Challenges and Advances in SLE Autoantibody Detection and Interpretation

Hydroxychloroquine and Chloroquine-Induced Cardiac Arrhythmias and Sudden Cardiac Death in Patients With Systemic Autoimmune Rheumatic Diseases: A Systematic Review and Meta-Analysis

ABSTRACT

Hydroxychloroquine (HCQ) and chloroquine (CQ) are foundational treatments for several systemic autoimmune rheumatic diseases, including systemic lupus erythematosus (SLE) and rheumatoid arthritis (RA). Concerns regarding the risk of cardiac arrhythmia and death have been raised, yet the burden of HCQ and CQ-related cardiac toxicities remains unclear. A systematic literature search was conducted in the MEDLINE and Embase databases for articles published between the earliest date and April 2023 reporting cardiac conduction abnormalities in patients with systemic autoimmune rheumatic diseases taking HCQ or CQ. Meta-analysis was performed to calculate the difference in mean corrected QT (QTc) interval and odds ratio of prolonged QTc interval in those taking HCQ or CQ versus not. Of 2673 unique records, 34 met the inclusion criteria, including 70,609 subjects. Thirty-three studies reported outcomes in HCQ and 9 in CQ. Five studies reported outcomes in RA, 11 in SLE, and 18 in populations with mixed rheumatic diseases. Eleven studies reported mean QTc and OR for prolonged QTc for meta-analysis, all reporting outcomes in HCQ. There was a significant increase in mean QTc (10.29 ms,  P  = 0.458) among HCQ users compared to non-HCQ users in patients with RA. There was no difference in mean QTc between HCQ and non-HCQ users in other systemic autoimmune rheumatic diseases. When rheumatic diseases were pooled, HCQ users were more likely to have prolonged QTc compared to non-HCQ users (odds ratio 1.57, 95% CI, 1.19, 2.08). The results of this study suggest that clinicians should be aware of potential adverse cardiac events of HCQ and consider QTc monitoring for patients on HCQ for the treatment of systemic autoimmune rheumatic diseases.

Antinuclear antibody (ANA) positivity pattern by line immunoassay in a hospital from eastern India: Update from a laboratory perspective

Context

The existence of more than one antibody in systemic autoimmune rheumatic diseases (SARDs) or connective tissue disease (CTD) along with features of more than one autoimmune disease (AD) in an individual is suggestive of overlap syndrome (OS). Line immunoassay (LIA) can target many autoantibodies in a single approach, thus making the identification of OS feasible.

Aims and Objectives

This study aimed to identify the pattern of distribution of antinuclear antibodies by LIA prevalent in a hospital population in eastern India and identify common forms of SARD in this belt based on laboratory findings.

Material and Methods

A total of 1660 samples received for ANA profile testing by LIA were analysed.

Statistical Analysis

Factor analysis was performed with factor loading scores used in the k-means algorithm to identify clustering of various autoantibodies.

Results

U1-snRNP positivity was the highest at 16.69%, and the least frequent autoantibody noted was anti-Jo-1 at 0.71% positivity. Based on the outcome of factor analysis, three clusters were determined. Cluster 1 showed a predominance of anti-PM/Scl antibodies, cluster 2 showed a predominance of anti-dsDNA, anti-histone, anti-SmD1, anti-nucleosomes, anti-PCNA, anti-Po, anti-SSA/Ro52, anti-SSA-Ro60, anti-SSB/La, anti-Scl-70, anti-Mi-2, anti-Ku and anti-AMA-M2, and cluster 3 showed a predominance of anti-U1-snRNP.

Conclusions

Mixed connective tissue disease (MCTD) and overlap syndrome (OS) are prevalent more than pure form of an AD in our study population. OS may be missed out by monospecific immunoassays and hence adds to diagnostic challenges. LIA may be more useful in identifying specific autoantibodies by a single approach rather than monospecific immunoassays in populations after a positive screen by indirect immunofluorescence (IIF).

Anti-dsDNA antibodies in the classification criteria of systemic lupus erythematosus

Anti-double stranded DNA (dsDNA) antibodies play an important role in the diagnosis, classification and management of systemic lupus erythematosus (SLE), an autoimmune disease characterized by heterogeneous clinical manifestations and a wide range of autoantibodies, which makes the diagnosis quite challenging. In the absence of diagnostic criteria, classification criteria have been used for many decades. The first classification criteria for SLE were formulated in 1971 by the American College of Rheumatology (ACR), followed by two revisions in 1982 and 1997. In order to improve their clinical performance and to reflect new knowledge on autoantibodies, new classification criteria for SLE were issued in 2012 by the Systemic Lupus International Collaborating Clinics (SLICC). These criteria proposed to classify only patients that have at least one immunologic criterion, overcoming SLE classification based solely on clinical manifestations. In 2019, the European League Against Rheumatism (EULAR)/ACR proposed new criteria that aimed to maintain the high specificity of the ACR criteria with a sensitivity close to the SLICC 2012 criteria. These 2019 criteria reinforced the importance of autoantibodies in SLE diagnosis, assigning the highest score (6 points) to anti-dsDNA antibodies in the fully weighted scoring of the disease. The current criteria require the use of an anti-dsDNA assay with at least 90% specificity, such as the Crithidia luciliae immunofluorescence test (CLIFT) or FARR assay. However, the criteria do not comment on all the tests currently widely used in clinical laboratories. Neither do they consider the technological evolutions, nor standardization issues. Since strict adherence to any of the classification criteria, including the serological items, could lead to possible misclassification of SLE and/or delayed diagnosis, test characteristics of the distinct immunoassays should be taken into consideration.

Detecting Autoantibodies by Multiparametric Assays: Impact on Prevention, Diagnosis, Monitoring, and Personalized Therapy in Autoimmune Diseases

BACKGROUND

The introduction of multiparametric autoantibody tests has been proposed to improve the accuracy of the immunological diagnosis of autoimmune diseases (AID) and to accelerate time for completing the diagnostic process. Multiplex tests are capable of detecting many autoantibodies in a single run whereas a traditional immunoassay uses a single antigen to detect only a single specificity of autoantibodies. The reasons why multiplex tests could replace conventional immunoassays lie in the evidence that they allow for more efficient handling of large numbers of samples by the laboratory, while ensuring greater diagnostic sensitivity in AID screening.

CONTENT

This review aims to highlight the important role that multiparametric tests could assume when designed for defined profiles they are used not only for diagnostic purposes but also to predict the onset of AID to identify clinical phenotypes and to define prognosis. Furthermore, differences in the antibody profile could identify which subjects will be responsive or not to a specific pharmacological treatment.

SUMMARY

The use of autoantibody profiles, when specifically requested and performed with clinically validated technologies, can represent a significant step toward personalized medicine in autoimmunology.

Update and clinical management of anti-DNA auto-antibodies

Anti-deoxyribonucleic acid (DNA) antibodies in the clinical laboratory are intimately linked to the diagnosis and monitoring of systemic lupus erythematosus (SLE); however, the characteristics of the analytical methods and the properties of the antibodies themselves are heterogeneous. To review the definition and properties of anti-double-stranded anti-DNA (anti-dsDNA) antibodies, the adequacy of analytical methods, and the clinical requirements for this biomarker. Through PubMed we searched the existing literature with the terms anti-dsDNA, editorial, review, guideline, meta-analysis and SLE. The last search, anti-dsDNA and SLE restricted to the last two years. Information was expanded through related articles and those published in official state bodies related to anti-dsDNA and SLE. Clinical laboratory methods for anti-dsDNA analysis and their characteristics are analyze. The clinical utility of anti-dsDNA in its diagnostic, clinical association and follow-up aspects of SLE is reviewed. There is wide variability in analytical methods and deficits in standardization persist. They are part of the current SLE classification criteria and are used as markers in the follow-up of the disease. Their diagnostic usefulness improves when they are determined in antinuclear antibody (ANA)-positive patients. In follow-up, quantification is of interest, preferably with the same analytical method (given the deficits in standardization).

Evaluation of structured data from electronic health records to identify clinical classification criteria attributes for systemic lupus erythematosus

Objective

Our objective was to develop algorithms to identify lupus clinical classification criteria attributes using structured data found in the electronic health record (EHR) and determine whether they could be used to describe a cohort of people with lupus and discriminate them from a defined healthy control cohort.

Methods

We created gold standard lupus and healthy patient cohorts that were fully adjudicated for the American College of Rheumatology (ACR), Systemic Lupus International Collaborating Clinics (SLICC) and European League Against Rheumatism/ACR (EULAR/ACR) classification criteria and had matched EHR data. We implemented rule-based algorithms using structured data within the EHR system for each attribute of the three classification criteria. Individual criteria attribute and classification criteria algorithms as a whole were assessed over our combined cohorts and the overall performance of the algorithms was measured through sensitivity and specificity.

Results

Individual classification criteria attributes had a wide range of sensitivities, 7% (oral ulcers) to 97% (haematological disorders) and specificities, 56% (haematological disorders) to 98% (photosensitivity), but all could be identified in EHR data. In general, algorithms based on laboratory results performed better than those primarily based on diagnosis codes. All three classification criteria systems effectively distinguished members of our case and control cohorts, but the SLICC criteria-based algorithm had the highest overall performance (76% sensitivity, 99% specificity).

Conclusions

It is possible to characterise disease manifestations in people with lupus using classification criteria-based algorithms that assess structured EHR data. These algorithms may reduce chart review burden and are a foundation for identifying subpopulations of patients with lupus based on disease presentation to support precision medicine applications.

Standardization and Quality Assessment Under the Perspective of Automated Computer-Assisted HEp-2 Immunofluorescence Assay Systems

The recent availability of automated computer-assisted diagnosis (CAD) systems for the reading and interpretation of the anti-nuclear antibody (ANA) test performed with the indirect immunofluorescence (IIF) method on HEp-2 cells, has improved the reproducibility of the results and initiated a process of harmonization of this test. Furthermore, CAD systems provide quantitative expression of fluorescence intensity, allowing the introduction of objective quality control procedures to the monitoring of the entire process. The calibration of the reading systems and the automated image interpretation are essential prerequisites for obtaining reproducible and harmonized IIF test results and form the basis for standardization, regardless of the computer algorithms used in the different systems. The use of automated CAD systems, facilitating control procedures, represents a step forward for the quality certification of the laboratory.

Autoantibodies associated with primary biliary cholangitis are common among patients with systemic lupus erythematosus even in the absence of elevated liver enzymes

Knowledge of concomitant autoimmune liver diseases (AILD) is more detailed in primary Sjögren's syndrome (pSS) compared to systemic lupus erythematosus (SLE). Herein, the prevalence of autoantibodies associated with autoimmune hepatitis (AIH) and primary biliary cholangitis (PBC) was investigated in stored sera from patients with SLE (n = 280) and pSS (n = 114). Antibodies against mitochondria (AMA), liver-kidney microsomal (LKM) antigen, smooth muscle (SMA) and anti-nuclear antibodies (ANA) were analysed with immunofluorescence microscopy. In addition, AILD-associated autoantibodies were tested with immunoblot. Prior to sampling, eight SLE (2·9%) and three pSS (2·6%) cases were diagnosed with AILD. Among SLE-cases without known AILD (n = 272), 26 (9·6%) had PBC-associated autoantibodies, 15 (5·5%) AIH-associated autoantibodies (excluding ANA) and one serological overlap. Most subjects with PBC-associated autoantibodies had liver enzymes within reference limits (22 of 27, 81%) or mild laboratory cholestasis (two of 27, 7·4%), while one fulfilled the diagnostic PBC-criteria. AMA-M2 detected by immunoblot was the most common PBC-associated autoantibody in SLE (20 of 272, 7·4%). The prevalence of SMA (4·4%) was comparable with a healthy reference population, but associated with elevated liver enzymes in four of 12 (25%), none meeting AIH-criteria. The patient with combined AIH/PBC-serology had liver enzymes within reference limits. Among pSS cases without known AILD (n = 111), nine (8·1%) had PBC-associated, 12 (10·8%) AIH-associated autoantibodies and two overlapped. PBC-associated autoantibodies were found as frequently in SLE as in pSS but were, with few exceptions, not associated with laboratory signs of liver disease. Overall, AILD-associated autoantibodies were predominantly detected by immunoblot and no significant difference in liver enzymes was found between AILD autoantibody-negative and -positive patients.