Biomarkers in Osteoarthritis Ali Mobasheri

Transcription

1 Biomarkers in Osteoarthritis, D.Phil. (Oxon) Musculoskeletal Research Group School of Veterinary Medicine and Science Faculty of Medicine and Health Sciences 1 Aim and scope The aim of this presentation is to: Provide an overview of current research on osteoarthritis (OA) biomarkers Highlight the lack of analytical tools and reagents in our toolbox Discuss the limitations of currently available biomarkers Explore future opportunities and identify key areas that are relevant to the pharmaceutical product pipeline 2 Overview of presentation Summary of the definitions of OA and biomarkers of OA Need for a better gold standard : Radiography is inadequate Recent developments in biomarker definition and classification Wet and dry biomarkers Post-genomic approaches for identification of new OA biomarkers aimed at early (pre-radiographic) identification of disease The advent of combination biomarkers 3 1

2 Background and context 4 Osteoarthritis (OA) Most common form of arthritis in humans and companion animals Major cause of pain, inflammation and loss of mobility 5 Osteoarthritis (OA) (2) Characterised by progressive deterioration and loss of articular cartilage Affects load-bearing synovial joints Associated with ageing and excessive or abnormal joint loading 6 2

3 Osteoarthritis (OA) (3) Synovium Synovial fluid Cartilage Subchondral bone Other features: Synovial inflammation Subchondral bone sclerosis Osteophyte development (formation of bony outgrowths) 7 Age Joint trauma Joint instability Genetics (breed in animals) Obesity Metabolic/endocrine disease Risk factors for OA 8 Obesity and OA Strong evidence supports a link between obesity and OA Obesity is a complex metabolic and inflammatory syndrome Adipokines, (adipocytokines) play important roles in the onset of disease Lifestyle changes for OA patients: Weight loss and calorie restriction Gabay, Hall, Berenbaum, Henrotin and Sanchez (2008) Joint Bone Spine 75, Abramson and Attur (2009) Arthritis Res Ther 11, 227 Iannone and Lapadula (2010) Curr Drug Targets 11,

4 General features of OA 10 Synovial space (joint space narrowing) as assessed by radiography Cartilage anabolism and impaired cartilage repair Synovial inflammation and hyperplasia Proteolytic activity (collagenases, gelatinases) Cartilage degeneration Loss of homeostasis leads to osteoarthritis Quiescence Synthesis Phenotypic Modulation Activation Degradation Articular cartilage Trauma Inflammation Genetic defects Aging Articular cartilage Calcified cartilage Subchondral trabecular bone Tidemark duplication Subchondral cortical bone 11 Slide courtesy of Dr. Mary Goldring, Hospital for Special Surgery, New York Vascular invasion The cytokine balance is perturbed in osteoarthritis IL-17 IL-1 IL-18 TNF-a anti-tnf therapy for RA LIF OSM IL-6 IL-8 IL-1ra stnfr IL-4 IL-10 IL-13 IGF-I BMPs FGFs PGE2 Cartilage matrix synthesis Cartilage matrix degradation 12 Modified from MB Goldring, Kelley s Textbook of Rheumatology, 8th Edition 4

5 13 Goldring MB, Goldring SR. J Cell Physiol 2007; 213: Synovial, chondral and subchondral changes in OA 14 Biomarker: definition A biomarker is a characteristic that is objectively measured and evaluated as an indicator of normal biologic processes, pathogenic processes, or pharmacologic responses to a therapeutic intervention 15 5

6 Rationale for the identification and development of osteoarthritis biomarkers Why do we need new OA biomarkers? 16 The gold standard (radiography) is inadequate 17 A better gold standard OA is often diagnosed radiographically when the clinical signs of pain and loss of mobility have already appeared Unfortunately by this stage the disease has progressed extensively and cartilage degradation is significant We need better methods and assays to predict OA progression and responses to therapy 18 6

7 Limitations of radiography Indirect measure of alterations in articular cartilage Fails to measure a dynamic process Changes overtime are small, and occur in only a subset (progressors) of patients Poor reproducibility Poor correlation with joint function and pain Numerous other confounders 19 Rationale for identifying early osteoarthritis biomarkers Early detection will facilitate earlier diagnosis and treatment because OA which is characterised by a prolonged pre-clinical molecular phase, a pre-radiographic phase, and a recalcitrant radiographic phase by which time there are extensive structural changes to joints along with pain and loss of function 20 Osteoarthritis and Cartilage 19(2011) Biomarkers could provide an early warning of joint degeneration which could prompt earlier, more targeted treatment Classification of OA biomarkers: BIPEDs Burden of Disease, Investigative, Prognostic, Efficacy of Intervention, Diagnostic, and Safety Safety 21 7

8 Osteoarthritis biomarkers network classification (Bauer et al., 2006) BURDEN OF DISEASE MARKER Biomarker associated with extent or severity of disease INVESTIGATIVE MARKER Biomarkers not yet meeting criteria for another category PROGNOSTIC MARKER Predict onset or progression EFFICACY OF INTERVENTION MARKER Indicative or predictive of treatment efficacy DIAGNOSTIC MARKER Differentiates diseased from non-diseased SAFETY BIOMARKERS 22 Reflect tissue and/or organ toxicity of a agent or intervention Classification of OA biomarkers and the OA biomarkers working group The Osteoarthritis Research Society International (OARSI) and the US Food and Drug Administration (FDA) have recently established the OARSI FDA Osteoarthritis Biomarkers Working Group 23 Classification of OA biomarkers The OARSI FDA Osteoarthritis Biomarkers Working Group has divided OA biomarkers into two major groups: Soluble or wet biomarkers The dry biomarkers 24 Soluble or «wet» biomarkers RNA, DNA Biochemicals Proteins Protein Fragments Peptides Metabolites Slide courtesy of Prof. Yves Henrotin, Université de Liège «Dry» biomarkers MRI X-ray Ultrasound Imaging, Questionnaire, VAS WOMAC Lequesne 8

9 The diagnostic and prognostic relevance of biomarkers for clinicians and patients Biomarkers have the capacity to detect early cartilage degradation in OA They can provide useful diagnostic information by: Reflecting disease relevant biological activity in the joint Predicting the course of disease progression 25 The relevance of biomarkers to the pharmaceutical product pipeline Biomarkers can serve as surrogate endpoints in the drug discovery process 26 The drug pipeline Drug discovery is protracted, risky and costly 27 9

10 Challenges facing the drug pipeline Convoluted not linear Leaky high levels of attrition Highly susceptible to the recession 28 Currently empty The OA drug pipeline Nothing new to offer patients and the OA research community 29 Surrogate OA biomarkers facilitate the drug discovery process Linking a biomarker to a clinical endpoint facilitates the drug discovery process Qualification is a process applied to a particular biomarker to support its use as a surrogate endpoint in: Drug discovery and development Post approval Regulatory decision making 30 10

11 Quantifiable decision points go/no-go decisions Use in translational medicine bridging information Early identification of responders & non-responders Early quantification of first clinical efficacy Identification of those in need of treatment Selection of patients most likely to respond Dose determination Phase II Safety and efficacy cost/benefit ratio Differentiating compounds from competitors Drug repositioning Monitoring of patients compliance Personalised health care (PHC) Pharmacovigilance 31 Applying the biochemical marker toolbox in drug discovery and development Slide courtesy of Dr. Anne-Christine Bay-Jensen, Nordic Bioscience Company The biomarker pipeline Biomarker Discovery Verification Qualification * Assay Development and Optimization Independent scientific and analytical verification of the biomarker this process involves verification of the analytical performance characteristics and clinical correlation of a biomarker with a biological process or clinical outcome * Linking a biomarker to a clinical endpoint Qualification is a process applied to a particular biomarker to support its use as a surrogate endpoint in drug discovery, development or post approval and, where appropriate, 32 in regulatory decision making Assessing all technical aspects of the biomarker assay Validation Commercialization Major classes of OA biomarkers Collagenous biomarkers Fragments of collagens (particularly type II collagen) Non-collagenous biomarkers Cartilage Oligomeric Matrix Protein (COMP) Hyaluronic acid (HA) Others: YKL-40 - chitinase 3-like 1 glycoprotein 33 11

12 34 Soluble OA biomarkers Biomarker Process Tissues of origin BIPED Classification uctx II Catabolism of type II collagen Mineralized and mineralized Knee: B, P, E, D and osteophyte burden cartilage, growth plate Hip: B, P, D cartilage, bone s/u Coll2 1 Type II collagen cleavage Cartilage Knee: D, B, P Hip: D, s/u Coll2 1NO2 Type II collagen cleavage and nitration Cartilage Knee: D, B, P Hip: D s/uc2c Type II collagen cleavage Cartilage Knee: E, D Hip: B s/uc1,2c Type I and II collagens cleavage Cartilage, bone, synovium Knee: D Hip: none scpii or PIICP Type II collagen synthesis Cartilage Knee: D Hip: B spiianp Type IIA collagen synthesis Cartilage Knee: B, P, D scomp Cartilage metabolism and osteophyte burden Cartilage, tendon, meniscus, Knee: B, P, D synovium, osteoblasts, arterial Hip: B, P, D wall Knee: B, P, E, D and ubiquitous in body Hip: P sha Osteophyte burden, synovitis Cartilage, meniscus, synovium sks Catabolic, aggrecan Cartilage Knee: B, P, E, D Hip: none scs 846 Anabolic, aggrecan Cartilage Knee: P sykl 40 Catabolic Macrophage, cartilage, synovial, cells of epithelial origin. Knee: B, E Hip: D BIPED biomarkers classification KNEE HIP uctx-ii sha, sks BPED spiianp, s/u Coll2-1NO2, scomp, s/u Coll2-1 BPD scomp, uctx-ii s/uc2c, utiine, sykl-40, uglc-gal-pyd BP or BD or ED sha, s/uc1,2c, scpii, s/u Coll2-1, s/uc1,2c, scpii, scs-846, MMP-3, MMP-13 s/u Coll2-1NO2,s/uC2C, sykl-40 B or P or E or D 35 The majority of biochemical markers has been investigated in knee OA Classification of cartilage biomarkers according to tissue of origin Cartilage Growth plate cartilage Bone Meniscus Tendon Synovium Coll2-1, Coll2-1NO2, CPII, TIINE, PIIANP, C2C, C1, 2C, CTX-II, HA, KS, CS-846, COMP, YKL-40 CTX-II, C1,2C CTX-II, COMP, C1,2C, NTX-I, CTX-I, PYD, DPD, OC COMP, HA, C1, 2C COMP COMP, HA, C1,2C, YKL-40, Glc-Gal-PYD 36 The majority of OA biomarkers originate from cartilage but some biomarkers are found in other connective tissues 12

13 Not all biomarkers are indicators of cartilage catabolism Cartilage catabolism Cartilage anabolism Osteophyte burden Synovitis/catabolism Bone turnover Coll2-1, Coll2-1NO2, CTX-II, COMP, C2C, C1,2C, TIINE, KS, CS-846, YKL-40 CPII, PIIANP CTX-II, COMP, HA HA, Glc-Gal-PYD, PIIINP NTX-1, CTX-I, PICP, PINP, PYD, DPD, OC, ICTP 37 The majority of OA biomarkers originate from cartilage but some biomarkers are found in other connective tissues The matrisome The full complement of ECM proteins The core matrisome comprises ~ 300 proteins in addition to ECM modifying enzymes, ECM-binding growth factors, and other ECM-associated proteins 38 Cold SpringHarb Perspect Biol 2012; 4: a Biomarkers originate from different synovial tissues and cells 39 13

14 Proteomic strategies to identify OA biomarkers 40 ECM proteins J 41 Proteomics 2012 Proteins involved in inflammation and the immune response J Proteome Res 2011 Nov 4; 10(11): COMP, Lumican, Tetranectin Complement proteins (alternative pathway) 14

15 Complement proteins as membrane biomarkers of OA The membrane attack complex (MAC) component of complement has been implicated in the pathogenesis of OA 43 Complement components are aberrantly expressed in OA 44 Nature Medicine 17, (2011) doi: /nm.2543 Lack of specificity Tissue Pathology Affected joints Current barriers to biomarkers achieving their full potential Lack of disease modifying drugs that can impact disease progression The drug and biomarker pipelines are mutually interdependent 45 15

16 Challenges to OA biomarker discovery, validation and qualification Biomarker candidates frequently vary in the body with changes in: Renal function (i.e., glomerular filtration rate) Hepatic function Food intake Physical activity Circadian rhythms 46 Performance and measurement of markers are dependent on much more than the assay Summary Biomarker discovery and validation for OA have accelerated significantly over the past decade This information has contributed to our understanding of molecules from joint tissues, their complex interactions and how they end up in blood after being handled by the liver and kidneys The absence of new drugs for OA in the pharmaceutical discovery pipeline is, in part, due to a lack of biomarkers that can predict responses to candidate structure modifying drugs We need to expand our toolbox and develop new biomarker tools and reagents New OA biomarkers will relieve key bottlenecks in the drug discovery pipeline and facilitate drug development for this debilitating disease 16

17 Conclusions There are currently no reliable biomarkers for early diagnosis of OA The existing biomarkers can only confirm what we know already (i.e., from radiography, the so-called gold standard ) The challenge is to identify sensitive and reliable pre-radiographic markers that can be accurately and reproducibly measured in body fluids The assays should be robust and easy to establish in any laboratory Conclusions (2) Future research in OA biomarker discovery will need to focus on the identification and validation of panels of protein and/or metabolite biomarkers that correlate with a range of diagnostic imaging techniques such as: Radiography Ultrasound Computed tomography (CT) Magnetic resonance imaging (MRI) Ideally, such biomarkers will serve in non or minimally-invasive, reliable diagnostic and prognostic assays of disease severity and act as reliable monitors of the patient response to a range of different therapies Current progress and existing bottlenecks 51 Proteomics is increasingly applied in cartilage biology and pathophysiology and the discovery of novel OA biomarkers Many existing biomarkers reflect catabolic and cartilage degradation in the later stages of OA Some biomarkers indicate normal cartilage turnover, tissue repair, or ECM remodelling We need to be able to discriminate between catabolic and maintenance events The definition of biomarker will need to reflect these diverse processes and the validation and qualification processes will ultimately depend on the context and specific purpose of their intended applications 17

18 52 Future priorities Development of new sophisticated analytical techniques for studying post-translational modifications in ECM molecules in OA Expanding the databases to allow detailed bioinformatic studies Current databases are too small size matters and small is not beautiful Refinement of bioinformatic tools and techniques to mine for information in databases Machine learning Clustering Data visualisation Biomarker combinations Development of new combination biomarkers that include biochemical markers, and imaging markers (i.e., radiographs, MRI) OA may be diagnosed better and much more sensitively when two or more biomarkers are assayed and the data combined with one or more imaging modalities (i.e., plain radiograph and MRI) Williams, MK (2009) Biomarkers: in combination they may do better; Arthritis Research & Therapy, 11: 130 doi: /ar Biomarkers of joint overuse and injury Joint injuries sustained by athletes are a major risk factor for the development of OA Developing biomarkers for monitoring joint overuse and injury in athletes can help monitor responses to different therapies (i.e., corticosteroid, NSAIDs, surgery) and avoid further joint damage associated with overuse injuries 54 18

19 Take-home message The is in the 55 We need: New biomarker targets Monoclonal antibodies Sensitive biomarker assays Affordable diagnostic kits Acknowledgements: funding and collaborators The D-BOARD Consortium Professor Yves Henrotin University of Liège, Belgium Dr. Julia Smith 56 Dr. Susan Liddell Dr. Jaume Bacardit Professor Charlie Hodgman 57 19