Detection of antinuclear antibodies: recommendations from EFLM, EASI and ICAP

Evaluation of a New Multiparametric Microdot Array-Based Immunoassay Panel for Systemic Autoimmune Disease Diagnosis

BACKGROUND

The early reliable detection and quantification of autoantibodies play an important role in autoimmune disease diagnosis and in disease-course monitoring. New technologies, such as the multiplexed determination of autoantibodies, have recently been introduced and are being adopted more frequently. The aim of this study was to evaluate the ability of a new microdot array-based multiparametric assay (ZENIT AMiDot CTD panel, A. Menarini Diagnostics, Firenze, Italy) to correctly classify patients with autoimmune rheumatic diseases (ARDs) and compare it to a fluorescence enzyme immunoassay (FEIA) for the detection of anti-ENAs.

METHODS

The study included 69 consecutive samples from patients with ARDs that were analyzed using two different methods (FEIA and AMiDot) to detect anti-CENP B and six anti-ENA antibodies: anti-Scl-70, anti-SSB/La, anti-Jo-1, anti-U1-RNP, anti-Ro52, and anti-Ro60. The control group sera came from sixty-eight blood donors. Tests were run on the automated slide processor ZENIT FLOW, and then the slides were imaged and analyzed using ZENIT fast.

RESULTS

Since the samples were selected for at least one antibody positivity with an ARD diagnosis, we did not calculate clinical sensitivity but only specificity, which was 98.53%, ranging from 90% for anti-SSB/La antibodies to 100% for anti-CENP B ones. Mean agreement among the methods assessed by Cohen's kappa was 0.816 ± 0.240.

CONCLUSIONS

The assay demonstrated good clinical performance and may be considered a valuable aid in detecting ARD patients, offering an alternative to methods such as FEIA which are largely in use today.

Harmonization of ANA testing challenge: quantification strategy to accurately predict end-point titers avoiding serial dilution

Despite the advantages of automated systems for antinuclear antibody (ANA) analysis, the prediction of end-point titers avoiding serial dilutions is still in progress. The aims of this study were to set a conversion table providing discriminant ranges of fluorescence signal intensity values (FI) corresponding to the end-point titers and validate this tool in a real-life laboratory setting. Eight hundred ninety-four serum samples were analyzed for ANA using Image Navigator System. In order to classify FI into non-overlapping groups corresponding to conventional end-point titers, statistical discriminant analysis was used. Validation study was performed calculating agreement and error rates between visual readings and conversion table of 1119 routine ANA positive samples. Setting of FI ranges corresponding to the end-point titers for different staining patterns was computed. For samples showing single pattern, the overall agreement between visual readings and conversion table was 98.4% for all titers ranging from 1:160 to 1:2560, of which 68.0% had the same titer and 30.4% were within ± one titer difference. Concordance rates according to ANA patterns were as follows: (1) nuclear 98.4%, of which 67.0% had the same titer and 31.4% ± one titer; (2) cytoplasmic 100%, of which 72.7% had the same titer and 27.3% than ± one titer; (3) mitotic 66.6%, of which 33.3% had more ± one titer. Our study developed a quantification method for autoantibodies titers assessment based on just one single sample dilution instead of traditional serial dilution approach, providing significant advantages in routine laboratory in terms of reduction in hand-on time and harmonization of results.

Comprehensive Exploration of Antinuclear Antibodies (ANAs): Unveiling Clinical Significance, Associations with Cancer, and the Nuances of Differential Diagnosis in Positive ANA Patients

This comprehensive review delves into the complex realm of antinuclear antibodies (ANAs), expanding beyond their traditional involvement in autoimmune rheumatic disorders. By digging into historical changes, diagnostic complexity, and clinical significance, the debate reveals the shifting relationships between ANAs, particularly with cancer. Specialized studies provide practical insights on ANA testing processes, standardization, and upcoming challenges. Examining prevalence trends in the United States provides a time dimension to ANA dynamics, linking autoimmune and oncological considerations. The debate delves into the complexity of lupus erythematosus, emphasizing ANAs' diverse presentations and their potential as flexible diagnostic and prognostic indicators. The complex relationship between ANAs and cancer is highlighted, demonstrating their potential as early markers or indicators of malignancies. Looking ahead, this synthesis anticipates advances in personalized medicine and collaborative research, putting ANAs at the forefront of advanced diagnostics and treatments for autoimmune disorders and cancer. This synthesis envisions a future for ANA research in which these antibodies play a critical role in promoting personalized treatment, enhancing diagnostics, and fostering collaborative initiatives that cross traditional boundaries. As ANAs grow more prominent at the junction of autoimmune illnesses and cancer, this synthesis lays the path for further research and novel advances in understanding, diagnosing, and treating complicated medical conditions.

Recognition of rare antinuclear antibody patterns based on a novel attention-based enhancement framework

Rare antinuclear antibody (ANA) pattern recognition has been a widely applied technology for routine ANA screening in clinical laboratories. In recent years, the application of deep learning methods in recognizing ANA patterns has witnessed remarkable advancements. However, the majority of studies in this field have primarily focused on the classification of the most common ANA patterns, while another subset has concentrated on the detection of mitotic metaphase cells. To date, no prior research has been specifically dedicated to the identification of rare ANA patterns. In the present paper, we introduce a novel attention-based enhancement framework, which was designed for the recognition of rare ANA patterns in ANA-indirect immunofluorescence images. More specifically, we selected the algorithm with the best performance as our target detection network by conducting comparative experiments. We then further developed and enhanced the chosen algorithm through a series of optimizations. Then, attention mechanism was introduced to facilitate neural networks in expediting the learning process, extracting more essential and distinctive features for the target features that belong to the specific patterns. The proposed approach has helped to obtained high precision rate of 86.40%, 82.75% recall, 84.24% F1 score and 84.64% mean average precision for a 9-category rare ANA pattern detection task on our dataset. Finally, we evaluated the potential of the model as medical technologist assistant and observed that the technologist's performance improved after referring to the results of the model prediction. These promising results highlighted its potential as an efficient and reliable tool to assist medical technologists in their clinical practice.

A novel way to evaluate autoantibody interference in samples with mixed antinuclear antibody patterns in the HEp-2 cell based indirect immunofluorescence assay and comparison of conventional microscopic and computer-aided pattern recognition

BACKGROUND

A major challenge of the HEp-2 cell-based indirect immunofluorescence (IIF) assays is the correct identification of the individual anti-nuclear antibodies (ANAs) if more than one is present in a sample. We created artificial mixes by pooling two different samples with a single autoantibody in different titers. Comparison of the expected and observed patterns and titers clarifies the interference between the two tested ANAs.

METHODS

Serum samples with a single homogeneous or speckled ANA pattern were serially diluted and mixed in 16 combinations, providing end-point titers of 1:5,120 to 1:80 for both patterns. These mixes were tested by a HEp-2 IIF assay and were evaluated by conventional evaluation, the EUROPattern (EPa) system and on-screen analysis.

RESULTS

Homogeneous pattern can alter the identification of the speckled pattern much more than vice versa, but both has an interfering effect on the other. The effect of the interfering on the tested pattern was higher if the titer of the former one was higher. The pattern recognition efficacy of conventional and the on-screen evaluation was similar and superior compared to the EPa analysis.

CONCLUSIONS

The application of artificial mixed samples can help the evaluation of the efficacy of manual and computer-aided ANA HEp-2 pattern recognition.

Analytical aspects of the antinuclear antibody test by HEp-2 indirect immunofluorescence: EFLM report on an international survey

OBJECTIVES

Detection of antinuclear antibodies (ANA) by indirect immunofluorescence assay using HEp-2 cells (HEp-2 IFA) is used to screen for various autoimmune diseases. HEp-2 IFA suffers from variability, which hampers harmonization.

METHODS

A questionnaire was developed to collect information on HEp-2 IFA methodology, computer-assisted diagnosis (CAD) systems, training, inter-observer variability, quality assessment, reagent lot change control, and method verification. The questionnaire was distributed to laboratories by Sciensano (Belgium), national EASI groups (Italy, Croatia, Portugal, Estonia, Greece) and ICAP (worldwide). Answers were obtained by 414 laboratories. The results were analysed in the framework of the recent EFLM/EASI/ICAP ANA recommendations (companion paper).

RESULTS

Laboratories used either HEp-2, HEp-2000, or HEp-20-10 cells and most laboratories (80%) applied the same screening dilution for children and adults. The conjugate used varied between laboratories [IgG-specific (in 57% of laboratories) vs. polyvalent]. Sixty-nine percent of CAD users reviewed the automatic nuclear pattern and 53% of CAD users did not fully exploit the fluorescence intensity for quality assurance. Internal quality control was performed by 96% of the laboratories, in 52% of the laboratories only with strongly positive samples. Interobserver variation was controlled by 79% of the laboratories. Limited lot-to-lot evaluation was performed by 68% of the laboratories. Method verification was done by 80% of the respondents.

CONCLUSIONS

Even though many laboratories embrace high-quality HEp-2 IFA, substantial differences in how HEp-2 IFA is performed and controlled remain. Acting according to the EFLM/EASI/ICAP ANA recommendations can improve the global performance and quality of HEp-2 IFA and nurture harmonization.