Ecological Risk Assessment and the Precautionary Principle

The Precautionary Principle, generated during the late 1980s as a unifying principle for regulating discharge of hazardous material into the North Sea, has been broadened to include a shifting of the burden of proof to the proponent of a proposed activity, adoption of a more holistic assessment process, and encompassing all environmental management decisions, not just pollution prevention activities. We argue that the Precautionary Principle remains a management philosophy, not a substitute for risk assessment. Risk assessment is a tool for organizing information used in environmental management decisions. However, increasing attention to reducing the Type II error of risk assessment studies would significantly reduce the skepticism with which many view the risk assessment process. A critical review of default assumptions used in risk assessments, inclusion of indirect effects within an ecologically relevant spatial/temporal framework, and better communication between risk assessors and risk managers also would enhance the acceptability of the process. Risk assessment can provide a sound basis for management decisions regardless of the underlying philosophies of environmental conservation or utilitarianism, but only if the inherent biases in the risk assessment assumptions are acknowledged explicitly throughout the assessment and management processes.     

Detecting shared pathways linked to rheumatoid arthritis with other autoimmune diseases in a in silico analysis

Pathway-based analysis approach has exploded in use during the last several years. It is successful in recognizing additional biological insight of disease and finding groupings of risk genes that represent disease developing processes. Therefore, shared pathways, with pleiotropic effects, are important for understanding similar pathogenesis and indicating the common genetic origin of certain diseases. Here, we present a pathway analysis to reveal the potential disease associations between RA and three potential RA-related autoimmune diseases: psoriasis, diabetes mellitus, type 1 (T1D) and systemic lupus erythematosus (SLE). First, a comprehensive knowledge mining of public databases is performed to discover risk genes associated with RA, T1D, SLE and psoriasis; then by enrichment test of these genes, disease-related risk pathways are detected to recognize the pathways common for RA and three other diseases. Finally, the underlying disease associations are evaluated with the association rules mining method. In total, we identify multiple RA risk pathways with significant pleiotropic effects, the most unsurprising of which are the immunology related pathways. Meanwhile for the first time we highlight the involvement of the viral myocarditis pathway related to cardiovascular disease (CVD) in autoimmune diseases such as RA, psoriasis, T1D and SLE. Further Association rule mining results validate the strong association between RA and T1D and RA and SLE. It is clear that pleiotropy is a common property of pathways associated with disease traits. We provide novel pathway associations among RA and three autoimmune diseases. These results ascertain that there are shared genetic risk profiles that predispose individuals to autoimmune diseases.     

Risk Assessment and Life-Cycle Impact Assessment (LCIA) for Human Health Cancerous and Noncancerous Emissions: Integrated and Complementary with Consistency within the USEPA

The historical parallels, complementary roles, and potential for integration of human health risk assessment (RA) and Life-Cycle Impact Assessment (LCIA) are explored. Previous authors have considered the comparison of LCA and risk assessment recognizing the inherent differences in LCA and risk assessment (e.g., LCA's focus on the functional unit, and the differences in perspective of LCA and risk assessment), and also the commonalities (e.g., the basis for the modeling). Until this time, however, no one has proposed a coordinated approach for conducting LCA and risk assessment using models consistent with the U.S. Environmental Protection Agency's (USEPA's) handbooks, policies, and guidelines. The current status of LCIA methodology development can be compared to the early days of human health RA when practitioners were overwhelmed with the model choices, assumptions, lack of data, and poor data quality. Although methodology developers can build on the shoulders of the giant, LCIA requires more innovation to deal with more impact categories, more life-cycle stages, and less data for a greater number of stressors. For certain impact categories, LCIA can use many of the guidelines, methodologies, and default parameters that have been developed for human health RA, in conjunction with sensitivity and uncertainty analysis to determine the level of detail necessary for various applications. LCIA can then identify “hot spots” that require the additional detail and level of certainty provided by RA. A comparison of the USEPA's Tool for the Reduction and Assessment of Chemical and other environmental Impacts (TRACI) and the USEPA's Risk-Screening Environmental Indicators (RSEI) will be explored.     

Antibodies to citrullinated proteins and differences in clinical progression of rheumatoid arthritis

Antibodies to citrullinated proteins (anti-cyclic-citrullinated peptide [anti-CCP] antibodies) are highly specific for rheumatoid arthritis (RA) and precede the onset of disease symptoms, indicating a pathogenetic role for these antibodies in RA. We recently showed that distinct genetic risk factors are associated with either anti-CCP-positive disease or anti-CCP-negative disease. These data are important as they indicate that distinct pathogenic mechanisms are underlying anti-CCP-positive disease or anti-CCP-negative disease. Likewise, these observations raise the question of whether anti-CCP-positive RA and anti-CCP-negative RA are clinically different disease entities. We therefore investigated whether RA patients with anti-CCP antibodies have a different clinical presentation and disease course compared with patients without these autoantibodies. In a cohort of 454 incident patients with RA, 228 patients were anti-CCP-positive and 226 patients were anti-CCP-negative. The early symptoms, tender and swollen joint count, and C-reactive protein level at inclusion, as well as the swollen joint count and radiological destruction during 4 years of follow-up, were compared for the two groups. There were no differences in morning stiffness, type, location and distribution of early symptoms, patients' rated disease activity and C-reactive protein at inclusion between RA patients with and without anti-CCP antibodies. The mean tender and swollen joint count for the different joints at inclusion was similar. At follow-up, patients with anti-CCP antibodies had more swollen joints and more severe radiological destruction. Nevertheless, the distribution of affected joints, for swelling, bone erosions and joint space narrowing, was similar. In conclusion, the phenotype of RA patients with or without anti-CCP antibodies is similar with respect to clinical presentation but differs with respect to disease course.     

Predicting the Risk of Rheumatoid Arthritis and Its Age of Onset through Modelling Genetic Risk Variants with Smoking

The improved characterisation of risk factors for rheumatoid arthritis (RA) suggests they could be combined to identify individuals at increased disease risks in whom preventive strategies may be evaluated. We aimed to develop an RA prediction model capable of generating clinically relevant predictive data and to determine if it better predicted younger onset RA (YORA). Our novel modelling approach combined odds ratios for 15 four-digit/10 two-digit HLA-DRB1 alleles, 31 single nucleotide polymorphisms (SNPs) and ever-smoking status in males to determine risk using computer simulation and confidence interval based risk categorisation. Only males were evaluated in our models incorporating smoking as ever-smoking is a significant risk factor for RA in men but not women. We developed multiple models to evaluate each risk factor''s impact on prediction. Each model''s ability to discriminate anti-citrullinated protein antibody (ACPA)-positive RA from controls was evaluated in two cohorts: Wellcome Trust Case Control Consortium (WTCCC: 1,516 cases; 1,647 controls); UK RA Genetics Group Consortium (UKRAGG: 2,623 cases; 1,500 controls). HLA and smoking provided strongest prediction with good discrimination evidenced by an HLA-smoking model area under the curve (AUC) value of 0.813 in both WTCCC and UKRAGG. SNPs provided minimal prediction (AUC 0.660 WTCCC/0.617 UKRAGG). Whilst high individual risks were identified, with some cases having estimated lifetime risks of 86%, only a minority overall had substantially increased odds for RA. High risks from the HLA model were associated with YORA (P<0.0001); ever-smoking associated with older onset disease. This latter finding suggests smoking''s impact on RA risk manifests later in life. Our modelling demonstrates that combining risk factors provides clinically informative RA prediction; additionally HLA and smoking status can be used to predict the risk of younger and older onset RA, respectively.     

Pyrophosphorolysis by Type II DNA polymerases: implications for pyrophosphorolysis-activated polymerization

We find that Type II DNA polymerases can catalyze pyrophosphorolysis, the reverse reaction of DNA polymerization. This property is applied utilizing pyrophosphorolysis-activated polymerization (PAP), a method of nucleic acid amplification using serial coupling of pyrophosphorolysis and polymerization. PAP can be used for ultrarare allele detection (detection of minimal residual disease and cancer risk assessment through measurement of mutation load) and for microarray-based scanning for unknown mutations. Herein, we show that Type II DNA polymerases efficiently catalyze template-dependent pyrophosphorolysis to activate oligonucleotides blocked at their 3' termini with acyclonucleotides in which a 2-hydroxyethoxymethyl group substitutes for the 2'-deoxyribofuranosyl sugar. Type II archeon DNA polymerases Vent (exo-) and Pfu (exo-) can be utilized for PAP or a bidirectional form of PAP with acyclonucleotide-blocked oligonucleotides, but not with dideoxynucleotide-blocked oligonucleotides. In contrast, a Type I DNA polymerase, TaqFS, can utilize either acyclonucleotide-blocked or dideoxynucleotide-blocked oligonucleotides. These findings expand the potential of nascent PAP technology.     

VEGF and imaging of vessels in rheumatoid arthritis

Angiogenesis is a prominent feature of rheumatoid synovitis. Formation of new blood vessels permits a supply of nutrients and oxygen to the augmented inflammatory cell mass and so contributes to perpetuation of joint disease. Vascular endothelial growth factor (VEGF) is a potent endothelial cell-specific growth factor that is upregulated by proinflammatory cytokines and by hypoxia. Serum VEGF concentrations are elevated in rheumatoid arthritis (RA) and correlate with disease activity. Furthermore, serum VEGF measured at first presentation in RA is highly significantly correlated with radiographic progression of disease over the subsequent year. Power Doppler ultrasonography is a sensitive method for demonstrating the presence of blood flow in small vessels and there is a very close relation between the presence or absence of vascular flow signal on power Doppler imaging and the rate of early synovial enhancement on dynamic gadolinium-enhanced magnetic resonance imaging (MRI) of joints with RA. Images obtained by both dynamic enhanced MRI and power Doppler ultrasonography correlate with vascularity of synovial tissue as assessed histologically. In early RA, there is a striking association between joint erosions assessed on high-resolution ultrasonography and vascular signal in power Doppler mode. Collectively, these findings implicate vascular pannus in the erosive phase of disease and strongly suggest that proangiogenic molecules such as VEGF are targets for novel therapies in RA. Animal model data supports this concept. It seems likely that serological and imaging measures of vascularity in RA will become useful tools in the assessment of disease activity and response to therapy.     

Early Vascular Alterations in SLE and RA Patients-A Step towards Understanding the Associated Cardiovascular Risk

Accelerated atherosclerosis represents a major problem in both systemic lupus erythematosus (SLE) and rheumatoid arthritis (RA) patients, and endothelial damage is a key feature of atherogenesis. We aimed to assess early endothelial changes in SLE and RA female patients (127 SLE and 107 RA) without previous CV events. Biomarkers of endothelial cell activation (intercellular adhesion molecule-1 (sICAM-1), vascular cell adhesion molecule-1 (sVCAM-1), thrombomodulin (TM), and tissue factor (TF)) were measured and endothelial function was assessed using peripheral artery tonometry. Reactive hyperemia index (RHI), an indicator of microvascular reactivity, and augmentation index (AIx), a measure of arterial stiffness, were obtained. In addition, traditional CV risk factors, disease activity and medication were determined. Women with SLE displayed higher sICAM-1 and TM and lower TF levels than women with RA (p?=?0.001, p<0.001 and p<0.001, respectively). These differences remained significant after controlling for CV risk factors and medication. Serum levels of vascular biomarkers were increased in active disease and a moderate correlation was observed between sVCAM-1 levels and lupus disease activity (rho?=?0.246) and between TF levels and RA disease activity (rho?=?0.301). Although RHI was similar across the groups, AIx was higher in lupus as compared to RA (p?=?0.04). Also in active SLE, a trend towards poorer vasodilation was observed (p?=?0.06). In conclusion, women with SLE and RA present with distinct patterns of endothelial cell activation biomarkers not explained by differences in traditional CV risk factors. Early vascular alterations are more pronounced in SLE which is in line with the higher CV risk of these patients.     

Developments in the clinical understanding of rheumatoid arthritis

The changes occurring in the field of rheumatoid arthritis (RA) over the past decade or two have encompassed new therapies and, in particular, a new look at the clinical characteristics of the disease in the context of therapeutic improvements. It has been shown that composite disease activity indices have special merits in following patients, that disease activity governs the evolution of joint damage, and that disability can be dissected into several components – among them disease activity and joint damage. It has also been revealed that aiming at any disease activity state other than remission (or, at worst, low disease activity) is associated with significant progression of joint destruction, that early recognition and appropriate therapy of RA are important facets of the overall strategy of optimal clinical control of the disease, and that tight control employing composite scores supports the optimization of the therapeutic approaches. Finally, with the advent of novel therapies, remission has become a reality and the treatment algorithms encompassing all of the above-mentioned aspects will allow us to achieve the rigorous aspirations of today and tomorrow.     

Molecular aspects of rheumatoid arthritis: role of environmental factors

Rheumatoid arthritis (RA) is a systemic, chronic inflammatory disease that affects 0.5-1% of the population. RA causes progressive joint destruction that leads to the restriction of activities of daily living and deterioration of quality of life. Although the pathogenesis of RA has not yet been fully elucidated, it is considered to be a complex, multifarious disease that is influenced by both genetic and environmental factors. Genetic influences that contribute to RA susceptibility have been demonstrated both in studies of twins and families, as well as in genome-wide linkage scans, and it is estimated that genetic factors are responsible for 50-60% of the risk of developing RA. Thus, environmental factors may explain the remaining risk of developing RA. A large variety of environmental factors such as infectious agents, smoking, sex hormones, pregnancy etc. have been extensively studied previously. Understanding of how these factors contribute to the development of RA may lead to the better understanding of pathogenesis of RA.     

Identification of blood biomarkers of rheumatoid arthritis by transcript profiling of peripheral blood mononuclear cells from the rat collagen-induced arthritis model

Rheumatoid arthritis (RA) is a chronic debilitating autoimmune disease that results in joint destruction and subsequent loss of function. To better understand its pathogenesis and to facilitate the search for novel RA therapeutics, we profiled the rat model of collagen-induced arthritis (CIA) to discover and characterize blood biomarkers for RA. Peripheral blood mononuclear cells (PBMCs) were purified using a Ficoll gradient at various time points after type II collagen immunization for RNA preparation. Total RNA was processed for a microarray analysis using Affymetrix GeneChip technology. Statistical comparison analyses identified differentially expressed genes that distinguished CIA from control rats. Clustering analyses indicated that gene expression patterns correlated with laboratory indices of disease progression. A set of 28 probe sets showed significant differences in expression between blood from arthritic rats and that from controls at the earliest time after induction, and the difference persisted for the entire time course. Gene Ontology comparison of the present study with previous published murine microarray studies showed conserved Biological Processes during disease induction between the local joint and PBMC responses. Genes known to be involved in autoimmune response and arthritis, such as those encoding Galectin-3, Versican, and Socs3, were identified and validated by quantitative TaqMan RT-PCR analysis using independent blood samples. Finally, immunoblot analysis confirmed that Galectin-3 was secreted over time in plasma as well as in supernatant of cultured tissue synoviocytes of the arthritic rats, which is consistent with disease progression. Our data indicate that gene expression in PBMCs from the CIA model can be utilized to identify candidate blood biomarkers for RA.     

Identification of blood biomarkers of rheumatoid arthritis by transcript profiling of peripheral blood mononuclear cells from the rat collagen-induced arthritis model

Rheumatoid arthritis (RA) is a chronic debilitating autoimmune disease that results in joint destruction and subsequent loss of function. To better understand its pathogenesis and to facilitate the search for novel RA therapeutics, we profiled the rat model of collagen-induced arthritis (CIA) to discover and characterize blood biomarkers for RA. Peripheral blood mononuclear cells (PBMCs) were purified using a Ficoll gradient at various time points after type II collagen immunization for RNA preparation. Total RNA was processed for a microarray analysis using Affymetrix GeneChip technology. Statistical comparison analyses identified differentially expressed genes that distinguished CIA from control rats. Clustering analyses indicated that gene expression patterns correlated with laboratory indices of disease progression. A set of 28 probe sets showed significant differences in expression between blood from arthritic rats and that from controls at the earliest time after induction, and the difference persisted for the entire time course. Gene Ontology comparison of the present study with previous published murine microarray studies showed conserved Biological Processes during disease induction between the local joint and PBMC responses. Genes known to be involved in autoimmune response and arthritis, such as those encoding Galectin-3, Versican, and Socs3, were identified and validated by quantitative TaqMan RT-PCR analysis using independent blood samples. Finally, immunoblot analysis confirmed that Galectin-3 was secreted over time in plasma as well as in supernatant of cultured tissue synoviocytes of the arthritic rats, which is consistent with disease progression. Our data indicate that gene expression in PBMCs from the CIA model can be utilized to identify candidate blood biomarkers for RA.     

New autoantibodies in early rheumatoid arthritis

Introduction

Rheumatoid arthritis (RA) is a chronic inflammatory joint disease causing articular cartilage and bone destruction. Since irreversible joint destruction can be prevented by intervention at the early stages of disease, early diagnosis of RA is important. In this study, we identified new autoantibodies in the sera of patients with early (less than one year) RA.

Methods

We screened the sera of 20 RA patients with disease duration less than one year, 19 RA patients with disease duration more than five years and 23 controls on 8,268 human protein arrays. We confirmed the validity of protein array detection by ELISA assays. We then performed epitope mapping with overlapping 15-mers to analyze RA sera reactivity.

Results

WIBG (within BGCN homolog (Drosophila)), GABARAPL2 (GABA(A) receptor associated protein like 2) and ZNF706 (zinc finger protein 706) proteins are preferentially recognized by autoantibodies from early RA patients. Of interest, autoantibodies to WIBG are very specific for early RA. Indeed, 33% of early RA patients'' sera recognize WIBG versus 5% of RA patients with disease duration more than 5 years and 2% of controls. We identified three linear peptides on WIBG GABARAPL2 and ZNF706 that are preferentially recognized by sera of early RA patients.

Conclusions

We identified new autoantibodies associated with RA with disease duration less than one year. These autoantibodies could be used as diagnosis markers in RA patients.     

Risk assessment for Clostridium botulinum: a network approach

The construction and implementation of a mathematical framework for the representation of the hazards that arise from Clostridium botulinum growth, and toxin production, in food are described. Botulism has been recognised as a serious foodborne illness for over a century and, more recently, has become the subject of increased concern due to changing processing and consumption patterns associated with foods. In this respect quantitative risk assessment has an increasingly important role to play in assisting risk management and ensuring the safety of minimally processed foods and foods with extended shelf life.Bayesian Belief Networks are a type of expert system that integrates a graphical, flow diagram like, representation of a hazard domain with a powerful technique for combining probabilities. This technique facilitates the accumulation of understanding and experience, for particular hazard domains, into computer tools that can be used to inspect risks and account for decisions.Analysis of the hazards associated with foodborne botulism involves Belief Network components that represent contamination processes, thermal death kinetics for spores, germination and growth of cells, toxin production and patterns of consumer behaviour, etc. These developments are discussed and three important aspects of the food safety information supply, complexity, dependency and uncertainty highlighted. The benefits associated with a Bayesian view of food safety assessment are illustrated by a Belief Network representation which supports, and prioritises, decisions and actions that (a) minimise the chances and extent of detrimental events and (b) maximise opportunities for awareness and control.     

Import‐based Indicator for the Geopolitical Supply Risk of Raw Materials in Life Cycle Sustainability Assessments

There is a growing concern over the security and sustainable supply of raw material among businesses and governments of developed, material‐intensive countries. This has led to the development of a systematic analysis of risk incorporated with raw materials usage, often referred as criticality assessment. In principle, this concept is based on the material flow approach. The potential role of life cycle assessment (LCA) to integrate resource criticality through broadening its scope into the life cycle sustainability assessment (LCSA) framework has been discussed within the LCA communities for some time. In this article, we aim at answering the question of how to proceed toward integration of the geopolitical aspect of resource criticality into the LCSA framework. The article focuses on the assessment of the geopolitical supply risk of 14 resources imported to the seven major advanced economies and the five most relevant emerging countries. Unlike a few previous studies, we propose a new method of calculation for the geopolitical supply risk, which is differentiated by countries based on the import patterns instead of a global production distribution. Our results suggest that rare earth elements, tungsten, antimony, and beryllium generally pose high geopolitical supply risk. Results from the Monte Carlo simulation allow consideration of data uncertainties for result interpretation. Issues concerning the consideration of the full supply chain are exemplarily discussed for cobalt. Our research broadens the scope of LCA from only environmental performance to a resource supply‐risk assessment tool that includes accessibility owing to political instability and market concentration under the LCSA framework.     

基于土地破坏的矿区生态风险评价:理论与方法

矿区生态风险评价已成为区域生态风险研究的热点领域。如何合理选择和表征区域生态风险源和风险受体,量化多风险源和多风险受体的交互作用,是目前区域生态风险评价研究的焦点。为此,在总结矿区生态风险评价研究成果的基础上,构建了矿区生态风险源、风险受体及作用对象与过程的因果链模型,结合矿区生态环境问题产生过程的独特性,将土地挖损、占用及塌陷等土地破坏作为矿区的直接生态风险源。基于土地破坏类型提出了适宜矿区的区域生态风险评价流程、指标体系与计算方法;并专门在定量化多风险源与多风险受体交互作用上做出探讨,构建了生态系统单元暴露指数和土地破坏累积作用指数来评价矿区土地破坏与生态系统单元间的暴露与危害作用关系。为矿区生态风险评价的实证研究提出了理论基础与方法框架,未来可结合实证研究对此方法及相关指标参数做出完善与改进,为矿区生态环境管理与生态安全建设提供科学的参考依据。     

Developments in the scientific understanding of rheumatoid arthritis

Rheumatoid arthritis (RA) is recognized to be an autoimmune disease that causes preclinical systemic abnormalities and eventually leads to synovial inflammation and destruction of the joint architecture. Recently identified genetic risk factors and novel insights from animal models of spontaneous arthritis have lent support to the concept that thymic selection of an autoreactive T-cell repertoire is an important risk factor for this disease. With advancing age, defects in the homeostatic control of the T-cell pool and in the setting of signaling thresholds lead to the accumulation of pro-inflammatory T-effector cell populations and loss of tolerance to neo-antigens, such as citrullinated peptides. As the breakdown of tolerance to modified self-antigens can precede synovitis by decades, repair of homeostatic defects may open a unique window of opportunity for preventive interventions in RA. The end result of RA, destruction of cartilage and bone, appears to be driven by cytokine- and cell contact-induced activation of synoviocytes and monocytic cells, some of which differentiate into tissue-destructive osteoclasts. Targeting mediators involved in this process has greatly improved the management of this chronic inflammatory syndrome.     

Effective use of TNF antagonists

Tumor necrosis factor (TNF) antagonists are biologic response modifiers that have significantly improved functional outcomes in patients with rheumatoid arthritis (RA). RA is a progressive disease in which structural joint damage can continue to develop even in the face of symptomatic relief. Before the introduction of biologic agents, the management of RA involved the use of disease-modifying antirheumatic drugs (DMARDs) early in the course of disease. This focus on early treatment, combined with the availability of the anti-TNF agents, has contributed to a shift in treatment paradigms favoring the early and timely use of DMARDs with biologic therapies. Improvement in symptom control does not always equate to a reduction in disease progression or disability. With the emergence of structure-related outcome measures as the primary means for assessing the effectiveness of antirheumatic agents, the regular use of X-rays is recommended for the continued monitoring and evaluation of patients. In addition to the control of symptoms and improvement in physical function, a reduction in erosions and joint-space narrowing should be considered among the goals of therapy, leading to a better quality of life. Adherence to therapy is an important element in optimizing outcomes. Durability of therapy with anti-TNF agents as reported from clinical trials can also be achieved in the clinical setting. Concomitant methotrexate therapy might be important in maintaining TNF antagonist therapy in the long term. Overall, the TNF antagonists have led to improvements in clinical and radiographic outcomes in patients with RA, especially those who have failed to show a complete response to methotrexate.     

Integrating data mining and transmission theory in the ecology of infectious diseases

Our understanding of ecological processes is built on patterns inferred from data. Applying modern analytical tools such as machine learning to increasingly high dimensional data offers the potential to expand our perspectives on these processes, shedding new light on complex ecological phenomena such as pathogen transmission in wild populations. Here, we propose a novel approach that combines data mining with theoretical models of disease dynamics. Using rodents as an example, we incorporate statistical differences in the life history features of zoonotic reservoir hosts into pathogen transmission models, enabling us to bound the range of dynamical phenomena associated with hosts, based on their traits. We then test for associations between equilibrium prevalence, a key epidemiological metric and data on human outbreaks of rodent‐borne zoonoses, identifying matches between empirical evidence and theoretical predictions of transmission dynamics. We show how this framework can be generalized to other systems through a rubric of disease models and parameters that can be derived from empirical data. By linking life history components directly to their effects on disease dynamics, our mining‐modelling approach integrates machine learning and theoretical models to explore mechanisms in the macroecology of pathogen transmission and their consequences for spillover infection to humans.     

Molecular basis of recognition of human osteopontin by 23C3, a potential therapeutic antibody for treatment of rheumatoid arthritis

Osteopontin plays an important role in the development and perpetuation of rheumatoid arthritis (RA). Antibodies targeting osteopontin have shown promising therapeutic benefits against this disease. We have previously reported a novel anti-RA monoclonal antibody, namely, 23C3, and shown it capable of alleviating the symptoms of RA in a murine collagen-induced arthritis model, restoring the cytokine production profile in joint tissues, and reducing T-cell recall responses to collagen type II. We describe here the crystal structure of 23C3 in complex with its epitope peptide. Analyses of the complex structure reveal the molecular mechanism of osteopontin recognition by 23C3. The peptide folds into two tandem β-turns, and two key residues of the peptide are identified to be critical for the recognition by 23C3: TrpP43 is deeply embedded into a hydrophobic pocket formed by AlaL34, TyrL36, LeuL46, TyrL49, PheL91, and MetH102 and therefore has extensive hydrophobic interactions with 23C3, while AspP47 has a network of hydrophilic interactions with residues ArgH50, ArgH52, SerH53, and AsnH56 of the antibody. Besides the complementarity-determining region loops, the framework region L2 of 23C3 is also shown to interact with the epitope peptide, which is not common in the antibody-antigen interactions and thus could be exploited in the engineering of 23C3. These results not only provide valuable information for further improvement of 23C3 such as chimerization or humanization for its therapeutic application, but also reveal the features of this specific epitope of osteopontin that may be useful for the development of new antibody drugs against RA.