Welcome to the Autoimmunity 2021 Congress Calendar

Background and Aims

In recent years, new autoantibodies specificities have been identified aimed at different neurological syndromes.New tests are now available for the detection of their autoantibodies, mainly in indirect immunofluorescence and immunoblot. The Laboratory of Autoimmunology is now a major element in the diagnostic pathway of patients suffering from disimmune peripheral neuropathies, demyelinizing diseases of CNS, paraneoplastic neurological syndromes and autoimmune encephalitis.

Methods

In 2018-2019, a total of 2057 tests were carried out in Modena ad Parma Autoimmunity Laboratories including: neuronal, ganglioside, AQP4, MOG, MAG, encephalitis antibodies.

Results

The positive percentages were higher for: neuronal antibodies and ganglioside antibodies respectively (18% and 35%). Autoantibody test positivity rates were very low for AQP4 and MOG (4%) and for Encephalitis research (3%). Relatively oligoclonal bands (O.B.) in CSF, support tests in infectious neurological diagnostics, cancer, inflammatory and autoimmune, we found 49/131 (37%) negative patients,35/131(27%) patients with reflex profile and 54/131 (36%) patients who are associated with MS. In terms of O.B. correlation and antibodies, patients who had positivity to different antibodies for antigens 13/88 (15%) have been largely negative for profiles MS-related CSF, except for one patient with positivity for anti-sulfatids antibodies.

Conclusions

The data shown in our study, related to the diagnostics for immuno-mediated diseases of the central and peripheral NS, indicate that there is a growing demand since these tests are proving to be of high use for clinical framing but to improve the prescriptive appropriateness, it will be necessary to improve the algorithm to be used and which matrix if serum or CSF use.

Background and Aims

Analyzing patient samples for anti-CCP autoantibodies and rheumatoid factor (RF) IgM represents a pivotal aid in the diagnosis of rheumatoid arthritis and has been included in the 2010 ACR/EULAR rheumatoid arthritis classification criteria. In the early phases of RA, its differential diagnosis from other diseases can be difficult. Some studies suggested an increase in diagnostic confidence by additionally testing for RF IgA and combining test results. We aimed to contribute to the ongoing scientific debate about the combination of test results by analyzing samples from early RA patients for anti-CCP, RF IgM and RF IgA autoantibodies.

Methods

A sample cohort of 100 rheumatoid arthritis patients (symptoms less than two years) and 149 disease controls were analyzed for the above mentioned serological markers with the respective EliA^TM tests.

Results

In this study, anti-CCP, RF IgM and RF IgA autoantibodies were measured in 62%, 62% and 50% of early RA patients at a specificity of 95.3%, 90.6% and 91.9%, respectively. 56 % of the RA samples but only 1.3% of the disease controls were positive for both anti-CCP and RF IgM leading to a positive likelihood ratio (LR(+)) of 41.72 and a positive predictive value (PPV) of 0.97. Triple positivity for all three autoantibodies was detected in 45% of the RA samples and only 0.7% of the controls. The calculated LR(+) and PPV was 67.1 and 0.98, respectively.

Conclusions

The combination of anti-CCP, RF IgM and RF IgA autoantibody testing can provide a higher diagnostic confidence of RA than testing for either marker alone.

Background and Aims

Image analysis is used for evaluation of immunofluorescence assays (IFA), e.g. detection of antinuclear antibodies (ANA) on HEp-2 cells. Automated IFA interpretation systems can capture these images, calculate relative fluorescence intensities and ascertain the pattern. Machine learning algorithms, partly referred to as 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 AI-supported model for the classification of ANA patterns according to ICAP nomenclature.

Methods

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

Sets of pre-classified images were created for each task: a) training set for supervised learning b) validation set and c) test set for evaluation of prediction accuracy.

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 ICAP nomenclature tree.

Conclusions

Machine learning algorithms add value to enhance the accuracy of image classification in automated IFA interpretation. In addition to classical pattern-recognition methods, these algorithms can provide extended information for the improvement of classification algorithms. Though our approach showed efficient learning, it required an adapted image capturing strategy.

This work was supported by BMBF - PRÆMED.BIO research grant (03WKDB).

Background and Aims

The anti-dense fine speckled 70 kD (DFS70) antibodies have been detected in patients with several chronic inflammatory conditions, cancer, rheumatic diseases and also in apparently healthy individuals. The impact of therapeutic intervention on the occurrence of these antibodies is still undefined. The aims of our study were to investigate effects of anti-TNFα therapies on the development of anti-DFS70 antibodies.

Methods

Sera from adult Rheumatoid arthritis (RA) and Spondyloarthritis (SpA) patients, fulfilling ACR/EULAR 2010 and ASAS 2011 criteria, respectively, were analyzed for anti-DFS70 antibodies as measured by indirect immunofluorescence and by immunoblotting. Medical history, demographic, clinical and laboratory data were collected at enrolment.

Results

The prevalence rate of anti-DFS70 antibodies was 4.0% (4/100) in RA and 3.8% (4/105) in SpA, respectively, showing no statistical differences between these disease groups (p>0.05). The evaluation of anti-DFS70 antibodies induction rate after biologic treatments showed that 3 out of 4 anti-DFS70 antibodies both in RA that in SpA cohort were induced by anti-TNFα therapy. Neither RA nor SpA anti-DFS70 positive patients developed the drug-induced lupus erythematosus syndrome (DIL) during treatment with anti-TNFα therapy.

Conclusions

This is the first study investigating the impact of TNFα blockers on the occurrence of anti-DFS70 antibodies. In our cohorts, the majority of anti-DFS70 antibodies were negative before initiating biologics and were induced by anti-TNFα agents. Anti-DFS70 antibodies developed after anti-TNFa therapy were not associated to clinical manifestation of DIL, thus supporting the hypothesis that these autoantibodies do not have pathogenetic role.

Background and Aims

Anti-RA33 antibodies have been observed in seronegative patients, and thus may provide added diagnostic value in early rheumatoid arthritis (RA).

Methods

134 sera from an investigation cohort (Vienna early RA cohort) and a validation cohort (Leeds early RA cohort) of 131 patients (both satisfying 2010 ACR/EULAR classification criteria) were tested for the presence of IgA, IgG and IgM isotypes of anti-RA33 antibodies by prototype assays using the EliA™ platform (Thermo Fisher Scientific). The cut-off values were chosen to achieve specificities of ≥95% against disease controls and 98% against healthy subjects*. In addition, RF-IgM as well as ACPA-IgG was detected by EliA™ (Thermo Fisher Scientific).

Results

In the investigation cohort anti-RA33 antibodies were detected in 8 out of 51 seronegative patients, reducing the ‘serological gap’ left by RF and ACPA routine testing by 15.7%. The anti-RA33 IgM isotype showed the highest sensitivity (10%) followed by IgG (6%) and IgA (3.7%) isotypes. Interestingly, the prevalence of anti-RA33 antibodies in the validation cohort was considerably higher without differences in titer. The highest sensitivity was found for the anti-RA33-IgG isotype (20.6%) followed by IgA (16%) and IgM (14.5%). Disease duration might have influenced the different distribution of anti-RA33 isotypes as as it ranged from 0.2 years (investigation cohort) 0.6 years (validation cohort). The added diagnostic value in the validation cohort was 24.5%.

Conclusions

Results suggests anti-RA33 antibody testing may aid in the diagnosis of (otherwise labelled seronegative) early RA. Furthermore disease duration might impact the distribution of anti-RA33 antibody isotypes.

* Sieghart et al. Front Immunol. 2018

Background and Aims

The development of new automated ANA screening techniques, based in simultaneous detection of autoantibodies using an array of purified/recombinant antigens has allowed identify patients who are isolated positive for some autoantibodies and who nevertheless do not have the clinic associated with these antibodies . The anti-RNP-A antibodies have very low specificity and are very often founded in the general asymptomatic population.

GOAL: To determine if these anti-RNP-A“false positives” could be identifying people who later developed an immune-mediated inflammatory disease (IMID).

Methods

310 patients isolate positive for anti RNP-A (BioPlex® 2200) and negative for ANA-immunofluorescence in the period 2012-2015 were followed-up prospectively until October 2019 (3-7 years)

Results

78 patients (25%) had previous IMID diagnosis (38.5% RA, 11.5% IBD-associated spondyloarthritis, 9% SLE, 7.7% APs, 6.4% PMR, 5% Sjögren's syndrome, 3.8% EspA-ax, and 18.1% others.
Of the 232 patients without IMID, in 76 (33%) ANA was request by routine and no follow-up was performed. In the other 156 (67%) during the follow-up, a diagnosis of IMID was reached in 23 patients (14.7%). Only in 9 (5.8%) was diagnosed an ANA-associated connective disease (1 SLE, 1 SLE induced by anti-TNFα, 2 EMTC, 2 SAF, 3 Sjögren), The other 14 (8.9%) had other autoimmune diseases not ANA-associated (5 APs, 3 RA, 2 PMR, 1 EspA-ax, 3 vasculitis). The others 133 patients (85.3%) continued without IMID

Conclusions

Our series shows only a small percentage of patients with isolated anti-RNP + get to develop an immune-mediated disease over several years of follow-up.

Background and Aims

Detection of autoantibodies is based on a two-step algorithm that includes indirect immunofluorescence (IIF) on HEp2 cells and subsequent confirmation of disease specific autoantibodies by a solid phase-based immunoassay (singleplex or multiplex). Simultaneous cell- and microbead-based autoantibodies detection by automated or visual indirect immunofluorescence (IIF) may be a specific and cost-effective alternative approach for the evaluation of SARDs.

Methods

Sera of 29 patients with SARDs and 56 patients without SARDs were assessed by HEp2 ANA IIF test (INOVA, NOVAView) and a subsequent (Bio-Rad, BioPlex 2200 ANA) assay for the presence of ANA-specific autoantibodies, respectively. The samples were also analyzed by a visual multiplex IIF test (CytoBead ANA 2 test) for the simultaneous evaluation of ANA pattern on HEp-2 cells and diseases-specific autoantibodies (anti-dsDNA, anti-Scl-70, anti-SS-A/Ro60, anti-SS-A/Ro52, anti-SS-B/La, anti-Jo-1, anti-CENP-B, anti-Sm, and anti-nRNP). For the validation of ANA/DFS IIF, anti-DFS70 positive sera samples were evaluated by DFS70 CIA using BIO-FLASH instrument.

Results

A good correlation was found between visual CytoBead ANA 2 test and automated ANA IIF (kappa=0.633). A very good agreement was found between CytoBead ANA 2 test and BioPlex 2200 ANA Screen with regard to specific autoantibodies (kappa>0.8 for every autoantibody), expect for anti-RNP antibodies (kappa = 0.660). All anti-DFS70 positive sera samples evaluated by ANA/ DFS IIF were also found to be positive by DFS70 CIA (kappa=1).

Conclusions

Based on these results, visual multiplex IIF using CytoBead ANA 2 test demonstrated a high diagnostic performance for detection of ANA and ANA-specific autoantibodies that was similar to the diagnostic performance of both screening and confirmation assays.