Novel autoimmune hepatitis-specific autoantigens identified using protein microarray technology

Identification of Anti-SNRPA as a Novel Serological Biomarker for Systemic Sclerosis Diagnosis

Systemic sclerosis (SSc) is a systemic autoimmune disorder that leads to vasculopathy and tissue fibrosis. A lack of reliable biomarkers has been a challenge for clinical diagnosis of the disease. We employed a protein array-based approach to identify and validate SSc-specific autoantibodies. Phase I involved profiled autoimmunity using human proteome microarray (HuProt arrays) with 90 serum samples: 40 patients with SSc, 30 patients diagnosed with autoimmune diseases, and 20 healthy subjects. In Phase II, we constructed a focused array with candidates identified antigens and used this to profile a much larger cohort comprised of serum samples. Finally, we used a western blot analysis to validate the serum of validated proteins with high signal values. Bioinformatics analysis allowed us to identify 113 candidate autoantigens that were significantly associated with SSc. This two-phase strategy allowed us to identify and validate anti-small nuclear ribonucleoprotein polypeptide A (SNRPA) as a novel SSc-specific serological biomarker. The observed positive rate of anti-SNRPA antibody in patients with SSc was 11.25%, which was significantly higher than that of any disease control group (3.33%) or healthy controls (1%). In conclusion, anti-SNRPA autoantibody serves as a novel biomarker for SSc diagnosis and may be promising for clinical applications.

Human antibody profiling technologies for autoimmune disease

Autoimmune diseases are caused by the break-down in self-tolerance mechanisms and can result in the generation of autoantibodies specific to human antigens. Human autoantigen profiling technologies such as solid surface arrays and display technologies are powerful high-throughput technologies utilised to discover and map novel autoantigens associated with disease. This review compares human autoantigen profiling technologies including the application of these approaches in chronic and post-infectious autoimmune disease. Each technology has advantages and limitations that should be considered when designing new projects to profile autoantibodies. Recent studies that have utilised these technologies across a range of diseases have highlighted marked heterogeneity in autoantibody specificity between individuals as a frequent feature. This individual heterogeneity suggests that epitope spreading maybe an important mechanism in the pathogenesis of autoimmune disease in general and likely contributes to inflammatory tissue damage and symptoms. Studies focused on identifying autoantibody biomarkers for diagnosis should use targeted data analysis to identify the rarer public epitopes and antigens, common between individuals. Thus, utilisation of human autoantigen profiling technology, combined with different analysis approaches, can illuminate both pathogenesis and biomarker discovery.

Serum Autoantibodies in Patients with Dry and Wet Age-Related Macular Degeneration

BACKGROUND

To assess the serum autoantibody profile in patients with dry and exudative age-related macular degeneration compared with healthy volunteers to detect potential biomarkers, e.g., markers for progression of the disease.

MATERIALS AND METHODS

IgG Immunoreactivities were compared in patients suffering from dry age-related macular degeneration (AMD) (n = 20), patients with treatment-naive exudative AMD (n = 29) and healthy volunteers (n = 21). Serum was analysed by customized antigen microarrays containing 61 antigens. The statistical analysis was performed by univariate and multivariate analysis of variance, predictive data-mining methods and artificial neuronal networks were used to detect specific autoantibody patterns.

RESULTS

The immunoreactivities of dry and wet AMD patients were significantly different from each other and from controls. One of the most prominently changed reactivity was against alpha-synuclein (p ≤ 0.0034), which is known from other neurodegenerative diseases. Furthermore, reactivities against glyceraldehyde-3-phosphat-dehydrogenase (p ≤ 0.031) and Annexin V (p ≤ 0.034), which performs a major role in apoptotic processes, were significantly changed. Some immunoreacitvities were antithetic regulated in wet and dry-AMD, such as Vesicle transport-related protein (VTI-B).

CONCLUSIONS

Comparison of autoantibody profiles in patients with dry and wet AMD revealed significantly altered immunoreactivities against proteins particularly found in immunological diseases, further neurodegenerative, apoptotic and autoimmune markers could be observed. A validation study has to explore if these antibody pattern can help to understand the underlying differences in pathogenesis, evaluate their prognostic value and if those could be possibly useful as additional therapeutic targets.

Research progress in protein microarrays: Focussing on cancer research

Although several effective treatment modalities have been developed for cancers, the morbidity and mortality associated with cancer continues to increase every year. As one of the most exciting emerging technologies, protein microarrays represent a powerful tool in the field of cancer research because of their advantages such as high throughput, small sample usage, more flexibility, high sensitivity and direct readout of results. In this review, we focus on the research progress in four types of protein microarrays (proteome microarray, antibody microarray, lectin microarray and reversed protein array) with emphasis on their application in cancer research. Finally, we discuss the current challenges faced by protein microarrays and directions for future developments. We firmly believe that this novel systems biology research tool holds immense potential in cancer research and will become an irreplaceable tool in this field.

B cells in autoimmune hepatitis: bystanders or central players?

B cells are central for the adaptive immune system to mount successful immune responses not only as antibody producers but also as regulators of cellular immunity. These multifaceted features are also reflected in autoimmunity where autoreactive B cells can fuel disease by production of cytotoxic autoantibodies, presentation of autoantigens to autoreactive T cells, and secretion of cytokines and chemokines that either promote detrimental immune activation or impair regulatory T and B cells. The role of B cells and autoantibodies in autoimmune hepatitis (AIH) have been controversially discussed, with typical autoantibodies and hypergammaglobulinemia indicating a key role, while strong HLA class II association suggests T cells as key players. In this review, we summarize current knowledge on B cells in AIH and how different B cell subpopulations may drive AIH progression beyond autoantibodies. We also discuss recent findings of B cell-directed therapies in AIH.

Quantification of polyreactive immunoglobulin G facilitates the diagnosis of autoimmune hepatitis

BACKGROUND AND AIMS

Detection of autoantibodies is a mainstay of diagnosing autoimmune hepatitis (AIH). However, conventional autoantibodies for the workup of AIH lack either sensitivity or specificity, leading to substantial diagnostic uncertainty. We aimed to identify more accurate serological markers of AIH with a protein macroarray.

APPROACH AND RESULTS

During the search for more-precise autoantibodies to distinguish AIH from non-AIH liver diseases (non-AIH-LD), IgG antibodies with binding capacities to many human and foreign proteins were identified with a protein macroarray and confirmed with solid-phase ELISAs in AIH patients. Subsequently, polyreactive IgG (pIgG) was exemplarily quantified by reactivity against human huntingtin-interacting protein 1-related protein in bovine serum albumin blocked ELISA (HIP1R/BSA). The diagnostic fidelity of HIP1R/BSA binding pIgG to diagnose AIH was assessed in a retrospective training, a retrospective multicenter validation, and a prospective validation cohort in cryoconserved samples from 1,568 adults from 10 centers from eight countries. Reactivity against HIP1R/BSA had a 25% and 14% higher specificity to diagnose AIH than conventional antinuclear and antismooth muscle antibodies, a significantly higher sensitivity than liver kidney microsomal antibodies and antisoluble liver antigen/liver pancreas antigen, and a 12%-20% higher accuracy than conventional autoantibodies. Importantly, HIP1R/BSA reactivity was present in up to 88% of patients with seronegative AIH and in up to 71% of AIH patients with normal IgG levels. Under therapy, pIgG returns to background levels of non-AIH-LD.

CONCLUSIONS

pIgG could be used as a promising marker to improve the diagnostic workup of liver diseases with a higher specificity for AIH compared to conventional autoantibodies and a utility in autoantibody-negative AIH. Likewise, pIgG could be a major source of assay interference in untreated AIH.

Applications of Protein Microarrays in Biomarker Discovery for Autoimmune Diseases

Dysregulated autoantibodies and cytokines were deemed to provide important cues for potential illnesses, such as various carcinomas and autoimmune diseases. Increasing biotechnological approaches have been applied to screen and identify the specific alterations of these biomolecules as distinctive biomarkers in diseases, especially autoimmune diseases. As a versatile and robust platform, protein microarray technology allows researchers to easily profile dysregulated autoantibodies and cytokines associated with autoimmune diseases using various biological specimens, mainly serum samples. Here, we summarize the applications of protein microarrays in biomarker discovery for autoimmune diseases. In addition, the key issues in the process of using this approach are presented for improving future studies.

Developments and Applications of Functional Protein Microarrays

Protein microarrays are crucial tools in the study of proteins in an unbiased, high-throughput manner, as they allow for characterization of up to thousands of individually purified proteins in parallel. The adaptability of this technology has enabled its use in a wide variety of applications, including the study of proteome-wide molecular interactions, analysis of post-translational modifications, identification of novel drug targets, and examination of pathogen-host interactions. In addition, the technology has also been shown to be useful in profiling antibody specificity, as well as in the discovery of novel biomarkers, especially for autoimmune diseases and cancers. In this review, we will summarize the developments that have been made in protein microarray technology in both in basic and translational research over the past decade. We will also introduce a novel membrane protein array, the GPCR-VirD array, and discuss the future directions of functional protein microarrays.

Low Level Antibodies Against Alpha-Tropomyosin Are Associated With Increased Risk of Coronary Heart Disease

Objective

Natural autoantibodies have been implicated to play a key role in the pathogenesis of coronary heart disease (CHD) because they augment autoimmune activation. The aim of this study was to identify novel specific autoantibodies of CHD, and analyze the relationship between their levels and CHD risk indicators.

Approach and Results

First, clinical data and sera from CHD patients were collected. Then, one protein microarray containing 37 proteins that represent candidate autoantigens was developed. The arrays were used to profile autoantibodies in randomly selected sera from 35 samples (20 CHD patients, and 15 healthy controls). After that, microarray data were analyzed and autoantibodies for CHD were screened out. Then, ELISA detection was conducted to validate the differentiable autoantibodies using larger numbers of serum samples (131 CHD patients, and 131 healthy controls). Finally, the associations of antibodies with CHD risk indicator parameters were assessed. Inter-group comparison by microarray indicated that three CHD novel autoantibodies, including glucose-6-phosphate isomerase (G6PI), alpha-tropomyosin (TPM1), and heterogeneous nuclear ribonucleoprotein D-like (HnRNPDL), were significantly (P < 0.05) increased when compared with the healthy controls. Moreover, a significant increase of IgG autoantibodies for these three autoantigens was confirmed in CHD patients by ELISA (P < 0.0001). The correction analysis revealed a negative correlation of anti-TPM1 antibody levels and total cholesterol (P = 0.0034), and low-density lipoprotein cholesterol (P = 0.0086), respectively.

Conclusion

G6PI, TPM1, and HnRNPDL were CHD natural autoantigens, and serum anti-TPM1 antibody could be used as a potential marker to predict the risk for CHD patients.

Two novel protein chips for the detection of antibodies against porcine parvovirus

Background

PPV is one of the most important pathogens causing porcine reproductive disorder. It has been shown in clinical cases to be a commonly mixed infection with other important swine diseases which can aggravate the severity of the disease and bring serious economic losses to the pig industry. Serological methods, such as hemagglutination inhibition assays (HAI), serum neutralization (SN), and the modified direct complement-fixation (MDCF) test were utilized earlier, whereas the enzyme-linked immunosorbent assay (ELISA) is the most frequently applied assay to detect PPV-specific antibodies.

Results

We establish the visible protein chip and the cyanine dye 3 (Cy3)-labeled protein chip to detect the clinical serum from pigs. In this study, the recombinant protein VP2 of PPV was expressed in E.coli, purified with nickel magnetic beads, and then printed onto epoxy-coated glass slides for preparation of the protein chip. After a series of experiments, the conditions of antigen protein concentration, incubation time of primary antibody or secondary antibody, and optimal serum dilution fold were optimized, resulting in a successful visible protein chip and Cy3-labeled protein chip. The results showed that the positive serum, diluted up to 6000-fold, can be detected by the visible protein chip, and the positive serum, diluted up to 12,800-fold, can be detected by the Cy3-labeled protein chip, suggesting the high sensitivity of these protein chips. Moreover, the positive detection ratio, sensitivity, and specificity of these two kinds of protein chips were higher than those of commercial ELISA antibody detection kits.

Conclusion

Overall, these two protein chips can be used to rapidly diagnose clinical samples with high throughput.

High prevalence of a variety of autoantibodies in a population of hepatitis C virus-infected individuals

Hepatitis C virus (HCV) infection has been related to self-reactivity, extrahepatic manifestations and autoimmune diseases. The main goals of this work were to study the prevalence of autoantibodies and their relationship with viral titers and biochemical markers of hepatic damage in patients infected with HCV. Autoantibodies (ANA, AMA, SMA, APC, LKM, DNAds, ANCA, ATG and RF) were determined in 73 individuals with chronic HCV infection and 44 healthy volunteers. The presence of these antibodies was related to demographic variables, viral titers and biochemical parameters. A high prevalence of autoantibodies, particularly for RF, that was associated with female gender was observed in HCV-infected patients. In addition, SMA, ANA and ATG showed increased frequencies in HCV infection. Interestingly, the concurrent detection of SMA and more than one autoantibody was associated with high gGT levels. Notably, concurrent higher gGT, HCV and SMA levels were observed in male patients as compared to their female counterparts. These results indicate a relationship between HCV infection and the concurrent detection of various autoantibodies in the absence of symptoms of autoimmune diseases. They also suggest a link among the presence of a variety of autoantibodies simultaneously with SMA, increased gGT levels and HCV titers in a population of male patients.

Advances in cell-free protein array methods

INTRODUCTION

Cell-free protein microarrays represent a special form of protein microarray which display proteins made fresh at the time of the experiment, avoiding storage and denaturation. They have been used increasingly in basic and translational research over the past decade to study protein-protein interactions, the pathogen-host relationship, post-translational modifications, and antibody biomarkers of different human diseases. Their role in the first blood-based diagnostic test for early stage breast cancer highlights their value in managing human health. Cell-free protein microarrays will continue to evolve to become widespread tools for research and clinical management. Areas covered: We review the advantages and disadvantages of different cell-free protein arrays, with an emphasis on the methods that have been studied in the last five years. We also discuss the applications of each microarray method. Expert commentary: Given the growing roles and impact of cell-free protein microarrays in research and medicine, we discuss: 1) the current technical and practical limitations of cell-free protein microarrays; 2) the biomarker discovery and verification pipeline using protein microarrays; and 3) how cell-free protein microarrays will advance over the next five years, both in their technology and applications.

PTMA, a new identified autoantigen for oral submucous fibrosis, regulates oral submucous fibroblast proliferation and extracellular matrix

Oral submucous fibrosis (OSF) is a chronic, insidious disease. The presence of autoantibodies in sera of OSF patients is the most characteristic and direct evidence of OSF being an autoimmune disease. To identify the specific autoantigens which could contribute to antibody production, the Human Proteome Microarrays composed of 19000 full-length unique proteins were employed. 45 proteins correlated with OSF were identified. To validate these results, we used ELISA to validate 28 OSF-associated autoantigens in extended samples. 8 autoantigens were positive in OSF serum with high frequency compared to the healthy controls. Moreover, the mRNA expression of 8 candidates was up-regulated in OSF oral submucous tissues; among them, the protein level of PTMA, the one with the highest positive frequency, was also increased. Through searching the Bioinformatics Public Database and performing the Spearman’s rank correlation analysis, we observed that PTMA was positively correlated with fibrosis-related TGFβ1 and SMAD4, the downstream gene of TGFβ1. In TGFβ1-induced fibrosis model of primary human oral submucous fibroblast, PTMA knockdown reversed TGFβ1-induced fibrosis process through inhibiting the cell viability and proliferation of fibroblast, reducing the protein levels of PTMA, Collagen I, α-SMA and MMP9 and increasing the protein levels of SMAD4. In contrast, PTMA overexpression enhanced TGFβ1-induced fibrosis process. Taken together, PTMA is involved in TGFβ1-induced fibrosis in the primary human submucous fibroblast by regulating the expression of ECM-related markers and the downstream genes of TGFβ1. In conclusion, PTMA presents an essential autoantigen during OSF process; targeting PTMA might be a promising strategy for OSF treatment.

Global Analysis of SUMO-Binding Proteins Identifies SUMOylation as a Key Regulator of the INO80 Chromatin Remodeling Complex

SUMOylation is a critical regulator of a broad range of cellular processes, and is thought to do so in part by modulation of protein interaction. To comprehensively identify human proteins whose interaction is modulated by SUMOylation, we developed an in vitro binding assay using human proteome microarrays to identify targets of SUMO1 and SUMO2. We then integrated these results with protein SUMOylation and protein-protein interaction data to perform network motif analysis. We focused on a single network motif we termed a SUMOmodPPI (SUMO-modulated Protein-Protein Interaction) that included the INO80 chromatin remodeling complex subunits TFPT and INO80E. We validated the SUMO-binding activity of INO80E, and showed that TFPT is a SUMO substrate both in vitro and in vivo We then demonstrated a key role for SUMOylation in mediating the interaction between these two proteins, both in vitro and in vivo By demonstrating a key role for SUMOylation in regulating the INO80 chromatin remodeling complex, this work illustrates the power of bioinformatics analysis of large data sets in predicting novel biological phenomena.

Myalgic encephalomyelitis/chronic fatigue syndrome and gulf war illness patients exhibit increased humoral responses to the herpesviruses-encoded dUTPase: Implications in disease pathophysiology

Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) and Gulf War Illness (GWI) are debilitating diseases with overlapping symptomology and there are currently no validated tests for definitive diagnosis of either syndrome. While there is evidence supporting the premise that some herpesviruses may act as possible triggers of ME/CFS, the involvement of herpesviruses in the pathophysiology of GWI has not been studied in spite of a higher prevalence of ME/CFS in these patients. We have previously demonstrated that the deoxyuridine triphosphate nucleotidohydrolases (dUTPase) encoded by Epstein-Barr virus (EBV), human herpesvirus-6 (HHV-6), and varicella-zoster virus (VZV) possess novel functions in innate and adaptive immunity. The results of this study demonstrate that a significant percentage of patients with ME/CFS (30.91-52.7%) and GWI (29.34%) are simultaneously producing antibodies against multiple human herpesviruses-encoded dUTPases and/or the human dUTPase when compared to controls (17.21%). GWI patients exhibited significantly higher levels of antibodies to the HHV-6 and human dUTPases than controls (P = 0.0053 and P = 0.0036, respectively), while the ME/CFS cohort had higher anti-EBV-dUTPase antibodies than in both GWI patients (P = 0.0008) and controls (P < 0.0001) as well as significantly higher anti-human dUTPase antibodies than in controls (P = 0.0241). These results suggest that screening of patients' sera for the presence of various combinations of anti-dUTPase antibodies could be used as potential biomarkers to help identify/distinguish patients with these syndromes and better direct treatment.

Protein Array-based Approaches for Biomarker Discovery in Cancer

Biomarkers are deemed to be potential tools in early diagnosis, therapeutic monitoring, and prognosis evaluation for cancer, with simplicity as well as economic advantages compared with computed tomography and biopsy. However, most of the current cancer biomarkers present insufficient sensitivity as well as specificity. Therefore, there is urgent requirement for the discovery of biomarkers for cancer. As one of the most exciting emerging technologies, protein array provides a versatile and robust platform in cancer proteomics research because it shows tremendous advantages of miniaturized features, high throughput, and sensitive detections in last decades. Here, we will present a relatively complete picture on the characteristics and advance of different types of protein arrays in application for biomarker discovery in cancer, and give the future perspectives in this area of research.

Immunoproteomics technologies in the discovery of autoantigens in autoimmune diseases

Proteomics technologies are often used for the identification of protein targets of the immune system. Here, we discuss the immunoproteomics technologies used for the discovery of autoantigens in autoimmune diseases where immune system dysregulation plays a central role in disease onset and progression. These autoantigens and associated autoantibodies can be used as potential biomarkers for disease diagnostics, prognostics and predicting/monitoring drug responsiveness (theranostics). Here, we compare a variety of methods such as mass spectrometry (MS)-based [serological proteome analysis (SERPA), antibody mediated identification of antigens (AMIDA), circulating immune complexome (CIC) analysis, surface enhanced laser desorption/ionization-time of flight (SELDI-TOF)], nucleic acid based serological analysis of antigens by recombinant cDNA expression cloning (SEREX), phage immunoprecipitation sequencing (PhIP-seq) and array-based immunoscreening (proteomic microarrays), luciferase immunoprecipitation systems (LIPS), nucleic acid programmable protein array (NAPPA) methods. We also review the relevance of immunoproteomic data generated in the last 10 years, with a focus on the aforementioned MS based methods.

Mining, visualizing and comparing multidimensional biomolecular data using the Genomics Data Miner (GMine) Web-Server

Genomics Data Miner (GMine) is a user-friendly online software that allows non-experts to mine, cluster and compare multidimensional biomolecular datasets. Various powerful visualization techniques are provided, generating high quality figures that can be directly incorporated into scientific publications. Robust and comprehensive analyses are provided via a broad range of data-mining techniques, including univariate and multivariate statistical analysis, supervised learning, correlation networks, clustering and multivariable regression. The software has a focus on multivariate techniques, which can attribute variance in the measurements to multiple explanatory variables and confounders. Various normalization methods are provided. Extensive help pages and a tutorial are available via a wiki server. Using GMine we reanalyzed proteome microarray data of host antibody response against Plasmodium falciparum. Our results support the hypothesis that immunity to malaria is a higher-order phenomenon related to a pattern of responses and not attributable to any single antigen. We also analyzed gene expression across resting and activated T cells, identifying many immune-related genes with differential expression. This highlights both the plasticity of T cells and the operation of a hardwired activation program. These application examples demonstrate that GMine facilitates an accurate and in-depth analysis of complex molecular datasets, including genomics, transcriptomics and proteomics data.

Antigen arrays for profiling autoantibody repertoires

Autoantibodies are a key component for the diagnosis, prognosis and monitoring of various diseases. In order to discover novel autoantibody targets, highly multiplexed assays based on antigen arrays hold a great potential and provide possibilities to analyze hundreds of body fluid samples for their reactivity pattern against thousands of antigens in parallel. Here, we provide an overview of the available technologies for producing antigen arrays, highlight some of the technical and methodological considerations and discuss their applications as discovery tools. Together with recent studies utilizing antigen arrays, we give an overview on how the different types of antigen arrays have and will continue to deliver novel insights into autoimmune diseases among several others.

Transitioning from Idiopathic to Explainable Autoimmune Hepatitis

Autoimmune hepatitis lacks an identifiable cause, and its diagnosis requires the exclusion of etiologically defined diseases that resemble it. Insights into its pathogenesis are moving autoimmune hepatitis from an idiopathic to explainable disease, and the goal of this review is to describe the insights that are hastening this transition. Two types of autoimmune hepatitis are justified by serological markers, but they also have distinctive genetic associations (DRB1 and DQB1 genes) and autoantigens. DRB1 alleles are the principal susceptibility factors in white adults, and a six amino acid sequence encoded in the antigen-binding groove of class II molecules of the major histocompatibility complex can influence the selection of autoantigens. Polymorphisms, including variants of SH2B3 and CARD10 genes, may affect immune reactivity and disease severity. The cytochrome mono-oxygenase, CYP2D6, is the autoantigen associated with type 2 autoimmune hepatitis, and it shares homologies with multiple viruses that might promote self-intolerance by molecular mimicry. Chemokines, especially CXCL9 and CXCL10, orchestrate the migration of effector cells to sites of injury and are associated with disease severity. Cells of the innate and adaptive immune responses promote tissue damage, and possible deficiencies in the number and function of regulatory T cells may facilitate the injurious process. Receptor-mediated apoptosis is the principal mechanism of hepatocyte loss, and cell-mediated and antibody-dependent mechanisms of cytotoxicity also contribute. Insights that explain autoimmune hepatitis will allow triggering exogenous antigens to be characterized, risk management to be improved, prognostic indices to be refined, and site-specific therapeutic interventions to emerge.

Characterization of monoclonal antibody's binding kinetics using oblique-incidence reflectivity difference approach

Monoclonal antibodies (mAbs) against human proteins are the primary protein capture reagents for basic research, diagnosis, and molecular therapeutics. The 2 most important attributes of mAbs used in all of these applications are their specificity and avidity. While specificity of a mAb raised against a human protein can be readily defined based on its binding profile on a human proteome microarray, it has been a challenge to determine avidity values for mAbs in a high-throughput and cost-effective fashion. To undertake this challenge, we employed the oblique-incidence reflectivity difference (OIRD) platform to characterize mAbs in a protein microarray format. We first systematically determined the K_on and K_off values of 50 mAbs measured with the OIRD method and deduced the avidity values. Second, we established a multiplexed approach that simultaneously measured avidity values of a mixture of 9 mono-specific mAbs that do not cross-react to the antigens. Third, we demonstrated that avidity values of a group of mAbs could be sequentially determined using a flow-cell device. Finally, we implemented a sequential competition assay that allowed us to bin multiple mAbs that recognize the same antigens. Our study demonstrated that OIRD offers a high-throughput and cost-effective platform for characterization of the binding kinetics of mAbs.

Two of Them Do It Better: Novel Serum Biomarkers Improve Autoimmune Hepatitis Diagnosis

BACKGROUND

Autoimmune hepatitis (AIH) is a chronic liver disease of unknown aetiology and characterized by continuing hepatocellular inflammation and necrosis. Autoantibodies represent accessible markers to measure the adaptive immune responses in the clinical investigation. Protein microarrays have become an important tool to discriminate the disease state from control groups, even though there is no agreed-upon standard to analyze the results.

RESULTS

In the present study 15 sera of patients with AIH and 78 healthy donors (HD) have been tested against 1626 proteins by an in house-developed array. Using a Partial Least Squares Discriminant Analysis (PLS-DA) the resulting data interpretation led to the identification of both new and previously identified proteins. Two new proteins AHPA9419 and Chondroadherin precursor (UNQ9419 and CHAD, respectively), and previously identified candidates as well, have been confirmed in a validation phase by DELFIA assay using a new cohort of AIH patients. A receiver operating characteristic analysis was used for the evaluation of biomarker candidates. The sensitivity of each autoantigen in AIH ranged from 65 to 88%; moreover, when the combination of the two new autoantigens was analyzed, the sensitivity increased to 95%.

CONCLUSIONS

Our findings demonstrate that the detection of autoantibodies against the two autoantigens could improve the performance in discriminating AIH patients from control classes and in combination with previously identified autoantigens and they could be used in diagnostic/prognostic markers.

A serum metabolomic analysis for diagnosis and biomarker discovery of primary biliary cirrhosis and autoimmune hepatitis

BACKGROUND

Because of the diversity of the clinical and laboratory manifestations, the diagnosis of autoimmune liver disease (AILD) remains a challenge in clinical practice. The value of metabolomics has been studied in the diagnosis of many diseases. The present study aimed to determine whether the metabolic profiles, based on ultraperformance liquid chromatography-mass spectrometry (UPLC-MS), differed between autoimmune hepatitis (AIH) and primary biliary cirrhosis (PBC), to identify specific metabolomic markers, and to establish a model for the diagnosis of AIH and PBC.

METHODS

Serum samples were collected from 20 patients with PBC, 19 patients with AIH, and 25 healthy individuals. UPLC-MS data of the samples were analyzed using principal component analysis, partial least squares discrimination analysis and orthogonal partial least squares discrimination analysis.

RESULTS

The partial least squares discrimination analysis model (R2Y=0.991, Q2=0.943) was established between the AIH and PBC groups and exhibited both sensitivity and specificity of 100%. Five groups of biomarkers were identified, including bile acids, free fatty acids, phosphatidylcholines, lysolecithins and sphingomyelin. Bile acids significantly increased in the AIH and PBC groups compared with the healthy control group. The other biomarkers decreased in the AIH and PBC groups compared with those in the healthy control group. In addition, the biomarkers were downregulated in the AIH group compared with the PBC group.

CONCLUSIONS

The biomarkers identified revealed the pathophysiological changes in AILD and helped to discriminate between AIH and PBC. The predictability of this method suggests its potential application in the diagnosis of AILD.

Serological comparative proteomics analysis of mitochondrial autoantibody-negative and -positive primary biliary cirrhosis

Here, we investigated the pathogenesis of primary biliary cirrhosis (PBC) by using 2D-DIGE to analyze serological differences between anti-mitochondrial antibody (AMA)-positive and -negative PBC patients. The study comprised 30 patients with PBC; 20 AMA-positive and ten AMA-negative patients matched for age, sex, and pathological stage. A screening group (four AMA-positive and four AMA-negative patients) was used for 2D-DIGE. Protein spots that were differently abundant between the two groups were identified via dye intensity and MS. Nine candidate proteins were identified from these spots. Western blotting was used to verify two of the identified proteins, serum amyloid P-component (SAP) and vitronectin (VN). VN levels were significantly higher in the sera of AMA-negative PBC patients (p < 0.01), whereas no significant difference was found between the two groups for SAP. To our knowledge, this is the first study to use serological comparative proteomics to explore differences between AMA-positive and -negative PBC patients. VN levels were higher in AMA-negative PBC patients, and this finding could be related to the more severe bile duct destruction observed in this group.

Autoantibody profiling on human proteome microarray for biomarker discovery in cerebrospinal fluid and sera of neuropsychiatric lupus

Autoantibodies in cerebrospinal fluid (CSF) from patients with neuropsychiatric systemic lupus erythematosus (NPSLE) may be potential biomarkers for prediction, diagnosis, or prognosis of NPSLE. We used a human proteome microarray with~17,000 unique full-length human proteins to investigate autoantibodies associated with NPSLE. Twenty-nine CSF specimens from 12 NPSLE, 7 non-NPSLE, and 10 control (non-systemic lupus erythematosus)patients were screened for NPSLE-associated autoantibodies with proteome microarrays. A focused autoantigen microarray of candidate NPSLE autoantigens was applied to profile a larger cohort of CSF with patient-matched sera. We identified 137 autoantigens associated with NPSLE. Ingenuity Pathway Analysis revealed that these autoantigens were enriched for functions involved in neurological diseases (score = 43).Anti-proliferating cell nuclear antigen (PCNA) was found in the CSF of NPSLE and non-NPSLE patients. The positive rates of 4 autoantibodies in CSF specimens were significantly different between the SLE (i.e., NPSLE and non-NPSLE) and control groups: anti-ribosomal protein RPLP0, anti-RPLP1, anti-RPLP2, and anti-TROVE2 (also known as anti-Ro/SS-A). The positive rate for anti-SS-A associated with NPSLE was higher than that for non-NPSLE (31.11% cf. 10.71%; P = 0.045).Further analysis showed that anti-SS-A in CSF specimens was related to neuropsychiatric syndromes of the central nervous system in SLE (P = 0.009). Analysis with Spearman’s rank correlation coefficient indicated that the titers of anti-RPLP2 and anti-SS-A in paired CSF and serum specimens significantly correlated. Human proteome microarrays offer a powerful platform to discover novel autoantibodies in CSF samples. Anti-SS-A autoantibodies may be potential CSF markers for NPSLE.

Up-to-Date Applications of Microarrays and Their Way to Commercialization

This review addresses up-to-date applications of Protein Microarrays. Protein Microarrays play a significant role in basic research as well as in clinical applications and are applicable in a lot of fields, e.g., DNA, proteins and small molecules. Additionally they are on the way to enter clinics in routine diagnostics. Protein Microarrays can be powerful tools to improve healthcare. An overview of basic characteristics to mediate essential knowledge of this technique is given. To reach this goal, some challenges still have to be addressed. A few applications of Protein Microarrays in a medical context are shown. Finally, an outlook, where the potential of Protein Microarrays is depicted and speculations how the future of Protein Microarrays will look like are made.

Antibody profiling of bipolar disorder using Escherichia coli proteome microarrays

To profile plasma antibodies of patients with bipolar disorder (BD), an E. coli proteome microarray comprising ca. 4200 proteins was used to analyze antibody differences between BD patients and mentally healthy controls (HCs). The plasmas of HCs and patients aged 18-45 years with bipolar I disorder (DSM-IV) in acute mania (BD-A) along with remission (BD-R) were collected. The initial samples consisting of 19 BD-A, 20 BD-R, and 20 HCs were probed with the microarrays. After selecting protein hits that recognized the antibody differences between BD and HC, the proteins were purified to construct BD focus arrays for training diagnosis committees and validation. Additional six BD-A, six BD-R, six HCs, and nine schizophrenic disorder (SZ, as another psychiatric control) samples were individually probed with the BD focus arrays. The trained diagnosis committee in BD-A versus HC combined top six proteins, including rpoA, thrA, flhB, yfcI, ycdU, and ydjL. However, the optimized committees in BD-R versus HC and BD-A versus BD-R were of low accuracy (< 0.6). In the single blind test using another four BD-A, four HC, and four SZ samples, the committee of BD-A versus HC was able to classify BD-A versus HC and SZ with 75% sensitivity and 80% specificity that both HC and SZ were regarded as negative controls. The consensus motif of the six proteins, which form the committee of BD-A versus HC, is [KE]DIL[AG]L[LV]I[NL][IC][SVKH]G[LV][VN][LV] by Gapped Local Alignment of Motifs. We demonstrated that the E. coli proteome microarray is capable of screening BD plasma antibody differences and the selected proteins committee was successfully used for BD diagnosis with 79% accuracy.

Identification of SUMO E3 ligase-specific substrates using the HuProt human proteome microarray

The functional protein microarray is a powerful and versatile systems biology and proteomics tool that allows the rapid activity profiling of thousands of proteins in parallel. We have recently developed a human proteome array, the HuProt array, which includes ~80 % of all the full-length proteins of the human proteome. In one recent application of the HuProt array, we identified numerous SUMO E3 ligase-dependent SUMOylation substrates. For many SUMO E3 ligases, only a small number of substrates have been identified and the target specificities of these ligases therefore remain poorly defined. In this protocol, we outline a method we developed using the HuProt array to screen the human proteome to identify novel SUMO E3 ligase substrates recognized by specific E3 ligases.

Autoimmune profiling with protein microarrays in clinical applications

In recent years, knowledge about immune-related disorders has substantially increased, especially in the field of central nervous system (CNS) disorders. Recent innovations in protein-related microarray technology have enabled the analysis of interactions between numerous samples and up to 20,000 targets. Antibodies directed against ion channels, receptors and other synaptic proteins have been identified, and their causative roles in different disorders have been identified. Knowledge about immunological disorders is likely to expand further as more antibody targets are discovered. Therefore, protein microarrays may become an established tool for routine diagnostic procedures in the future. The identification of relevant target proteins requires the development of new strategies to handle and process vast quantities of data so that these data can be evaluated and correlated with relevant clinical issues, such as disease progression, clinical manifestations and prognostic factors. This review will mainly focus on new protein array technologies, which allow the processing of a large number of samples, and their various applications with a deeper insight into their potential use as diagnostic tools in neurodegenerative diseases and other diseases. This article is part of a Special Issue entitled: Biomarkers: A Proteomic Challenge.

Serological autoantibody profiling of type 1 diabetes by protein arrays

The need for biomarkers that illuminate the pathophysiology of type 1 diabetes (T1D), enhance early diagnosis and provide additional avenues for therapeutic intervention is well recognized in the scientific community. We conducted a proteome-scale, two-stage serological AAb screening followed by an independent validation study. In the first stage, the immunoreactivity was compared between T1D cases and healthy controls against ~6000 human proteins using the nucleic acid programmable protein array (NAPPA). Genes identified with higher signal intensities in patients were challenged with a larger sample set during the second stage. Statistical analysis revealed 26 novel autoantigens and a known T1D-associated autoantigen. During validation, we verified the presence of AAbs to dual specificity tyrosine-phosphorylation-regulated kinase 2 (DYRK2) using the Luciferase ImmunoPrecipitation System (LIPS) assay (36% sensitivity, 98% specificity). The AUC for a combination of DYRK2A and the classical T1D AAb IA-2A was 0.90 compared to 0.72 for DYRK2A and 0.64 for IA-2A alone. This is the first systematic screening for seroreactivity against a large number of human proteins in T1D patients. We demonstrated the application of protein microarrays to identify novel autoantigens in T1D, expanded the current T1D "autoantigenome" and help fulfill the goal of searching for novel biomarker candidates for T1D.

BIOLOGICAL SIGNIFICANCE

Protein microarrays provide a high-throughput platform that enables the profiling of serum antibodies to a large number of protein antigens. The value of AAb biomarkers in diagnosis, prognosis and treatment is well recognized in autoimmune diseases including T1D. We performed a systematic screening for new T1D-associated autoantigens by adapting the innovative protein array platform NAPPA. We believe that the discovery in this study will add information on candidate autoantigens that could potentially improve the diagnosis and help uncover the pathophysiology of T1D. The successful use of NAPPA for T1D AAb profiling will open the window for larger studies including more human antigen genes and other autoimmune diseases.

[Review of overlap syndromes in autoimmune liver diseases. Diagnostic and therapeutic difficulties]

Overlap syndromes are biochemical, serological, histological and radiological overlaps across the classic autoimmune liver diseases in the presence of autoimmun hepatitis and primary biliary cirrhosis or primary sclerosing cholangitis. The exact prevalence of the disease is not known, but it may vary between 5% and 20%. Because it has no generally accepted diagnostic criteria, clinical signs, biochemical, serological, radiological and histological findings are evaluated together. Treatment depends on the predominant feature of the overlap syndrome; ursodeoxycholic acid and/or immunsuppressive (corticosteroid) treatment are used, based on observations from retrospective, non-randomized studies.

A new type of protein chip to detect hepatocellular carcinoma-related autoimmune antibodies in the sera of hepatitis C virus-positive patients

Background

We report here a new type of protein chip to detect antibodies in sera. This chip method was used to a prototype created to detect hepatocellular carcinoma (HCC) -related autoantibodies in the sera of hepatitis C virus (HCV) infected individuals.

Results

Five cysteine-tagged (Cys-tag) and green fluorescent protein (GFP)-fused recombinant heat shock protein 70 (HSP70), superoxide dismutase 2 (SOD2), and peroxiredoxin 6 (PRDX6), were spotted and immobilized on maleimide-incorporated diamond-like carbon (DLC) substrates. The antibodies in diluted sera were trapped by these proteins at each spot on the chip, and visualized by a fluorescence-conjugated anti-human IgG. The total immobilized protein level of each spot was detected with anti-GFP mouse IgG and a fluorescence-conjugated secondary anti-mouse IgG. The ratio between the two fluorescence intensities was used to quantify autoantibody levels in each serum sample. Heat treatment of the chip in a solution of denaturing and reducing agents, before serum-incubation, improved autoantibody detection. We tested serum samples from healthy individuals and HCC patients using the chips. The HSP70 autoantibodies were found at high levels in sera from HCV-positive HCC patients, but not in HCV-negative sera.

Conclusion

This protein chip system may have useful properties to capture a specific set of antibodies for predicting the onset of particular cancers such as HCC in HCV-infected individuals.

Complementary serum proteomic analysis of autoimmune hepatitis in mice and patients

Background

Autoimmune hepatitis (AIH) is a chronic liver disease caused by inflammation of the liver. The etiology of AIH remains elusive, and there are no reliable serum biomarkers.

Methods

In order to identify candidate biomarkers, 2-DE analysis of serum proteins was performed using a mouse model of AIH induced by treatment with concanavalin A (ConA). To enrich samples for low abundance molecules a commercial albumin removal reagent was used. In an independent analysis, candidate biomarkers were identified in AIH patient’s serum by a targeted iTRAQ (isobaric tags for relative and absolute quantification) identification. Candidates were validated in independent cohorts of ConA treated mice and AIH patients by ELISA (enzyme-linked immuno sorbent assay).

Results

Nine proteins were differentially expressed in AIH mice treated with con-A. Two of these, the third component of complement (C3) and alpha-2-macroglobulin (A2M) were also up-regulated in AIH patient’s sera by a targeted iTRAQ identification. In separate validation studies, serum C3 and A2M levels were increased in mice with ConA treatment after 20-40 h and in 34 AIH patients in a subgroup analysis, females with AIH aged 20–50 years old displayed the largest increases in serum A2M level. Biological network analysis implements the complement cascade and protease inhibitors in the pathogenesis of AIH.

Conclusion

The serum proteins C3 and A2M are increased both in a mouse model and in patients with AIH by both 2-DE and iTRAQ methods. This integrated serum proteomics investigation should be applicable for translational researchers to study other medical conditions.

Overview of protein microarrays

Protein microarray technology is an emerging field that provides a versatile platform for the characterization of hundreds of thousands of proteins in a highly parallel and high-throughput manner. Protein microarrays are composed of two major classes: analytical and functional. In addition, tissue or cell lysates can also be fractionated and spotted on a slide to form a reverse-phase protein microarray. Applications of protein microarrays, especially functional protein microarrays, have flourished over the past decade as the fabrication technology has matured. In this unit, advances in protein microarray technologies are reviewed, and then a series of examples are presented to illustrate the applications of analytical and functional protein microarrays in both basic and clinical research. Relevant areas of research include the detection of various binding properties of proteins, the study of protein post-translational modifications, the analysis of host-microbe interactions, profiling antibody specificity, and the identification of biomarkers in autoimmune diseases.

Does autoimmunity play a part in the pathogenesis of glaucoma?

Glaucoma is a chronic neurodegenerative disease and one of the leading causes of blindness. Several risk factors have been described, e.g. an elevated intraocular pressure (IOP), oxidative stress or mitochondrial dysfunction. Additionally, alterations in serum antibody profiles of glaucoma patients, upregulation (e.g. anti-HSP60, anti-MBP) and downregulation (e.g. anti-14-3-3), have been described, but it still remains elusive if the autoantibodies seen in glaucoma are an epiphenomenon or causative. However, it is known that elicited autoimmunity causes retinal ganglion cell loss resulting in glaucomatous-like damage and according to the autoaggressive nature of some autoantibodies we found antibody deposits in human glaucomatous retinae in a pro-inflammatory environment. Furthermore, glaucomatous serum has the potential to influence neuroretinal cell regulatory processes. Importantly, we demonstrate that some autoantibodies hold neuroprotective potential for neuroretinal cells. The protective nature of autoantibodies and the molecular mechanisms underlying the very sensitive equilibrium between autoaggression and protection remain subject of future examinations and offer promising target sites for new therapeutic approaches. Additionally, the changes in antibody profiles could be used as highly sensitive and specific marker for diagnostics purposes. Early diagnosis and intervention in risk patients would offer the chance of early treatment and to slow down the progression of glaucoma and delay the resulting blindness.

Biomarker discovery for heterogeneous diseases

BACKGROUND

Modern genomic and proteomic studies reveal that many diseases are heterogeneous, comprising multiple different subtypes. The common notion that one biomarker can be predictive for all patients may need to be replaced by an understanding that each subtype has its own set of unique biomarkers, affecting how discovery studies are designed and analyzed.

METHODS

We used Monte Carlo simulation to measure and compare the performance of eight selection methods with homogeneous and heterogeneous diseases using both single-stage and two-stage designs. We also applied the selection methods in an actual proteomic biomarker screening study of heterogeneous breast cancer cases.

RESULTS

Different selection methods were optimal, and more than two-fold larger sample sizes were needed for heterogeneous diseases compared with homogeneous diseases. We also found that for larger studies, two-stage designs can achieve nearly the same statistical power as single-stage designs at significantly reduced cost.

CONCLUSIONS

We found that disease heterogeneity profoundly affected biomarker performance. We report sample size requirements and provide guidance on the design and analysis of biomarker discovery studies for both homogeneous and heterogeneous diseases.

IMPACT

We have shown that studies to identify biomarkers for the early detection of heterogeneous disease require different statistical selection methods and larger sample sizes than if the disease were homogeneous. These findings provide a methodologic platform for biomarker discovery of heterogeneous diseases.

Autoantibodies in liver disease: important clues for the diagnosis, disease activity and prognosis

It has been well established that numerous kinds of autoantibodies have been detected in liver disease. Some kinds of autoantibodies may be helpful in the diagnosis of autoimmune liver diseases including autoimmune hepatitis, primary biliary cirrhosis or primary sclerosing cholangitis. However, these autoantibodies are present even in sera of patients with viral hepatitis, drug-induced hepatitis, alcoholic liver disease, non-alcoholic fatty liver disease and hepatocelluar carcinoma as well as in sera of patients with autoimmune liver diseases. Other kinds of autoantibodies are recognized as predictive hallmarks for disease activity or prognosis in liver diseases. On the other hand, treatment with interferon initiates the production of several types of autoantibodies in patients with chronic hepatitis C virus infection. Some of autoantibodies induced by interferon may postulate the treatment outcome in those patients. Recent studies also revealed the close correlation between oxidative stress and the production of autoantibodies in liver diseases. This article primarily reviews the recent advances of autoantibodies in the liver diseases and discusses the clinical significance of these autoantibodies.

Interactome mapping: using protein microarray technology to reconstruct diverse protein networks

A major focus of systems biology is to characterize interactions between cellular components, in order to develop an accurate picture of the intricate networks within biological systems. Over the past decade, protein microarrays have greatly contributed to advances in proteomics and are becoming an important platform for systems biology. Protein microarrays are highly flexible, ranging from large-scale proteome microarrays to smaller customizable microarrays, making the technology amenable for detection of a broad spectrum of biochemical properties of proteins. In this article, we will focus on the numerous studies that have utilized protein microarrays to reconstruct biological networks including protein–DNA interactions, posttranslational protein modifications (PTMs), lectin–glycan recognition, pathogen–host interactions and hierarchical signaling cascades. The diversity in applications allows for integration of interaction data from numerous molecular classes and cellular states, providing insight into the structure of complex biological systems. We will also discuss emerging applications and future directions of protein microarray technology in the global frontier.

Identification of new autoimmune hepatitis-specific autoantigens by using protein microarray technology

Autoimmune hepatitis (AIH) is a chronic necroinflammatory disease of the liver with a poorly understood etiology. Detection of non-organ-specific and liver-related autoantibodies using immunoserological approaches has been widely used for diagnosis and prognosis. However, unambiguous and accurate detection of the disease requires the identification and characterization of disease-specific autoantigens. In the present study, we have used protein microarray technology to profile the autoantigen repertoire of patients with AIH versus those with other liver diseases, identifying and validating novel and highly specific biomarkers for AIH. Using two algorithms developed in the current study, we were able to demonstrate that a panel of six autoantigens could be used in combination to clearly diagnose AIH-positive serum samples.

Functional protein microarray as molecular decathlete: a versatile player in clinical proteomics

Functional protein microarrays were developed as a high-throughput tool to overcome the limitations of DNA microarrays and to provide a versatile platform for protein functional analyses. Recent years have witnessed tremendous growth in the use of protein microarrays, particularly functional protein microarrays, to address important questions in the field of clinical proteomics. In this review, we will summarize some of the most innovative and exciting recent applications of protein microarrays in clinical proteomics, including biomarker identification, pathogen-host interactions, and cancer biology.

Identification of new autoantigens by protein array indicates a role for IL4 neutralization in autoimmune hepatitis

Autoimmune hepatitis (AIH) is an unresolving inflammation of the liver of unknown cause. Diagnosis requires the exclusion of other conditions and the presence of characteristic features such as specific autoantibodies. Presently, these autoantibodies have relatively low sensitivity and specificity and are identified via immunostaining of cells or tissues; therefore, there is a diagnostic need for better and easy-to-assess markers. To identify new AIH-specific autoantigens, we developed a protein microarray comprising 1626 human recombinant proteins, selected in silico for being secreted or membrane associated. We screened sera from AIH patients on this microarray and compared the reactivity with that of sera from healthy donors and patients with chronic viral hepatitis C. We identified six human proteins that are specifically recognized by AIH sera. Serum reactivity to a combination of four of these autoantigens allows identification of AIH patients with high sensitivity (82%) and specificity (92%). Of the six autoantigens, the interleukin-4 (IL4) receptor fibronectin type III domain of the IL4 receptor (CD124), which is expressed on the surface of both lymphocytes and hepatocytes, showed the highest individual sensitivity and specificity for AIH. Remarkably, patients' sera inhibited STAT6 phosphorylation induced by IL4 binding to CD124, demonstrating that these autoantibodies are functional and suggesting that IL4 neutralization has a pathogenetic role in AIH.

Identification of new autoantigens for primary biliary cirrhosis using human proteome microarrays

Primary biliary cirrhosis (PBC) is a chronic cholestatic liver disease of unknown etiology and is considered to be an autoimmune disease. Autoantibodies are important tools for accurate diagnosis of PBC. Here, we employed serum profiling analysis using a human proteome microarray composed of about 17,000 full-length unique proteins and identified 23 proteins that correlated with PBC. To validate these results, we fabricated a PBC-focused microarray with 21 of these newly identified candidates and nine additional known PBC antigens. By screening the PBC microarrays with additional cohorts of 191 PBC patients and 321 controls (43 autoimmune hepatitis, 55 hepatitis B virus, 31 hepatitis C virus, 48 rheumatoid arthritis, 45 systematic lupus erythematosus, 49 systemic sclerosis, and 50 healthy), six proteins were confirmed as novel PBC autoantigens with high sensitivities and specificities, including hexokinase-1 (isoforms I and II), Kelch-like protein 7, Kelch-like protein 12, zinc finger and BTB domain-containing protein 2, and eukaryotic translation initiation factor 2C, subunit 1. To facilitate clinical diagnosis, we developed ELISA for Kelch-like protein 12 and zinc finger and BTB domain-containing protein 2 and tested large cohorts (297 PBC and 637 control sera) to confirm the sensitivities and specificities observed in the microarray-based assays. In conclusion, our research showed that a strategy using high content protein microarray combined with a smaller but more focused protein microarray can effectively identify and validate novel PBC-specific autoantigens and has the capacity to be translated to clinical diagnosis by means of an ELISA-based method.

Circulating and synovial antibody profiling of juvenile arthritis patients by nucleic acid programmable protein arrays

INTRODUCTION

Juvenile idiopathic arthritis (JIA) is a heterogeneous disease characterized by chronic joint inflammation of unknown cause in children. JIA is an autoimmune disease and small numbers of autoantibodies have been reported in JIA patients. The identification of antibody markers could improve the existing clinical management of patients.

METHODS

A pilot study was performed on the application of a high-throughput platform, the nucleic acid programmable protein array (NAPPA), to assess the levels of antibodies present in the systemic circulation and synovial joint of a small cohort of juvenile arthritis patients. Plasma and synovial fluid from 10 JIA patients was screened for antibodies against 768 proteins on NAPPAs.

RESULTS

Quantitative reproducibility of NAPPAs was demonstrated with > 0.95 intra-array and inter-array correlations. A strong correlation was also observed for the levels of antibodies between plasma and synovial fluid across the study cohort (r = 0.96). Differences in the levels of 18 antibodies were revealed between sample types across all patients. Patients were segregated into two clinical subtypes with distinct antibody signatures by unsupervised hierarchical cluster analysis.

CONCLUSION

The NAPPAs provide a high-throughput quantitatively reproducible platform to screen for disease-specific autoantibodies at the proteome level on a microscope slide. The strong correlation between the circulating antibody levels and those of the inflamed joint represents a novel finding and provides confidence to use plasma for discovery of autoantibodies in JIA, thus circumventing the challenges associated with joint aspiration. We expect that autoantibody profiling of JIA patients on NAPPAs could yield antibody markers that can act as criteria to stratify patients, predict outcomes and understand disease etiology at the molecular level.

Rapid identification of monospecific monoclonal antibodies using a human proteome microarray

To broaden the range of tools available for proteomic research, we generated a library of 16,368 unique full-length human ORFs that are expressible as N-terminal GST-His₆ fusion proteins. Following expression in yeast, these proteins were then individually purified and used to construct a human proteome microarray. To demonstrate the usefulness of this reagent, we developed a streamlined strategy for the production of monospecific monoclonal antibodies that used immunization with live human cells and microarray-based analysis of antibody specificity as its central components. We showed that microarray-based analysis of antibody specificity can be performed efficiently using a two-dimensional pooling strategy. We also demonstrated that our immunization and selection strategies result in a large fraction of monospecific monoclonal antibodies that are both immunoblot and immunoprecipitation grade. Our data indicate that the pipeline provides a robust platform for the generation of monoclonal antibodies of exceptional specificity.

Novel systemic lupus erythematosus autoantigens identified by human protein microarray technology

Systemic lupus erythematosus (SLE) is a systemic autoimmune disease affecting many organs. Many autoantibodies have been associated with the disease, but either in low specificity or low sensitivity of detection. In an aim to screen for better autoantibodies, we profiled the autoantibody repertoire in sera from 30 SLE patients versus 30 healthy controls using a protein microarray containing 5011 non-redundant human proteins, and identified four candidates. We then selected CLIC2 for further verification by ELISA in an extended cohort including 110 SLE, 121 non-AD, 118 RA, 117 SSc, and 105 pSS patients. The positive rate of anti-CLIC2 was 28.18% in SLE patients, significantly higher than those in non-AD, RA, and SSc patients. The presence of anti-CLIC2 in SLE had positive correlation with disease activity in terms of SLEDAI score and several indexes (p<0.05).

Applications of functional protein microarrays in basic and clinical research

The protein microarray technology provides a versatile platform for characterization of hundreds of thousands of proteins in a highly parallel and high-throughput manner. It is viewed as a new tool that overcomes the limitation of DNA microarrays. On the basis of its application, protein microarrays fall into two major classes: analytical and functional protein microarrays. In addition, tissue or cell lysates can also be directly spotted on a slide to form the so-called "reverse-phase" protein microarray. In the last decade, applications of functional protein microarrays in particular have flourished in studying protein function and construction of networks and pathways. In this chapter, we will review the recent advancements in the protein microarray technology, followed by presenting a series of examples to illustrate the power and versatility of protein microarrays in both basic and clinical research. As a powerful technology platform, it would not be surprising if protein microarrays will become one of the leading technologies in proteomic and diagnostic fields in the next decade.

[Recent development of microfluidic diagnostic technologies]

Microfluidic devices exhibit a great promising development in clinical diagnosis and disease screening due to their advantages of precise controlling of fluid flow, requirement of miniamount sample, rapid reaction speed and convenient integration. In this paper, the improvements of microfluidic diagnostic technologies in recent years are reviewed. The applications and developments of on-chip disease marker detection, microfluidic cell selection and cell drug metabolism, and diagnostic micro-devices are discussed.