Welcome to the 13th International Congress on Autoimmunity interactive program

Abstract Body

Published autoimmune serology research almost universally only concern free autoantibodies in body fluids, mostly in serum. In a number of autoimmune diseases, like rheumatoid arthritis (RA) and systemic lupus erythematosus (SLE), disease-associated autoantibodies are known to form immune complexes (IC) in the circulation and/or in the target organs; in joints of RA patients and in e.g. in kidneys and skin of SLE patients. We regard “serum” as functionally constituting two separate compartments: free monomeric autoantibodies, and autoantibodies bound in immune complexes (IC), and hypothesise that the autoantibody fraction bound in IC is pathologically more relevant in a number of IC-associated autoimmune diseases. Following this hypothesis, it is logical to aim to evaluate autoantibody levels in the IC fraction in serum. But techniques to quantitate and to study the functional role of autoantibodies in IC is an unmet need, which our group explores. We have developed a technique to quantitate autoantibodies in the IC fraction in sera and other body fluids. The technique is based on magnetic beads with covalently coupled bioactive C1q. When the beads are mixed with body fluids, IgG/IgM-containing IC attach. Subsequently we elute and dissolve the bound IC, whereafter autoantibody content is measured in the eluates and results compared to serum levels and related to clinical phenotypes e.g. disease activity and treatment responses.

In the presentation I will present our work using this technique to study the role of IC-bound autoantibodies in SLE.

Abstract Body

Although autoantibodies are known as important parameters in the diagnosis of autoimmune diseases, their value in patient stratification is less understood and utilized. However, there is ample and growing evidence that autoantibodies can aid in stratifying patients with autoimmune conditions in more homogenous subsets that will eventually lead to more tailored treatment approaches and patient outcomes. Scientific evidence is available that show utility of autoantibodies in diseases such as rheumatoid arthritis (RA), myositis, systemic sclerosis (SSc) and systemic lupus erythematosus (SLE). Despite tremendous scientific progress, barriers for clinical implications persist including outdated classification criteria, the lack of education programs and regulatory constraints. This presentation summarizes some relevant aspects and aims to trigger future efforts to embrace the use of autoantibody-based stratification of patients for precision medicine.

Background and Aims

Anti-fibrillarin(U3-RNP) antibodies are useful in establishing diagnosis and prognosis in Systemic Sclerosis(SSc). Anti-fibrillarin causes a characteristic clumpy nucleolar pattern in indirect immunofluorescence assay on HEp-2 cells (HEp-2-IFA). Immunoprecipitation is the gold standard for anti-fibrillarin determination and solid-phase immunoassays (SPIA) yield inconsistent results, possibly because of antigen denaturation. We established an anti-fibrillarin Cell-Based Assay (CBA) and compared its performance with immunoprecipitation and SPIA.

Methods

To the fibrillarin gene, we added a TransMembrane Signal(TMS) that “relocates” fibrillarin to the cytoplasmic membrane. HEp-2 cells transfected with the plasmid pCMV_TMS-fibrillarin_P2A_OFP-myc were used as substrate for IFA in the CBA. Sixty-two samples with high-titer nucleolar pattern by HEp-2-IFA (41 AC-9/clumpy and 21 AC-8/AC-10 homogeneous/punctate) were tested in the fibrillarin-CBA, immunoprecipitation, line-blot and ELISA.

Results

TMS-fibrillarin was properly relocated to the cytoplasmic membrane and recognized by autoantibodies (Figure). Thirty-eight of 41 AC-9/clumpy nucleolar samples (92.7%) and none of 21 samples with other nucleolar patterns were positive for anti-fibrillarin in CBA. There was 100% agreement between the positive/negative results in the CBA and the immunoprecipitation tests. Among the 38 CBA-positive samples, only 15(39.5%) and 11(29%) were considered positive in the line-blot and ELISA assays, respectively. Among the 24 CBA-negative, only 1 was positive by line-blot and 1 by ELISA.

Conclusions

With an innovative strategy of relocating the autoantigen to the cell membrane, we developed a new assay for detection of anti-fibrillarin autoantibodies. This new CBA presented high sensitivity and specificity comparable to the gold standard Immunoprecipitation. Additionally, the fibrillarin-CBA showed much higher sensitivity than SPIA such as line-blot and ELISA.

Background and Aims

ANCA specific antibodies are related with small vessel vasculitis (SVV). Nevertheless, atypical ANCA (xANCA) are frequent in clinical practice and its positivity raises doubts and consultation in order to rule out a systemic autoimmune disease. The aim of this study is to assess whether xANCA are related with autoimmune diseases.

Methods

We collected all patients with xANCA result during 2015-2021 in a county hospital (Hospital General de Granollers) and its diagnostic.

Results

78 patients were identified, with a mean age of 62+/-8 yo, 63% of them being women and 14% smokers. None of them reported cocaine use.

14 patients (18%) were diagnosed with interstitial lung disease being interstitial usual pneumonitis (IUP)/ pulmonary fibrosis the most frequent (10 patients).

11 patients (14%) were diagnosed with inflammatory bowel disease (10 ulcerative colitis and 1 Chron’s disease), 3 autoimmune hepatitis and 2 primary biliary cholangitis.

10 patients (13%) had a bacterial infection requiring hospitalization and intravenous antibiotics (being the most frequent respiratory tract infections and urinary tract infections). One patient had an acute Epstein-Barr infection, three patients had latent tuberculosis and one patient cured syphilis.

Only one patient was diagnosed with autoimmune systemic disease: a sarcoidosis. 5 patients had been previously diagnosed with seropositive rheumatoid arthritis and three of CTD (two antiphospholipid syndrome and one undifferentiated CTD).

Conclusions

No patient was diagnosed with SVV. Multitude of diseases with autoimmune or inflammatory background and bacterial infections are related with xANCA. ANCA should be restricted when suspecting a SVV and an unspecific result (xANCA) should be careful assessed.

Background and Aims

Multiparametric anti-ganglioside antibodies ELISAs allow for a targeted investigation of immune-mediated neuropathies. There are no recognized reference materials nor reference measurement procedures for anti-ganglioside antibodies. To ensure consistency of results over time, we guarantee a transparent traceability chain. This is achieved by using an internal reference material (IRM) to produce standardized calibrators. Due to the similar structure of gangliosides, anti-GM1 antibodies can serve as a surrogate standardization.

Methods

Sialic acid residues determine fine specificities of anti-ganglioside antibodies. GM1 represents the antigenic core structure of four C6 sugars and one sialic acid, that is commonly shared among different gangliosides. Therefore, anti-GM1 antibodies were used exemplarily to standardize multiparametric anti-ganglioside antibodies ELISAs. An IRM was generated from monoclonal anti-GM1 IgG and IgM antibodies. Following the protocol by Blirup-Jensen et al.,2008, the value of the IRM is assigned to a calibrator stock, which is subsequently gravimetrically diluted into calibrators.

Results

Based on the anti-GM1 antibodies standardization, the total relative uncertainty of the calibrators of the Ganglioside-ELISAs is calculated. The IRM traceable Ganglioside-ELISAs will be compared to the current version in a validation stage. The assays were designed to fulfill European IVDR requirements (EU Regulation 2017/746).

Conclusions

Based on the modularity and structural similarity of various gangliosides, that are targeted by autoantibodies in neuropathies, anti-GM1 antibodies can serve as a surrogate standardization. The transparent anti-GM1 antibodies-based traceability chain of the anti-ganglioside antibodies ELISAs truly displays the standardization of the assays.

Background and Aims

The use of first-line biologics such as the anti-TNF monoclonal antibody infliximab is now routine in the treatment of many IMIDs, but the efficacy of these drugs is limited in ~50% of patients by development of immunogenic antibodies against them. The prevalent extended HLA haplotype DRB1*03:01_DQA1*05:01_DQB1*02:01(DQ2) has been repeatedly implicated in the development of this immunogenicity against infliximab. We therefore hypothesized that presentation of specific anti-TNF drug peptides by one or more of the relevant HLA heterodimers contribute to the development of anti-drug immunogenicity.

Methods

Monocyte-derived dendritic cells from patients homozygously expressing DQ2 (n=4) or control haplotypes (n=9) were pulsed with infliximab, followed by acid elution of HLA presented peptides. Samples were concentrated and analysed in duplicate via LC-MS. Resulting spectra were queried via PEAKS software against a human proteome database with sequences for adalimumab and infliximab included. Uniquely identified peptides were synthesized and used in cultured ELISPOTs to assess T-cell restimulation capacity of each peptide.

Results

LC-MS analysis of PBMC samples identified unique peptides originating from the infliximab biologic that are only presented in cells expressing the DQ2 haplotype. Additionally, ELISPOT analysis indicates a DQ2 specific response to infliximab peptides, observable in individuals who have recently stopped infliximab therapy or those currently on the drug.

Conclusions

Based on these data, we suggest specific infliximab peptide presentation by either allele in the DQ2 extended haplotype may contribute to the development of immunogenicity against the drug, and that it may therefore be possible to engineer a non-immunogenic alternative.

Background and Aims

Rheumatoid factor (RF) and anti-citrullinated protein/peptide antibodies (ACPA) are important biomarkers for diagnosis and classification of rheumatoid arthritis (RA). However, there is poor harmonization of RF and ACPA assays. The aim of this study was to refine RF and ACPA interpretation across commercial assays.

Methods

Six total RF isotype-nonspecific assays, three RF IgM isotype-specific assays and nine ACPA IgG assays of thirteen different companies were evaluated using 398 diagnostic samples from RA patients and 1073 disease controls.

Results

Using cut-offs proposed by the manufacturer, there was a large variability in sensitivity and specificity between assays. Thresholds of antibody levels were determined based on predefined specificities and used to define test result intervals. Test result interval-specific likelihood ratios (LRs) were concordant across the different RF and ACPA assays. For all assays, the LR for RA increased with increasing antibody level. Higher LRs were found for ACPA than for RF. ACPA levels associated with LRs >80 were found in a substantial fraction (>22%) of RA patients.

Conclusions

Defining thresholds for antibody levels and assigning test result interval-specific LRs allows alignment of clinical interpretation for all RF and ACPA assays.

Background and Aims

Chronic inflammatory diseases which include cardiovascular disease (CVD, atherosclerosis, rheumatic and autoimmune diseases and others, . Phosphorylcholine (PC) is a both a danger associated molecular pattern (DAMP), present on oxidized LDL (OxLDL) in atherosclerotic lesions and dead cells, and a pathogen associated molecular pattern (PAMP).

Methods

We have used a combination of cohort studies, measuring anti-PC in different cohort studies, in relation to atherosclerosis, cardiovascular disease, rheumatic disease, especially SLE and determined that anti-PC is associated with protection in these disease conditions, using ELISA. Several different experimental methods were used to determine potential underlying mechanisms.

Results

anti-PC, especially IgM and IgG1 anti-PC are associated with protection in atherosclerosis, CVD, rheumatic disease, especially SLE and also other chronic inflammatory diseases. Anti-PC inhibits pro-inflammatory effects of oxidized lipids exposing PC, promotes polarization of anti-inflammatory T regulatory cells, from healthy donors, atherosclerotic plaques, and also SLE-patients, inhibits uptake of oxLDL by macrophagesand inhibits clearance of dead cells

Conclusions

IgM and IgG1 anti-PC are associated with protection in chronic inflammatory diseases, especially atherosclerosis and SLE, but also in a growing number of related ones. This notion is supported by epidemiological and experimental evidence, where also plausible mechanisms have been described. One cause of low anti-PC levels may be lack of exposure to PC-carrying microorganisms, including parasites, nematodes and bacteria which from an evolutionary point of view were more present in previous times. Immunization to raise these antibodies could therefore be an interesting possibility, which deserves attention.

Background and Aims

Detection of antinuclear antibodies (ANA) on HEp-2 cells by automated immunofluorescence assay (IFA) interpretation systems is the tool of choice for IFA automation. Machine-learning algorithms, a branch of artificial intelligence (AI), are considered the state-of-the-art in image classification. Especially deep learning algorithms based on convolutional neural networks (CNN) are regarded particularly powerful. The aim of the study was to create a complete automated AI-supported classification of ANA patterns according to revised ICAP nomenclature tree.

Methods

CNNs were established and trained for major ANA sub-classification tasks: a) metaphase recognition in DAPI, b) metaphase pattern, c) interphase pattern, d) pleomorphic pattern and e) cytoplasmic pattern. Images were obtained by an automated IFA interpretation system (akironNEO, Medipan, Germany).

Sets of pre-classified images were manually created for each task: a) training set for supervised learning b) validation set and c) test set for evaluation of prediction accuracy. Followed by merging rules of single model results to achieve final ICAP conform pattern result.

Results

Trained CNNs showed true classification rates above 95% for all models. The CNN were able to learn important features for major ANA sub-classification tasks. Merged results provided a classification model for revised ICAP nomenclature tree at competent-level that achieved high accuracy in consecutive routine samples.

Conclusions

Machine-learning algorithms add value to enhance the accuracy of image classification in automated IFA interpretation systems. Our approach showed efficient learning of competent-level pattern allowing full automation of ICAP nomenclature conform ANA classification.