"Medicine, Faculty of"@en . "Medical Genetics, Department of"@en . "DSpace"@en . "UBCV"@en . "Randall, Derrick Raymond"@en . "2010-01-08T01:58:18Z"@en . "2006"@en . "Master of Science - MSc"@en . "University of British Columbia"@en . "The mucopolysaccharidoses are a clinically heterogeneous group of lysosomal\r\nstorage disorders presenting with broad multi-system disease and a continuous range of\r\nphenotypes. Currently there are no objective biomarkers of MPS disease that clearly\r\nreflect disease severity or therapeutic responsiveness. Using proteomic studies in the\r\nmurine MPS I model, I have identified the formation of the heparin cofactor II-thrombin\r\n(HCII-T) complex, a well-known serine protease inhibitor (serpin)-serine protease\r\ncomplex, as an informative biomarker for MPS I. MPS I patients showed a range of\r\nserum HCII-T concentrations from 16,300 - 208,600 pM, whereas the control values\r\nvaried from 38.94 - 1491 pM. HCII-T complex was also elevated in plasma from MPS I\r\npatients and mice. The degree of HCII-T complex formation appears to correlate with\r\ndisease severity and is responsive to therapy. In addition to its role as a biomarker, the\r\ndiscovery of increased serpin-serine protease complex formation provides a valuable\r\ninsight into possible pathophysiological mechanisms of MPS disease."@en . "https://circle.library.ubc.ca/rest/handle/2429/17747?expand=metadata"@en . "IDENTIFICATION OF A SERUM B I O M A R K E R FOR MUCOPOLYSACCHARIDOSIS I by DERRICK R A Y M O N D R A N D A L L B.Sc.H., The University of British Columbia, 2003 A THESIS SUBMITTED IN PARTIAL F U L F I L L M E N T OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE in THE F A C U L T Y OF G R A D U A T E STUDIES (Medical Genetics) THE UNIVERSITY OF BRITISH C O L U M B I A April 2006 \u00C2\u00A9 Derrick Raymond Randall, 2006 Abstract The mucopolysaccharidoses are a clinically heterogeneous group of lysosomal storage disorders presenting with broad multi-system disease and a continuous range of phenotypes. Currently there are no objective biomarkers of MPS disease that clearly reflect disease severity or therapeutic responsiveness. Using proteomic studies in the murine MPS I model, I have identified the formation of the heparin cofactor II-thrombin (HCII-T) complex, a well-known serine protease inhibitor (serpin)-serine protease complex, as an informative biomarker for MPS I. MPS I patients showed a range of serum HCII-T concentrations from 16,300 - 208,600 pM, whereas the control values varied from 38.94 - 1491 pM. HCII-T complex was also elevated in plasma from MPS I patients and mice. The degree of HCII-T complex formation appears to correlate with disease severity and is responsive to therapy. In addition to its role as a biomarker, the discovery of increased serpin-serine protease complex formation provides a valuable insight into possible pathophysiological mechanisms of MPS disease. ii Table of Contents Abstract i i Table of Contents i i i List of Tables v List of Figures vi List of Abbreviations vii Acknowledgements viii Co-Authorship Statement ix Chapter 1: Introduction 1 1.1 T H E S I S Focus A N D C H A P T E R O V E R V I E W 1 1.2 M U C O P O L Y S A C C H A R I D O S I S 1 2 1.3 T E C H N I Q U E S F O R P R O T E O M I C A N A L Y S I S .\u00E2\u0080\u00A2 8 1.4 T H E S E R U M P R O T E O M E ' S T E C H N I C A L C H A L L E N G E 12 1.5 M U R I N E M O D E L O F M P S I H 13 1.6 T H E S I S O B J E C T I V E A N D H Y P O T H E S I S 15 1.6.1 Objective 15 1.6.2 Hypothesis 15 1.7 R E F E R E N C E S 16 Chapter 2: Serum 2-Dimensional Gel Electrophoresis Studies in the MPS I Murine Model 20 2.1 I N T R O D U C T I O N '. 20 2.2 M E T H O D S 22 2.2.7 Protein quantification 22 2.2.2 Acetone precipitation 22 2.2.3 2D Gel Electrophoresis 22 2.3 R E S U L T S 23 2.3.1 Protein quantification 23 2.3.2 2D gel electrophoresis 24 2.4 D I S C U S S I O N 25 2.5 R E F E R E N C E S 28 Chapter 3: Heparin Cofactor II-Thrombin Complex in MPS I: A Biomarker of MPS Disease 29 3.1 I N T R O D U C T I O N 29 3.2 M E T H O D S 31 3.2.1 Sample collection 31 3.2.2 High abundance protein depletion 31 3.2.3 iTRAQ analysis 32 3.2.3.1 iTRAQ reagent labelling 32 3.2.3.2 L C - M S / M S analysis 32 3.2.3.3 Data acquisition and analysis 33 3.2.4 Western blotting 35 3.2.5 ELISA 35 3.3 R E S U L T S 36 3.3.1 iTRAQ serum proteomic studies 36 3.3.2 Heparin cofactor II western blot analysis in MPS I mice 42 i i i 3.3.3 Heparin cofactor II western blot analysis in MPS I patients 42 3.3.4 HCII-T ELISA analysis 44 3.3.5 Antithrombin III western blot analysis 45 3.4 D I S C U S S I O N 4 6 3.5 R E F E R E N C E S 53 Chapter 4 : Heparin Cofactor II-Thrombin Complex Levels in MPS I Patients Undergoing Enzyme Replacement Therapy 56 4.1 I N T R O D U C T I O N 56 4.2 M E T H O D S 57 4.2.1 ELISA 57 4.2.2 Subject sample collection 58 4.3 R E S U L T S 58 4.3.1 ELISA data on serum samples from 72 additional control subjects 58 4.3.2 ELISA data on serum samples from 11 patients undergoing enzyme replacement therapy 59 4.3.3 ELISA data on serum samples from two additional patients undergoing ERT 61 4.4 D I S C U S S I O N 63 4.5 R E F E R E N C E S 67 Chapter 5: Summary & Conclusion 68 5.1 P R O T E O M I C S I N D I S E A S E R E S E A R C H 68 5.2 R E P L I C A B I L I T Y O F I T R A Q 72 5.3 I D E N T I F I C A T I O N O F A S E R U M B I O M A R K E R F O R M P S I D I S E A S E 74 5.4 S E R I N E P R O T E A S E S A N D S E R I N E P R O T E A S E I N H I B I T O R S I N M P S D I S E A S E 78 5.5 F U T U R E W O R K 8 0 5.5.7 Validation in other MPS disorders 81 5.5.2 Recombinant human IDUA dose titration 81 5.5.3 Sample preparation and blood GAG concentration fluctuation 81 5.5.4 Analysis of the HCII-T complex biomarker in serum of IDUA overexpressing mice for use in gene transfer 82 5.5.5 HCII-T complex as a plasma biomarker 83 5.5.6 Further proteomic analyses 83 5.6 R E F E R E N C E S 86 Appendix 1: iTRAQ Replicability Analysis 92 A 1.1 M E T H O D S 92 Al.1.1 Computations 92 Al.1.2 Terminology 92 A l . 2 R E S U L T S 93 A 1.2.1 Like-pool comparisons 93 Al.2.2 Data re-acquisition 94 Appendix 2: Mucopolysaccharidosis diagnostics patent 99 iv List of Tables Table 2.1: Protein concentrations of high abundance protein depleted pools 24 Table 3.1: iTRAQ summary data 36 Table 3.2: Number of unique peptides per protein in iTRAQ data collection, >94% Protein Confidence 37 Table 3.3: Proteins identified at >99% confidence with significantly altered relative abundance in the MPS mouse serum, Idua+/+ mixed sex denominator 41 Table 3.4: HCII-T ELISA in serum and plasma samples of MPS I patients, MPS I mice, and controls 45 Table 3.5: Known serpins with GAG-mediated activities 51 Table 4.1: HCII-T complex levels in patients undergoing ERT 61 Table A l . 1: Effects of iTRAQ variability on abundance ratios 96 Table A2.1: Mucopolysaccharidoses and the respective enzyme deficiency and stored glycosaminoglycan 107 Table A2.2: Examples of serpins with GAG-mediated activities 112 Table A2.3: iTRAQ Summary Data 117 Table A2.4: Number of unique peptides per protein in iTRAQ data collection, 94% Protein Confidence 117 Table A2.5: Proteins with significantly altered relative abundance in the MPS mouse serum, Idua+/+ mixed sex denominator 118 Table A2.6: HCII-T ELISA 121 List of Figures Fig. 1.1: Lysosomal storage disorders 3 Fig. 1.2: Iduronidase action in dermatan sulphate degradation 4 Fig. 1.3: Iduronidase action in heparan sulphate degradation 5 Fig. 1.4: The iTRAQ reagent and principle 10 Fig. 1.5: iTRAQ data output 11 Fig. 2.1: 2DGE images of nascent and high abundance protein depleted mouse serum samples 24 Fig. 2.2: 2DGE images of MPS and wild-type mouse depleted serum samples 25 Fig. 3.1: Box plots of relative abundances for proteins identified with 99% confidence 38 Fig. 3.2: Logarithmic plot of average relative abundance of proteins in Idua'1' pools vs. Idua+/+ mixed sex, >99% confidence, with proteins rank ordered from left to right based on descending Protein % Confidence score 40 Fig. 3.3: Western blot of serum samples from WT (Idua1*) and MPS (Idua'') mice for HCII 42 Fig. 3.4: Western blot of MPS patients for HCII 43 Fig. 3.5: HCII-T levels in MPS 1H serum samples following enzyme replacement therapy 44 Fig. 3.6: Western blot of MPS patient samples for ATIII 46 Fig. 4.1: Control range of serum HCII-T concentration 59 Fig. 4.2: Serum HCII-T concentrations for MPS I patients undergoing a randomized, double-blind, placebo-controlled ERT trial 60 Fig. 4.3: Serum HCII-T complex concentration over a Hurler patient's treatment course 62 Fig. 4.4: Serum HCII-T complex concentration and antibody titre over an attenuated patient's treatment course 63 Fig. 5.1: Serine protease inhibitor action 80 Fig. A 1.1: Individual protein ratios, expressed as absolute values of the fold-differences between the Idua\"/_ male:Idua7\" mixed sex ratio 94 Fig. A l .2: Change in Unused Protein Score from iTRAQ Acquisition A to Acquisition A+B 95 Fig. A 1.3: Change in Unused Protein Score versus Unused Protein Score from iTRAQ Acquisition A 98 Fig. A2.1: Box plots of relative abundances for proteins identified with 99% confidence 123 Fig. A2.2: Logarithmic plot of average relative abundance of proteins in Idua'' pools vs. Idua+I+ mixed sex, >99% confidence, with proteins rank ordered from left to right based on descending Protein % Confidence score 124 Fig. A2.3: Western blot of serum samples from WT (Idua+/+) and MPS (Idua'') mice for HCII 125 Fig. A2.4: Western blot of MPS patients for HCII 126 Fig. A2.5: HCII-T levels in MPS 1H serum samples following enzyme replacement therapy 127 Fig. A2.6: Western blot of MPS patient samples for ATIII 128 vi List of Abbreviations 2DGE - 2-dimensional gel electrophoresis ATIII - antithrombin III ATIII-T - antithrombin III-thrombin complex B M T - bone marrow transplantation CHAPS - 3-[(3-cholamidopropyl)dimethlyammonio]-1 -propanesulphonate CS - chondroitin sulphate Da - daltons DIGE - differential 2-dimensional gel electrophoresis DS - dermatan sulphate DTT - dithiothreitol EC - enzyme catalogue E C M - extracellular matrix ERT - enzyme replacement therapy 12 fmol - femtomoles (10\" moles) G A G - glycosaminoglycan GalNAc - N-acetylgalactosamine HCII - heparin cofactor II HCII-T - heparin cofactor II-thrombin complex H P L C - high performance liquid chromatography HS - heparan sulphate ICAT - isotope coded affinity tags IDUA - human a-L-iduronidase protein Idua - murine a-L-iduronidase protein Idua - murine a-L-iduronidase gene IEF - isoelectric focusing IgG - immunoglobulin gamma iTRAQ - isobaric tagging for relative and absolute quantification kDa - kilodaltons (103 Da) KS - keratan sulphate MPS - mucopolysaccharidosis MPS I - mucopolysaccharidosis type I (general term) MPS IH - mucopolysaccharidosis type I (Hurler syndrome) MPS IH/S - mucopolysaccharidosis type I (Hurler-Scheie syndrome) MPS IS - mucopolysaccharidosis type I (Scheie syndrome) MS - mass spectrometry O M I M - Online Mendelian Inheritance in Man serpin - serine protease inhibitor UPS - Unused Protein Score WT - wild-type vn Acknowledgements I would like to acknowledge the people who have been important influences during the course of my studies. First, I want to thank my supervisor Lome Clarke for taking me into his lab and teaching me an incredible amount in only 20 months. Lome has been more supportive and inspiring than I could possibly imagine, and I have grown considerably on account of his leadership. Jan Friedman and Robert McMaster provided excellent suggestions and guidance during my research, having me consider questions I did not think to ask. Graham Sinclair, as much mentor as former lab member, offered useful technical suggestions and guidance in a number of situations that helped me to succeed. I could never forget to acknowledge Karen Colobong, from the preparative work and sample collection she does for me, to being there every day in the lab to talk and share experiences. Cheryl Bishop: she was always on my side and curious about my goals. M y parents are very important people to me and I want to recognize how they were always supportive and interested in what I did, ensuring that I was able to explain the details so that an outsider would understand. Finally, I want to thank my wife Kym for always knowing that this was the best idea, and for her encouragement every day. vin Co-Authorship Statement This thesis is the product of research performed entirely by me during my Master of Science program, all manual work and data analysis inclusive, except where noted in the acknowledgements. The initial experimental design was planned by Dr. Lome Clarke, Dr. Graham Sinclair, and me. A l l text in this thesis is original work written by me, with editing contributions from Drs. Clarke and Sinclair in Chapter 3. ix Chapter 1: Introduction 1.1 Thesis Focus and Chapter Overview This thesis describes the identification of a serum biomarker for mucopolysaccharidosis I (MPS I) through proteomic analysis in the MPS I murine model, and its validation in mouse and human serum samples. MPS I is a progressive, multi-system disease with a spectrum of clinical phenotypes ranging from a severe form with onset in infancy leading to death by the end of the first decade of life, to an attenuated form presenting later in life that is associated with morbidity but usually a normal life span. Many patients fit within this broad spectrum. This clinical heterogeneity leads to differences in progression for individual patients as well as difficulty evaluating therapeutics. Therefore the development of an objective biomarker of MPS disease would be clinically helpful. Identifying a reliable, accurate biomarker has the potential to greatly improve patient care and treatment. Using the murine model of MPS I, I identified a serum biomarker of the disease, validated it in mice and humans, and measured its responsiveness to enzyme replacement therapy. Chapter 1 is a brief introduction describing the disease and issues surrounding current biomarkers. The proteomic techniques involved in this thesis follow, with a discussion of strengths and weaknesses of the different methods. There is also a section on the obstacles associated with analyzing the serum proteome without a priori knowledge of possible biomarkers. Finally, the thesis objective is stated with the underlying hypothesis and rationale for the project. 1 Chapter 2 is a presentation of the utility of high abundance serum protein depletion and 2-dimensional gel electrophoresis images obtained over the course of my research. The success of the methodology and a putative biomarker are briefly evaluated. Chapter 3 is a manuscript of a published paper that describes the identification of the biomarker and its validation in both murine and human samples. A discussion of the implications of the biomarker and insights into MPS pathophysiology is included. In Chapter 4, I produce a manuscript containing results of a subsequent assessment of the biomarker with a larger set of MPS I patients enrolled in an enzyme replacement therapy clinical trial, as well as data from two MPS I patients not enrolled in the trial but with a larger number of sample collections, thereby allowing more detailed understanding of the therapeutic response. Chapter 5 presents a discussion of the results I obtained and their application to MPS research. A critical evaluation of the iTRAQ technology used in this study and its application to proteomic research follows. I also describe future topics to address through related studies. Finally, two appendices describe additional work relevant to this thesis that I have performed but not included in the manuscripts: a computational evaluation of iTRAQ reproducibility, as well as a patent submitted on the measurement of the biomarker for diagnostic purposes. 1.2 Mucopolysaccharidosis I Mucopolysaccharidosis I (MPS I, OMIM #252800) is an autosomal recessive disorder with heterogeneous clinical presentation. A member of the broad family of 2 lysosomal storage disorders, MPS I is one of seven classes of MPS disorders, which can be subdivided into thirteen subcategories (Fig. 1.1). The MPS category encompasses all the disorders related to the catabolism of mucopolysaccharides, otherwise known as glycosaminoglyeans (GAGs). Representing the \"glyco\" part of glycoprotein, GAGs are linear carbohydrate chains attached to proteins, and they range in size and complexity from a few monomers in a single chain to tens of thousands of monomers in multi-branched appendages. In some instances, the mass of the carbohydrate chains exceed that of the protein. Glycoproteins are involved in many cellular systems\u00E2\u0080\u0094signalling, adhesion, extracellular matrix structure, ligand binding\u00E2\u0080\u0094and the carbohydrate moieties of a glycoprotein can change throughout development [1]. Therefore, glycoproteins regularly enter the protein degradation pathway for recycling. MPS Subtype Storage Molecule MPS IH DS, HS MPS IH/S DS, HS MPS IS DS, HS MPS II DS, HS MPS IMA HS MPS 1MB HS MPSIIIC HS MPS HID HS MPS IVA KS, CS MPS IVB KS MPS VI DS MPS Vll DS, HS, CS MPS IX Hyaluronan Fig. 1.1: Lysosomal storage disorders The mucopolysaccharidoses are one of several lysosomal metabolic diseases. MPS disorders involve the breakdown of one or more of the glycosaminoglycans chondroitin sulphate (CS), dermatan sulphate (DS), heparan sulphate (HS), keratan sulphate (KS), or hyaluronan. 3 MPS I patients are deficient in the enzyme a-I-iduronidase (IDUA), an exoglycosidase responsible for degrading GAGs in the lysosome. Specifically, IDUA is a lysosomal hydrolase essential for the step-wise degradation of dermatan sulphate (DS) and heparan sulphate (HS) by cleaving the terminal, unsulphated iduronic acid residue (Figs. 1.2 and 1.3). DS is a polymer of P-linked iduronic or glucuronic residues linked by alternating 4-O-sulphated N-acetylgalactosamine (GalNAc) monomers. DS may also be sulphated at the C-2 position of the uronic acid (but this is cleaved by the preceding enzyme in the degradative pathway) and is a common G A G involved in structural elements such as bone and cartilage. HS is a higher charge-density G A G than DS and consists of the same uronic acids alternated by a-linked glucosamine monomers. The increased charge density occurs because HS can carry sulphate groups on the uronic acid, and through N - , C-3, and C-6 linkages on glucosamine. This additional heterogeneity allows HS to mediate many different protein interactions, and, as might therefore be expected, HS is more widespread than DS. QwwDS QVAWDS Fig. 1.2: Iduronidase action in dermatan sulphate degradation a-\u00C2\u00A3-iduronidase catalyzes the cleavage of the terminal iduronic acid in dermatan sulphate chains. 4 CH 2 OH H0-\" HO a-Z_-iduronidase HO HS CH 2 OH HO HS Fig. 1.3: Iduronidase action in heparan sulphate degradation a-\u00C2\u00A3-iduronidase catalyzes the cleavage of the terminal iduronic acid in heparan sulphate chains. Storage of these undegraded GAGs in the lysosomes results in the remarkable phenotypes associated with MPS I, characterized by excretion of partially degraded DS and HS in the urine. Children with the severe form of MPS I, known as Hurler disease (MPS IH), have a normal appearance at birth and typically show phenotypic signs between 6 - 1 8 months of age. The disease shows relentless progression and patients have a life expectancy of 10 years. It is a multi-system disorder with developmental delay, arthropathy, cardiac and respiratory abnormalities, dysostosis multiplex, hepatosplenomegaly, short stature, and corneal clouding. Respiratory and cardiac complications cause the majority of patient deaths. Approximately 20% of MPS I patients present with an attenuated phenotype. In some cases, where onset usually occurs in adolescence, the symptoms may be limited to joint stiffness, cardiac valvular dysfunction, and corneal clouding. These patients are 5 classified as Scheie patients (MPS IS) and often have normal life spans,with normal intelligence and average height. Many patients fit a clinical phenotype between that of Hurler syndrome and Scheie syndrome in the aptly named Hurler-Scheie syndrome (MPS IH/S); these patients have an attenuated phenotype which fills the broad and continuous spectrum from MPS IH to MPS IS. Onset of symptoms can occur in childhood with progressive arthropathy and cardiac involvement, as well as CNS and peripheral nervous system involvement. Untreated, most of these patients die within the third decade. Molecular studies of mutations at the IDUA locus indicate that residual enzyme activity is the most likely factor underlying this clinical heterogeneity [2-4]. However, residual enzyme activity and catalytic capacity measured with artificial substrates from severe and attenuated patients show overlapping ranges [5]. Determining the phenotypic severity of patients diagnosed with MPS I early in their clinical course is challenging. Clinical criteria gained from extensive clinical evaluation are helpful in the determination of the degree of disability or clinical effects in individual patients. Nonetheless, these features are subjective, limited in utility for short-term evaluation of treatment or intervention effects, and not easily translatable to different physicians or care centres. The current gold standard assay to diagnose a patient with MPS I is to measure IDUA enzyme activity in leukocytes or fibroblasts [6]. However, this measure does not delineate the different clinical phenotypes [6,7] nor assess therapeutic response. Urinary G A G concentration shows reduction following therapy [8] and is marginally useful as a preliminary screen, but it is not highly specific for MPS patients since elevated urinary GAGs are observed in many healthy, young children [9-12]. In addition, whether the urinary GAGs reflect a general level of disease 6 involvement among the organs or simply that of the kidneys is an unresolved issue. Although some genotype-phenotype correlation does exist\u00E2\u0080\u0094homozygotes or compound heterozygotes for the prevalent W402X or other nonsense mutations always present with Hurler syndrome [13]\u00E2\u0080\u0094many families have private mutations for which phenotype cannot be accurately predicted from genotype [13]. Combinations of nonsense and missense mutations produce unpredictably variable residual activity levels in in vitro studies [5,6,13]. It is well accepted that tissue G A G accumulation underlies the pathological consequences of MPS disorders, but there is a generally poor understanding of the mechanisms behind the pathophysiology of this complex disease. Precisely how GAGs cause the progression is unknown; one of the few clues is the presence of DS in MPS disorders with skeletal deformities and HS in those with neurological involvement. Further complexity arises from the observation that secondary build-up of metabolites, such as GM2 and GM3 gangliosides, occur in the central nervous system of MPS I patients who have neurological involvement [ 14,15]. How these secondary molecules accumulate remains to be answered, as does their role in the CNS symptoms [6]. Identification of a serum biomarker would be very useful for MPS I clinical care and research. With the advent and licensing of recombinant human enzyme replacement therapy (ERT, Aldurazyme\u00E2\u0084\u00A2 [8]), there is hope for many patients suffering with the disease and their families that treatment will mitigate the devastating effects of the disease. Thus, a biomarker would have potential use in monitoring clinical severity from an objective, measurable standpoint and optimizing individual dosages. In addition, while ERT does not provide a cure for MPS I, it is accepted that early intervention may 7 dampen the impact of the symptoms in individuals by replacing the metabolic deficiency prior to onset of irreversible damage [16-18]. 1.3 Techniques for Proteomic Analysis Understanding the different tissue proteomes has become a goal of many human disease researchers. Whereas the genome predicts potential gene products, the complete proteome is a detailed snapshot of the protein compliment of a given state. By developing proteome maps of different tissues under discrete conditions, researchers should be able to identify abnormally regulated proteins and post-translational modifications undetectable through genome analysis. Ideally, the entire proteome would be analyzed, with no biases or assumptions surrounding constituent proteins. However, technical aspects to be described hinder this in many proteome analyses. Although some success has been achieved with studies that select large subsets of proteins for analysis [19-24], such studies are limited in capacity to identify unanticipated, novel results. Therefore, it remains preferable to use unbiased techniques, particularly in disorders such as MPS I where hypothesis-based research has not provided solutions to disease progression. The original proteomic technique, two-dimensional gel electrophoresis (2DGE), separates proteins based on isoelectric point, then by molecular weight. This method has been improved since its inception three decades ago: replicability has been improved through new systems, buffer and desalting optimization minimizes horizontal streaking to improve clarity, and loading limits have increased to enhance visualization of low expression level proteins. Nonetheless, the methods are cumbersome and require 8 multiple, complex steps to arrive at a protein identification. Recently, techniques relying on mass spectrometry and database searching have become increasing prevalent; however, these methods are insensitive to post-translational modifications [25] and so 2DGE still provides a useful tool for proteome analysis. Differential mass spectrometry-based methods are improving in power and their ability to recognize valid differences between proteomes, evidenced by recent results [26-32]. One of the original methods, Isotope Coded Affinity Tag (ICAT) reagents, relies on the principle of differentially labeling two pools of trypsinized proteins (each constituting a different proteome) with cysteine-reactive tags: each pool labeled with different isotopic tags [33]. This permits both peptide pools to be combined and simultaneously analyzed by mass spectrometry to determine the relative abundances of peptides (and therefore parent proteins) in each proteome [33]. However, ICAT analysis is restricted to proteins containing cysteine amino acids, and can only identify the select peptides from proteins possessing cysteines. With the average 50 kDa, 450 amino acid, vertebrate protein containing 13 cysteinyl residues (compared to 35 alanyl residues) [34], and many proteins and peptide hormones holding none, the observed proteome is clearly incomplete. Furthermore, few corroborating peptides cause low confidence abundance ratios. A new generation of differential labeling, isobaric Tagging for Relative and Absolute Quantitation (iTRAQ), has emerged with the potential for comprehensive proteome analysis. iTRAQ uses four different non-isotopic isobaric tags, all with a total mass of 145 Da; each isobaric tag contains a reporter tag of one of 114, 115, 116, or 117 Da, and a corresponding balance tag of 31, 30, 29, or 28 Da, respectively [35]. As a 9 result, four unique protein pools can be tested concurrently for protein abundance variations. When fragmented during MS, the reporter tags appear in a quiet region of a typical peptide MS profile and can be unambiguously identified and quantified (Fig. 1.4). a) b) Balance tag: 31 -28 Da _ A Amine-reactive group Reporter tag: 114-117Da Repor ter a n d B a l a n c e r e m a i n intact m M S \ / MS fragmentation sites E q u a l Pept ide F r a g m e n t s 2 \u00E2\u0080\u0094 J fi 1 1 IN-D I F F E R E N T Reporter Ions in M S M S o Fig. 1.4: The i T R A Q reagent and principle a) Differentially labeling protein mixtures with isobaric tags containing reporter tags with unique masses allows identification of peptides and their abundances by mass spectrometry. Adapted from [36]. b) The protein abundances are calculated from the abundances of the reporter tags in a second MS scan. From [36]. A key feature of iTRAQ reagents is that they bind to peptides through an amine-reactive group. Theoretically, every lysyl residue and N-terminus will carry an iTRAQ tag, so every peptide in the reaction mixture becomes identifiable and quantifiable. After trypsin-digested proteins are labeled with a specific iTRAQ reagent, the samples are pooled, separated by liquid chromatography on hydrophobicity, and subjected to tandem mass spectrometry (LC-MS/MS). One round of MS identifies peptides, and the second identifies and quantifies the reporter tags (Fig. 1.4). Since the pooled peptides enter the 10 ionization chamber at the same time, all identical peptides are fragmented during the same window, which increases sample quantity and the likelihood of correct peptide identification. The observed peptide fragmentation patterns are compared to patterns in a database to identify the peptide sequence. An automated database search then provides a probabilistic identification of the parent protein, with confidence values based on the number of peptides identified and their fit to spectra in the database [35,37]. After compiling a list of identified proteins, an abundance value is calculated for each protein as a weighted average of the abundances of the reporter tags measured in the same fragmentation window as the peptides to which they were bound. This protein abundance permits calculation of a ratio for each protein in one pool relative to the corresponding protein in the other three pools, along with a protein identification probability and ratio error factor. This is presented in colour-coded tabular format indicating proteins with altered abundances (Fig. 1.5). In order to account for small changes in total protein concentration due to sample handling and labeling efficiency, each protein abundance is multiplied by a correction factor based on the ratio of all strongly identified proteins. Protein Name 116:114 116:114 117:114 Ratio P Val EF Ratio P Val E F Ratio P V a l E F Factor XII 0.8342 0.0044 1.127 0.927 0.2659 1.1471 0.8803 0.0386 1.1279 Fibrinogen, gamma polypeptide 5.5328 0.0196 36672 0.9048 0.2187 1.2006 4.4442 0.0337 3.7483 Fig. 1 . 5 : i T R A Q data output A l l identified proteins are listed with their observed ratios and ratio error factors. Shaded boxes indicate the ratio is truly different from the denominator pool based on protein identification probability. Limitations of the iTRAQ methodology are that sample preparation could cause artifactual changes in individual proteins that would not be corrected by a global protein correction factor. The colour-coding system is not based on the probability a protein 11 ratio truly deviates from equal concentrations but rather that the protein identification is correct. Thus, an observed ratio of 0.9992 could be deemed significant by the program but likely carries no biological value because the difference is within the natural variation seen between individuals. 1.4 The Serum Proteome's Technical Challenge As convenient as it is to acquire, serum presents a major challenge to proteomic analysis: a steep, sigmoidal protein concentration dynamic range [38]. Although high abundance proteins impair all tissue proteome analyses, the majority of the serum protein content is composed of three proteins: albumin, IgG, and transferrin; a second tier of eight high abundance proteins also exists [38]. These high abundance proteins impede identification of the low abundance proteins through 2DGE because protein loading limits accommodate limited visualization of low abundance proteins; low abundance proteins that can be detected are not likely to have the requisite 75 fmol for identification [39]. MS is similarly impaired because duty cycles of the analytical equipment recognize a portion of the peptides in each window: ergo, the most highly abundant proteins' peptides will present the strongest signals and be more frequently identified [40]. It is unlikely these major constituents represent informative biomarkers, so the potentially interesting proteins\u00E2\u0080\u0094which comprise approximately 10% of the total serum protein content [41-43]\u00E2\u0080\u0094need to be identified beneath the high abundance protein pattern. One available method to circumvent this problem is protein depletion, where the high abundance proteins are removed from serum samples before analysis. A number of methods are available: antibody affinity, albumin-specific reagents, and albumin-specific 12 desalting techniques [44], to name a few. However, an important requirement is that depletion be highly efficient and specific, avoiding concomitant loss of potentially valuable low abundance proteins. Antagonistically, albumin and transferrin biologically function as carrier proteins to stabilize and shuttle other proteins through circulation. Therefore, a degree of specific and non-specific protein loss inevitably results from all methods [45,46]. Fortunately, the potential value of the serum proteome prompted several companies to produce multiple antibody affinity columns for HPLC systems. These f columns contain antibodies specific for several of the high abundance proteins and are optimized to elute both low abundance proteins and proteins bound nonspecifically to the carrier proteins. The efficiency and reproducibility of these columns has been recently reviewed [47]. 1.5 Murine Model of MPS IH Our lab developed a murine model of severe MPS I through a targeted knock-out of the Idua gene [48]. Homozygous null mice recapitulate most symptoms of human MPS IH and are excellent models for MPS disease research [6,49,50]. Using a mouse model for the biomarker discovery phase presents several advantages over using human samples. First, the low incidence of MPS I (1/100,000 [51-53]) makes collection of sufficient samples to identify a biomarker applicable to other patients difficult, particularly with the advent of ERT, as biomarkers will probably not be apparent in post-treatment samples. Validation of candidate biomarkers in large, independent samples would be nearly impossible in humans, but it is easily achievable in 13 a mouse colony. Finally, due to the level of genetic and environmental heterogeneity between people it is difficult to avoid inter-individual variability causing spurious results in humans, but collecting samples from genetically homogeneous, identically raised mice minimizes this inherent variability. 14 1.6 Thesis Objective and Hypothesis 1.6.1 Objective To identify a serum biomarker indicative of MPS I disease. 1.6.2 Hypothesis The primary block of glycosaminoglycan degradation in MPS I will lead to altered levels of proteoglycans. These proteoglycans may be useful as disease biomarkers. 15 1.7 References [I] Essentials of Glycobiology 1st ed. A . Varki, R. Cummings, J. Esko, H. Freeze, G. Hart, and J. Marth, editors, Cold Spring Harbor Laboratory Press, Plainview, 1999, http://www.ncbi.nlm.nih.gov/books/bv.fcgi?rid=glyco.section.60. [2] H.S. Scott, P.V. Nelson, T. Litjens, J.J. Hopwood, and C P . 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Lowry, Incidence of inborn errors of metabolism in British Columbia, 1969-1996, Pediatrics 105 (2000), p. elO. 19 Chapter 2: Serum 2-Dimensional Gel Electrophoresis Studies in the MPS I Murine Model 2.1 Introduction Since its inception in 1975 [1], 2-dimensional gel electrophoresis (2DGE) has been used as a preparative and analytical tool in protein and proteome studies. As the original proteomic analysis method, 2DGE has proven useful for identifying changes in protein concentrations and post-translational modifications in many diseases and been the principal technique for developing tissue proteome maps [2]. In light of criticism surrounding replicability and utility in resolving basic proteins, hydrophobic proteins, as well as those of low molecular weight [2,3], considerable attention has focused on strengthening the technique through the use of new technologies. Indeed, 2DGE remains the first method routinely used in most proteomic studies and the preferred unbiased technique to identify post-translational modifications in the proteome [3,4]. Nonetheless, the low resolution of 2DGE, a product of loading limits and staining methods, limits the technique's potential to identify informative biomarkers and to characterize low abundance proteome constituents; this is especially true in plasma and serum, which promise to hold a wealth of informative, medically relevant biomarkers. However, due to the dynamic differences in protein concentrations between common, uninformative proteins and the low abundance, informative ones, identifying these biomarkers requires simplification of the proteome. Mucopolysaccharidosis I (MPS I; OMIM #252800) is a multi-system disorder, characterized by a spectrum of phenotypes ranging from severe disease, known as Hurler 20 syndrome, to the most attenuated form, Scheie syndrome [5]. Patients with Hurler syndrome commonly present in the first year of life and, when untreated, have a life expectancy of 10 years with a progressive multi-system disease with developmental delay, arthropathy, cardiac and respiratory abnormalities, dysostosis multiplex, hepatosplenomegaly, and corneal clouding. The remainder of patients have an attenuated phenotype which covers a broad and continuous spectrum ranging from onset of symptoms in late adolescence with normal life expectancy and little or no associated arthropathy, cardiac involvement, or direct CNS involvement, to those individuals with onset in childhood and more significant systemic involvement, often leading to death within the second decade. The primary metabolic defect in MPS I is deficiency of the lysosomal enzyme a-L-iduronidase (IDUA; EC 3.2.1.76). IDUA deficiency results in abnormalities in the degradation of the glycosaminoglycans (GAGs) heparan sulphate and dermatan sulphate, which subsequently accumulate in the lysosome. Genotype to phenotype correlation does exist to some extent for IDUA deficiency, however the large number of private mutations does not allow genotype to predict phenotype in a considerable proportion of patients [6,7]. Currently, no disease biomarkers unambiguously allow for the determination of disease severity or responsiveness to treatment. As such, identification of a serum biomarker would be invaluable to MPS I diagnostics and research. In this project, I depleted three high abundance proteins from pooled serum of Idua'1' mice, the murine model for MPS I developed by our lab [8], and wild-type mice. The remaining serum proteins were analyzed by 2DGE in an attempt to discover a serum 21 biomarker of MPS I. No candidate biomarkers were isolated and identified by this method. 2.2 Methods 2.2.1 Protein quantification Immediately following high abundance protein depletion, samples containing the pooled flow-through fractions were quantified for total protein using the Bio-Rad D c protein assay to confirm similar total protein contents. An eight point standard curve was developed with bovine serum albumin (Bio-Rad, Hercules, CA) and all samples were tested in triplicate. 2.2.2 Acetone precipitation Samples subjected to high abundance protein depletion required desalting prior to 2DGE. Acetone (Fisher, Fair Lawn, NJ) was pre-chilled to -20\u00C2\u00B0C. 300 uL of each protein sample was mixed with 1200 uL of cold acetone, vortexed, and immediately placed at -20\u00C2\u00B0C for 90 minutes. Samples were then centrifuged at 15,000g. The supernatant was discarded and the pellet washed once with cold acetone. Samples were air dried in a fumehood at room temperature for 30 minutes. 2.2.3 2D Gel Electrophoresis Acetone precipitated samples containing a predicted protein content of 170 Lig were solvated in 200 LIL of rehydration buffer containing 7 M urea (Invitrogen, Carlsbad, CA), 2 M thiourea (Invitrogen), 2% CHAPS (Invitrogen), 0.5% carrier ampholytes 22 (Invitrogen), 0.002% bromophenol blue (Fisher), and 20 m M DTT (Sigma, St. Louis, MO). 45 uL of this sample (38 ug protein) was diluted with 120 uL of rehydration buffer. 155 | iL (36 pig) was applied to rehydrate each Z O O M 3 - 1 0 non-linear IPG strip (Invitrogen) overnight. Strips were subjected to step gradient voltage changes for the following time periods: 200 V for 20 minutes, 450 V for 15 minutes, 750 V for 15 minutes, 2000 V for 45 minutes. Following IEF, strips were immediately reduced with NuPAGE LDS Sample Buffer (Invitrogen) containing NuPAGE Sample Reducing Agent (Invitrogen) for 15 minutes. The reducing buffer was decanted and the strips were alkylated with NuPAGE Sample Buffer containing 125 m M iodoacetamide (Sigma). Reduced, alkylated strips were subjected to 133 Vh at 200 V on NuPAGE 4 -12% Bis-Tris IPG gels (Invitrogen). Gels were fixed for 2 x 15 minutes with 50% methanol, 7% acetic acid, then stained overnight at room temperature with Sypro Ruby (Invitrogen). Gels were washed for 75 minutes with 10% methanol, 7% acetic acid, then for 3 x 5 minutes with ddF^O and visualized at 302 nm. Images were taken with Alphalmager software, v2.0 (Alpha Innotech, San Leandro, CA). 2.3 Results 2.3.1 Protein quantification Table A l . l shows the column's replicability and the amount of protein albumin, IgG, and transferrin contribute to the serum proteome. 23 Table 2.1: Protein concentrations of high abundance protein depleted pools Sample Pre-depletion protein content (mg) Post-depletion concentration (mg/mL) Post-depletion protein content (mg) Idua+ / +, mixed sex 4.26 0.53 1.19 Idua+ / +, male 4.26 0.58 1.30 Idua\"\", mixed sex 4.26 0.59 1.34 Idua\"'\", male 4.26 0.56 1.27 2.3.2 2D gel electrophoresis Fig. A 1.1 shows 2DGE images obtained with and without high abundance protein depletion. The use of high abundance protein depletion clearly removes the major albumin spot and enhances visibility of low abundance proteins. I I I I 9 8 7 6 Fig. 2.1: 2DGE images of nascent and high abundance protein depleted mouse serum samples a) 2DGE of 40 ug undepleted serum. Note the large spot at pH 5.2 representing albumin, b) 2DGE of 38 ug high-abundance protein depleted serum. The major albumin spot appears entirely absent and many previously hidden spots are now visible. Fig. 2.2 shows 2DGE images obtained for the four sample pools of high abundance protein depleted serum. With the exception of one small spot indicated, there 24 does not appear to be any consistent, major change to the MPS I mouse serum proteome. This spot was of insufficient size for successful protein identification. Fig. 2.2: 2DGE images of MPS and wild-type mouse depleted serum samples a) Idud1' mixed sex pool, b) Idua+,+ mixed sex pool, c) Idud1' male pool, d) Idua+/+ male pool. The white arrow indicates a small spot that was present in both MPS mouse pools but not in the WT pools. A l l samples contained 38 ug of protein. 2.4 Discussion My results indicate there are no major visible changes in the serum proteome to distinguish between serum from MPS I and normal mice. I observed one minor variation in the proteome but was unable to identify the candidate due to an insufficient quantity of protein. Unfortunately, increasing the sample load produced unclear gels that could not 25 be used to isolate more protein. Without means to validate the observed up-regulation in this unidentified protein's concentration, it is difficult to confirm the change. Occasionally, small spots arise as carbamylation by-products due to poor sample handling allowing iso-cyanate ions to bind to lysyl side chains and alter the pH of the protein [9], giving the impression the protein is unique from its neighbours. However, given the location of the protein in question and the pattern of the more acidic major serum protein, this does not appear to be a carbamylation artefact. Furthermore, reproduction in both Idud1' pools in conjunction with the absence of the spot in either wild-type pool argues against this being a chance by-product. Despite these results, there are likely a number of potential biomarkers that may be useful in MPS I research, but they remain undetectable by this method. In addition, although depletion of albumin, IgG, and transferrin greatly enhanced the number of proteins visualized in my experiments, it is insufficient to identify a biomarker of MPS I as a result of the dynamic concentration range of the remaining serum proteins. A possible method to enhance the resolution of the low abundance proteins is to perform further prefractionations of the samples by isoelectric focusing, which increases the sample loading limits and focuses on definable pH windows. Preliminary results have shown this to be a viable option but hindered by high salt concentrations following protein depletion, which interferes with isoelectric focusing and obscures visualization through horizontal streaking. Reproducibility is another related issue interfering with further prefractionations as each step carries an error factor in the proteins partitioned into each fraction. 26 On a global level, my 2DGE experiments indicate there is no major change in the MPS I serum proteome. Further reductions of the proteome may yield informative biomarkers that explain aspects of the clinical heterogeneity and pathophysiology seen in MPS I patients, but the technological limitations of 2DGE are too great to identify these factors. 27 2.5 References [1] P.H. O'Farrell, High resolution two-dimensional electrophoresis of proteins, J. Biol. Chem. 250 (1975), pp. 4007-4021. [2] C.I. Phillips and M . Bogyo, Proteomics meets microbiology: technical advances in the global mapping of protein expression and function, Cell. Microbiol. 7 (2005), pp. 1061-1076. [3] G. Baggerman, E. Vierstraete, A. De Loof, and L. Schoofs, Gel-based versus gel-free proteomics: a review, Comb. Chem High Throughput Screen. 8 (2005), pp. 669-677. [4] L. Thadikkaran, M.A. Siegenthaler, D. Crettaz, P.A. Queloz, P. Schneider, and J.D. Tissot, Recent advances in blood-related proteomics, Proteomics 5 (2005), pp. 3019-3034. [5] E.F. Neufeld and J. Muenzer, in The metabolic and molecular bases of inherited disease, 8 t h edition, C R . Scriver, A . L . Beaudet, W.S. Sly, and D. Valle, editors, McGraw-Hill, New York, 2001, pp. 3421-3452. [6] C E . Beesley, C A . Meaney, G. Greenland, V. Adams, A . Vellodi, E.P. Young, and B.G. Winchester. Mutational analysis of 85 mucopolysaccharidosis type I families: frequency of known mutations, identification of 17 novel mutations and in vitro expression of missense mutations, Hum. Genet. 109 (2001), pp. 503-511. [7] N.J. Terlato and G.F. Cox, Can mucopolysaccharidosis type I disease severity be predicted based on a patient's genotype? A comprehensive review of the literature, Genet. Med. 5 (2003), pp. 286-294. [8] L .A. Clarke, C S . Russell, S. Pownall, C.L. Warrington, A . Borowski, J.E. Dimmick, J. Toone, and F.R. Jirik, Murine mucopolysaccharidosis type I: targeted disruption of the murine alpha-L-iduronidase gene, Hum. Mol. Genet. 6 (1997), pp. 503-511. [9] P.G. Righetti, Real and imaginary artefacts in proteome analysis via two-dimensional maps, J. Chromatogr. B Analyt. Technol. Biomed. Life Sci. Epub 2006 Mar 3. 28 Chapter 3: Heparin Cofactor II-Thrombin Complex in MPS I: A Biomarker of MPS Disease* 3.1 Introduction Mucopolysaccharidosis I (MPS I; OMIM #252800) is a severe, multi-system, progressive lysosomal storage disorder resulting from deficiency of the enzyme a-L-iduronidase (IDUA; EC 3.2.1.76) [1]. IDUA deficiency results in abnormalities in the degradation of the glycosaminoglycans (GAGs) heparan sulphate and dermatan sulphate, which subsequently accumulate in the lysosome. MPS I is inherited as an autosomal recessive disorder with an incidence of approximately 1 in 100,000 live births and is considered prototypical of the severe MPS disorders. Clinically, MPS I manifests in a spectrum of phenotypes ranging from severe disease, known as Hurler syndrome, to the most attenuated form, Scheie syndrome. Patients with Hurler syndrome commonly present in the first year of life and, when untreated, have a life expectancy of 10 years with a progressive multi-system disease with developmental delay, arthropathy, cardiac and respiratory abnormalities, dysostosis multiplex, hepatosplenomegaly, and corneal clouding. The remainder of patients have an attenuated phenotype which covers a broad and continuous spectrum ranging from onset of symptoms in late adolescence with normal life expectancy and little or no associated arthropathy, cardiac involvement, or direct CNS involvement, to those individuals with onset in childhood and more significant systemic involvement, often leading to death within the second decade. The recent introduction of recombinant enzyme replacement therapy (Aldurazyme\u00E2\u0084\u00A2) for A version of this chapter has been accepted for publication as Derrick R. Randall, Graham B. Sinclair, Karen E. Colobong, Elly Hetty, and Lome A. Clarke. \"Heparin Cofactor II-Thrombin Complex in MPS I: A Biomarker of MPS Disease.\" Molecular Genetics and Metabolism, in press. 29 MPS I [2] will undoubtedly alter the progression of this disease, particularly for patients with attenuated forms. Although the primary enzyme deficiency and the associated metabolic pathway are well understood, there is a poor understanding of the true pathophysiology of disease complications. Genotype to phenotype correlation does exist to some extent for IDUA deficiency; however, the large number of private mutations does not allow genotype to predict phenotype in a considerable proportion of patients [3,4]. In addition, there are no disease biomarkers that unambiguously allow for the determination of disease severity or responsiveness to treatment. The serum proteome is a potentially rich source of protein that may contain biomarkers indicative of disease severity and disease responsiveness, as well as factors underlying disease progression. Efficient depletion of the high abundance proteins prior to proteomic analysis has proven effective in recognizing expression changes of less abundant proteins in disease states [5-7]. The recent development of iTRAQ reagents [8], has enabled multiplex analysis of up to four independent proteomes through differentially weighted reporter tags. Unlike ICAT proteomic studies, which restrict anlaysis to cysteine containing proteins, iTRAQ reagents ligate to all free amine groups of peptides [9]. This method has been demonstrated to be highly informative [9-11]. Using a depleted serum proteomic approach in the MPS I murine model [12] we have demonstrated significant reduction in the level of heparin cofactor II (HCII), a serine protease inhibitor (serpin), in affected animals. Further analysis revealed that although native HCII levels are reduced, there is marked elevation of HCII-thrombin (HCII-T) complex formation in affected animals. Translation of these observations to humans with MPS I show equivalent findings. Importantly, the elevation of HCII-T 30 complex appears to be correlated to disease severity and is responsive to treatment. Modulation of serpins by glycosaminoglycans has been well studied, but this is the first report relating serpins to MPS disease. Our results indicate that HCII-T is an excellent biomarker for MPS I and represents a novel finding that may implicate other G A G modulated serpins and their proteases in the pathophysiology of MPS diseases. 3.2 Methods 3.2.1 Sample collection Mouse serum samples were collected by cardiac puncture and added to Beckton Dickinson serum separator tubes (Franklin Lakes, NJ). Samples were allowed to clot for 30 minutes at room temperature and centrifuged for 15 minutes at 3000xg- at room temperature. Samples were aliquoted immediately and stored at -80\u00C2\u00B0C. Mouse plasma samples were collected by cardiac puncture, with sodium citrate added to 0.4%. Citrated samples were centrifuged for 15 minutes at 1500xg at 4\u00C2\u00B0C. Human plasma and serum samples were collected by clean venipuncture using a 2 syringe technique, as described [13] and processed as above. 3.2.2 High abundance protein depletion Albumin, immunoglobulin, and transferrin were depleted from murine serum samples using a 100 mm Ms-3 Multiple Affinity Removal System (Agilent Technologies, Palo Alto, CA), according to the manufacturer's instructions. 4 age- and sex-matched pools of mouse serum samples were normalized for total protein to 12 mg/mL by diluting them in running buffer (Agilent Technologies). Each pool contained 6 independent 31 serum samples. A K D Scientific syringe pump (Holliston, M A ) was used to maintain a constant flow rate of 15 mL/h. 320 | i L were subsequently used for high abundance protein depletion with identical pool collections obtained for all samples. 3.2.3 iTRAQ analysis 3.2.3.1 iTRAQ reagent labelling The depleted mouse serum samples were labelled with the iTRAQ reagent following the manufacturer's protocol (Applied Biosystems, Foster City, CA). Briefly, 100 \ig of total protein from each of the 4 depleted serum pools was precipitated with acetone and resuspended in iTRAQ dissolution buffer for reduction, alkylation, and tryptic digestion. Each of the resulting peptide pools was then labelled with a different isotopic iTRAQ Reagent (114 - 117 Daltons) as follows: Idua+/+ mixed sex pool (114 Da), Idua~'~ male pool (115 Da), Idua+/+ male pool (116 Da) and Idua'1' mixed sex pool (117 Da). The four differentially labelled pools were then combined and subjected to strong cation exchange (SCX) chromatography using a polysulfoethyl A column (Poly L C , Columbia, MD). The combined sample was diluted in 10 m M K P 0 4 (pH 2.7), 25% acetonitrile (Buffer C); applied to the column; and peptides eluted over a 33 minute gradient to 65% Buffer C and 35% lOmM K H 2 P 0 4 , 25% acetonitrile, 0.5 M KC1 (Buffer D). Fractions were collected at one minute intervals. 3.2.3.2 LC-MS/MS analysis The resulting 33 SCX fractions were then subjected to LC-MS/MS analysis utilizing a QStar Pulsar hybrid quadrupole-TOF instrument (Applied Biosystems) and an 32 UltiMate micro HPLC (LC Packings, Sunnyvale, CA). The HPLC was equipped with a C18 PepMap guard column (LC Packings) separated from a C18 Pepmap Nano L C column (LC Packings) by a switching valve to allow for precolumn sample clean-up before switching inline for reversed phase chromatography and MS/MS analysis. Each SCX fraction was evaporated to dryness, resuspended in 5% acetonitrile and 3% formic acid, and 25% of the sample was injected onto the C18 guard column in 98% water/acetonitrile (98:2), 0.05% formic acid (Buffer A) with the HPLC flowing to waste to remove sample contaminants. Following 10 minutes at 100 ul/mL, the guard column was switched inline with the C18 resolving column and mass spectrometer, and the peptides were eluted with a linear gradient to 60% water/acetonitrile (2:98), 0.05% formic acid (Buffer B) over 40 minutes. Following a 5 minute ramp to 80% Buffer B, the column was re-equilibrated in 98% buffer A for 15 minutes prior to the injection of the next SCX fraction. 3.2.3.3 Data acquisition and analysis MS data were acquired automatically using Analyst QS 1.0 software Service Pack 8 (ABI MDS SCIEX, Concord, Canada). An information-dependent acquisition method consisting of a 1 second TOFMS survey scan of mass range 400-1200 amu and two 2.5 second product ion scans of mass range 100 - 1500 amu was utilized. The two most intense peaks over 20 counts, with charge state 2 - 5 were selected for fragmentation and a 6 amu window was used to prevent the peaks from the same isotopic cluster from being fragmented again. Once an ion was selected for MS/MS fragmentation it was put onto an exclusion list for 180 seconds. Following the initial data acquisition run (iTRAQ 33 acquisition A), an exclusion list was created for all peptides identified with a confidence of 95% or greater in each of the SCX fractions. A second injection of each S C X fraction using the exclusion list for that fraction and the same LC and MS conditions as the first run was then performed in order to detect the lower concentration proteins present in plasma (iTRAQ acquisition B). The resulting data files were combined and processed using the Interrogator\u00E2\u0084\u00A2 algorithm in the ProQuant software (vl.O) (Applied Biosystems) in Analyst using the following parameters: The MS and MS/MS mass tolerances were set to 0.20. A rodent subset of the Celera Discovery Systems Database (01/24/2004) was used for searching. Methyl methanethiosulphonate (MMTS) modification of cysteines was used as a fixed modification. The number of missed cleavages was set to 1. A l l results were written to a Microsoft Access database and, to reduce redundancy, ProGroup Viewer version 1.0.5 (Applied Biosystems) was used to assemble and report the data. Protein % Confidence Scores, which are influenced by the closeness of the observed peptide spectrum to the predicted spectrum, the number of peptides identified for a given protein, as well as the variance of abundance of each peptide for the given protein, were used to calculate a Protein Score using the equation Protein Score = -log[l - (Protein % Confidence)/100]. Abundances of each identified protein in the sample pools were calculated based on the abundance of reporter tags bound to the peptide tryptic fragments for each pool. Where more than one peptide was identified for a protein, the protein abundance was calculated by weighted averaging of the abundances of the individual peptides and reported with a 95% confidence interval based on the standard deviation of the weighted average. Protein abundances were adjusted for global labeling bias by a correction factor 34 that assumed an average relative protein abundance of 1 across all samples. Relative abundances are determined by dividing the abundance of each protein from each pool by the corresponding protein in another pool. A l l proteins found to have significantly altered relative abundances were manually verified by inspecting the corresponding peptide matches. 3.2.4 Western blotting Western blot analysis was performed on 7.5% Tris-glycine gels and transferred to Pall (East Hills, N Y ) BioTrace NT membranes. Anti-human HCII and anti-human antithrombin III antibodies were from Affinity Biologicals (Hamilton, ON). Membranes were blocked with 5% Carnation powdered skim milk (Nestle, North York, ON) in phosphate-buffered saline with 0.05% Tween-20 overnight at 4\u00C2\u00B0C. Western blot analysis of human samples used primary antibody at a concentration of 1 ug/mL, with secondary antibody at a concentration of 1.3 (xg/mL. Western blot analysis of mouse samples used 3 Lig/mL primary antibody, and 1.3 Lig/mL secondary antibody. Antibody incubations were performed for 60 minutes at room temperature. Proteins were detected with West Pico detection kits (Pierce, Rockford, IL) according to the manufacturer's instructions. 3.2.5 ELISA HCII-T ELISA kits were obtained from Affinity Biologicals (Hamilton, ON) and used according to the manufacturer's instructions. This kit uses polyclonal sheep anti-human thrombin antibody for capture and peroxidase-conjugated polyclonal goat anti-human HCII antibody for detection. Standards were derived from purified human HCII 35 and thrombin (Enzyme Research Laboratories, South Bend, IN) reacted in the presence of 0.05 U/mL heparin (Sigma, St. Louis, MO). MPS IH serum samples were diluted 500-fold and MPS IH/S samples were diluted 100-fold in factor Il-depleted plasma (Affinity Biologicals) while control samples were undiluted. A l l standards and samples were tested in triplicate. 3.3 Results 3.3.1 iTRAQ serum proteomic studies Using a 94% Protein Confidence score cut-off applied to data observed over two cumulative MS/MS acquisitions, iTRAQ analysis resulted in the identification of 1701 distinct peptides belonging tO-198 unique proteins (Table 3.1). 181 proteins were identified on the strength of two or more peptides, the majority of which were represented by at least 5 peptides (Table 3.2). This weighting toward 5+ peptides per protein is likely due to the dynamic range of protein concentrations in serum, where more abundant proteins can be expected to be identified by several peptides. The second MS/MS data acquisition resulted in a 30% increase in the total number of serum proteins identified. Table 3.1: i T R A Q summary data iTRAQ Acquisition A iTRAQ Acquisition A+B Protein Confidence Level, % 94 95 99 94 95 99 # of Peptides 1132 1131 1048 1701 1686 1577 # of Proteins 151 150 114 198 195 150 36 Table 3.2: Number of unique peptides per protein in iTRAQ data collection, >94% Protein Confidence. Number of Peptides/Protein Total # of Proteins 1 2 3 - 4 5+ iTRAQ Acquisition A 22 17 11 10 91 151 iTRAQ Acquisition A+B 17 21 30 16 114 198 To investigate intersample variation, we compared the relative abundances observed in the Idua+/+ male pool to the Idua+/+ mixed sex pool as well as the Idua'' male pool to the Idua'' mixed sex pool at a 99% Protein Confidence level (Fig. 3.1). The vast majority of proteins show no significant change in expression levels between like pools, with the exception of one outlier. The possibility of a sex-specific expression difference observed in the outlier (~16-fold decreased) in the Idua+/+ Ma\e:Idua+,+ Mixed sex comparison is eliminated by the absence of such a difference in the Idua'' pools comparison and the decreased relative abundance of this protein (alpha-1-B glycoprotein) was assumed to be an artifactual in the Idua+/+ mixed sex control pool. 37 4 24 CD o c CO \"O C < \u00C2\u00A7 0 \u00E2\u0080\u00A24\u00E2\u0080\u0094' ro 0) cr O) O T T +/+ Male: +/+ Mixed sex -/- Male: -/- Mixed sex -/- Average: +/+ Mixed sex Fig. 3.1: Box plots of relative abundances for proteins identified with 99% confidence. Grey boxes cover the interquartile range, whiskers extend to 10 th and 90 t h centiles, and individual points indicate the outliers. Protein abundances are compared between the two WT pools, the two Idud'' pools, and the average of the two Idud1' pools versus the WT mixed sex pool. Comparison of the average protein relative abundances of the two Idud' pools with the Idua+/+ mixed sex pool reveals the variation between mutant and control pools is similar to that observed between like pools; however, a few proteins showed more extreme abundance differences (Fig. 3.1). This suggests there is minimal variation in protein quantities between the MPS and normal serum proteomes, with no single protein present at a dramatically different level, unlike the high concentration of chitotriosidase 38 (chitinase I) in many patients with Gaucher disease [14]. This result confirms earlier results obtained from 2D gel electrophoresis experiments (Chapter 2). In order to select a panel of proteins to be investigated as candidate biomarkers with significantly altered relative abundances in the Idud1' serum proteome, the relative abundances of each protein in the two Idud1' pools were averaged then tested for two factors. First, we determined which proteins showed average relative abundances exceeding the 95% confidence intervals of the same proteins' abundances in the Idua+/+ male pool. Second, proteins that also showed average relative abundances with confidence intervals not overlapping 0.00 (on a logarithmic scale) were considered strong candidates. The Idua+I+ mixed sex pool was used as the denominator pool for both analyses. Combining these criteria selected proteins exceeding their natural variability in both the MPS and WT animals regardless of the absolute value of the change. Candidate biomarkers selected by these criteria are indicated as red squares in Fig. 3.2 and listed in Table 3.3. Candidate proteins with the most extreme deviation from the normal state were fibrinogen gamma (4.96-fold increased), fibrinogen alpha (2.20-fold increased), and heparin cofactor II (1.79-fold decreased). 39 3 Fig. 3.2: Logarithmic plot of average relative abundance of proteins in Idua'1' pools vs. Idua+I+ mixed sex, >99% confidence, with proteins rank ordered from left to right based on descending Protein % Confidence score. Dashed lines indicate a two-fold increase or decrease in the average relative abundance of a protein present in the Idua'1' pools compared to the Idua^ mixed sex pool. Proteins marked as red squares were considered candidates based on significant changes in relative abundance and are listed on Table 3.3. \ 40 Table 3.3: Proteins identified at >99% confidence with significantly altered relative abundance in the MPS mouse serum, Idua mixed sex denominator. GenBank Accession Number Protein % Confidence Score Rank Protein Log2 of Average Relative Abundance Fold Increase/Decrease Biological Function AAH19506 95 Fibrinogen, gamma polypeptide 2.310 +4.96 Blood clotting AAH05467 71 Fibrinogen, alpha polypeptide 1.137 +2.20 Blood clotting AAC28866 87 Alpha-1-antitrypsin 1-5 0.636 + 1.55 Serine protease inhibitor (serpin) AAH13465 56 Inter-alpha trypsin inhibitor, heavy chain 1 0.480 + 1.40 Serpin AAA37246 5 Apolipoprotein B 0.347 + 1.27 Lipid and fatty acid transport AAH57983 2 Pzp protein 0.154 + 1.11 Serpin AAH23143 29 Gelsolin -0.144 -1.11 Cytoskeletal protein BAA19743 26 Kininogen precursor -0.281 -1.22 Protein metabolism and modification BAB33095 31 Histidine-rich glycoprotein -0.309 -1.24 Biological process unclassified AAC28865 23 Alpha-1 proteinase inhibitor 2 -0.377 -1.30 Serpin AAH21776 102 Apolipoprotein C-III -0.386 -1.31 Lipid metabolism AAH30166 90 Factor XIII beta -0.395 -1.31 Blood clotting AAH12706 64 Paraoxonase 1 -0.414 -1.33 Peroxidase AAH34543 78 Heparin cofactor II -0.840 -1.79 Serpin 41 An analysis of the reproducibility of iTRAQ and the effect of acquiring additional peptides is made possible by the double pool, supplementary iTRAQ data acquisition phases of this study. This information is presented in Appendix 1. 3.3.2 Heparin cofactor II western blot analysis in MPS I mice To investigate the HCII reduction in the serum of Idua'1' mice, western blot analysis was used utilizing goat anti-human HCII antibodies (Fig. 3.3). Surprisingly, the marked reduction in native HCII levels was associated with the presence of a higher molecular weight protein only in the mutant animals' sera, consistent with the published size of the HCII-thrombin (HCII-T) complex [15]. +/+ +/+ +/+ +/+ -/- -/- -/- -/-\u00E2\u0080\u0094 H C I I - T \u00E2\u0080\u0094 H C I I Fig. 3.3: Western blot of serum samples from W T (Idua+I+) and MPS (Idua'1') mice for HCII . 15 ug of sample was applied per well. 3.3.3 Heparin cofactor II western blot analysis in MPS I patients Fig. 3.4 shows the corresponding dramatic elevation of serum HCII-T complex in severe and attenuated cases of MPS I compared to that of controls. Also included is the complex formed from the incubation of pure HCII and thrombin in the presence of heparin to confirm that the complex truly is HCII-thrombin. Interestingly, the largest amounts of HCII-T complex are seen in the MPS IH patients in comparison to the MPS IH/S patient. Western analysis revealed no detectable HCII-T in plasma samples from Idua'1' or WT mice (data not shown), nor in plasma samples from humans without MPS I. 4 2 Plasma Fig. 3.4: Western blot of M P S patients for HCII. 2.5 ug of protein was loaded in wells 1 - 7, 8 ng of protein was loaded in wells 8 and 9. Figure 3.5a-b shows the level of HCII-T in a Hurler patient receiving enzyme replacement therapy (ERT) preceding and following bone marrow transplantation (BMT), and one Hurler-Scheie patient undergoing ERT only. Enzyme treatment in the Hurler patient (Fig. 3.5a) did not normalize HCII-T levels, but significantly reduced the amount of HCII-T levels to that seen in the attenuated patient studied. Further reduction in HCII-T occurred following bone marrow transplantation. Although well engrafted by week 52, this patient subsequently died of pulmonary hemorrhage. The Hurler-Scheie patient, Fig. 3.5b, showed marked reduction of HCII-T early during ERT exposure but then subsequently developed detectable HCII-T complex later during treatment. 43 Fig. 3.5: HCII-T levels in MPS 1H serum samples following enzyme replacement therapy. a) Hurler patient, 12 months of age at start of ERT. Al l lanes contain 2.5 ug of protein. Patient received a bone marrow transplant between 36 and 52 weeks, b) Hurler-Scheie patient, 8 years of age at start of ERT. A l l lanes contain 2.5 ug of protein. 3.3.4 HCII-T ELISA analysis Table 3.4 illustrates the dramatic elevation of HCII-T in the serum of MPS 1H and MPS 1H/S patients as well as murine MPS I samples in comparison to controls. MPS IH patients' serum HCII-T complex levels ranged from 174,700 - 208,600 pM, with an average value of 188,600 pM, representing a 630-fold increase relative to controls. The serum sample from a MPS IH/S patient had a HCII-T concentration of 46,000 pM (154-fold increase), reflective of the patient's attenuated phenotype. In contrast to the lack of detectable complex by western blot, ELISA revealed that plasma HCII-T levels were increased in MPS patients and the MPS I mouse, with the minimum concentration of HCII-T complex in MPS IH patients exceeding the maximum control value by 68%. 44 Table 3.4: HCII-T ELISA in serum and plasma samples of MPS I patients, MPS I mice, and controls. Sample (age in brackets) Serum [HCII-T] (pM \u00C2\u00B1 SD) Plasma [HCII-T] (pM \u00C2\u00B1 SD) Control (10 yrF) 115.1 17.92 Control (10 yrM) 398.0 9.91 Control (30 yr M) 384.7 6.27 MPS lH(10mo, Patient A) 174 700 30.15 MPS lH(12mo, Patient B) 182 400 Not tested MPS 1H(14 mo, Patient C) 208 600 98.37 MPS 1H/S (8 yr, Patient D) 46 000 Not tested Idua+I+ (n = 5) 75.46 \u00C2\u00B14.99 3.77 \u00C2\u00B1 1.20 Idud1- (n = 3) 628.1 \u00C2\u00B1 163.2 79.50 \u00C2\u00B138.9 3.3.5 Antithrombin III western blot analysis. Antithrombin III (ATIII) is the principal circulating serpin, present at approximately twice the plasma concentration of HCII [16], and is known to be activated exclusively by heparan sulphate [17]. Therefore, it was expected that MPS I patients would also show elevated serum levels of ATIII-thrombin complex (ATIII-T), as confirmed in Fig. 3.6. In our small sample set, the reduced dynamic range of the ATIII-T complex in comparison to the HCII-T complex suggests its use as a biomarker may not prove as reliable. Importantly, the clear presence of ATIII-T complex in the control serum indicated that the specificity of this biomarker might not be as accurate as HCII-T for distinguishing the attenuated phenotypes and for measuring subtle changes in response to treatment. Further studies must be done to determine ATIII-T complex's utility as a biomarker. 45 v. ,>o v. >>- ^ .O 99% confidence, with proteins rank ordered from left to right based on descending Protein % Confidence score. Dashed lines indicate a two-fold increase or decrease in the average relative -/- +/+ abundance of a protein present in the Idua pools compared to the Idua mixed sex pool. Proteins marked in red were considered candidates based on significant changes in relative abundance and are listed on Table 2.. +/+ -/-Figure A2.3 shows a western blot of serum samples from WT (Idua ) and MPS (Idua ) mice for HCII. 15 ug of sample was applied per well. Figure A2.4 is a western blot of MPS patients for HCII. 2.5 ug of protein was loaded in wells 1 - 7 and 8 ng of protein was loaded in wells 8 and 9 Figure A2.5 shows HCII-T levels in MPS IH serum samples following enzyme replacement therapy, a) Hurler patient, 12 months of age at start of ERT. A l l lanes contain 2.5 ug of protein. The patient received a bone marrow transplant between 36 and 52 weeks, b) Hurler-Scheie patient, 8 years of age at start of ERT. A l l lanes contain 2.5 jag of protein. Figure A2.6 shows a western blot of MPS patient samples for ATIII. 10 ug of protein was loaded per well. DETAILED DESCRIPTION Patients diagnosed with an MPS are deficient in the ability to break down specific glycosaminoglycans into simpler sugars and amino acids. This deficiency results from insufficient production or targeting of the enzyme, or production of an inactive enzyme. A variety of heritable mutations may be involved. The MPS share many clinical features with varying degrees of severity and phenotypic effects. Table 1 lists the 10 MPS disorders, their specific enzyme deficiency and the G A G stored in the lysosome as a result of the enzyme deficiency. 106 Table A2.1: Mucopolysaccharidoses and the respective enzyme deficiency and stored glycosaminoglycan. Disorder Enzyme Deficiency Stored Material MPS I H, (Hurler) MPS I H/S, (Hurler/Scheie) MPS I S, (Scheie) alpha-L-Iduronidase Dermatan sulfate Heparan sulfate MPS II (Hunter) Iduronate sulfatase Dermatan sulfate Heparan sulfate MPS III A (Sanfilippo A) Heparan-N-sulfatase Heparan sulfate MPS III B (Sanfilippo B) N-Acetyl-alpha-glucosaminidase Heparan sulfate MPS III C (Sanfilippo C) Acetyl-CoA: alpha-glucosaminide N -acetyltransferase Heparan sulfate MPS III D (Sanfilippo D) N-Acetylglucosamine-6-sulfate sulfatase Heparan sulfate MPS IV A (Morquio) N-Acetylgalactosamines-sulfate sulfatase Keratan sulphate Chondroitin-6 sulfate MPS VI B (Morquio) Beta-Galactosidase MPS VI (Maroteaux-Lamy) Arylsulfatase B Dermatan sulfate MPS VII (Sly) Beta-Glucuronidase Dermatan sulphate Heparan sulfate 107 Definitions Any terms not directly defined herein shall be understood to have the meanings commonly associated with them as understood within the art of the invention. As employed throughout the specification, the following terms, unless otherwise indicated, shall be understood to have the following meanings. As used herein, a 'glycosaminoglycan' (GAG) is a long, unbranched polysaccharide molecule, composed of repeating disaccharide units. The first sugar residue in the repeating disaccharide is an amino sugar, such as N-acetylglucosamine or N -acetylgalactosamine, and is usually sulfated. The second sugar residue is a uronic acid, such as glucuronic or iduronic acid. Four groups of GAGs include hyaluronan, chondroitin sulfate and dermatan sulfate, heparan sulfate and heparin, and keratin sulfate. GAGs may be covalently linked to proteins in the form of proteoglycans, and are major structural components of connective tissue such as cartilage, and of the cornea of the eye. An alternate name for a glycosaminoglycan is a mucopolysaccharide. As used herein, a subject refers to an animal, such as a mammal. A subject may be a mouse, or other experimental animal such as a dog, or may refer to a human (a 'patient'). A human subject may be diagnosed with an MPS, suspected of having an MPS, or may be undiagnosed. The mouse or other experimental animal may be 'wild-type', or may be a transgenic animal. Examples of transgenic mouse models for LSDs include those described in WO 2005/080574 or US 6002067. A 'normal' or 'control', or 'unaffected' subject refers to a subject that is unaffected with an MPS. As used herein, a phenotype refers to the physical manifestation of a subject, including anatomical, metabolic and behavioural traits. Phenotype may result from heredity, or the environment of the subject, or a combination of these factors. As used herein, a mucopolysaccharidosis (MPS) refers to a subgroup of lysosomal storage disorders (LSD). MPS are characterized by the accumulation and storage of G A G within lysosomes. An MPS phenotype refers to the clinical signs or symptoms of an MPS in a subject. The clinical signs or symptoms may be varied, depending on the severity and specific MPS disorder. MPS IH (Hurler syndrome) is an autosomal recessive disorder resulting from numerous different mutations of alpha-L-idurondase. Progressive mental retardation, hepatosplenomegaly, skeletal malformations and cardiopulmonary compromises typically lead to death in the first decade. Affected individuals appear normal at birth, with the characteristic appearance and accelerated growth developing in the first year. Clinical diagnosis may be suggested in the first 2 years by, for example, hepatosplenomegaly, corneal clouding, coarse features and joint problems. Developmental delay is observed between the first and second years, with subsequent slow mental development and/or regression. Additional complications of this disorder include hearing loss, chronic respiratory infections, valvular heart disease and brain ventricular enlargement. 108 MPS IS (Scheie syndrome) and MPS IH/S (Hurler/Scheie syndrome) are less severe variants of MPS IH. MPS IS subjects may survive into late adulthood, although severe progressive skeletal disease that resembles osteoarthritis is observed. Normal intelligence is also found. MPS II (Hunter syndrome) is an X-linked recessive disorder resulting from mutations of iduronate sulfatase. Clinical manifestations of MPS II range from severe CNS and involvement of the viscera with death in late childhood, to milder forms having normal CNS function and survival into adulthood. MPS III A , B, C and D (Sanfilippo syndromes) are autosomal recessive disorders resulting from various enzyme deficiencies as noted in Table 1. Skeletal defects and hepatosplenomegaly are less pronounced than in MPS I and II, however progressive behavioural problems, mental retardation and seizures are observed. Affected subjects may survive into early to mid-adulthood. MPS IV (Morquio syndrome) is an autosomal recessive disorder characterized by deficiency in N-acetylgalactosamine-6-sulfate (type A) or beta-galactosidase deficiency (type B). Type A presents the more clinically severe skeletal disease, Extreme shortening of the trunk may occur due to vertebral collapse, and joint laxity may lead to osteoarthritis-like damage of the joints. Paralysis may also result from instability of the upper cervical spine compressing the spinal cord. Mitral valve insufficiencies may also be present. MPS VI (Maroteaux-Lamy syndrome) is an autosomal recessive disorder resulting from mutations in the arylsulfatase B gene. The general phenotype resembles MPS IH, although it may be clinically variable. Intelligence is normal and life span may last to early to mid-adulthood. Valvular disease and progressive pulmonary hypertension may be present and may be a frequent cause of death. MPS VII (Sly syndrome) is an autosomal recessive disorder resulting from mutations in the beta-glucuronidase gene. Clinical symptoms include mental retardation, short stature, skeletal dysplasia, hepatosplenomegaly. Survival into adulthood may occur in milder cases, with osteoarthritis-like joint complications common. Other examples of clinical signs or symptoms of an MPS will be known to a physician versed in the art, and may be found in, for example \"Neufeld EF and Muenzer, J. In The th metabolic and molecular basis of inherited disease 8 edition, CR Scriver et al, editors. McGraw-Hill, N Y 2005. pp 3421-3452\" As used herein, an MPS biomarker refers to a marker that is associated with the diagnosis of an MPS in a subject. The biomarker may be a protein or proteins, a complex of a protein with another molecule, such as an oligosaccharide or G A G , a genetic sequence, marker or mutation. The biomarker may be present in greater or lesser levels than in a subject unaffected with an MPS (a 'normal' subject). The biomarker may be associated 109 with the onset of the clinical phenotype of the MPS, or may be detectable before clinical onset of the MPS phenotype. As used herein, a 'gene' is an ordered sequence of nucleotides located in a particular position on a particular chromosome that encodes a specific functional product and may include untranslated and untranscribed sequences in proximity to the coding regions (5' and 3' to the coding sequence). Such non-coding sequences may contain regulatory sequences needed for transcription and translation of the sequence or introns etc. or may as yet to have any function attributed to them beyond the occurrence of the mutation of interest. A \"mutation\" as described herein may be the result of a \"single nucleotide polymorphism\" (SNP) occurring at a polymorphic site occupied by a single nucleotide, which is the site of variation between allelic sequences. A single nucleotide polymorphism may arise due to substitution of one nucleotide for another at the polymorphic site. A \"transition\" is the replacement of one purine by another purine or one pyrimidine by another pyrimidine. A \"transversion\" is the replacement of a purine by a pyrimidine or vice versa. A mutation may also arise from a deletion of one or more nucleotides or an insertion of one or more nucleotides relative to a reference sequence of a particular gene. Alternatively, a mutation may result in a frameshift of the sequence resulting from a deletion or insertion as described above or from an inversion etc. Additionally, a mutation as described herein may be a multisite mutation, whereby the mutation is comprised of two or more mutations. As used herein, a 'vector' includes any means for delivery of a nucleic acid sample to a cell. For example, a vector may include a plasmid, artificial chromosome, a virus, etc. As used herein, gene therapy refers to delivery of a vector to a cell, wherein the vector comprises a gene of interest and regulatory sequences for expression of the gene of interest. Methods of delivering the vector to the cell are known in the art, and may include, for example, direct injection, or by transfection, or infection in the case of a viral vector. Examples of viral vectors are known in the art, and may include adenovirus, adeno-associated virus, lentivirus, poxvirus, herpesvirus. As used herein, a 'serpin' is a member of the serine protease inhibitor superfamily of proteins. Serpins specifically inhibit serine proteases as part of the regulation of various metabolic pathways in living cells and whole organisms. Examples of serpins include those in the coagulation pathway, such as thrombin, antithrombin, heparin cofactor II, faxtor Xa, protease nexin I, pigment epithelium-derived factor (PEDF) and protein C inhibitor. Each serpin regulates the activity of its protease through a \"suicide\" mechanism by which the protease initiates proteolysis of the serpin but cannot complete the reaction process, thereby forming a covalent association between the two proteins (Gettins, PG. Serpin structure, mechanism and function Chem Rev. 102:4751-4804). This complex formation is essentially irreversible and causes a dramatic structural change in the protease leading to its inactivity. The HCII-T complex is subsequently recognized by specific receptors and degraded in the liver. 110 As used herein, a 'sample' or a 'tissue sample' refer to a small quantity of tissue or body fluid from a subject affected, suspected of being affected or unaffected with an MPS disorder. Samples may be obtained by curettage, needle aspiration biopsy or needle (core) biopsy, incisional biopsy for sampling of tissue at a specific site, or by excisional biopsy. Samples may include cells, blood, serum, muscle, bone, neurological tissue, saliva, urine, mucus or other sample acquired in biopsy. Samples such as blood, saliva, urine, mucus, etc may be collected using methods known in the art. Glycosaminoglycan degradation The deficient enzymes in the various MPS (Table 1) are part of a highly ordered degradation pathway for GAGs. Generally, the long chain G A G is cleaved into smaller fragments by endoglucuronidases or endohexosaminidases, and the individual monosaccharides subsequently removed by specific enzymes. It is these specific enzymes that are deficient in the various MPS. Details of the pathways for degradation of specific GAGs, including the enzymes involved at each step and the substrates of each may be found in, for example, \"Essentials of Glycobiology, A. Varki, R. Cummings, et al., eds. 1999. Cold Spring harbor Laboratory Press, Cold Spring Harbor, N Y . Diagnosis of MPS Clinical phenotypes of MPS are not usually evident at birth, but may appear within a few months of birth, or as late as several years of age. During infancy and childhood, physical and mental development may be affected or delayed. Clinical symptoms such as short stature, bony dysplasia, hirsutism may be observed, as well as more characteristic facies of the MPS disorders, such as thick lips, open mouth or flattened nasal bridge. Depending on the specific MPS, mental retardation may also be present. The specific clinical phenotype of each specific MPS will be known to a physician versed in the art, and may th be found in, for example \"The Merck Manual of Diagnosis and Therapy\" 17 edition. M H Beers and R Berkow, editors. 1999-2005, Merck & Co. \"Neufeld EF and Muenzer, J. th In The metabolic and molecular basis of inherited disease 8 edition, CR Scriver et al, editors. McGraw-Hill, N Y 2001. pp 3421-3452. With the exception of MPS II, which is X-linked, all the MPS disorders are autosomal recessive. A wide variety of mutations, including point mutations, insertions, deletions and polymorphisms are observed and affected individuals may be heterozygous for their specific mutations - each parent contributing a different defective copy of the gene. Some correlation exists between the severity of the MPS and the specific mutation, but this may not be practical for widespread use as a diagnostic, given the heterogeneous genetic makeup of the affected population. Diagnosis of specific MPS may be made using a combination of observed clinical phenotype, urinary analysis for GAGs and enzyme assays. For example, MPS I results from a deficiency of the enzyme a-L-iduronidase (IDUA; EC 3.2.1.76) (Neufeld supra). IDUA deficiency results in abnormalities in the degradation of the glycosaminoglycans 111 (GAGs) heparan sulphate and dermatan sulphate, which subsequently accumulate in the lysosome. Severity of the disorder is estimated subjectively, based on clinical phenotype. Therapies for M P S Few treatment options exist for subjects affected with MPS. Supportive therapy and/or palliative care may be offered largely to improve quality of life of the subject. With each MPS disorder, supportive management of the clinical manifestations is provided. For example, patients presenting with chronic respiratory complications would be treated for the frequent infections and congestion of the chest and airway, but the underlying cause (the buildup of the G A G in the lysosome) cannot be addressed in this manner. Bone marrow transplantation is a therapeutic option for some MPS subjects, although the efficacy of this procedure varies with the severity of the disease. Enzyme replacement therapy has been shown to be a useful therapeutic approach in some MPS subjects. For example, in MPS I affected subjects, clinical studies have demonstrated that administration of recombinant alpha-L-iduronidase (ALDURAZYME\u00E2\u0084\u00A2; U.S. Patent No. 6426208) can alter the phenotype of MPS I patients to varying degrees (Wraith JE et al., 2004. Enzyme replacement therapy for mucopolysaccharidosis J: a randomized, double-blinded placebo-controlled, multinational study of recombinant human alpha-L-iduronidase (laronidase) J. Pediatr. 144: 581-588). Success of the therapeutic approach may be estimated subjectively, based on clinical phenotype. Monitoring of disease progress or therapeutic efficacy The progress of MPS may be monitored by the alterations in clinical phenotypes. Analysis of urinary GAGs may provide some guidance, but does not correlate specifically with disease severity. One embodiment of the present invention provides for the use of a serpin biomarker to monitor disease severity. Serpins may be regulated by GAGs, which accelerate the interaction between serpins and their target coagulation proteases. Examples of such serpins may be found in Table 2. Serum levels of heparin cofactor II-thrombin (HCII-T) complex in MPS I patients are elevated well beyond that seen in control serum samples and provide a biomarker of MPS disease. Table A 2 . 2 : Examples of serpins with GAG-mediated activities. GAGs that Known target Tissue Biological Serpin modulate activity proteases specificity function 112 di-antitrypsin (aiAT, aiPI, SERPINA1) HS, DS Neutrophil elastase, Plasmin, Thrombin Plasma General inhibitor, inflammation [17,38,39] Thrombin, activated Protein C, Urinary Protein C inhibitor (PAI-3, SERPINA5) HS plasminogen activator, Tissue plasminogen activator, Plasma kallikrein, Acrosin Plasma Coagulation [17] Antithrombin III (ATIII, SEPvPINCl) HS Thrombin, Factor IXa, Factor Xa Plasma, extravascular space Coagulation [17] Heparin cofactor II (HCII, SERPIND1) HS, DS Thrombin, Cathepsin G, Chymotrypsin Plasma, extravascular space Coagulation, unknown [17] Thrombin, Acrosin, Glia-derived nexin (PN 1, SERPINE2) HS Urinary plasminogen activator, Tissue plasminogen activator, Fibroblasts, neurons, extracellular space Neurotrophic, E C M remodelling [17,34,35] 113 Factor XIa Pigment epithelium-derived factor (PEDF, SERPINF1) HS N / A Cornea, cartilage, bone Neurotrophic, antiangiogenic [17,36] 1. Methods Sample Collection Mouse serum samples were collected by cardiac puncture and added to Beckton Dickinson serum separator tubes (Franklin Lakes, NJ). Samples were allowed to clot for 30 minutes at room temperature and centrifuged for 15 minutes at 3000xg at room temperature. Samples were aliquoted immediately and stored at -80\u00C2\u00B0C. Mouse plasma samples were collected by cardiac puncture, with sodium citrate added to 0.4%. Citrated samples were centrifuged for 15 minutes at 1500xg at 4\u00C2\u00B0C. Human plasma and serum samples were collected by clean venipuncture using a 2 syringe technique, as described by Petzer (Petzer H et al 1988. Determination of human thrombin-antithrombin III complex in plasma with an enzyme linked immunosorbent assay. Thromb. Haemos. 59:101-106), and processed as above. High Abundance Protein Depletion Albumin, immunoglobulin, and transferrin were depleted from murine serum samples using a 100 mm Ms-3 Multiple Affinity Removal System (Agilent Technologies, Palo Alto, CA), according to the manufacturer's instructions. 4 age- and sex-matched pools of mouse serum samples were normalized for total protein to 12 mg/mL by diluting them in running buffer (Agilent Technologies). Each pool contained 6 independent serum samples. A K D Scientific syringe pump (Holliston, M A ) was used to maintain a constant flow rate of 15 mL/h. 320 uL were subsequently used for high abundance protein depletion with identical pool collections obtained for all samples. iTRAQ Analysis iTRAQ reagent labelling The depleted mouse serum samples were labelled with the iTRAQ reagent following the manufacturer's protocol (Applied Biosystems, Foster City, CA). Briefly, 100 ug of total protein from each of the 4 depleted serum pools was precipitated with acetone and resuspended in iTRAQ dissolution buffer for reduction, alkylation, and tryptic digestion. Each of the resulting peptide pools was then labelled with a different isotopic iTRAQ +/+ -/-Reagent (114-117 Da) as follows: Idua mixed sex pool (114 Da), Idua male pool (115 114 +/+ -/-Da), Idua male pool (116 Da) and Idua mixed sex pool (117 Da). The four differentially labelled pools were then combined and subjected to strong cation exchange (SCX) chromatography using a polysulfoethyl A column (Poly LC, Columbia, MD). The combined sample was diluted in 10 mM K P 0 4 (pH 2.7), 25% A C N , applied to the column and peptides eluted over a 33 minute gradient to 35% lOmM K H 2 P 0 4 , 25% C A N , 0.5 M KC1 with fractions collected at one minute intervals. LC-MS/MS Analysis The resulting 33 SCX fractions were then subjected to LC-MS/MS analysis utilizing a QStar Pulsar hybrid quadrupole-TOF instrument (Applied Biosystems) and an UltiMate micro HPLC (LC Packings, Sunnyvale, CA). The HPLC was equipped with a C18 PepMap guard column (LC Packings) separated from a C18 Pepmap Nano LC column (LC Packings) by a switching valve to allow for precolumn sample clean-up before switching inline for reversed phase chromatography and MS/MS analysis. Each SCX fraction was evaporated to dryness, resuspended in 5% A C N and 3% formic acid, and 25%> of the sample was injected onto the C18 guard column in 98% water/acetonitrile (98:2), 0.05%) formic acid (Buffer A) with the HPLC flowing to waste to remove sample contaminants. Following 10 minutes at 100 ul/ml, the guard column was switched inline with the C18 resolving column and mass spectrometer, and the peptides were eluted with a linear gradient to 60% water/acetonitrile (2:98), 0.05% formic acid (Buffer B) over 40 minutes. Following a 5 minute ramp to 80% Buffer B, the column was re-equilibrated in 98%o buffer A for 15 minutes prior to the injection of the next SCX fraction. Data Acquisition and Analysis MS data was acquired automatically using Analyst QS 1.0 software Service Pack 8 (ABI MDS SCIEX, Concord, Canada). An information-dependent acquisition method consisting of a 1 second TOFMS survey scan of mass range 400-1200 atomic mass units and two 2.5 second product ion scans of mass range 100 - 1500 atomic mass units was utilized. The two most intense peaks over 20 counts, with charge state 2 - 5 were selected for fragmentation and a 6 amu window was used to prevent the peaks from the same isotopic cluster from being fragmented again. Once an ion was selected for MS/MS fragmentation it was put onto an exclusion list for 180 seconds. Following the initial data acquisition run (iTRAQ acquisition A), an exclusion list was created for all peptides identified with a confidence of 95 % or greater in each of the SCX fractions. A second injection of each SCX fraction using the exclusion list for that fraction and the same L C and MS conditions as the first run was then performed in order to detect the lower concentration proteins present in plasma. (iTRAQ acquisition B). The resulting data files were combined and processed using the Interrogator\u00E2\u0084\u00A2 algorithm in the ProQuant software (vl.0) (Applied Biosystems) in Analyst using the following parameters: The MS and MS/MS mass tolerances were set to 0.20. A rodent subset of the Celera Discovery Systems Database (01/24/2004) was used for searching. Methyl methanethiosulphonate (MMTS) modification of cysteines was used as a fixed 115 modification. The number of missed cleavages was set to 1. A l l results were written to a Microsoft Access database and, to reduce redundancy, ProGroup Viewer version 1.0.5 (Applied Biosystems) was used to assemble and report the data. Protein % Confidence Scores, which are influenced by the closeness of the observed peptide spectrum to the predicted spectrum, the number of peptides identified for a given protein, as well as the variance of abundance of each peptide for the given protein, were used to calculate a Protein Score using the equation Protein Score = -log[l - (Protein % Confidence)/100]. Abundances of each identified protein in the sample pools were calculated based on the abundance of reporter tags bound to the peptide tryptic fragments for each pool. Where more than one peptide was identified for a protein, the abundance was calculated by weighted averaging of the abundance of the individual peptides including a 95% confidence interval. Protein abundances were adjusted for global labeling bias by a correction factor that assumed an average relative protein abundance of 1 across all samples. Relative abundances are determined by dividing the abundance of each protein from each pool by the corresponding protein in another pool. A l l proteins found to have significantly altered relative abundances were manually verified by inspecting the corresponding peptide matches. Western Blotting Western blot analysis was performed on 7.5% Tris-glycine gels and transferred to Pall (East Hills, NY) BioTrace NT membranes. Anti-human HCII and anti-human antithrombin III antibodies were from Affinity Biologicals (Hamilton, ON). Membranes were blocked with 5% Carnation powdered skim milk, 0.05% PBS-T overnight at 4\u00C2\u00B0C. Western blot analysis of human samples used primary antibody at a concentration of 1 ug/mL, with secondary antibody at a concentration of 1.3 ug/mL. Western blot analysis of mouse samples used 3 ug/mL primary antibody, and 1.3 ug/mL secondary antibody. Antibody incubations were performed for 60 minutes at room temperature. Proteins were detected with West Pico detection kits (Pierce, Rockford, IL) according to the manufacturer's instructions. E L I S A HCII-T ELISA kits were obtained from Affinity Biologicals (Hamilton, ON)\" and used according to the manufacturer's instructions. This kit uses polyclonal sheep anti-human thrombin antibody for capture and peroxidase-conjugated polyclonal goat anti-human HCII antibody for detection. Standards were derived from purified human HCII and thrombin (Enzyme Research Laboratories, South Bend, IN) reacted in the presence of 0.05 U/mL heparin (Sigma, St. Louis, MO). MPS IH serum samples were diluted 500-fold and MPS IH/S samples were diluted 100-fold in factor Il-depleted plasma (Affinity Biologicals) while control samples were undiluted. A l l standards and samples were tested in triplicate. 2. Examples 116 Example 1 iTRAQ serum proteomic studies Serum samples from normal and idua -I- mice were depleted of albumin, immunoglobulin, and transferrin using a 100 mm Ms-3 Multiple Affinity Removal System (Agilent Technologies, Palo Alto, CA) according to the manufacturer's +/+ +/+ instructions. 4 age- and sex-matched pools (Idua mixed sex pool, Idua male pool, Idua mixed sex pool and Idua male pool) of mouse serum samples from 6 animals were normalized for total protein to 12 mg/mL by diluting them in running buffer (Agilent Technologies). 320 uL were subsequently used for high abundance protein depletion with identical pool collections obtained for all samples. Pools were labeled with different isotopic iTRAQ reagents as described supra, and analyzed by LC-MS/MS analysis as described supra. Using a 94% Protein Confidence score cut-off applied to data observed over two cumulative MS/MS acquisitions, iTRAQ analysis resulted in the identification of 1701 distinct peptides belonging to 198 unique proteins (Table 3). 181 proteins were identified on the strength of two or more peptides, the majority of which were represented by at least 5 peptides (Table 4). This weighting toward 5+ peptides per protein is likely due to the dynamic range of protein concentrations in serum, where more abundant proteins can be expected to be identified by several peptides. The second MS/MS data acquisition resulted in a 30% increase in the total number of serum proteins identified. Table A2.3: iTRAQ Summary Data iTRAQ Acquisition A iTRAQ Acquisition A+B Protein Confidence Level, % 94 95 99 94 95 99 # of Peptides 1132 1131 1048 1701 1686 1577 # of Proteins 151 150 114 198 195 150 Table A2.4: Number of unique peptides per protein in iTRAQ data collection, 94% Protein Confidence. Number of Peptides/Protein Total # of Proteins 1 2 3 4 5+ iTRAQ Acquisition A 22 17 11 10 91 151 iTRAQ Acquisition A+B 17 21 30 16 114 198 117 To investigate intersample variation, we compared the relative abundances observed in +/+ +/+ ./-the Idua male pool to the Idua mixed sex pool as well as the Idua male pool to the Idua mixed sex pool at a 99% Protein Confidence level (Fig. 1). The vast majority of proteins show no significant change in expression levels between like pools, with the exception of one outlier. The possibility of a sex-specific expression difference observed +/+ +/+ in the outlier (~16-fold decreased) in the Idua Ma\e:Idua Mixed sex comparison is -/-eliminated by the absence of such a difference in the Idua pools comparison and the decreased relative abundance of this protein (alpha- 1-B glycoprotein) was assumed to be +/+ an artifactual in the Idua mixed sex control pool. Comparison of the average protein relative abundances of the two Idua pools with the +/+ Idua mixed sex pool reveals the variation between mutant and control pools is similar to that observed between like pools; however, a few proteins showed more extreme abundance differences (Fig. 1). This suggests there is minimal variation in protein quantities between the MPS and normal serum proteomes, with no single protein present at a dramatically different level. In order to select a panel of proteins to be investigated as candidate biomarkers with -/-significantly altered relative abundances in the Idua serum proteome, the relative -/-abundances of each protein in the two Idua pools were averaged then tested for two factors. First, we determined which proteins showed average relative abundances +/+ exceeding the 95% confidence intervals of the same proteins' abundances in the Idua male pool. Second, proteins that also showed average relative abundances with confidence intervals not overlapping 0.00 (on a logarithmic scale) were considered strong +/+ candidates. The Idua mixed sex pool was used as the denominator pool for both analyses. Combining these criteria selected proteins exceeding the natural variability of proteins in both the MPS and WT animals, regardless of the absolute value of the change. Candidate biomarkers selected by these criteria are indicated as red spots in Fig. 2 and listed in Table 5. Candidate proteins with the most extreme deviation from the normal state were fibrinogen gamma (4.96-fold increased), fibrinogen alpha (2.20-fold increased), and heparin cofactor II (1.79-fold decreased). Elevated fibrinogen in mutant serum samples suggests impaired thrombin activity during clotting to form serum. 5 of the 17 proteins identified by iTRAQ with modified abundance in MPS I mice are serine protease inhibitors (Table 5). Table A2.5: Proteins with significantly altered relative abundance in the MPS mouse serum, Idua mixed sex denominator. GenBank Protein % Log2 of Fold Biological Accession Confidence Protein Average Increase/ Function Number Score Rank Relative Decrease 118 Abundance AAH19506 95 Fibrinogen, gamma polypeptide 2.310 +4.96 Blood clotting AAH05467 71 Fibrinogen, alpha polypeptide 1.137 +2.20 Blood clotting AAC28866 87 Alpha-1-anti trypsin 1-5 0.636 + 1.55 Serine protease inhibitor Inter-alpha trypsin inhibitor, heavy chain 1 Serine AAH13465 56 0.480 + 1.40 protease inhibitor AAA37246 5 Apolipoprotein B 0.347 + 1.27 Lipid and fatty acid transport Serine AAH57983 2 Pzp protein 0.154 + 1.11 protease inhibitor AAH23143 29 Gelsolin -0.144 -1.11 Cytoskeletal protein Protein BAA19743 26 Kininogen precursor -0.281 -1.22 metabolism and modification BAB33095 31 Histidine-rich glycoprotein -0.309 -1.24 Biological process unclassified AAC28865 23 Alpha-1 proteinase -0.377 -1.30 Serine protease 119 inhibitor 2 inhibitor AAH21776 102 Apolipoprotein C-III -0.386 -1.31 Lipid metabolism AAH30166 90 Factor XIII beta -0.395 -1.31 Blood clotting AAH12706 64 Paraoxonase 1 -0.414 -1.33 Peroxidase AAH34543 78 Heparin cofactor II -0.840 -1.79 Serine protease inhibitor Example 2 Heparin Cofactor II western blot analysis in MPS I mice and humans To investigate the HCII reduction in the serum of Idua mice, western blot analysis was used utilizing goat anti-human HCII antibodies (Fig. 3). Surprisingly, the marked reduction in native HCII levels was associated with the presence of a higher molecular weight protein only in the mutant animals' sera, consistent with the published size of the HCII-thrombin (HCII-T) complex (Tollefsen D M et al, 1982. Heparin cofactor II. Purification and properties of a heparin-dependent inhibitor of thrombin in human plasma, J. Biol. Chem. 257:2162-2169). Antibodies directed to thrombin confirmed that this was indeed HCII-thrombin complex. Fig. 4 shows the elevation of serum HCII-T complex in serum samples from both severe and attenuated human cases of MPS I compared to that of controls. Interestingly, the largest amounts of HCII-T complex are seen in the MPS IH patients in comparison to the MPS IH/S patient. Western analysis -/-revealed no detectable HCII-T in plasma samples of Idua or WT mice, nor in plasma samples from humans. Example 3 Heparin Cofactor II western blot analysis in treated MPS I patients Figure 5a-b shows the level of HCII-T in a Hurler patient receiving enzyme replacement therapy (ERT) preceding and following bone marrow transplantation (BMT), and one Hurler-Scheie patient undergoing ERT only. Enzyme treatment in the Hurler patient (Fig. 5a) did not normalize HCII-T levels, but significantly reduced the amount of HCII-T levels to that seen in the attenuated patient studied. Further reduction in HCII-T occurred following bone marrow transplantation. Although well engrafted by week 52, this patient subsequently died of pulmonary hemorrhage. The Hurler-Scheie patient, Fig. 5b, showed marked reduction of HCII-T early during ERT exposure but then subsequently developed detectable HCII-T complex later during treatment. 120 Example 4 HCII-T E L I S A analysis Table 6 illustrates the dramatic elevation of HCII-T in the serum of MPS IH and MPS IH/S patients as well as murine MPS I samples in comparison to controls. MPS IH patients' serum HCII-T complex levels ranged from 174,700 - 208,600 pM, with an average value of 188,600 pM, representing a 630-fold increase relative to controls. The serum sample from a MPS IH/S patient had a HCII-T concentration of 46,000 pM (154-fold increase), reflective of the patient's attenuated phenotype. In contrast to the lack of detectable complex by western blot, ELISA revealed that plasma HCII-T levels were increased in MPS patients and the MPS I mouse, with the minimum concentration of HCII-T complex in MPS IH patients exceeding the maximum control value by 68%. Table A2.6: HCII-T E L I S A . Sample (age in brackets) Serum [HCII-T] (pM \u00C2\u00B1 SD) Plasma [HCII-T] (pM \u00C2\u00B1 SD) Control (10 yr F) 115.1 17.92 Control (10 yr M) 398.0 9.91 Control (30 yr M) 384.7 6.27 MPS lH(10mo, Patient A) 174 700 30.15 MPS lH(12mo, Patient B) 182 400 Not tested MPS lH(14mo, Patient C) 208 600 98.37 MPS IH/S (8 yr, Patient D) 46 000 Not tested Idua+/+ (n = 5) 75.46 \u00C2\u00B1 4.99 3.77 \u00C2\u00B1 1.20 Idua'' (n = 3) 628.1 \u00C2\u00B1 163.2 79.50 \u00C2\u00B138.9 Significantly decreased levels of the serine protease inhibitor (serpin), heparin cofactor II (HCII) is present in MPS-affected animals. Although native HCII levels are reduced, there is marked HCII-thrombin (HCII-T) complex elevation in MPS-affected animals. Translation of these findings to humans with MPS I show equivalent findings. Importantly, in humans the elevation of HCII-T complex appears to be correlated to disease severity and is responsive to treatment. GAGs play a major role in MPS pathophysiology, and a large body of literature exists for GAG-modulated serpin activity. These results indicate that HCII-T is an excellent biomarker for MPS I and represents a novel finding that may implicate other G A G modulated serpins in the pathophysiology of MPS diseases. 121 In addition, the level of HCII-T complex correlates with the clinical measures of disease severity as well as responsiveness to therapy. Further, patients undergoing E R T and/or B M T maintain residual amounts of serum HCII-T. Example 5 Antithrombin III western blot analysis. Antithrombin III (ATIII) is the principle circulating serpin, present at approximately twice the plasma concentration of HCII , and is known to be activated exclusively by heparan sulphate. Elevated serum levels of antithrombin III-thrombin complex (ATIII-T) is also found in serum samples from M P S I patients. (Fig. 6). The reduced dynamic range of the ATIII-T complex in comparison to the HCII-T complex suggests its use as a biomarker is not as reliable, because the clear presence of ATIII-T complex in the control serum indicates the specificity of this biomarker may not be as accurate as HCII-T for distinguishing the attenuated phenotypes and for measuring treatment efficacy. C L A I M S : We claim: 1. A method of diagnosing an M P S , the method comprising: obtaining a tissue sample from a subject and determining the quantity of a biomarker of an M P S present in a tissue sample. A B S T R A C T A method of diagnosing, monitoring or screening for an M P S disorder in an individual affected, or suspected of being affected by an M P S . Biomarkers correlating with severity of M P S , and methods of detecting these biomarkers are disclosed. Examples of biomarkers include heparan cofactor II and antithrombin III. 122 4 +/+ Male: -/- Male: -/- Average: +/+ Mixed sex -/- Mixed sex +/+ Mixed sex Fig. A2.1: Box plots of relative abundances for proteins identified with 99% confidence. 123 3 -3 Protein % Confidence Score Rank Fig. A2.2: Logarithmic plot of average relative abundance of proteins in Idua'1' pools vs. Idua*l+ mixed sex, >99% confidence, with proteins rank ordered from left to right based on descending Protein % Confidence score. 124 +/+ +/+ +/+ +/+ \u00C2\u00AB\u00E2\u0080\u0094HCII-T \u00C2\u00AB\u00E2\u0080\u0094HCII Fig. A2.3: Western blot of serum samples from WT (Idua+/+) and MPS (Idua'1') mice for HCII . 125 Plasma Serum Fig. A2.4: Western blot of MPS patients for HCII . 126 fi> \u00C2\u00A3 & ^ # 3^ \u00E2\u0080\u00A2HCII-T \u00E2\u0080\u00A2HCII Fig. A2.5: HCII-T levels in MPS I H serum samples following enzyme replacement therapy. 127 Co # # # # -ATIII-T ATIII I Plasma Serum Fig. A2.6: Western blot of MPS patient samples for ATIII. 128 "@en . "Thesis/Dissertation"@en . "2006-05"@en . "10.14288/1.0092570"@en . "eng"@en . "Medical Genetics"@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 . "Identification of a serum biomarker for mucopolysaccharidosis I"@en . "Text"@en . "http://hdl.handle.net/2429/17747"@en .