults. Immunol Lett 96, 247-51 (2005). 47. Haas, S. L. et al. -137 (G/C) IL-18 promoter polymorphism in patients with inflammatory bowel disease. Scand J Gastroenterol 40, 1438-43 (2005). 48. Sivalingam, S. P., Yoon, K. H., Koh , D. R. & Fong, K. Y . Single-nucleotide polymorphisms of the interleukin-18 gene promoter region in rheumatoid arthritis patients: protective effect of A A genotype. Tissue Antigens 62, 498-504 (2003). 49. Imboden, M . et al. The common G-allele of interleukin-18 single-nucleotide polymorphism is a genetic risk factor for atopic asthma. The S A P A L D I A Cohort Study. Clin Exp Allergy 36, 211-8 (2006). 50. Nolsoe, R. L. et al. Mutation scan of a type 1 diabetes candidate gene: the human interleukin-18 binding protein gene. Ann N Y Acad Sci 1005, 332-9 (2003). 145 Durrant, C. & Morris, A . P. Linkage disequilibrium mapping via cladistic analysis of phase-unknown genotypes and inferred haplotypes in the Genetic Analysis Workshop 14 simulated data. BMC Genet 6 Suppl 1, S100 (2005). 146 CHAPTER 6: SUMMARY AND FUTURE DIRECTIONS 6.1 Summary of Completed Research 6.1.1 IL-10 in the CSICU We identified a novel haplotype of the IL-10 gene associated with improved outcome following C P B surgery (Chapter 2). The -627C/734T/3368G haplotype was found to be associated with decreased need for prolonged I C U care, lower post-CPB markers of inflammation such as neutrophil count and pulmonary dysfunction, and increased post-CPB serum IL-10 levels. The discovery of a novel haplotype of the IL-10 gene protecting Caucasian patients from post-CPB inflammatory injury is paradoxical with regard to improving patient care, the question of how to use this potentially protective haplotype in a clinical setting remains an open question. The majority of the literature involving inflammatory mediator gene haplotypes and polymorphisms involve identification of risk variants, rather than protective variants. This strategy allows for the identification of patients who could benefit from more intensive treatment following the inflammatory insult. Our study, identifying a potentially protective variant, would be more difficult to implement in today's C S I C U setting. While there is no doubt that identification of patients who would be predicted to perform better following C P B surgery would allow for more efficient management of resources in the C S I C U , this beneficial result may not follow directly from the results presented here. 147 The results of our IL-10 study in the C S I C U setting are in line with the majority of current art regarding variations in the IL-10 gene and outcomes from inflammatory states. The C T G haplotype associated with improved outcome and increased serum IL-10 in our cohort is part of a larger haplotype containing the -1117G/-827C/-627C alleles associated with improved outcome and increased serum IL-10 in the literature 1' 2. A similar study into haplotypes of the IL-10 gene in an intensive care unit cohort by Wattanathum and colleagues identified an alternative IL-10 haplotype, the -627C/527G/3368G haplotype, that is associated with worse outcome in Caucasians with pulmonary sepsis 3. Our results do not conflict with Wattanathum et al, in fact they are complimentary in that we have shown one haplotype of the IL-10 gene to be associated with improved outcome from inflammatory disease (post-CPB inflammation) while Wattanathum et al have shown a different haplotype (selected using the same htSNPs) to be associated with poor outcome from a different inflammatory disease (pulmonary sepsis). Taken with the literature surrounding polymorphisms and haplotypes of the IL-10 gene, our study is an extension of current knowledge. Need for prolonged I C U care following C P B surgery is a meaningful marker of poor outcome 4 ' 5 and increased costs 6 used in the literature. Our finding that an IL-10 haplotype reduces this outcome has the potential to identify patients more likely to perform well following C P B surgery, and therefore to allocate resources to those more likely to perform worse. 148 6.1.2 IL-18 in the CSICU We identified a novel SNP in an intronic region of the IL-18 gene that is associated with worse outcome following C P B surgery (Chapter 3). Patients possessing the TT genotype of the 9545 T / G SNP had increased need for prolonged I C U care, increased prevalence of low SVRI . As intermediate phenotype, increased serum IL-18, increased serum T N F - a and decreased serum IL-10 24 hours post-CPB were associated with the TT genotype of the 9545 T / G htSNP. These disparate markers of poor outcome and pro-inflammatory state related to this novel SNP indicate a strong contribution of this htSNP genotype to poor outcome in the C S I C U cohort. The htSNP (9545 T /G) reported in our IL-18 study is a novel polymorphism. Two promoter SNPs (-607 C / A and -137 G /C) have been extensively reported in the literature 7 8 as related to serum IL-18 levels ' and outcome from inflammatory diseases such as sepsis 9 and type I diabetes 1 0. We failed to find a significant association of either the -607 C / A or -137 G /C SNP with outcome or serum IL-18 level in our study. We identified the novel 9545 T / G SNP as a risk locus in the C P B setting, a SNP that would not have been identified relying on traditional literature reports of risk loci , as discussed below. Our study involving IL-18 SNPs and haplotypes in a C P B surgery setting was novel for the IL-18 gene in a C P B surgery setting, indicating that SNPs in the IL-18 gene, already recognized as a key modulator of inflammatory responses in a critical illness setting, have the potential to serve as a useful marker of poor outcome for patients undergoing C P B surgery. 149 This use of SNPs to mark patients at risk for poor outcomes is exactly what patient-tailored therapies rely upon for function. While no anti-IL-18 clinical therapies have been brought forward to date, the prospect has been discussed as a follow-up to the failure of anti -TNF treatment in inflammatory d iseases 1 1 1 2 . Since IL-18 holds a key position regulating both T h l and Th2 responses in inflammation, great care must be taken to use any potential anti-IL-18 treatment with precision and accuracy. The identification of a novel risk polymorphism in the IL-18 gene related to serum IL-18 levels has great potential for use in design of clinical trials and eventual treatment using anti-IL-18 treatments. 6:1.3 IL-18R1 in the CSICU A novel SNP, 6691 C/T, in the IL-18R1 gene was associated with poor outcome following C P B surgery in our Caucasians cohort (Chapter 4). The rare T allele was associated with increased prevalence of low SVRI , despite increased need for vasopressors post-CPB. Increased serum T N F - a post-CPB was associated with the risk allele, serving as an intermediate phenotype related to the gene of interest. Disparate measures of poor outcome were associated with this novel SNP in the IL-18R1 gene, and elevated serum T N F - a levels associated with the T allele give plausibility in terms of intermediate phenotype. 150 IL-18R1 is one of two subunits for the IL-18 receptor, the other being IL -18RAP. Although a previous report has identified novel polymorphisms in the IL-18R1 gene 1 3, ours is the first to identify a separate novel SNP associated with altered outcome from an inflammatory condition (CPB surgery). Cytokine receptors are an obvious target for therapeutic interventions in complex diseases since antagonism of the receptors can attenuate much of the signal of the cytokine 1 4 . Identification of a variant of the IL-18R1 gene associated with poor outcome from C P B surgery promotes the idea of a novel target for therapeutic intervention in the form of antagonism. 6.1.4 IL-18 Pathway Haplotypes and htSNP Genotypes in the ICU A s an attempt to validate previous findings using IL-18 genes in the C S I C U , we used haplotypes and htSNP genotypes of IL-18 pathway genes as markers for altered outcome in the ICU. No significant associations between haplotypes or htSNP genotypes in any IL-18 pathway gene (IL-18, IL -18BP, IL-18R1 or IL -18RAP) were found in our cohort, despite strong associations previously reported in the C S I C U cohort (Chapter 5). Thus, we must report that we were unable to validate our significant findings in a separate cohort. This unfortunately weakens our claims of novel SNPs associated with worse outcomes to some degree, yet they remain valid for the cohort in which they were first described. The negative results in the ICU were likely not due to lack of statistical power, but instead may reflect the degree to which IL-18 pathway SNPs possess modest effects on outcomes from inflammatory stimuli. The IL-18 pathway SNPs previously described may have enough effect to alter outcomes from a less risky inflammatory 151 injury such as C P B surgery, but may be too modest to alter outcomes from such a strident injury as critical illness. Our negative findings included two polymorphisms of the IL-18 gene already reported as related to outcome from critical illness, the -607 C / A and -137 G / C SNPs 9 . The fact that we were unable to observed altered outcomes based on these SNPs in our well-powered study, nor were we able to observe alterations in serum IL-18 levels by these SNPs (Chapter 3) calls into question the reliance on these literature SNPs in particular and the use of literature SNPs for disease association studies in general for complex inflammatory diseases. Our use of haplotype-based methods for selection of SNPs and tests of outcomes show no relevance of these SNPs to outcome in either of our inflammatory cohorts. 152 6.2 Strengths of the Completed Research The completed research uses a haplotype-based method for analysis of the gene of interest (Chapter 2) or for selection of htSNPs with which to analyze the genes of interest (Chapters 3-5). This method gives greater statistical power over traditional single SNP-based or literature-derived SNP-based disease association studies 1 5. It also has the advantage of broadening the scope of research into potential associations beyond literature reports of functional SNPs. Linkage disequilibrium extends beyond gene boundaries, increasing the possibility that information about a causative SNP wi l l be captured by genotyping an htSNP within a gene of interest. Our research also focused on large cohorts (approximately 500 individuals or more), giving reasonable statistical power to detect associations from SNPs of modest effect sizes 1 6 . Concurrently, we were able to avoid the problem of statistically significant findings deriving from clinically insignificant differences in outcomes. That is, our positive outcomes in the C S I C U cohort are clinically significant in addition to being statistically significant. We have restricted our analyses to Caucasians cohorts stimulated by homogeneous inflammatory insults (CPB surgery or critical illness) in an effort to maximize the detectable effects of variations within the genes of interest on outcome, and to minimize the background genetic noise produced by differences in allele or haplotype frequencies based on ethnicity 1 7 . 153 Wherever possible, intermediate phenotypes have been included to provide a biologically plausible mechanism for observed phenotypic variations. Serum cytokine levels serve as excellent intermediate phenotypes because they re the direct product of gene expression and are often heavily influenced by polymorphisms of the gene of interest. Additionally, serum cytokine levels represent secondary clinical targets for treatment in a clinical setting 1 8 , while gene therapy (such as short interfering R N A ) to 'correct' risk variants of genes has only now begun to enter phase I clinical tr ials 1 9 . 154 6.3 Weaknesses of the Completed Research The completed research, while strongly indicative of the protective or risk effects of haplotypes and polymorphisms of the genes of interest in the C S I C U setting, failed to be validated in the I C U cohort. While this failure to validate does not by any means indicate invalid findings in the C S I C U cohort, it casts some doubt on the functionality of identified haplotypes or SNPs. The completed research does not address functionality of the identified SNPs/haplotypes, and therefore cannot definitively explain the disparity in results between the C S I C U and I C U cohorts. No study was made of the potential interaction between genes, either between IL-10 and IL-18 gene, or among the IL-18 pathway genes. There is currently no standard model for the analysis of potential interactions of genes in disease association studies, though this lack of standard is a current research topic 2 0 \" 2 2 . Since SNPs and haplotypes do not act in a vacuum, interactions between them must form part of a larger disease association framework, and should be a major focus of future research. 155 6.4 Future Directions The individual reports of outcomes based on haplotypes and htSNP genotypes within the IL-10 and IL-18 pathway genes do not identify mechanism of pathogenesis. Therefore, investigation of mechanistic details of these effects is strongly recommended for future study. The era of publication of genotype-phenotype associations without associated functional details is drawing to a close. Functional studies must become the new standard for acceptance for S N P - or haplotype-based disease association studies. Serum cytokine levels as intermediate phenotypes give an idea of potential mechanism of alterations in outcomes based on SNPs, but are not a definitive measure. The example of T N F - a in sepsis alone indicates an over-crowded field confused by contradictory reports and lack of uniformity in cohorts and diseases 2 3\" 2 9. A clear mechanistic study, universally applicable and easily understandable, would simplify this field immensely. The use of haplotypes in future disease association studies can perform two tasks simultaneously: broaden the range of polymorphic loci under examination for functional effects, and reduce the number of statistical tests performed (thereby reducing the possibility of type I error). Incorporating haplotypes into mechanistic studies would increase the power of the studies, the precision of the studies and the information content of those studies. Mechanistic studies of polymorphisms in inflammatory diseases can provide insight into how common variants can contribute to complex diseases. Some methods for 156 incorporating mechanistic studies into complex disease association studies are presented below. 6.4.1 Whole-Haplotype Transfection Assays One method to assay the effects of entire haplotypes on outcomes from inflammatory diseases is to transfect entire haplotypes into otherwise genetically identical cell lines. In this way, background genetic noise can be eliminated and the effects of the haplotype alone can be assayed. Although this does not give any direct functional information, this approach combines the advantages of haplotype-based studies and in vitro systems to identify potentially causative loci in model systems for complex diseases . Whole-haplotype transfection, using either traditional cloning vectors or novel adenovirus-based techniques , can act as an excellent first step on the road to identifying functional variants. Following identification of a haplotype associated with altered responses to inflammatory stimuli, intensive focus on single polymorphic loci can proceed with confidence. 6.4.2 Single SNP-based Alteration of Mechanism Single SNPs can alter the mechanism of gene expression sufficiently to alter outcomes from complex diseases. Some mechanisms include alteration of binding sites for transcription factors , enhancer or repressor elements, spliceosomes , or m R N A stabilization elements , all potentially leading to alterations in gene expression. Preferential activity of transcription factors, enhancers and repressors for alternative alleles of polymorphisms can be tested directly using electrophoretic mobility shift assays 157 (EMSA) by identifying homozygotes for each allele at the putative functional SNP, cross-linking D N A to the protein of interest and then measuring extent of binding to alternative alleles . In much the same way, single base mutations can be introduced via site-directed mutagenesis to alter the D N A sequence within the consensus sequence of the DNA-b ind ing protein of interest 3 8. In this way, background differences in genome sequence that may otherwise affect DNA-protein interactions can be eliminated and the effects of the SNP of interest can be identified exactly. This approach is beginning to find traction, and has recently been used to identify a SNP in an intron, altering splicing of the pre-mRNA of the neurofibromin gene into its final form 3 8 . This approach, though historically difficult and expensive, is becoming much more feasible given recent developments in commercially available kits for performing site-directed mutagenesis, splice alteration assays and allele-specific DNA-protein cross-linking assays. 158 6.5 Summary The completed research has identified novel haplotypes and polymorphisms of key inflammatory mediator genes (IL-10 and IL-18) and receptor genes (IL-18R1) in a cardiac surgery setting. These haplotypes and polymorphisms represent novel variants of known targets, or novel targets that can be used to manage inflammatory responses to C P B surgery so as to improve patient outcomes with finer control. Serum cytokine levels are correlated with the novel variants, indicating potential mechanistic outlines and important clinical targets. Variations within these genes and others within the IL-18 pathway (IL-18BP and IL -18RAP) were not associated with altered outcomes from critical illness, suggesting that the effects discovered in the cardiac surgery setting are too modest to affect survival and organ dysfunction in a critical care setting. Mechanistic details of action of the novel variants were not identified, and remain important research goals in future studies. 159 6.6 References 1. Suarez, A. , Castro, P., Alonso, R., Mozo, L. & Gutierrez, C. Interindividual variations in constitutive interleukin-10 messenger R N A and protein levels and their association with genetic polymorphisms. Transplantation 75, 711-7 (2003). 2. Cunningham, L. M . , Chapman, C , Dunstan, R., Be l l , M . C. & Joske, D. J . Polymorphisms in the interleukin 10 gene promoter are associated with susceptibility to aggressive non-Hodgkin's lymphoma. Leuk Lymphoma 44, 251-5 (2003). 3. Wattanathum, A. , Manocha, S., Groshaus, H., Russell, J . A . & Walley, K. R. Interleukin-10 haplotype associated with increased mortality in critically i l l patients with sepsis from pneumonia but not in patients with extrapulmonary sepsis. Chest 128, 1690-8 (2005). 4. Wil l iams, M . R. et al. Long-term survival and quality of life in cardiac surgical patients with prolonged intensive care unit length of stay. Ann Thorac Surg 73, 1472-8 (2002). 5. Christakis, G. T. et al. Impact of preoperative risk and perioperative morbidity on I C U stay following coronary bypass surgery. Cardiovasc Surg 4, 29-35 (1996). 6. Nakasuji, M . , Matsushita, M . & Asada, A . Risk factors for prolonged I C U stay in patients following coronary artery bypass grafting with a long duration of cardiopulmonary bypass. JAnesth 19, 118-23 (2005). 7. Kretowski, A . & Kinalska, I. Serum levels of interleukin-18\u00E2\u0080\u0094a potential marker of cardiovascular death\u00E2\u0080\u0094could be determined by genetic predisposition. Circulation 107, e206-7; author reply e206-7 (2003). 160 8. Giedraitis, V . , He, B., Huang, W. X . & Hillert, J . Cloning and mutation analysis of the human IL-18 promoter: a possible role of polymorphisms in expression regulation. JNeuroimmunol 112, 146-52 (2001). 9. Stassen, N . A . , Breit, C. M. , Norfleet, L. A . & Polk, H. C , Jr. IL-18 promoter polymorphisms correlate with the development of post-injury sepsis. Surgery 134, 351-6 (2003). 10. Kretowski, A . et al. Interleukin-18 promoter polymorphisms in type 1 diabetes. Diabetes 51, 3347-9 (2002). 11. Abraham, E. et al. Double-blind randomised controlled trial of monoclonal antibody to human tumour necrosis factor in treatment of septic shock. N O R A S E P T II Study Group. Lancet 351, 929-33 (1998). 12. Mclnnes, I. B. & Gracie, J . A . Targeting cytokines beyond tumor necrosis factor-alpha and interleukin-1 in rheumatoid arthritis. Curr Rheumatol Rep 6, 336-42 (2004). 13. Cardoso, S. P., Keen, L. & Bidwel l , J . Identification of two novel single nucleotide polymorphisms in the promoter of the human interleukin-18 receptor alpha. Eur J Immunogenet 31, 27-9 (2004). 14. Day, J . R. et al. Aprotinin inhibits proinflammatory activation of endothelial cells by thrombin through the protease-activated receptor 1. J Thorac Cardiovasc Surg 131,21-7 (2006). 15. de Bakker, P. I. et al. Efficiency and power in genetic association studies. Nat Genet 37, 1217-23 (2005). 161 16. Long, A . D. & Langley, C. H. The power of association studies to detect the contribution of candidate genetic loci to variation in complex traits. Genome Res 9, 720-31 (1999). 17. Cardon, L. R. & Be l l , J . I. Association study designs for complex diseases. Nat Rev Genet 2, 91-9 (2001). 18. de Mendonca-Filho, H. T. et al. Circulating inflammatory mediators and organ dysfunction after cardiovascular surgery with cardiopulmonary bypass: a prospective observational study. Crit Care 10, R46 (2006). 19. Cejka, D., Losert, D. & Wacheck, V . Short interfering R N A (s iRNA) : tool or therapeutic? Clin Sci (Lond) 110, 47-58 (2006). 20. Becker, T., Schumacher, J . , Cichon, S., Baur, M . P. & Knapp, M . Haplotype interaction analysis of unlinked regions. Genet Epidemiol 29, 313-22 (2005). 21. Newton-Cheh, C. & Hirschhorn, J . N . Genetic association studies of complex traits: design and analysis issues. Mutat Res 573, 54-69 (2005). 22. Greenberg, D. A . et al. Construction of the model for the Genetic Analysis Workshop 14 simulated data: genotype-phenotype relationships, gene interaction, linkage, association, disequilibrium, and ascertainment effects for a complex phenotype. BMC Genet 6 Suppl 1, S3 (2005). 23. Stuber, F. et al. -308 tumor necrosis factor (TNF) polymorphism is not associated with survival in severe sepsis and is unrelated to lipopolysaccharide inducibility of the human T N F promoter. J Inflamm 46, 42-50 (1995). 24. Stuber, F., Petersen, M . , Bokelmann, F. & Schade, U. A genomic polymorphism within the tumor necrosis factor locus influences plasma tumor necrosis factor-162 alpha concentrations and outcome of patients with severe sepsis. Crit Care Med 24,381-4(1996). 25. Knight, J . C. & Kwiatkowski , D. Inherited variability of tumor necrosis factor production and susceptibility to infectious disease. Proc Assoc Am Physicians 111, 290-8 (1999). 26. Majetschak, M . et al. Relation of a T N F gene polymorphism to severe sepsis in trauma patients. Ann Surg 230, 207-14 (1999). 27. Mira, J . P. et al. Association of TNF2, a TNF-alpha promoter polymorphism, with septic shock susceptibility and mortality: a multicenter study. Jama 282, 561-8 (1999). 28. Waterer, G. W., Quasney, M . W., Cantor, R. M . & Wunderink, R. G. Septic shock and respiratory failure in community-acquired pneumonia have different T N F polymorphism associations. Am JRespir Crit Care Med 163, 1599-604 (2001). 29. Majetschak, M . et al. Tumor necrosis factor gene polymorphisms, leukocyte function, and sepsis susceptibility in blunt trauma patients. Clin Diagn Lab Immunol 9, 1205-11 (2002). 30. Wood, T. C. et al. Human Arsenic Methyltransferase (AS3MT) Pharmacogenetics: G E N E R E S E Q U E N C I N G A N D F U N C T I O N A L G E N O M I C S STUDIES. JBiol Chem 281, 7364-73 (2006). 31. Kato, H. et al. Association of single-nucleotide polymorphisms in the suppressor of cytokine signaling 2 (SOCS2) gene with type 2 diabetes in the Japanese. Genomics (2006). 163 32. Nishiyama, C. et al. Polymorphisms in the Fc epsilon RI beta promoter region affecting transcription activity: a possible promoter-dependent mechanism for association between Fc epsilon RI beta and atopy. J Immunol 173, 6458-64 (2004). 33. Tsukada, S. et al. Intronic polymorphisms within T F A P 2 B regulate transcriptional activity and affect adipocytokine gene expression in differentiated adipocytes. Mol Endocrinol (2005). 34. Okamoto, K. et al. Identification of I kappa B L as the second major histocompatibility complex-linked susceptibility locus for rheumatoid arthritis. Am J Hum Genet 72, 303-12 (2003). 35. Emmert, S., Schneider, T. D., Khan, S. G. & Kraemer, K. H. The human X P G gene: gene architecture, alternative splicing and single nucleotide polymorphisms. Nucleic Acids Res 29, 1443-52 (2001). 36. Wang, J . , Pitarque, M . & Ingelman-Sundberg, M . 3 ' -UTR polymorphism in the human C Y P 2 A 6 gene affects m R N A stability and enzyme expression. Biochem Biophys Res Commun 340, 491-7 (2006). 37. Wittwer, J . , Marti-Jaun, J. & Hersberger, M . Functional polymorphism in A L O X 1 5 results in increased allele-specific transcription in macrophages through binding of the transcription factor SPI1. Hum Mutat 27, 78-87 (2006). 38. Raponi, M. , Upadhyaya, M . & Baralle, D. Functional splicing assay shows a pathogenic intronic mutation in neurofibromatosis type 1 (NF1) due to intronic sequence exonization. Hum Mutat 27, 294-5 (2006). 164 A P P E N D I X A : TaqMan P C R primer and allelic discrimination probe sequences used in genotyping patients for genes in this study. Gene SNP Forward Primer Reverse Primer Common Allele Probe Rare Allele Probe IL-10 -627 G G T A A A G G A G C C T G G A A C A C A T C C C C T T C C A T T T T A C T T T C C A G A G A C G C C T G T C C T G T A G G C G C C T G T A C T G T A G G A 734 G C C C C G A A G G G T T G A C A T A T G A C T C A G T C C T G G T C T T C T T T C T G C C T T A A A G C C G A A T G T C C C T T A A A G C C T A A T G T 3368 T G G G A G A A C A C A G A C A T T T A A A A G G T G C A G A G T T T G A T G A A A A G A C A T T A G A T C A C C G T C T T G C T T T C T C A C C A T C T T G C T T T IL-18 -607 T C T C C C C A A G C T T A C T T T C T G T T G T G C A A G C C A C A C G G A T A C C A T C A T T A G A A T T T T A T G T A A T A A T A T C A T T A G A A T T T T A T T T A A T A A T -137 C A C A G A G C C C C A A C T T T T A C G G G C A G A G G A T A C G A G T A C T T C T T T T A C T A T T T T C A T G A A A T C T T T T C T T T T T C A T G A A A T G T T T T C T 8148 A G T A A T G A G T T T A A A C C A T G T C T C A A G A T C T C A G T A C T T G T G A C T C T G T C A T T A A T A G A A A T A C C T T G T G C T A C A G T T A T T G C A T T G T G C T A C A A T T A T T G C A 9545 T C C C A A A G C A A A T T G G C A A A T T A T G T C C A G C C T G G G C A A C A G A A A A C A G A A C T C T A A A T T T A G A C A G A A C T C T A C A T T T A G IL -18BP -1765 C T G G A C T G T C T C T C T C A G A A A C C C C A G C A T C T C C A G G A G T T A G G C A G C C T T G C T T C C T G A C A G C C T T G C C T C C T G A 3041 C C C C A A C C C C A C T C C T G C A C C T G C C A G A G G A T G C T A T G G G C C C T G T G T C T A T G G G C C C T A T G T C T IL -18R1 5158 A A A A A A G T T A C C T T G T C A T T T T G G T T T T T G T T T T G T T C C C C T T C A A C C A C A G T A A T G T C A A G A T T C T T C A A A A G A T T A A G A T T C T T C A G A A G A T T 6691 G A G A T A A C A G A A G C A A A T G G C A T T G G C T T G C T T C C A T T G T T G C T T C C T A A G A T T C T C T A C T A C C C G T A T C A G C T C T A C T A C C C A T A T C A G 19158 A T G A C A C T G G A T A C A C A T T T C A T A T T T A C T G A A G T C A G G T T A A A A G T G G C A A C A T T C A A C A A A A C T A A G A G A A G A G T G C A A A A C T A A G A A A A G A G T G IL -18RAP 14336 G G T T G T C C A T G A A T A T G T C C C T G A T T G G T G A T A G G T A C C T G G A T G T C A T T T C A T A C A T T T T T A A A A T T T T T T C A T A C A T T T T T T A A A T T T 20354 C C A G A C T G C T T G G A G A T A A G T A A T A T G T G T G G C A C C G G T G A A A A G C C T G C T T A C C C T C A C T C T C T G C T T A C C C C C A C T C T 27120 C T G C C C A G G A G T T A T G A T T G T C T T T A A G T A C T T G C T C G G A G A G T T G A T G C A T A T C A G C A T A T G G G C A T A T C A G C G T A T G G G C 165 (0 > 3 100 90 -80 -70 -60 50 40 30 H 20 10 4. 0 A P P E N D I X B: Supplementary results for C H A P T E R 5. Panel A : 28 day survival by IL-18 gene htSNP genotype. p=0.910 p=0.724 p=0.183 C C A C A A I L - 1 8 - 6 0 7 C / A G e n o t y p e G G C G C C I L - 1 8 - 1 3 7 G / C G e n o t y p e C C C T T T IL-18 8148 C /T G e n o t y p e T T G T G G IL-18 9545 T / G G e n o t y p e Panel B: 28 day mortality by IL-18BP gene htSNP genotype. 100 - i 90 -80 -70 -\u00C2\u00B0^ 60 -> 50 -\"> \u00E2\u0080\u00A23 40 -30 -20 -10 -0 -p=0.424 T T C T C C IL-18BP -1765 T/C Genotype C C C T T T IL-18BP 3041 C/T Genotype 166 Panel C: 28 day mortality by IL-18R1 gene htSNP genotype. 100 n 90 -80 -70 -4 60 -ival 50 -> 3 40 -V) 30 -20 -10 -0 --p=0.973 I N = 254 N = 70 T T C T C C IL-18R1 5158 T/C Genotype C C C T T T IL-18R1 5158 C/T Genotype p=0.115 GG GA AA IL-18R1 19158 G/A Genotype Panel D: 28 day mortality by IL -18RAP gene htSNP genotype A A A T T T IL-18RAP 14336 A/T Genotype T T C T c c IL-18RAP 20354 T/C Genotype p=0.517 r T N = 177 N = 261 AA AG GG IL-18RAP 27120 A/G Genotype 167 Panel E: Days alive and free of organ dysfunction by IL-18 gene haplotype. Q 28 24 20 16 12 8 4 H 0 \u00E2\u0080\u00A2 IL-18 Haplotype A (N=451) \u00E2\u0080\u00A2 ED IL-18 Haplotype B (N=140.) \u00E2\u0080\u00A2 IL-18 Haplotype C (N=282) \u00E2\u0080\u00A2 IL-18 Haplotype D (N=222) p=0.772 p=0.888 p=0.789 p=0.429 p=0.653 DAF DAF Cadriovascular Respiratory Dysfunction Dysfunction DAF Renal DAF DAF Hepatic Dysfunction Hematologic Dysfunction Dysfunction Panel F: Days alive and free of organ dysfunction by IL -18BP gene haplotypes. 28 24 p=0.759 p=0.644 \u00E2\u0080\u00A2 IL-18BP Haplotype A (N=1013) \u00E2\u0080\u00A2 IL-18BP Haplotype B (N=40) \u00E2\u0080\u00A2 IL-18BP Haplotype C (N=45) p=0.942 p=0.977 DAF DAF DAF Renal DAF DAF Hepatic Cardiovascular Respiratory Dysfunction Hematologic Dysfunction Dysfunction Dysfunction Dysfunction 168 PanelG: Days alive and free of organ dysfunction by IL-18R1 gene haplotype. \u00E2\u0080\u00A2 IL-18R1 Haplotype A (N=104) \u00E2\u0080\u00A2 IL-18R1 Haplotype B (N=290) \u00E2\u0080\u00A2 IL-18R1 Halpotype C (N=298) \u00E2\u0080\u00A2 IL-18R1 Haplotype D (N=405) p=0.474 p=0.369 r p=0.241 p=0.183 Tp=0.823 DAF Cardiovascular Dysfunction DAF Respiratory Dysfunction DAF Hematologic Dysfunction DAF Renal Dysfunction DAF Heptatic Dysfunction Panel H : Days alive and free of organ dysfunction by IL -18RAP gene haplotype. \u00E2\u0080\u00A2 IL-18RAP Haplotype A (N=243) \u00E2\u0080\u00A2 IL-18RAP Haplotype B (N=347) 2 8 \u00E2\u0080\u00A2 IL-18 RAP Haplotype C (N=90) 1 g IL-18RAP Haplotype D (N=287) n A \ \u00E2\u0080\u00A2 IL-18RAP Haplotype E (N=130) DAF DAF DAF Renal DAF DAF Hepatic Cardiovascular Respiratory Dysfunction Hematologic Dysfunction Dysfunction Dysfunction Dysfunction 169 "@en . "Thesis/Dissertation"@en . "2006-11"@en . "10.14288/1.0092797"@en . "eng"@en . "Experimental Medicine"@en . "Vancouver : University of British Columbia Library"@en . "University of British Columbia"@en . "For non-commercial purposes only, such as research, private study and education. Additional conditions apply, see Terms of Use https://open.library.ubc.ca/terms_of_use."@en . "Graduate"@en . "Novel haplotypes and polymorphisms of interleukin-10 and interleukin-18 pathway genes in complex inflammatory diseases"@en . "Text"@en . "http://hdl.handle.net/2429/18148"@en .