Serum protein profile in systemic-onset juvenile idiopathic arthritis differentiates response versus nonresponse to therapy

Systemic-onset juvenile idiopathic arthritis (SJIA) is a disease of unknown etiology with an unpredictable response to treatment. We examined two groups of patients to determine whether there are serum protein profiles reflective of active disease and predictive of response to therapy. The first group (n = 8) responded to conventional therapy. The second group (n = 15) responded to an experimental antibody to the IL-6 receptor (MRA). Paired sera from each patient were analyzed before and after treatment, using surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS). Despite the small number of patients, highly significant and consistent differences were observed before and after response to therapy in all patients. Of 282 spectral peaks identified, 23 had mean signal intensities significantly different (P < 0.001) before treatment and after response to treatment. The majority of these differences were observed regardless of whether patients responded to conventional therapy or to MRA. These peaks represent potential biomarkers of active disease. One such peak was identified as serum amyloid A, a known acute-phase reactant in SJIA, validating the SELDI-TOF MS platform as a useful technology in this context. Finally, profiles from serum samples obtained at the time of active disease were compared between the two patient groups. Nine peaks had mean signal intensities significantly different (P < 0.001) between active disease in patients who responded to conventional therapy and in patients who failed to respond, suggesting a possible profile predictive of response. Collectively, these data demonstrate the presence of serum proteomic profiles in SJIA that are reflective of active disease and suggest the feasibility of using the SELDI-TOF MS platform used as a tool for proteomic profiling and discovery of novel biomarkers in autoimmune diseases.     

Protein arrays as tools for serum autoantibody marker discovery in cancer

Protein array technology has begun to play a significant role in the study of protein–protein interactions and in the identification of antigenic targets of serum autoantibodies in a variety of autoimmune disorders. More recently, this technology has been applied to the identification of autoantibody signatures in cancer.The identification of tumour-associated antigens (TAAs) recognised by the patient's immune response represents an exciting approach to identify novel diagnostic cancer biomarkers and may contribute towards a better understanding of the molecular mechanisms involved. Circulating autoantibodies have not only been used to identify TAAs as diagnostic/prognostic markers and potential therapeutic targets, they also represent excellent biomarkers for the early detection of tumours and potential markers for monitoring the efficacy of treatment. Protein array technology offers the ability to screen the humoral immune response in cancer against thousands of proteins in a high throughput technique, thus readily identifying new panels of TAAs. Such an approach should not only aid in improved diagnostics, but has already contributed to the identification of complex autoantibody signatures that may represent disease subgroups, early diagnostics and facilitated the analysis of vaccine trials.     

The use of post‐translationally modified peptides for detection of biomarkers of immune‐mediated diseases

Biomarkers are decision‐making tools at the basis of clinical diagnostics and essential for guiding therapeutic treatments. In this context, autoimmune diseases represent a class of disorders that need early diagnosis and steady monitoring. These diseases are usually associated with humoral or cell‐mediated immune reactions against one or more of the body's own constituents. Autoantibodies fluctuating in biological fluids can be used as disease biomarkers and they can be, thus, detected by diagnostic immunoassays using native autoantigens. However, it is now accepted that post‐translational modifications may affect the immunogenicity of self‐protein antigens, triggering an autoimmune response and creating neo‐antigens. In this case, post‐translationally modified peptides represent a more valuable tool with respect to isolated or recombinant proteins. In fact, synthetic peptides can be specifically modified to mimic neo‐antigens and to selectively detect autoantibodies as disease biomarkers. A ‘chemical reverse approach’ to select synthetic peptides, bearing specific post‐translational modifications, able to fishing out autoantibodies from patients' biological fluids, can be successfully applied for the development of specific in vitro diagnostic/prognostic assays of autoimmune diseases. Herein, we report the successful application of this approach to the identification of biomarkers in different autoimmune diseases, such as systemic lupus erythematosus, rheumatoid arthritis and multiple sclerosis. Copyright © 2009 European Peptide Society and John Wiley & Sons, Ltd.     

Biomarkers for Primary Sjgren's Syndrome

Primary Sjo¨gren's syndrome(p SS) is a systemic autoimmune disease with exocrine gland dysfunction and multi-organ involvement. Recent progress in understanding the pathogenesis of p SS offers an opportunity to find new biomarkers for the diagnosis and assessment of disease activity. Screening noninvasive biomarkers from the saliva and tears has significant potential. The need for specific and sensitive biomarker candidates in p SS is significant. This review aims to summarize recent advances in the identification of biomarkers of Sjo¨gren syndrome, trying to identify reliable, sensitive, and specific biomarkers that can be used to guide treatment decisions.     

Autoimmunity as a Candidate for the Etiopathogenesis of Meniere's Disease: Detection of Autoimmune Reactions and Diagnostic Biomarker Candidate

Meniere''s disease is an inner ear disorder that can manifest as fluctuating vertigo, sensorineural hearing loss, tinnitus, and aural fullness. However, the pathologic mechanism of Meniere''s disease is still unclear. In this study, we evaluated autoimmunity as a potential cause of Meniere''s disease. In addition we tried to find useful biomarker candidates for diagnosis. We investigated the protein composition of human inner ear fluid using liquid column mass spectrometry, the autoimmune reaction between circulating autoantibodies in patient serum and multiple antigens using the Protoarray system, the immune reaction between patient serum and mouse inner ear tissues using western blot analysis. Nine proteins, including immunoglobulin and its variants and interferon regulatory factor 7, were found only in the inner ear fluid of patients with Meniere''s disease. Enhanced immune reactions with 18 candidate antigens were detected in patients with Meniere''s disease in Protoarray analysis; levels of 8 of these antigens were more than 10-fold higher in patients than in controls. Antigen-antibody reactions between mouse inner ear proteins with molecular weights of 23–48 kDa and 63–75 kDa and patient sera were detected in 8 patients. These findings suggest that autoimmunity could be one of the pathologic mechanisms behind Meniere''s disease. Multiple autoantibodies and antigens may be involved in the autoimmune reaction. Specific antigens that caused immune reactions with patient''s serum in Protoarray analysis can be candidates for the diagnostic biomarkers of Meniere''s disease.     

Evidence for a role of autoantibodies to heat shock protein 60, 70, and 90 in patients with dermatitis herpetiformis

Heat shock proteins (Hsp) are highly conserved immunomodulatory molecules upregulated when cells are exposed to stressful stimuli, such as inflammation. Their involvement in various autoimmune diseases, including autoimmune bullous diseases and celiac disease, has been increasingly recognized. To further study the role of Hsp in autoimmune bullous diseases, we have investigated for the first time the humoral autoimmune response to Hsp40, Hsp60, Hsp70, and Hsp90 in patients with dermatitis herpetiformis (DH; n = 26), bullous pemphigoid (BP; n = 23), and pemphigus vulgaris (PV; n = 16), the first representing a cutaneous manifestation of celiac disease. While in patients with active BP and PV, serum levels of autoantibodies against these Hsp did not differ from the corresponding age- and gender-matched healthy controls (n = 9–14); circulating autoantibodies against Hsp60, Hsp70, and Hsp90 were found to be increased at the active disease stage of DH. Further analysis of this latter patient subgroup showed that these anti-Hsp autoantibodies decreased in parallel with serum autoantibodies against epidermal and tissue transglutaminase during remission of skin lesions following a gluten-free diet, revealing significantly positive correlations. Although further studies on larger groups of patients will be needed to confirm the present data, our results support the notion that autoantibodies against Hsp60, Hsp70, and Hsp90 deserve attention in the study of the mechanisms that promote the development and maintenance of DH and possibly also the underlying celiac disease as well as potential novel disease biomarkers.     

Nonischemic Cardiomyopathy Associated with Autoimmune Polyglandular Syndrome Type II

ObjectiveTo report a case of nonischemic cardiomyopathy associated with autoimmune polyglandular syndrome type II (APS-II).MethodsWe describe our patient’s clinical features, evaluation, and outcome. In addition, a literature review of cardiomyopathy associated with polyendocrinopathy syndromes is presented.ResultsThe component disorders of APS-II are Addison’s disease in combination with either autoimmune thyroid disease or type 1 (insulin-dependent) diabetes. Although numerous other autoimmune conditions have been reported in conjunction with APS-II, cardiomyopathy has not been previously described as part of this syndrome. The current patient was a 32-year-old man who, during a 5-year period, was diagnosed as having type 1 diabetes mellitus, Crohn’s disease, and Addison’s disease. In 2001, he presented with severe heart failure that progressed rapidly and eventually necessitated cardiac transplantation.ConclusionAlthough autoimmune cardiomyopathy has been associated with other autoimmune disorders, to our knowledge this is the first reported case of cardiomyopathy in association with an autoimmune polyglandular syndrome. Patients with this syndrome should undergo clinical evaluation for heart failure. (Endocr Pract. 2007;13:59-62)     

多发性硬化生物标记物的研究进展

多发性硬化(MS)是主要以中枢神经系统(CNS)白质脱髓鞘病变为主要特点的自身免疫性疾病。生物标记物是中枢神经系统自身免疫性疾病病因、诊断和预后的重要参考因素,因为他们可能反映遗传以及环境变化所引起的某些免疫反应的存在,性质和强度。因此生物标记有助于MS的早期诊断和鉴别诊断,指导治疗方案,推断MS疾病活动性,以及判断疗效。本文概述了多发性硬化领域当前的生物标记物研究状况及其相关的临床实践,并通过对三种具有较大潜力的生物标记物与病理的特异性、灵敏度、可靠性和临床实用工具进行分析,以确定最优化的治疗以防止致残,同时还可以对疾病修饰药物的有效性进行测试。     

Polychromatic flow cytometry in evaluating rheumatic disease patients

B cells are central players in multiple autoimmune rheumatic diseases as a result of the imbalance between pathogenic and protective B-cell functions, which are presumably mediated by distinct populations. Yet the functional role of different B-cell populations and the contribution of specific subsets to disease pathogenesis remain to be fully understood owing to a large extent to the use of pauci-color flow cytometry. Despite its limitations, this approach has been instrumental in providing a global picture of multiple B-cell abnormalities in multiple human rheumatic diseases, more prominently systemic lupus erythematosus, rheumatoid arthritis and Sjogren’s syndrome. Accordingly, these studies represent the focus of this review. In addition, we also discuss the added value of tapping into the potential of polychromatic flow cytometry to unravel a higher level of B-cell heterogeneity, provide a more nuanced view of B-cell abnormalities in disease and create the foundation for a precise understanding of functional division of labor among the different phenotypic subsets. State-of-the-art polychromatic flow cytometry and novel multidimensional analytical approaches hold tremendous promise for our understanding of disease pathogenesis, the generation of disease biomarkers, patient stratification and personalized therapeutic approaches.     

Serum protein profiling of systemic lupus erythematosus and systemic sclerosis using recombinant antibody microarrays

Systemic lupus erythematosus (SLE) and systemic sclerosis (SSc) are two severe autoimmune connective tissue diseases. The fundamental knowledge about their etiology is limited and the conditions display complex pathogenesis, multifaceted presentations, and unpredictable courses. Despite significant efforts, the lack of fully validated biomarkers enabling diagnosis, classification, and monitoring of disease activity represents significant unmet clinical needs. In this discovery study, we have for the first time used recombinant antibody microarrays for miniaturized, multiplexed serum protein profiling of SLE and SSc, targeting mainly immunoregulatory proteins. The data showed that several candidate SLE-associated multiplexed serum biomarker signatures were delineated, reflecting disease (diagnosis), disease severity (phenotypic subsets), and disease activity. Selected differentially expressed markers were validated using orthogonal assays and a second, independent patient cohort. Further, biomarker signatures differentiating SLE versus SSc were demonstrated, and the observed differences increased with severity of SLE. In contrast, the data showed that the serum profiles of SSc versus healthy controls were more similar. Hence, we have shown that affinity proteomics could be used to de-convolute crude, nonfractionated serum proteomes, extracting molecular portraits of SLE and SSc, further enhancing our fundamental understanding of these complex autoimmune conditions.     

The role of proteomics in assessing beta-cell dysfunction and death in type 1 diabetes

Introduction: Type 1 diabetes (T1D) is characterized by autoimmune-induced dysfunction and destruction of the pancreatic beta cells. Unfortunately, this process is poorly understood, and the current best treatment for type 1 diabetes is the administration of exogenous insulin. To better understand these mechanisms and to develop new therapies, there is an urgent need for biomarkers that can reliably predict disease stage.

Areas covered: Mass spectrometry (MS)-based proteomics and complementary techniques play an important role in understanding the autoimmune response, inflammation and beta-cell death. MS is also a leading technology for the identification of biomarkers. This, and the technical difficulties and new technologies that provide opportunities to characterize small amounts of sample in great depth and to analyze large sample cohorts will be discussed in this review.

Expert opinion: Understanding disease mechanisms and the discovery of disease-associated biomarkers are highly interconnected goals. Ideal biomarkers would be molecules specific to the different stages of the disease process that are released from beta cells to the bloodstream. However, such molecules are likely to be present in trace amounts in the blood due to the small number of pancreatic beta cells in the human body and the heterogeneity of the target organ and disease process.     

Long non‐coding RNAs in rheumatoid arthritis

Rheumatoid arthritis, a disabling autoimmune disease, is associated with altered gene expression in circulating immune cells and synovial tissues. Accumulating evidence has suggested that long non‐coding RNAs (lncRNAs), which modulate gene expression through multiple mechanisms, are important molecules involved in immune and inflammatory pathways. Importantly, many studies have reported that lncRNAs can be utilized as biomarkers for disease diagnosis and prognostication. Recently, dysregulation of lncRNAs in rheumatoid arthritis and other autoimmune diseases has been revealed. Experimental studies also confirmed their crosstalk with matrix metalloproteinases, nuclear factor‐κB signalling and T‐cell response pertinent to autoimmunity and inflammation. Circulating lncRNAs, such as HOTAIR, differentiated patients with rheumatoid arthritis from healthy subjects. Taken together, lncRNAs are good candidates as biomarkers and therapeutic targets in rheumatoid arthritis. Further investigation on in vivo delivery of these regulatory molecules and large‐cohort validation of their clinical applicability may be useful.     

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.     

Recent thymic emigrants as the bridge between thymoma and autoimmune diseases

Recent thymic emigrants (RTEs) are naïve T cells that egress the thymus following intrathymic development. This continuous process, including self-renewal, is crucial to establish and maintain human immune function. Several biomarkers can identify RTEs, but none of them is specific. Additional methods to detect and study RTEs phenotypically and functionally revealed alterations in RTEs in various adverse health conditions, including autoimmune diseases, systemic disorders and thymic abnormalities such as thymoma. Often associated with autoimmune disease, thymoma is the only tumor that can generate RTEs. However, a causal relationship between RTEs and autoimmune disease remains uncertain. Here, we review current knowledge about the connections between thymoma, RTEs and autoimmune diseases to provide new perspectives for therapeutic strategies.     

Proteome Profiling in Murine Models of Multiple Sclerosis: Identification of Stage Specific Markers and Culprits for Tissue Damage

The identification of new biomarkers is of high interest for the prediction of the disease course and also for the identification of pathomechanisms in multiple sclerosis (MS). To specify markers of the chronic disease phase, we performed proteome profiling during the later phase of myelin oligodendrocyte glycoprotein induced experimental autoimmune encephalomyelitis (MOG-EAE, day 35 after immunization) as a model disease mimicking many aspects of secondary progressive MS. In comparison to healthy controls, high resolution 2 dimensional gel electrophoresis revealed a number of regulated proteins, among them glial fibrilary acidic protein (GFAP). Phase specific up-regulation of GFAP in chronic EAE was confirmed by western blotting and immunohistochemistry. Protein levels of GFAP were also increased in the cerebrospinal fluid of MS patients with specificity for the secondary progressive disease phase. In a next step, proteome profiling of an EAE model with enhanced degenerative mechanisms revealed regulation of alpha-internexin, syntaxin binding protein 1, annexin V and glutamate decarboxylase in the ciliary neurotrophic factor (CNTF) knockout mouse. The identification of these proteins implicate an increased apoptosis and enhanced axonal disintegration and correlate well the described pattern of tissue injury in CNTF −/− mice which involve oligodendrocyte (OL) apoptosis and axonal injury.In summary, our findings underscore the value of proteome analyses as screening method for stage specific biomarkers and for the identification of new culprits for tissue damage in chronic autoimmune demyelination.     

A Case of Nonischemic Cardiomyopathy Associated with Autoimmune Polyglandular Syndrome Type III

Objective:To report a case of nonischemic dilated cardiomyopathy associated with autoimmune polyglandular syndrome (APS) type III.MethodsA review of our patient’s medical records was undertaken, and her clinical history, investigations, and outcome are described. In addition, a literature review of nonischemic dilated cardiomyopathy occurring in association with autoimmune polyendocrinopathies was performed.ResultsAPS is diagnosed once a patient has developed at least 2 organ specific autoimmune diseases. APS III involves a combination of autoimmune diabetes and Graves’ disease without adrenal insufficiency. Autoimmune cardiomyopathies are not described as a feature of this condition; however, there are a few reported cases of patients with autoimmune polyendocrinopathies developing a nonischemic dilated cardiomyopathy. In this case, a 30-year-old female developed vitiligo, Graves’ disease, and latent autoimmune diabetes of the adult (LADA) over a 5-year period before presenting with conscious ventricular tachycardia (VT). This evolved into acute severe biventricular failure within a few weeks, which failed to resolve after adequate treatment of her other autoimmune conditions.ConclusionAlthough nonischemic cardiomyopathies have been associated with APS in a few published cases, this is the first case to our knowledge in a patient with APS III. (Endocr Pract. 2014;20:e183-e186)     

Capillary electrophoresis mass spectrometry-based saliva metabolomics identified oral,breast and pancreatic cancer-specific profiles

Saliva is a readily accessible and informative biofluid, making it ideal for the early detection of a wide range of diseases including cardiovascular, renal, and autoimmune diseases, viral and bacterial infections and, importantly, cancers. Saliva-based diagnostics, particularly those based on metabolomics technology, are emerging and offer a promising clinical strategy, characterizing the association between salivary analytes and a particular disease. Here, we conducted a comprehensive metabolite analysis of saliva samples obtained from 215 individuals (69 oral, 18 pancreatic and 30 breast cancer patients, 11 periodontal disease patients and 87 healthy controls) using capillary electrophoresis time-of-flight mass spectrometry (CE-TOF-MS). We identified 57 principal metabolites that can be used to accurately predict the probability of being affected by each individual disease. Although small but significant correlations were found between the known patient characteristics and the quantified metabolites, the profiles manifested relatively higher concentrations of most of the metabolites detected in all three cancers in comparison with those in people with periodontal disease and control subjects. This suggests that cancer-specific signatures are embedded in saliva metabolites. Multiple logistic regression models yielded high area under the receiver-operating characteristic curves (AUCs) to discriminate healthy controls from each disease. The AUCs were 0.865 for oral cancer, 0.973 for breast cancer, 0.993 for pancreatic cancer, and 0.969 for periodontal diseases. The accuracy of the models was also high, with cross-validation AUCs of 0.810, 0.881, 0.994, and 0.954, respectively. Quantitative information for these 57 metabolites and their combinations enable us to predict disease susceptibility. These metabolites are promising biomarkers for medical screening.     

Developing a tool for noninvasive monitoring of renal allografts

Renal transplantation has emerged as the therapy of choice for many patients with end-stage renal disease. One of the major goals is to tailor immunosuppressive therapy to the individual needs of every patient at every time point post transplant, balancing the risk for rejection and over-immunosuppression. Such individualized treatment will require assays that can detect harmful processes in the allograft early and that can be measured repeatedly. In this review, advantages and disadvantages of current assays to monitor renal allografts noninvasively and how proteomic technology might contribute to the development of novel biomarkers to improve patient management will be discussed.