Behcet disease (BD) is a chronic systemic vasculitis and considered as an autoimmune disease. Although rare, BD can be fatal due to ruptured vascular aneurysms or severe neurological complications. To date, no known biomarker has been reported for this disease, making it difficult to diagnosis in the clinics. To undertake this challenge, we employed the HuProt arrays, each comprised of ∼20,000 unique human proteins, to identify BD-specific autoantibodies using a Two-Phase strategy established previously. In Phase I, we profiled the autoimmunity on the HuProt arrays with 75 serum samples collected from 40 BD patients, 15 diagnosed autoimmune patients who suffer from Takayasu arteritis (TA; n = 5)), ANCA associated vasculitis (AAV; n = 5), and Sjogren's syndrome (SS; n = 5), and 20 healthy subjects, and identified 20 candidate autoantigens that were significantly associated with BD. To validate these candidates, in Phase II we constructed a focused array with these 20 candidate BD-associated antigens, and use it to profile a much larger cohort, comprised of serum samples collected from 130 BD patients, 103 autoimmune patients (i.e. 40TA, 40 AAV and 23 SS), and 110 healthy controls. This allowed us to validate CTDP1 (RNA polymerase II subunit A C-terminal domain phosphatase)as a BD-specific autoantigen. The association of anti-CTDP1 with BD patients was further validated using the traditional Western blotting analysis. In conclusion, anti-CTDP1 antibody serves a novel autoantibody for Behcet disease and is expected to help more accurate clinical diagnosis.

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.

Background: Interstitial lung disease (ILD) is a relatively prevalent extra-articular manifestation of rheumatoid arthritis (RA) and contributes to significant morbidity and mortality. This study aimed to analyze the association between chitinase-3 like-protein-1(CHI3L1) and the presence of RA-ILD.Methods: A total of 239 RA patients fulfilling the American Rheumatism Association (ACR) 1987 revised criteria were enrolled and subclassified as RA-ILD and RA-nILD based on the results of high-resolution computed tomography scans (HRCT) of the chest. The disease activity of RA was assessed by Disease Activity Score for 28 joints (DAS28) and categorized as high, moderate, low, and remission. Chemiluminescence immunoassays were applied to determine the serum levels of CHI3L1. Univariate analysis was performed and the receiver operating characteristics (ROC) curves were plotted to evaluate the correlation between RA-ILD and CHI3L1.Results: Among the eligible RA patients studied, 60 (25.1%) patients were diagnosed with RA-ILD. Compared with RA-nILD, RA patients with ILD had significantly higher median age (median [IQR], 68.00 [62.00-71.75] vs 53.00 [40.00-63.00], p<0.001) and a higher proportion of males (21 (35.0%) vs 30 (16.8%), p=0.003). Notably, differences in DAS28 scores between the two groups were not observed. The serum level of CHI3L1 was significantly higher in RA-ILD patients (median [IQR], 69.69 [44.51-128.66] ng/ml vs 32.19 [21.63-56.99] ng/ml, p<0.001). Furthermore, the areas under the curve (AUC) of CHI3L1 attained 0.74 (95% confidence interval [CI], 0.68-0.81, p<0.001) in terms of identifying patients with RA-ILD from those without ILD. Similar trends were seen across the spectrum of disease activity based on DAS28-ESR.Conclusion: Our findings of elevated serum CHI3L1 levels in RA-ILD patients suggest its possible role as a biomarker to detect RA-ILD noninvasively.

Objective: Primary biliary cholangitis (PBC) is an autoimmune cholestatic liver disease whose diagnosis is based significantly on autoantibody detection. This study aims to investigate the glycosylation profile of serum IgG in PBC patients using high-throughput lectin microarrays technology. Method: Lectin microarray containing 56 lectins was used to detect and analyze the expression of serum IgG glycosylation in 99 PBC patients, 70 disease controls (DCs), and 38 healthy controls (HCs). Significant differences in PBC from control groups as well as across PBC subgroups positive for various autoantibodies were explored and verified by lectin blot technique. Results: Lectin microarray detection revealed that compared to DC and HC groups, the specific glycan level of serum IgG sialic acid in PBC patients was increased. For each PBC subgroup, glycan levels of IgG mannose and galactose were decreased in AMA-M2 positive PBC patients compared to the AMA-M2 negative group. IgG N-Acetylgalactosamine (GalNAc) and fucose were decreased in anti-sp100 positive patients. IgG galactose was increased in anti-gp210 positive patients. IgG mannose was decreased in ACA-positive patients. Although the difference in overall sialic acid level was not observed using lectin blot, all results among the above PBC subgroups were consistent with the results of the technique. Conclusion: Lectin microarray is an effective and reliable technique for analyzing glycan structure. PBC patients positive for different autoantibody exhibits distinct glycan profile. Altered levels of glycosylation may be related to the occurrence and development of the disease, which could provide a direction for new biomarker identification.

This study investigates the positivity and relevance of non-criteria antiphospholipid antibodies (aPLs) with clinical phenotypes in patients highly suspected of or diagnosed with antiphospholipid antibody syndrome (APS). Outpatient cases were included from a prospectively-maintained database, and patients were grouped into APS (n = 168), seronegative APS (SNAPS, n = 9), those meeting the diagnostic criteria for clinical events without laboratory results (only event, n = 15), those that had aPLs positivity without clinical manifestations (asymptomatic APA, n = 39), and healthy controls (n = 88). Criteria aPLs results and APS-related clinical features were extracted. Sixteen non-criteria aPLs were tested and analyzed. LA, aCL, and aβ2GpI were positive in 84.5%, 61.3%, and 74.4% of APS patients, and 61.5%, 59.0%, and 74.4% of asymptomatic APA patients. In patients negative for criteria serological tests, 23 out of 24 were positive for at least 1 non-criteria aPLs. Triple-positive patients also had significantly higher tests of some aPLs in comparison with other groups. Stroke was associated with anti-phosphatidyl-inositol (aPI) IgG and anti-phosphatidyl-glycerol (aPG) IgG. Late embryonic loss correlated with aPI IgM, and premature birth/eclampsia was associated with aPI IgG and aPG IgG. There were also positive associations between heart valve lesions and anti-phosphatidylserine–prothrombin (PS/PT) IgM, APS nephropathy and anti-phosphatidyl-choline (aPC) IgG or aPS/PT IgG, and livedo reticularis and anti-phosphatidyl-ethanolamine (aPE) IgM. The prevalence of non-criteria aPLs differed from diagnostic biomarkers in patients diagnosed with or suspected of APS. Detection of aPLs provided additive value in the evaluation of APS-related clinical manifestations.

Background: RA is a common chronic and systemic autoimmune disease, and the diagnosis is based significantly on autoantibody detection. This study aims to investigate the glycosylation profile of serum IgG in RA patients using high-throughput lectin microarray technology. Method: Lectin microarray containing 56 lectins was applied to detect and analyze the expression profile of serum IgG glycosylation in 214 RA patients, 150 disease controls (DC), and 100 healthy controls (HC). Significant differential glycan profiles between the groups of RA and DC/HC as well as RA subgroups were explored and verified by lectin blot technique. The prediction models were created to evaluate the feasibility of those candidate biomarkers. Results: As a comprehensive analysis of lectin microarray and lectin blot, results showed that compare with HC or DC groups, serum IgG from RA patients had a higher affinity to the SBA lectin (recognizing glycan GalNAc). For RA subgroups, RA-seropositive group had higher affinities to the lectins of MNA-M (recognizing glycan mannose) and AAL (recognizing glycan fucose), and RA-ILD group had higher affinities to the lectins of ConA (recognizing glycan mannose) and MNA-M while a lower affinity to the PHA-E (recognizing glycan Galβ4GlcNAc) lectin. The predicted models indicated corresponding feasibility of those biomarkers. Conclusion: Lectin microarray is an effective and reliable technique for analyzing multiple lectin–glycan interactions. RA, RA-seropositive, and RA-ILD patients exhibit distinct glycan profiles, respectively. Altered levels of glycosylation may be related to the pathogenesis of the disease, which could provide a direction for new biomarkers identification.