Autoantibody systems in rheumatoid arthritis: specificity, sensitivity and diagnostic value

The diagnosis of rheumatoid arthritis (RA) is primarily based on clinical symptoms, so it is often difficult to diagnose RA in very early stages of the disease. A disease-specific autoantibody that could be used as a serological marker would therefore be very useful. Most autoimmune diseases are characterized by a polyclonal B-cell response targeting multiple autoantigens. These immune responses are often not specific for a single disease. In this review, the most important autoantibody/autoantigen systems associated with RA are described and their utility as a diagnostic and prognostic tool, including their specificity, sensitivity and practical application, is discussed. We conclude that, at present, the antibody response directed to citrullinated antigens has the most valuable diagnostic and prognostic potential for RA.     

Protein array diagnostics for guiding therapy in rheumatoid arthritis

Early diagnosis and effective management of rheumatoid arthritis (RA) are pivotal, given the progressive, chronic, inflammatory, multi-systemic nature of the disease. Currently, proper initiation of adequate, individually tailored interventions in RA is delayed by the difficulty of early diagnosis and the limitations of disease activity and therapeutic response assessment tools. This is a significant challenge to rheumatologists, further complicated by the dynamic and progressively evolving autoimmune nature of RA, which is characterized by several immune mediators in a complex network that regulates the perpetuation of inflammation. Protein arrays constitute the most advanced current technology that can provide a comprehensive parallel analysis of this diverse network in RA, providing an individualized insight into immune status and host immune response. The last few years have seen significant transitions in the field of protein arrays, demonstrated by a technologic shift from the bench to the bedside, paving the way for the medical and scientific community to deliver patient-specific assessments and personalized management. Screening of protein arrays with sera or tissues from patients with RA enables the probing of immune responses and the identification of autoantibody signatures that can be used for the diagnosis and therapeutic management of patients. This article reviews the technology and the applications for protein arrays in the diagnosis and prognosis of RA. Clinical assessment tools could be derived from protein arrays, which may provide a means to continually track patients, allowing better evaluation of intervention strategies on a patient-specific basis and identification of diagnostic and disease activity biomarkers that could be used to guide optimal therapy in RA.     

Autoantibodies in rheumatoid arthritis and their clinical significance

Autoantibodies are proven useful diagnostic tools for a variety of rheumatic and non-rheumatic autoimmune disorders. However, a highly specific marker autoantibody for rheumatoid arthritis (RA) has not yet been determined. The presence of rheumatoid factors is currently used as a marker for RA. However, rheumatoid factors have modest specificity (~70%) for the disease. In recent years, several newly characterized autoantibodies have become promising candidates as diagnostic indicators for RA. Antikeratin, anticitrullinated peptides, anti-RA33, anti-Sa, and anti-p68 autoantibodies have been shown to have >90% specificity for RA. These autoantibodies are reviewed and the potential role of the autoantibodies in the pathogenesis of RA is briefly discussed.     

Tumor-associated antigen arrays for the serological diagnosis of cancer

The recognition that human tumors stimulate the production of autoantibodies against autologous cellular proteins called tumor-associated antigens (TAAs) has opened the door to the possibility that autoantibodies could be exploited as serological tools for the early diagnosis and management of cancer. Cancer-associated autoantibodies are often driven by intracellular proteins that are mutated, modified, or aberrantly expressed in tumor cells and hence are regarded as immunological reporters that could help uncover molecular events underlying tumorigenesis. Emerging evidence suggests that each type of cancer might trigger unique autoantibody signatures that reflect the nature of the malignant process in the affected organ. The advent of novel genomic, proteomic, and high throughput approaches has accelerated interest in the serum autoantibody repertoire in human cancers for the discovery of candidate TAAs. The use of individual anti-TAA autoantibodies as diagnostic or prognostic tools has been tempered by their low frequency and heterogeneity in most human cancers. However, TAA arrays comprising several antigens significantly increase this frequency and hold great promise for the early detection of cancer, monitoring cancer progression, guiding individualized therapeutic interventions, and identification of novel therapeutic targets. Our recent studies suggest that the implementation of TAA arrays in screening programs for the diagnosis of prostate cancer and other cancers should be preceded by the optimization of their sensitivity and specificity through the careful selection of the most favorable combinations of TAAs.     

Detection of multiple autoantibodies in patients with ankylosing spondylitis using nucleic acid programmable protein arrays

Ankylosing spondylitis (AS) is a common, inflammatory rheumatic disease that primarily affects the axial skeleton and is associated with sacroiliitis, uveitis, and enthesitis. Unlike other autoimmune rheumatic diseases, such as rheumatoid arthritis or systemic lupus erythematosus, autoantibodies have not yet been reported to be a feature of AS. We therefore wished to determine whether plasma from patients with AS contained autoantibodies and, if so, characterize and quantify this response in comparison to patients with rheumatoid arthritis (RA) and healthy controls. Two high density nucleic acid programmable protein arrays expressing a total of 3498 proteins were screened with plasma from 25 patients with AS, 17 with RA, and 25 healthy controls. Autoantigens identified were subjected to Ingenuity Pathway Analysis to determine the patterns of signaling cascades or tissue origin. 44% of patients with ankylosing spondylitis demonstrated a broad autoantibody response, as compared with 33% of patients with RA and only 8% of healthy controls. Individuals with AS demonstrated autoantibody responses to shared autoantigens, and 60% of autoantigens identified in the AS cohort were restricted to that group. The autoantibody responses in the AS patients were targeted toward connective, skeletal, and muscular tissue, unlike those of RA patients or healthy controls. Thus, patients with AS show evidence of systemic humoral autoimmunity and multispecific autoantibody production. Nucleic acid programmable protein arrays constitute a powerful tool to study 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.     

Tumor-associated autoantibodies as diagnostic and prognostic biomarkers

In the process of tumorigenesis, normal cells are remodeled to cancer cells and protein expression patterns are changed to those of tumor cells. A newly formed tumor microenvironment elicits the immune system and, as a result, a humoral immune response takes place. Although the tumor antigens are undetectable in sera at the early stage of tumorigenesis, the nature of an antibody amplification response to antigens makes tumor-associated autoantibodies as promising early biomarkers in cancer diagnosis. Moreover, the recent development of proteomic techniques that make neo-epitopes of tumor-associated autoantigens discovered concomitantly has opened a new area of ‘immuno-proteomics’, which presents tumor-associated autoantibody signatures and confers information to redefine the process of tumorigenesis. In this article, the strategies recently used to identify and validate serum autoantibodies are outlined and tumor-associated antigens suggested until now as diagnostic/prognostic biomarkers in various tumor types are reviewed. Also, the meaning of autoantibody signatures and their clinical utility in personalized medicine are discussed. [BMB Reports 2012; 45(12): 677-685]     

Are synovial biopsies of diagnostic value?

Synovial tissue is readily accessible by closed needle or arthroscopic biopsy. These techniques provide adequate tissue for most diagnostic requirements. Examination of synovial tissue can assist in the diagnosis of some joint infections, and in several atypical or rare synovial disorders. Histological confirmation is not normally required for diagnosis of the common forms of inflammatory arthritis, including rheumatoid arthritis (RA). In patients with either established or early RA, immunohistological measures of inflammation in synovial tissue are associated with clinical measures of disease activity, may predict the clinical outcome, and change in response to treatment. Surrogate markers of disease activity and outcome that have been identified in synovial tissue include components of the cellular infiltrate, and several mediators of inflammation and matrix degradation. There is evidence that the very early introduction of disease-modifying therapy inhibits progressive structural damage maximally. Clinicians exploiting this 'window of opportunity' therefore require very early indicators of the diagnosis and outcome in patients who present with an undifferentiated inflammatory arthritis. Some immunohistological features have been described that distinguish patients who are likely to develop progressive RA and who might benefit most from early aggressive therapeutic intervention. In this regard, the inclusion of pharmacogenomic and proteomic techniques in the analysis of synovial tissue presents some exciting possibilities for future research.     

Rheumatoid factor,not antibodies against citrullinated proteins,is associated with baseline disease activity in rheumatoid arthritis clinical trials

IntroductionAlthough the prognostic value of rheumatoid factor (RF) and autoantibodies against citrullinated proteins (ACPAs) in patients with rheumatoid arthritis (RA) is well established, their association with RA disease activity remains unclear. Here, we investigate this association in a large study using data from clinical trials.MethodsWe used baseline data from four recent randomized controlled clinical trials of RA. We investigated individual and composite measures of disease activity. The relationship of RF and ACPAs with these measures was investigated by using stratified analysis (comparing four groups of patients according to the presence or absence of RF and ACPAs) and matched analysis (disease activity levels compared between patients negative and patients highly positive for one autoantibody who were matched for levels of the other autoantibody as well as for age, gender, and duration of RA).ResultsA total of 2118 patients were analysed in the different cohorts. In the stratified analysis, RF⁺ patients, regardless of ACPA status, had the highest levels of disease activity, whereas ACPA⁺ patients had disease activity that was similar to or lower than that of ACPA⁻ patients, both in the presence and in the absence of RF. When matched for ACPA levels, patients with highly positive RF had significantly higher disease activity for all composite indices compared with patients who were RF⁻ (P = 0.0067), whereas ACPA-highly-positive and ACPA-negative patients matched for RF levels had similar disease activity, again even with the tendency toward lower disease activity for ACPA⁺ patients (P = 0.054).ConclusionThe data presented suggest that the presence of RF has a clear association with higher levels of disease activity but that the presence of ACPAs has not and even appears to be associated with lower disease activity.

Electronic supplementary material

The online version of this article (doi:10.1186/s13075-015-0736-9) contains supplementary material, which is available to authorized users.     

Extracting a few functionally reproducible biomarkers to build robust subnetwork-based classifiers for the diagnosis of cancer

In microarray-based case–control studies of a disease, people often attempt to identify a few diagnostic or prognostic markers amongst the most significant differentially expressed (DE) genes. However, the reproducibility of DE genes identified in different studies for a disease is typically very low. To tackle the problem, we could evaluate the reproducibility of DE genes across studies and define robust markers for disease diagnosis using disease-associated protein–protein interaction (PPI) subnetwork. Using datasets for four cancer types, we found that the most significant DE genes in cancer exhibit consistent up- or down-regulation in different datasets. For each cancer type, the 5 (or 10) most significant DE genes separately extracted from different datasets tend to be significantly coexpressed and closely connected in the PPI subnetwork, thereby indicating that they are highly reproducible at the PPI level. Consequently, we were able to build robust subnetwork-based classifiers for cancer diagnosis.     

Targeted Synovial Fluid Proteomics for Biomarker Discovery in Rheumatoid Arthritis

Objective  Rheumatoid arthritis (RA) is an autoimmune disease that targets the synovium. The autoantigens involved in the autoantibody responses in RA are unknown. A targeted proteomics approach was used to identify proteins in RA synovial fluid (SF) that are recognized by autoantibodies in RA sera. Methods  RA SF, depleted of abundant proteins, was fractionated by two-dimensional liquid chromatography (chromatofocusing followed by reverse phase HPLC). Protein arrays constructed from these fractions were probed with RA and normal control sera, and proteins within reactive fractions were identified by mass spectrometry. The reactivity of RA sera to an identified peptide was confirmed by ELISA. Results  RA sera specifically reacted to a SF fraction containing fibrin. Mass spectrometry analyses established the presence of a citrullinated arginine at position 271 of the fibrin fragment present in RA SF. A synthetic peptide corresponding to fibrin residues 259–287, containing the citrulline substitution at Arg 271, was recognized by 10 of 12 RA sera, but by two of 18 normal control sera and one of 10 systemic lupus erythematosus sera. Conclusion  Proteomics methodology can be used to directly characterize post-translational modifications in candidate autoantigens isolated from sites of disease activity. The finding that RA sera contain antibodies to the citrullinated fibrin 259–287 peptide may ultimately lead to improved diagnostic tests for RA and/or biomarkers for disease activity. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

ATRPred: A machine learning based tool for clinical decision making of anti-TNF treatment in rheumatoid arthritis patients

Rheumatoid arthritis (RA) is a chronic autoimmune condition, characterised by joint pain, damage and disability, which can be addressed in a high proportion of patients by timely use of targeted biologic treatments. However, the patients, non-responsive to the treatments often suffer from refractoriness of the disease, leading to poor quality of life. Additionally, the biologic treatments are expensive. We obtained plasma samples from N = 144 participants with RA, who were about to commence anti-tumour necrosis factor (anti-TNF) therapy. These samples were sent to Olink Proteomics, Uppsala, Sweden, where proximity extension assays of 4 panels, containing 92 proteins each, were performed. A total of n = 89 samples of patients passed the quality control of anti-TNF treatment response data. The preliminary analysis of plasma protein expression values suggested that the RA population could be divided into two distinct molecular sub-groups (endotypes). However, these broad groups did not predict response to anti-TNF treatment, but were significantly different in terms of gender and their disease activity. We then labelled these patients as responders (n = 60) and non-responders (n = 29) based on the change in disease activity score (DAS) after 6 months of anti-TNF treatment and applied machine learning (ML) with a rigorous 5-fold nested cross-validation scheme to filter 17 proteins that were significantly associated with the treatment response. We have developed a ML based classifier ATRPred (anti-TNF treatment response predictor), which can predict anti-TNF treatment response in RA patients with 81% accuracy, 75% sensitivity and 86% specificity. ATRPred may aid clinicians to direct anti-TNF therapy to patients most likely to receive benefit, thus save cost as well as prevent non-responsive patients from refractory consequences. ATRPred is implemented in R.     

Autoantibody epitope spreading in the pre-clinical phase predicts progression to rheumatoid arthritis

Rheumatoid arthritis (RA) is a prototypical autoimmune arthritis affecting nearly 1% of the world population and is a significant cause of worldwide disability. Though prior studies have demonstrated the appearance of RA-related autoantibodies years before the onset of clinical RA, the pattern of immunologic events preceding the development of RA remains unclear. To characterize the evolution of the autoantibody response in the preclinical phase of RA, we used a novel multiplex autoantigen array to evaluate development of the anti-citrullinated protein antibodies (ACPA) and to determine if epitope spread correlates with rise in serum cytokines and imminent onset of clinical RA. To do so, we utilized a cohort of 81 patients with clinical RA for whom stored serum was available from 1-12 years prior to disease onset. We evaluated the accumulation of ACPA subtypes over time and correlated this accumulation with elevations in serum cytokines. We then used logistic regression to identify a profile of biomarkers which predicts the imminent onset of clinical RA (defined as within 2 years of testing). We observed a time-dependent expansion of ACPA specificity with the number of ACPA subtypes. At the earliest timepoints, we found autoantibodies targeting several innate immune ligands including citrullinated histones, fibrinogen, and biglycan, thus providing insights into the earliest autoantigen targets and potential mechanisms underlying the onset and development of autoimmunity in RA. Additionally, expansion of the ACPA response strongly predicted elevations in many inflammatory cytokines including TNF-α, IL-6, IL-12p70, and IFN-γ. Thus, we observe that the preclinical phase of RA is characterized by an accumulation of multiple autoantibody specificities reflecting the process of epitope spread. Epitope expansion is closely correlated with the appearance of preclinical inflammation, and we identify a biomarker profile including autoantibodies and cytokines which predicts the imminent onset of clinical arthritis.     

Microarray profiling of lymphocytes in internal diseases with an altered immune response: potential and methodology

Recently it has become possible to investigate expression of all human genes with microarray technique. The authors provide arguments to consider peripheral white blood cells and in particular lymphocytes as a model for the investigation of pathophysiology of asthma, RA, and SLE diseases in which inflammation is a major component. Lymphocytes are an alternative to tissue biopsies that are most often difficult to collect systematically. Lymphocytes express more than 75% of the human genome, and, being an important part of the immune system, they play a central role in the pathogenesis of asthma, RA, and SLE. Here we review alterations of gene expression in lymphocytes and methodological aspects of the microarray technique in these diseases. Lymphocytic genes may become activated because of a general nonspecific versus disease-specific mechanism. The authors suppose that in these diseases microarray profiles of gene expression in lymphocytes can be disease specific, rather than inflammation specific. Some potentials and pitfalls of the array technologies are discussed. Optimal clinical designs aimed to identify disease-specific genes are proposed. Lymphocytes can be explored for research, diagnostic, and possible treatment purposes in these diseases, but their precise value should be clarified in future investigation.     

Suppression of proteoglycan-induced arthritis by anti-CD20 B Cell depletion therapy is mediated by reduction in autoantibodies and CD4+ T cell reactivity

B cells have been implicated in the pathogenesis of rheumatoid arthritis (RA) since the discovery of RA as an autoimmune disease. There is renewed interest in B cells in RA based on the clinical efficacy of B cell depletion therapy in RA patients. Although, reduced titers of rheumatoid factor and anti-cyclic citrullinated peptide Abs are recorded, the mechanisms that convey clinical improvement are incompletely understood. In the proteoglycan-induced arthritis (PGIA) mouse model of RA, we reported that Ag-specific B cells have two important functions in the development of arthritis. PG-specific B cells are required as autoantibody-producing cells as well as Ag-specific APCs. Herein we report on the effects of anti-CD20 mAb B cell depletion therapy in PGIA. Mice were sensitized to PG and treated with anti-CD20 Ab at a time when PG-specific autoantibodies and T cell activation were evident but before acute arthritis. In mice treated with anti-CD20 mAb, development of arthritis was significantly reduced in comparison to control mAb-treated mice. B cell depletion reduced the PG-specific autoantibody response. Furthermore, there was a significant reduction in the PG-specific CD4(+) T cell recall response as well as significantly fewer PG-specific CD4(+) T cells producing IFN-gamma and IL-17, but not IL-4. The reduction in PG-specific T cells was confirmed by the inability of CD4(+) T cells from B cell-depleted mice to adoptively transfer disease into SCID mice. Overall, B cell depletion during PGIA significantly reduced disease and inhibited both autoreactive B cell and T cell function.     

Identification of autoantibodies associated with systemic lupus erythematosus

Systemic lupus erythematosus (SLE) is an autoimmune disease characterized by the presence of antinuclear antibodies. We performed serological analysis of cDNA expression library (SEREX) to identify autoantibodies associated with SLE. The screening of three different cDNA expression libraries with pooled sera of patients with SLE yielded 11 independent clones that reacted with pooled sera of patients with SLE. In this screening, autoantibodies to poly(ADP-ribose) polymerase (PARP), U1snRNP, and galectin-3 were prevalent in the sera of patients with SLE (26/68, 25/68, 12/63, respectively). The frequency of autoantibody to PARP was significantly higher in SLE than that of healthy donors (0/76) (38.2% vs 0%, p<0.00001). The autoantibody to PARP was infrequently detected in the serum of patients with RA (1/50). However, autoantibody to PARP was not found in the sera of patients with other rheumatic diseases including Sjogren's syndrome (0/19), systemic sclerosis (0/18), and polymyositis/myositis (0/37). The frequency of autoantibody to human galectin-3 (12/63) was significantly higher in SLE than that of healthy donors (0/56) (19% vs 0%, p=0.0006). Autoantibody to galectin-3 was not found in the sera of patients with rheumatoid arthritis (0/50), Sjogren's syndrome (0/18), and systemic sclerosis (0/19). Interestingly, autoantibody to galectin-3 was also prevalent in the sera of patients with polymyositis/dermatomyositis (16/37, 43.2%). Further functional characterization of these autoantibodies would be necessary to determine their value as diagnostic markers or to define clinical subsets of patients with SLE. Statistical analysis revealed that the presence of autoantibody to PARP was inversely related with pleurisy, and the presence of autoantibody to galectin-3 related with renal disease.     

Effects of Excess Copper Ions on Decidualization of Human Endometrial Stromal Cells

Rheumatoid arthritis (RA) is a chronic autoimmune inflammatory disease, which mainly involves the joints. RA is prevalent worldwide with increasing prevalence in elderly people. The mechanism of RA pathogenesis is still undefined, and it is interplaying between genetic susceptibility and environmental factors. Although risk factors for RA are not fully established, various studies have focused on the role of trace elements in association with RA. Trace elements act as co-factors for most of the enzymes, and their deficiency is associated with many untoward effects on human health. The homeostatic alterations in the metabolism of trace elements may partly be due to inflammatory response in RA. The objective of the present study was to determine the serum concentrations and correlation of zinc, copper, and iron in RA patients and healthy controls. The study comprised of 61 RA patients and 61 age- and sex-related healthy individuals of Pakistani population. Serum levels of Zn, Cu, and Fe were measured in all the participants by atomic absorption spectrophotometer. Serum Zn and Fe were significantly reduced in the RA patients than those in the healthy controls. Serum Cu concentrations were found elevated in the RA patients. Correlation studies of trace elements determine that there was negative correlation between Zn and Cu in the RA patients and no correlation in the control group. It is very important to explore the deficiency of essential trace metals in biological samples of the RA patients in different populations which may be helpful for diagnosis and supplementary management of rheumatoid arthritis patients.     

Rheumatoid arthritis: regulation of synovial inflammation

Rheumatoid arthritis (RA) is a systemic, inflammatory autoimmune disorder that presents as a symmetric polyarthritis associated with swelling and pain in multiple joints, often initially occurring in the joints of the hands and feet. Articular inflammation causes activation and proliferation of the synovial lining, expression of inflammatory cytokines, chemokine-mediated recruitment of additional inflammatory cells, as well as B cell activation with autoantibody production. A vicious cycle of altered cytokine and signal transduction pathways and inhibition of programmed cell death contribute to synoviocyte and osteoclast mediated cartilage and bone destruction. A combination of targeted interventions at various stages in the pathogenesis of RA will likely be required to control symptoms in certain patients with this complex and potentially disabling disease. The regulation of rheumatoid synovial inflammation will be reviewed, followed by a brief summary of the therapeutic implications of these advances, including strategies targeting key cytokines, signal transduction molecules, co-stimulatory molecules, B cells, chemokines, and adhesion molecules.     

Balance between survivin,a key member of the apoptosis inhibitor family,and its specific antibodies determines erosivity in rheumatoid arthritis

Rheumatoid arthritis (RA) is a highly heterogeneous disease with respect to its joint destructivity. The reasons underlying this heterogeneity are unknown. Deficient apoptosis in rheumatoid synovial tissue has been recently demonstrated. We have therefore decided to study the synovial expression of survivin, a key member of the apoptosis inhibitor family. The levels of survivin and antibodies against survivin were assessed by an ELISA in matched blood and synovial fluid samples collected from 131 RA patients. Results were related to joint erosivity at the time of sampling. Monocytes were transfected with survivin anti-sense oligonucleotides and were assessed for their ability to produce inflammatory cytokines. Survivin levels were significantly higher in patients with destructive disease as compared with in RA patients displaying a non-erosive disease. High survivin levels were an independent prognostic parameter for erosive RA. In contrast, high levels of antibodies against survivin were found in patients with non-erosive RA, and were negatively related to erosivity. Survivin levels in RA patients were influenced by treatment, being significantly lower among patients treated with disease-modifying anti-rheumatic drugs. Specific suppression of survivin mRNA resulted in downregulation of IL-6 production. We conclude that survivin determines the erosive course of RA, whereas survivin antibodies lead to a less aggressive course of the disease. These findings together with decreased survivin levels upon disease-modifying anti-rheumatic drug treatment, and the downregulation of inflammatory response using survivin anti-sense oligonucleotides, suggest that extracellular survivin expression mediates the erosive course of joint disease whereas autoimmune responses to the same molecule, manifested as survivin targeting antibodies, mediate protection.     

Proteomics and autoantibody

Autoimmune response is diverse. This diversity is thought not to take place at the beginning of the autoimmune process but to occur as the disease evolves. It is mainly the consequence of the so-called epitope-spreading phenomenon and of the cross-reactivity of antibodies. Analysing autoantibody repertoire constitutes a powerful means to understand physiopathological processes at work in various diseases, mainly autoimmune diseases. In particular this analysis opens the way to precisely identify autoantigens and their changes in various pathological situations, and allows providing new biological markers in chronic inflammatory diseases. New methodologies have recently emerged for the analysis of the autoantibody repertoire in a given individual. They propose diagnostic approaches no more related upon few markers but founded upon analysis of global changes of the antibody repertoire. They belong to methodologies called target-oriented proteomics. Their common feature is to isolate autoantigens by means of affinity chromatography based upon antibody/antigen reactions. Autoantibodies to be studied interact with a protein substratum susceptible to include autoantibody targets. These interactions take place on solid macro- or microsurfaces, i.e. membrane filters or chips. Several strategies can be used for locating the specific autoantibody/autoantigen complexes and for identifying behind autoantigens. In this paper three approaches, namely, the recombinant protein chips, the SELDI techniques and the 2-D gel electrophoresis linked to mass spectrometry are described and compared.