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

Prediction model for developing neuropsychiatric systemic lupus erythematosus in lupus patients

OBJECTIVE

This study aimed to construct a predictive model for assessing the risk of development of neuropsychiatric systemic lupus erythematosus (NPSLE) among patients with SLE based on clinical, laboratory, and meteorological data.

METHODS

A total of 2232 SLE patients were included and were randomly assigned into training and validation sets. Variables such as clinical and laboratory data and local meteorological data were screened by univariate and least absolute shrinkage and selection operator (LASSO) logistic regression modelling. After 10-fold cross-validation, the predictive model was built by multivariate logistic regression, and a nomogram was constructed to visualize the risk of NPSLE. The efficacy and accuracy of the model were assessed by receiver operating characteristic (ROC) curve and calibration curve analysis. Net clinical benefit was assessed by decision curve analysis.

RESULTS

Variables that were included in the predictive model were anti-dsDNA, anti-SSA, lymphocyte count, hematocrit, erythrocyte sedimentation rate, pre-albumin, retinol binding protein, creatine kinase isoenzyme MB, Nterminal brain natriuretic peptide precursor, creatinine, indirect bilirubin, fibrinogen, hypersensitive C-reactive protein, CO, and mild contamination. The nomogram showed a broad prediction spectrum; the area under the curve (AUC) was 0.895 (0.858-0.931) for the training set and 0.849 (0.783-0.916) for the validation set.

CONCLUSION

The model exhibits good predictive performance and will confer clinical benefit in NPSLE risk calculation. Key Points • Clinical, laboratory, and meteorological data were incorporated into a predictive model for neuropsychiatric systemic lupus erythematosus (NPSLE) in SLE patients. • Anti-dsDNA, anti-SSA, LYM, HCT, ESR, hsCRP, IBIL, PA, RBP, CO, Fib, NT-proBNP, Crea, CO, and mild contamination are predictors of the development of NPSLE and may have potential for research. • The nomogram has good predictive performance and clinical value and can be used to guide clinical diagnosis and treatment.

Constitutive knockout of interleukin-6 ameliorates memory deficits and entorhinal astrocytosis in the MRL/lpr mouse model of neuropsychiatric lupus

BACKGROUND

Neuropsychiatric lupus (NPSLE) describes the cognitive, memory, and affective emotional burdens faced by many lupus patients. While NPSLE's pathogenesis has not been fully elucidated, clinical imaging studies and cerebrospinal fluid (CSF) findings, namely elevated interleukin-6 (IL-6) levels, point to ongoing neuroinflammation in affected patients. Not only linked to systemic autoimmunity, IL-6 can also activate neurotoxic glial cells the brain. A prior pre-clinical study demonstrated that IL-6 can acutely induce a loss of sucrose preference; the present study sought to assess the necessity of chronic IL-6 exposure in the NPSLE-like disease of MRL/lpr lupus mice.

METHODS

We quantified 1308 proteins in individual serum or pooled CSF samples from MRL/lpr and control MRL/mpj mice using protein microarrays. Serum IL-6 levels were plotted against characteristic NPSLE neurobehavioral deficits. Next, IL-6 knockout MRL/lpr (IL-6 KO; n = 15) and IL-6 wildtype MRL/lpr mice (IL-6 WT; n = 15) underwent behavioral testing, focusing on murine correlates of learning and memory deficits, depression, and anxiety. Using qPCR, we quantified the expression of inflammatory genes in the cortex and hippocampus of MRL/lpr IL-6 KO and WT mice. Immunofluorescent staining was performed to quantify numbers of microglia (Iba1 +) and astrocytes (GFAP +) in multiple cortical regions, the hippocampus, and the amygdala.

RESULTS

MRL/lpr CSF analyses revealed increases in IL-17, MCP-1, TNF-α, and IL-6 (a priori p-value < 0.1). Serum levels of IL-6 correlated with learning and memory performance (R2 = 0.58; p = 0.03), but not motivated behavior, in MRL/lpr mice. Compared to MRL/lpr IL-6 WT, IL-6 KO mice exhibited improved novelty preference on object placement (45.4% vs 60.2%, p < 0.0001) and object recognition (48.9% vs 67.9%, p = 0.002) but equivalent performance in tests for anxiety-like disease and depression-like behavior. IL-6 KO mice displayed decreased cortical expression of aif1 (microglia; p = 0.049) and gfap (astrocytes; p = 0.044). Correspondingly, IL-6 KO mice exhibited decreased density of GFAP + cells compared to IL-6 WT in the entorhinal cortex (89 vs 148 cells/mm2, p = 0.037), an area vital to memory.

CONCLUSIONS

The inflammatory composition of MRL/lpr CSF resembles that of human NPSLE patients. Increased in the CNS, IL-6 is necessary to the development of learning and memory deficits in the MRL/lpr model of NPSLE. Furthermore, the stimulation of entorhinal astrocytosis appears to be a key mechanism by which IL-6 promotes these behavioral deficits.

Neuropsychiatric Systemic Lupus Erythematosus: Molecules Involved in Its Imunopathogenesis, Clinical Features, and Treatment

Systemic lupus erythematosus (SLE) is an idiopathic chronic autoimmune disease that can affect any organ in the body, including the neurological system. Multiple factors, such as environmental (infections), genetic (many HLA alleles including DR2 and DR3, and genes including C4), and immunological influences on self-antigens, such as nuclear antigens, lead to the formation of multiple autoantibodies that cause deleterious damage to bodily tissues and organs. The production of autoantibodies, such as anti-dsDNA, anti-SS(A), anti-SS(B), anti-Smith, and anti-neuronal DNA are characteristic features of this disease. This autoimmune disease results from a failure of the mechanisms responsible for maintaining self-tolerance in T cells, B cells, or both. Immune complexes, circulating antibodies, cytokines, and autoreactive T lymphocytes are responsible for tissue injury in this autoimmune disease. The diagnosis of SLE is a rheumatological challenge despite the availability of clinical criteria. NPSLE was previously referred to as lupus cerebritis or lupus sclerosis. However, these terms are no longer recommended because there is no definitive pathological cause for the neuropsychiatric manifestations of SLE. Currently, the treatment options are primarily based on symptomatic presentations. These include the use of antipsychotics, antidepressants, and anxiolytic medications for the treatment of psychiatric and mood disorders. Antiepileptic drugs to treat seizures, and immunosuppressants (e.g., corticosteroids, azathioprine, and mycophenolate mofetil), are directed against inflammatory responses along with non-pharmacological interventions.

Autoantibody profiling of monoamine oxidase A knockout mice, an autism spectrum disorder model

Monoamine oxidase A (MAO A) is the critical enzyme to degrade serotonin in the brain and the knockout mouse exhibits hyperserotonemia and abnormalities that are observed in autism spectrum disorder (ASD). Thus, the MAO A knockout mouse is a valuable model for studying neurological and behavioral impairments in ASD. Based on the immune dysfunction hypothesis, dysregulated humoral immunity may cause neurological impairments. To address this hypothesis, we use high-density proteome microarray to profile the serum antibodies in both wild-type and MAO A knockout mice. The distingue autoantibody signatures were observed in the MAO A knockout and wild-type controls and showed 165 up-regulated and 232 down-regulated autoantibodies. The up-regulated autoantibodies were prone to target brain tissues while down-regulated ones were enriched in sex organs. The identified autoantibodies help bridge the gap between ASD mouse models and humoral immunity, not only yielding insights into the pathological mechanisms but also providing potential biomarkers for translational research in ASD.

Identification of Diagnostic Gene Markers and Immune Infiltration in Systemic Lupus

Background

Systemic lupus erythematosus (SLE) is an autoimmune disease involving multiple organs, with atypical clinical manifestations and indefinite diagnosis and treatment. So far, the etiology of the disease is not completely clear. Current studies have known the interaction of genetic system, endocrine system, infection, environment, and other factors. Due to abnormal immune function, the human body, with the participation of various immune cells such as T cells and B cells, abnormally recognizes autoantigens, so as to produce a variety of autoantibodies and combine them to form immune complexes. These complexes will stay in the skin, kidney, serosa cavity, large joints, and even the central nervous system, resulting in multisystem damage of the body. The disease is heterogeneous, and it can show different symptoms in different populations and different disease stages; patients with systemic lupus erythematosus need individualized diagnosis and treatment. Therefore, we aimed to search for SLE immune-related hub genes and determine appropriate diagnostic genes to provide help for the detection and treatment of the disease.

Methods

Gene expression data of whole blood samples of SLE patients and healthy controls were downloaded from the GEO database. Firstly, we analyzed and identified the differentially expressed genes between SLE and the normal population. Meanwhile, the single-sample gene set enrichment analysis (ssGSEA) was used to identify the activation degree of immune-related pathways based on gene expression profile of different patients, and weighted gene coexpression network analysis (WGCNA) was used to search for coexpressed gene modules associated with immune cells. Then, key networks and corresponding genes were found in the protein-protein interaction (PPI) network. The above corresponding genes were hub genes. After that, this study used receiver operating characteristic (ROC) curve to evaluate hub gene in order to verify its ability to distinguish SLE from the healthy control group, and miRNA and transcription factor regulatory network analyses were performed for hub genes.

Results

Through bioinformatics technology, compared with the healthy control group, 2996 common differentially expressed genes (DEGs) were found in SLE patients, of which 1639 genes were upregulated and 1357 genes were downregulated. These differential genes were analyzed by ssGSEA to obtain the enrichment fraction of immune-related pathways. Next, the samples were selected by WGCNA analysis, and a total of 18 functional modules closely related to the pathogenesis of SLE were obtained. Thirdly, the correlation between the above modules and the enrichment fraction of immune-related pathways was analyzed, and the turquoise module with the highest correlation was selected. The 290 differential genes of this module were analyzed by GO and KEGG. The results showed that these genes were mainly enriched in coronavirus disease (COVID-19), ribosome, and human T cell leukemia virus 1 infection pathway. The 290 DEGs with PPI network and 28 genes of key networks were selected. ROC curve showed that 28 hub genes are potential biomarkers of SLE.

Conclusion

The 28 hub genes such as RPS7, RPL19, RPS17, and RPS19 may play key roles in the advancement of SLE. The results obtained in this study can provide a reference in a certain direction for the diagnosis and treatment of SLE in the future and can also be used as a new biomarker in clinical practice or drug research.

Abnormal cortical thickness and structural covariance networks in systemic lupus erythematosus patients without major neuropsychiatric manifestations

BACKGROUND

Non-neuropsychiatric systemic lupus erythematosus (non-NPSLE) has been confirmed to have subtle changes in brain structure before the appearance of obvious neuropsychiatric symptoms. Previous literature mainly focuses on brain structure loss in non-NPSLE; however, the results are heterogeneous, and the impact of structural changes on the topological structure of patients' brain networks remains to be determined. In this study, we combined neuroimaging and network analysis methods to evaluate the changes in cortical thickness and its structural covariance networks (SCNs) in patients with non-NPSLE.

METHODS

We compare the cortical thickness of non-NPSLE patients (N=108) and healthy controls (HCs, N=88) using both surface-based morphometry (SBM) and regions of interest (ROI) methods, respectively. After that, we analyzed the correlation between the abnormal cortical thickness results found in the ROI method and a series of clinical features. Finally, we constructed the SCNs of two groups using the regional cortical thickness and analyzed the abnormal SCNs of non-NPSLE.

RESULTS

By SBM method, we found that cortical thickness of 34 clusters in the non-NPSLE group was thinner than that in the HC group. ROI method based on Destrieux atlas showed that cortical thickness of 57 regions in the non-NPSLE group was thinner than that in the HC group and related to the course of disease, autoantibodies, the cumulative amount of immunosuppressive agents, and cognitive psychological scale. In the SCN analysis, the cortical thickness SCNs of the non-NPSLE group did not follow the small-world attribute at a few densities, and the global clustering coefficient appeared to increase. The area under the curve analysis showed that there were significant differences between the two groups in clustering coefficient, degree, betweenness, and local efficiency. There are a total of seven hubs for non-NPSLE, and five hubs in HCs, the two groups do not share a common hub distribution.

CONCLUSION

Extensive and obvious reduction in cortical thickness and abnormal topological organization of SCNs are observed in non-NPSLE patients. The observed abnormalities may not only be the realization of brain damage caused by the disease, but also the contribution of the compensatory changes within the nervous system.

Advances and Utility of the Human Plasma Proteome

The study of proteins circulating in blood offers tremendous opportunities to diagnose, stratify, or possibly prevent diseases. With recent technological advances and the urgent need to understand the effects of COVID-19, the proteomic analysis of blood-derived serum and plasma has become even more important for studying human biology and pathophysiology. Here we provide views and perspectives about technological developments and possible clinical applications that use mass-spectrometry(MS)- or affinity-based methods. We discuss examples where plasma proteomics contributed valuable insights into SARS-CoV-2 infections, aging, and hemostasis and the opportunities offered by combining proteomics with genetic data. As a contribution to the Human Proteome Organization (HUPO) Human Plasma Proteome Project (HPPP), we present the Human Plasma PeptideAtlas build 2021-07 that comprises 4395 canonical and 1482 additional nonredundant human proteins detected in 240 MS-based experiments. In addition, we report the new Human Extracellular Vesicle PeptideAtlas 2021-06, which comprises five studies and 2757 canonical proteins detected in extracellular vesicles circulating in blood, of which 74% (2047) are in common with the plasma PeptideAtlas. Our overview summarizes the recent advances, impactful applications, and ongoing challenges for translating plasma proteomics into utility for precision medicine.

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.

Management of Severe Refractory Systemic Lupus Erythematosus: Real-World Experience and Literature Review

Systemic lupus erythematosus (SLE) is a highly heterogeneous disease affecting multiple organs and is characterized by an aberrant immune response. Although the mortality of SLE has decreased significantly since the application of glucocorticoids, severe or refractory SLE can potentially cause irreversible organ damage and contribute to the disease morbidity and mortality. Early recognition of severe SLE or life-threatening conditions is of great challenge to clinicians since the onset symptoms can be rapid and aggressive, involving the visceral organs of the neuropsychiatric, gastrointestinal, hematologic, renal, pulmonary, and cardiovascular systems, etc. Additionally, SLE patients with specific comorbidities and detrimental complications could lead to a clinical dilemma and contribute to poor prognosis. Prompt and adequate treatment for severe refractory SLE is crucial for a better prognosis. However, as evidence from well-designed randomized controlled trials is limited, this review aims to provide real-world evidence based on cohort studies from Peking Union Medical College Hospital, the national tertiary referral center in China, together with the literature, on clinical characteristics, risks and prognostic factors, and treatment strategies for severe and/or refractory SLE.

Serological comparison of systemic lupus erythematosus with neuropsychiatric lupus using synthetic nucleic acid antigens

Neuropsychiatric systemic lupus erythematosus is an autoimmune disorder characterized by an irregular exchange between the central nervous system and the immune system, leading to the outbreak of neurological conditions with possible disabling effects. Although neuropsychiatric systemic lupus erythematosus is the most common expression of lupus condition, it is still poorly understood. In this study, we focus on the development of an advantageous method based on the application of synthetic nucleic acids and protein-based antigen arrays in order to characterize autoreactive antibodies in neuropsychiatric systemic lupus erythematosus. We confirmed the benefits of using synthetic oligonucleotides such as assay reproducibility, elevated affinity and specificity to autoreactive antibodies. We also demonstrated presence of autoantibodies towards three particular synthetic double stranded antigens and verify similarity of antinuclear antibody patterns in ordinary lupus and neuropsychiatric systemic lupus erythematosus.

Discovery of new serum biomarker panels for systemic lupus erythematosus diagnosis

OBJECTIVE

Clinical diagnosis of SLE is currently challenging due to its heterogeneity. Many autoantibodies are associated with SLE and are considered potential diagnostic markers, but systematic screening and validation of such autoantibodies is lacking. This study aimed to systematically discover new autoantibodies that may be good biomarkers for use in SLE diagnosis.

METHODS

Sera from 15 SLE patients and 5 healthy volunteers were analysed using human proteome microarrays to identify candidate SLE-related autoantibodies. The results were validated by screening of sera from 107 SLE patients, 94 healthy volunteers and 60 disease controls using focussed arrays comprised of autoantigens corresponding to the identified candidate antibodies. Logistic regression was used to derive and validate autoantibody panels that can discriminate SLE disease. Extensive ELISA screening of sera from 294 SLE patients and 461 controls was performed to validate one of the newly discovered autoantibodies.

RESULTS

A total of 31, 11 and 18 autoantibodies were identified to be expressed at significantly higher levels in the SLE group than in the healthy volunteers, disease controls and healthy volunteers plus disease control groups, respectively, with 25, 7 and 13 of these differentially expressed autoantibodies being previously unreported. Diagnostic panels comprising anti-RPLP2, anti-SNRPC and anti-PARP1, and anti-RPLP2, anti-PARP1, anti-MAK16 and anti- RPL7A were selected. Performance of the newly discovered anti-MAK16 autoantibody was confirmed by ELISA. Some associations were seen with clinical characteristics of SLE patients, such as disease activity with the level of anti-PARP1 and rash with the level of anti-RPLP2, anti-MAK16 and anti- RPL7A.

CONCLUSION

The combined autoantibody panels identified here show promise for the diagnosis of SLE and for differential diagnosis of other major rheumatic immune diseases.

Plasma proteomic and autoantibody profiles reveal the proteomic characteristics involved in longevity families in Bama, China

Background

Chinese Bama Yao Autonomous County is a well-known longevity region in the world. In the past 30 years, population and genome studies were undertaken to investigate the secret of longevity and showed that longevity is the result of a combination of multiple factors, such as genetic, environmental and other causes. In this study, characteristics of the blood plasma proteomic and autoantibody profiles of people from Bama longevity family were investigated.

Methods

Sixty-six plasma donors from Chinese Bama longevity area were recruited in this study. Thirty-three offsprings of longevous families were selected as case studies (Longevous group) and 33 ABO (blood type), age, and gender-matched subjects from non-longevous families were selected as controls (Normal group). Each group contains 3 biological replicates. Tandem mass tag-based proteomic technique was used to investigate the differentially expressed plasma proteins between the two groups. The auto-reactive IgG antibody profiles of the 3 pooled samples in each group were revealed by human proteome microarrays with 17,000 recombinant human proteins.

Results

Firstly, 525 plasma proteins were quantified and 12 proteins were discovered differentially expressed between the two groups. Secondly, more than 500 proteins were recognized by plasma antibodies, 14 proteins ware differentially reacted with the autoantibodies in the two groups. Bioinformatics analysis showed some of the differential proteins and targeted autoantigens were involved in cancer, cardiovascular disease and immunity.

Conclusions

Proteomic and autoantibody profiles varied between the offspring of longevous and normal families which are from the same area and shared the same environmental factors. The identified differences were reported to be involved in several physiological and pathological pathways. The identified proteins will contribute to a better understanding of the proteomic characteristics of people from Bama longevous area and a revelation of the molecular mechanisms of longevity.

RPLP1 promotes tumor metastasis and is associated with a poor prognosis in triple-negative breast cancer patients

Background

Cancer metastasis is the major reason for cancer related deaths, and the mechanism of cancer metastasis still unclear. RPLP1, a member of a group of proteins known as ribosomal proteins, is associated with tumorigenesis and primary cell immortalization and is involved in cellular transformation. However, the expression and potential function of RPLP1 in TNBC remain unclear.

Methods

The expression of RPLP1 in TNBC tissues and cell lines were detected with Real-Time PCR and western blotting. 81 cases of TNBC tissue samples and adjacent non-tumor tissue samples were tested by immunochemistry to determine the correlation between the RPLP1 expression and clinicopathological characteristics. In vitro, we determined the role and mechanistic pathways of RPLP1 in tumor metastasis in TNBC cell lines.

Results

In this study, we detected high levels of RPLP1 expression in TNBC samples and cell lines. RPLP1 is upregulated in triple-negative breast cancer (TNBC) tissues and cells, and high expression levels correlate with an increased risk of recurrence and metastasis. Furthermore, high RPLP1 expression was associated with a poor prognosis and was an independent prognostic marker for TNBC. In RPLP1-induced cancer metastasis, RPLP1 may increase cancer cell invasion, which is likely the result of its effect on the cancer cell epithelial-mesenchymal transition.

Conclusions

Altogether, our findings indicate RPLP1 is a poor prognostic potential biomarker and anti-metastasis candidate therapeutic target in triple-negative breast cancer.

Advances in the development of human protein microarrays

INTRODUCTION

High-content protein microarrays in principle enable the functional interrogation of the human proteome in a broad range of applications, including biomarker discovery, profiling of immune responses, identification of enzyme substrates, and quantifying protein-small molecule, protein-protein and protein-DNA/RNA interactions. As with other microarrays, the underlying proteomic platforms are under active technological development and a range of different protein microarrays are now commercially available. However, deciphering the differences between these platforms to identify the most suitable protein microarray for the specific research question is not always straightforward. Areas covered: This review provides an overview of the technological basis, applications and limitations of some of the most commonly used full-length, recombinant protein and protein fragment microarray platforms, including ProtoArray Human Protein Microarrays, HuProt Human Proteome Microarrays, Human Protein Atlas Protein Fragment Arrays, Nucleic Acid Programmable Arrays and Immunome Protein Arrays. Expert commentary: The choice of appropriate protein microarray platform depends on the specific biological application in hand, with both more focused, lower density and higher density arrays having distinct advantages. Full-length protein arrays offer advantages in biomarker discovery profiling applications, although care is required in ensuring that the protein production and array fabrication methodology is compatible with the required downstream functionality.

Emerging technologies in autoantibody testing for rheumatic diseases

Testing for the presence of antinuclear antibodies (ANAs) is a key step in the diagnosis of systemic lupus erythematosus (SLE) and other systemic autoimmune rheumatic diseases (SARD). The standard slide-based indirect immunofluorescence (IIF) test is widely used, but is limited by a relative lack of specificity for SLE and not all SARD-ANAs are detected. Alternative immunoassays that might offer enhanced diagnostic and prognostic information have evolved, and some of these have entered clinical practice. This review summarizes the current state of ANA testing and multiplex techniques for detecting other autoantibodies, the possibility of point-of-care testing, and approaches for applications in early disease stages.

Neuropsychiatric Systemic Lupus Erythematosus Involvement: Towards a Tailored Approach to Our Patients?

Neuropsychiatric involvement in systemic lupus erythematosus (NPSLE) is a complex condition that remains poorly understood, and includes heterogeneous manifestations involving both the central and peripheral nervous system, with disabling effects. There are several models to improve NPSLE diagnosis when a neurological syndrome is present. In the last couple of years, the growing knowledge of the role of cytokines and antibodies in NPSLE, as well as the development of new functional imaging techniques, has brought some insights into the physiopathology of the disease, but their validation for clinical use remains undetermined. Furthermore, besides the classic clinical approach, a new tool for screening the 19 NPSLE syndromes has also been developed. Regarding NPSLE therapeutics, there is still no evidence-based treatment approach, but some data support the safety of biological medication when classic treatment fails. Despite the tendency to reclassify SLE patients in clinical and immunological subsets, we hope that these data will inspire medical professionals to approach NPSLE in a manner more tailored to the individual patient.

Lupus brain fog: a biologic perspective on cognitive impairment, depression, and fatigue in systemic lupus erythematosus

Cognitive disturbances, mood disorders and fatigue are common in SLE patients with substantial adverse effects on function and quality of life. Attribution of these clinical findings to immune-mediated disturbances associated with SLE remains difficult and has compromised research efforts in these areas. Improved understanding of the role of the immune system in neurologic processes essential for cognition including synaptic plasticity, long term potentiation and adult neurogenesis suggests multiple potential mechanisms for altered central nervous system function associated with a chronic inflammatory illness such as SLE. This review will focus on the biology of cognition and neuroinflammation in normal circumstances and potential biologic mechanisms for cognitive impairment, depression and fatigue attributable to SLE.

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.

Autoantigen Microarray for High-throughput Autoantibody Profiling in Systemic Lupus Erythematosus

Systemic lupus erythematosus (SLE) is a complex autoimmune disease characterized by the production of autoantibodies to a broad range of self-antigens. Profiling the autoantibody repertoire using array-based technology has emerged as a powerful tool for the identification of biomarkers in SLE and other autoimmune diseases. Proteomic microarray has the capacity to hold large number of self-antigens on a solid surface and serve as a high-throughput screening method for the determination of autoantibody specificities. The autoantigen arrays carrying a wide variety of self-antigens, such as cell nuclear components (nucleic acids and associated proteins), cytoplasmic proteins, phospholipid proteins, cell matrix proteins, mucosal/secreted proteins, glomeruli, and other tissue-specific proteins, have been used for screening of autoantibody specificities associated with different manifestations of SLE. Arrays containing synthetic peptides and molecular modified proteins are also being utilized for identification of autoantibodies targeting to special antigenic epitopes. Different isotypes of autoantibodies, including IgG, IgM, IgA, and IgE, as well as other Ig subtypes, can be detected simultaneously with multi-color labeled secondary antibodies. Serum and plasma are the most common biologic materials for autoantibody detection, but other body fluids such as cerebrospinal fluid, synovial fluid, and saliva can also be a source of autoantibody detection. Proteomic microarray as a multiplexed high-throughput screening platform is playing an increasingly-important role in autoantibody diagnostics. In this article, we highlight the use of autoantigen microarrays for autoantibody exploration in SLE.