Autoantibodies in SLE: prediction and the p value matrix

Clinical Significance of Uncommon, Non-Clinical, and Novel Autoantibodies

Autoantibodies are a common mark of autoimmune reaction and their identification in the patients' serum, cerebrospinal fluid, or tissues is generally believed to represent diagnostic or prognostic biomarkers of autoimmune diseases or autoinflammatory conditions. Traditionally, autoantibody testing is an important part of the clinical examination of suspected patients, and in the absence of reliable T cell tests, characterization of autoantibody responses might be suitable in finding causes of specific autoimmune responses, their strength, and sometimes commencement of autoimmune disease. Autoantibodies are also useful for prognostic stratification in clinically diverse groups of patients if checked repeatedly. Antibody discoveries are continuing, with important consequences for verifying autoimmune mechanisms, diagnostic feasibility, and clinical management. Adding newly identified autoantibody-autoantigen pairs to common clinical laboratory panels should help upgrade and harmonize the identification of systemic autoimmune rheumatic disorders and other autoimmune conditions. Herein, we aim to summarize our current knowledge of uncommon and novel autoantibodies in the context of discussing their validation, diagnostic practicability, and clinical relevance. The regular updates within the field are important and well justified.

Diagnostic significance of combined anti-extractable nuclear antigens antibody, anti-cardiolipin antibody and anti-β2-glycoprotein 1 in systemic lupus erythematosus patients

Objective

This study aimed to investigate the diagnostic value of a combination of anti-extractable nuclear antigens (anti-ENA) antibodies, anti-cardiolipin antibodies (ACA), and anti-β2-glycoprotein 1 (anti-β2 GPI) antibodies in patients with systemic lupus erythematosus (SLE).

Methods

A total of 646 SLE patients diagnosed in our hospital between January 2020 and April 2023 were randomly selected as study subjects, while 2075 non-SLE subjects during the same period were selected as the control group. The levels of anti-extractable nuclear antigen (ENA) antibody, ACA, and anti-β2 GPI antibodies were measured, and their diagnostic value for SLE was analyzed using binary logistic regression and receiver operating characteristic (ROC) analysis.

Results

The rates of positive anti-RNP, anti-Sm, anti-Sjögren's syndrome (SS-A), and anti-SS-B antibodies in the SLE patient group were significantly higher than those in the control group, with all differences being statistically significant (P < 0.01). The rates of positive ACA, as well as the levels of ACA IgA, ACA IgG, and ACA IgM, were significantly higher in the SLE patients group compared to the control group, with statistically differences (P < 0.05). Similarly, the rates of positive anti-β2 GPI antibodies, anti-β2 GPI antibody IgA, IgG, and IgM, were significantly higher in the SLE patient group compared to the control group, with all differences being statistically significant (P < 0.01). Gender, age, positive anti-JO1 antibodies, positive anti-RNP antibodies, positive anti-SS-A antibodies, positive ACA, high level ACA IgG and ACA IgM, positive anti-β2 GPI antibodies, and high level of anti-β2 GPI antibody IgA were identified as independent risk factors for the development of SLE (P < 0.05). The combined use of age, sex, anti-ENA antibodies, ACA, and anti-β2 GPI antibodies yielded a sensitivity of 82.12% (80.41%-83.71%) and a specificity of 80.03% (76.77%-82.93%) for the diagnosis of SLE.

Conclusion

The combination of age, sex, anti-ENA antibodies, ACA, and anti-β2 GPI antibodies shows high diagnostic value for SLE and holds potential for clinical application as an auxiliary diagnostic tool for SLE.

Deep learning model to predict lupus nephritis renal flare based on dynamic multivariable time-series data

OBJECTIVES

To develop an interpretable deep learning model of lupus nephritis (LN) relapse prediction based on dynamic multivariable time-series data.

DESIGN

A single-centre, retrospective cohort study in China.

SETTING

A Chinese central tertiary hospital.

PARTICIPANTS

The cohort study consisted of 1694 LN patients who had been registered in the Nanjing Glomerulonephritis Registry at the National Clinical Research Center of Kidney Diseases, Jinling Hospital from January 1985 to December 2010.

METHODS

We developed a deep learning algorithm to predict LN relapse that consists of 59 features, including demographic, clinical, immunological, pathological and therapeutic characteristics that were collected for baseline analysis. A total of 32 227 data points were collected by the sliding window method and randomly divided into training (80%), validation (10%) and testing sets (10%). We developed a deep learning algorithm-based interpretable multivariable long short-term memory model for LN relapse risk prediction considering censored time-series data based on a cohort of 1694 LN patients. A mixture attention mechanism was deployed to capture variable interactions at different time points for estimating the temporal importance of the variables. Model performance was assessed according to C-index (concordance index).

RESULTS

The median follow-up time since remission was 4.1 (IQR, 1.7-6.7) years. The interpretable deep learning model based on dynamic multivariable time-series data achieved the best performance, with a C-index of 0.897, among models using only variables at the point of remission or time-variant variables. The importance of urinary protein, serum albumin and serum C3 showed time dependency in the model, that is, their contributions to the risk prediction increased over time.

CONCLUSIONS

Deep learning algorithms can effectively learn through time-series data to develop a predictive model for LN relapse. The model provides accurate predictions of LN relapse for different renal disease stages, which could be used in clinical practice to guide physicians on the management of LN patients.

Interferons and systemic lupus erythematosus: Pathogenesis, clinical features, and treatments in interferon-driven disease

Type I interferons (IFNs) have recently received a lot of attention with the elucidation of the pathogenesis of systemic lupus erythematosus (SLE). Type I IFNs are associated with many SLE symptoms and play a role in the pathogenesis of autoimmune diseases that may occur concurrently with SLE, such as Sjögren's syndrome, antiphospholipid syndrome, myositis, scleroderma, and interferonopathy. Type I IFNs could be the link between these diseases. However, direct measurement of type I IFN levels and the IFN gene signature is currently unavailable in clinical practice. This review discusses type I IFN signalling in SLE, investigates the role of type I IFN in the clinical manifestations and symptoms associated with SLE and other IFN-related diseases, and discusses the clinical tests that can be used to diagnose SLE and measure disease activity. In addition, the role of type I IFN-blocking therapies as potential treatments for SLE is discussed.

Identification and Clinical Correlation Analysis of IFI44 in Systemic Lupus Erythematosus Combined with Bioinformatics and Immune Infiltration Analysis

Purpose

Systemic lupus erythematosus (SLE) is a chronic autoimmune disease that can cause systemic damage to multiple organs. This study aims to analyze the value and function of IFI44 in the diagnosis and pathology of SLE by bioinformatics and immune infiltration analysis.

Patients and Methods

GSE49454 and GSE65391 of SLE were obtained from the GEO dataset, and R software was employed to identify DEGs and investigate their functions. The PPI network was utilized to identify hub genes associated with SLE. CIBERSORT was used to assess differences in immune cell infiltration in SLE patients and controls. ROC curve analysis was performed to evaluate the diagnostic value of IFI44 in SLE. The expression of IFI44 in PBMCs was detected by RT-qPCR, and the correlation between IFI44 expression and SLE-related clinical indicators was analyzed.

Results

A total of 65 DEGs were identified from the GSE49454 and GSE65391 databases. Through PPI analysis, IFI44 and RSAD2 were identified as significantly aberrantly expressed in SLE patients. SLE patients and controls showed a significant difference in the proportion of immune cell infiltration. IFI44 expression was positively correlated with activated DCs, monocytes, PCs, neutrophils, and activated memory CD4+T cells, while negatively correlated with M0 and CD8+T cells. The expression of IFI44 was significantly higher in SLE patients (P<0.01), especially in male patients (P=0.0376). ROC curve analysis demonstrated that IFI44 had a high diagnostic value for SLE. Correlation analysis indicated that IFI44 expression was correlated with levels of RBC, HGB, HCT, IgA, ESR, UPRO, C3, C4, and ENA in SLE patients.

Conclusion

IFI44 may play a role in the pathogenesis of SLE by influencing the immune microenvironment of SLE patients, and thus has the potential to serve as a diagnostic marker and therapeutic target for SLE.

Bioinformatics analysis of the pathogenic link between Epstein-Barr virus infection, systemic lupus erythematosus and diffuse large B cell lymphoma

Epstein-Barr virus (EBV) is a risk factor for diffuse large B-cell lymphoma (DLBCL) and systemic lupus erythematosus (SLE). While prior research has suggested a potential correlation between SLE and DLBCL, the molecular mechanisms remain unclear. The present study aimed to explore the contribution of EBV infection to the pathogenesis of DLBCL in the individuals with SLE using bioinformatics approaches. The Gene Expression Omnibus database was used to compile the gene expression profiles of EBV-infected B cells (GSE49628), SLE (GSE61635), and DLBCL (GSE32018). Altogether, 72 shared common differentially expressed genes (DEGs) were extracted and enrichment analysis of the shared genes showed that p53 signaling pathway was a common feature of the pathophysiology. Six hub genes were selected using protein-protein interaction (PPI) network analysis, including CDK1, KIF23, NEK2, TOP2A, NEIL3 and DEPDC1, which showed preferable diagnostic values for SLE and DLBCL and involved in immune cell infiltration and immune responses regulation. Finally, TF-gene and miRNA-gene regulatory networks and 10 potential drugs molecule were predicted. Our study revealed the potential molecular mechanisms by which EBV infection contribute to the susceptibility of DLBCL in SLE patients for the first time and identified future biomarkers and therapeutic targets for SLE and DLBCL.

Autoreactive B cell responses targeting nuclear antigens in systemic sclerosis: Implications for disease pathogenesis

A hallmark of disease pathogenesis of systemic sclerosis (SSc) is the presence of autoreactive B cell responses targeting nuclear proteins. Almost all SSc-patients harbour circulating antinuclear autoantibodies of which anti-topoisomerase 1, anti-centromere protein, anti-RNA polymerase III and anti-fibrillarin autoantibodies (ATA, ACA, ARA and AFA, respectively) are the most common and specific for SSc. In clinical practice, autoantibodies serve as diagnostic biomarkers and can aid in the identification of clinical phenotypes of the disease. However, factors driving disease progression in SSc are still poorly understood, and it is difficult to predict disease trajectories in individual patients. Moreover, treatment decisions remain rather empirical, with variable response rates in clinical trials due to patient heterogeneity. Current evidence has indicated that certain patients may benefit from B cell targeting therapies. Hence, it is important to understand the contribution of the antinuclear autoantibodies and their underlying B cell response to the disease pathogenesis of SSc.

Longitudinal analysis of ANA in the Systemic Lupus International Collaborating Clinics (SLICC) Inception Cohort

OBJECTIVES

A perception derived from cross-sectional studies of small systemic lupus erythematosus (SLE) cohorts is that there is a marked discrepancy between antinuclear antibody (ANA) assays, which impacts on clinicians' approach to diagnosis and follow-up. We compared three ANA assays in a longitudinal analysis of a large international incident SLE cohort retested regularly and followed for 5 years.

METHODS

Demographic, clinical and serological data was from 805 SLE patients at enrolment, year 3 and 5. Two HEp-2 indirect immunofluorescence assays (IFA1, IFA2), an ANA ELISA, and SLE-related autoantibodies were performed in one laboratory. Frequencies of positivity, titres or absorbance units (AU), and IFA patterns were compared using McNemar, Wilcoxon and kappa statistics, respectively.

RESULTS

At enrolment, ANA positivity (≥1:80) was 96.1% by IFA1 (median titre 1:1280 (IQR 1:640-1:5120)), 98.3% by IFA2 (1:2560 (IQR 1:640-1:5120)) and 96.6% by ELISA (176.3 AU (IQR 106.4 AU-203.5 AU)). At least one ANA assay was positive for 99.6% of patients at enrolment. At year 5, ANA positivity by IFAs (IFA1 95.2%; IFA2 98.9%) remained high, while there was a decrease in ELISA positivity (91.3%, p<0.001). Overall, there was >91% agreement in ANA positivity at all time points and ≥71% agreement in IFA patterns between IFA1 and IFA2.

CONCLUSION

In recent-onset SLE, three ANA assays demonstrated commutability with a high proportion of positivity and titres or AU. However, over 5 years follow-up, there was modest variation in ANA assay performance. In clinical situations where the SLE diagnosis is being considered, a negative test by either the ELISA or HEp-2 IFA may require reflex testing.

Understanding the Concept of Pre-Clinical Autoimmunity: Prediction and Prevention of Systemic Lupus Erythematosus: Identifying Risk Factors and Developing Strategies Against Disease Development

There is growing evidence that preceding the diagnosis or classification of systemic lupus erythematosus (SLE), patients undergo a preclinical phase of disease where markers of inflammation and autoimmunity are already present. Not surprisingly then, even though SLE management has improved over the years, many patients will already have irreversible disease-related organ damage by time they have been diagnosed with SLE. By gaining a greater understanding of the pathogenesis of preclinical SLE, we can potentially identify patients earlier in the disease course who are at-risk of transitioning to full-blown SLE and implement preventative strategies. In this review, we discuss the current state of knowledge of SLE preclinical pathogenesis and propose a screening and preventative strategy that involves the use of promising biomarkers of early disease, modification of lifestyle and environmental risk factors, and initiation of preventative therapies, as examined in other autoimmune diseases such as rheumatoid arthritis and type 1 diabetes.

Systemic lupus erythematosus: overview, management and COVID-19

Systemic lupus erythematosus is a complex multi-system disease affecting various systems of the body. The aetiology remains unclear; however, it is thought that immune system dysregulation, environmental factors and viral susceptibility can trigger the disease. Mortality remains high due to cardiovascular disease, infection and lupus nephritis. Clinical assessment should comprise an extensive history, detailed physical examination and relevant laboratory tests. Management begins with an in-depth understanding of disease-specific complications and associated comorbidities. Treatments should be based on a shared decision-making process between the patient and the clinician. Review by a specialist nurse is vital for ongoing support and education. Current treatments can increase the risk of COVID-19 infection and disease severity, so caution is needed in the current climate. New treatments are emerging and offer hope to those with refractory disease.

A scoping review of autoantibodies as biomarkers for canine autoimmune disease

Background

Autoantibody biomarkers are valuable tools used to diagnose and manage autoimmune diseases in dogs. However, prior publications have raised concerns over a lack of standardization and sufficient validation for the use of biomarkers in veterinary medicine.

Objectives

Systematically compile primary research on autoantibody biomarkers for autoimmune disease in dogs, summarize their methodological features, and evaluate their quality; synthesize data supporting their use into a resource for veterinarians and researchers.

Animals

Not used.

Methods

Five indices were searched to identify studies for evaluation: PubMed, CAB Abstracts, Web of Science, Agricola, and SCOPUS. Two independent reviewers (AET and ELC) screened titles and abstracts for exclusion criteria followed by full‐text review of remaining articles. Relevant studies were classified based on study objectives (biomarker, epitope, technique). Data on study characteristics and outcomes were synthesized in independent data tables for each classification.

Results

Ninety‐two studies qualified for final analysis (n = 49 biomarker, n = 9 epitope, and n = 34 technique studies). A high degree of heterogeneity in study characteristics and outcomes reporting was observed. Opportunities to strengthen future studies could include: (1) routine use of negative controls, (2) power analyses to inform sample sizes, (3) statistical analyses when appropriate, and (4) multiple detection techniques to confirm results.

Conclusions

These findings provide a resource that will allow veterinary clinicians to efficiently evaluate the evidence supporting the use of autoantibody biomarkers, along with the varied methodological approaches used in their development.

The Role of Clinical Features and Serum Biomarkers in Identifying Patients with Incomplete Lupus Erythematosus at Higher Risk of Transitioning to Systemic Lupus Erythematosus: Current Perspectives

Discovery of antinuclear antibodies (ANA) enabled earlier diagnosis of systemic lupus erythematosus (SLE) and other ANA⁺ connective tissue diseases (CTD). Rheumatologists increasingly encounter high referral volume of ANA⁺ patients. It has been estimated that only a small percentage of these patients will eventually transition to either SLE or other specified CTD. Incomplete lupus erythematosus (ILE) has been defined as a subset of patients who have some SLE-specific clinical manifestations but do not meet currently accepted classification criteria for SLE. Several studies have been performed with the goal of identifying clinical features, serum and tissue biomarkers that can distinguish those patients with ILE at risk of transitioning to SLE from those who will not. Increased autoantibody diversity, presence of anti-double-stranded DNA (dsDNA) antibodies, high expression of type I and type II interferon (IFN)-gene products, increased serum levels of B-cell-activating factor of the TNF family (BAFF), and certain serum cytokines and complement products have been identified as markers with positive predictive value, particularly when combined together. Once this patient population is better characterized biochemically, clinical trials should be considered with the primary objective to completely halt or slow down the transition from ILE to SLE. Hydroxychloroquine (HCQ) appears to be a promising agent due to its good tolerability and low toxicity profile and open-label studies in ILE patients have already shown its ability to delay the onset of SLE. Other therapeutics, like those targeting abnormal type I and type II IFN-signatures, B-cell specific signaling pathways, complement activation pathways and high BAFF levels should also be evaluated, but the risk to benefit ratio must be carefully determined before they can be considered.

Disease criteria of systemic lupus erythematosus (SLE); the potential role of non-criteria autoantibodies

Patients with SLE show a broad spectrum of more than 200 autoantibodies. They can be pathogenic, predictive, prognostic or even an epiphenomenon. Here, we discuss different autoantibodies that have not been included in EULAR/ACR 2019 classification criteria. Most of them have been addressed to monitor and detect disease activity and not specifically as classification criteria. Indeed, markers to assess disease activity fluctuate as compared with classification criteria and their validation is different. The development of new methods will probably bring new clinical associations and be evaluated as potential classification criteria.

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Most of the autoantibodies described in SLE are of utility in monitoring disease activity.

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The validation of activity biomarkers is different from classification criteria biomarkers.

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The new methods coming into the clinical routine will bring new associations and potentially classification criteria.

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

Systemic lupus erythematosus is characterized by autoantibodies and immune complex deposition. Several autoantibodies against mainly nuclear autoantigens have been described. One of these nuclear autoantigens is the Smith antigen. In this review, we focus on the position of autoantibodies against the Smith antigen in the classification criteria, the characteristics of the antigen, the production of anti-Smith antibodies in SLE and we discuss the different test methods available, together with their pitfalls, to detect these autoantibodies.

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Patients having anti-Sm antibodies already fulfil sixty percent of the criteria required for SLE classification.

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Correct interpretation of anti-Smith antibody test results is strongly related to the choice of the test used for detection.

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Anti-Sm antibodies are very specific for SLE.

Serum Anti-14-3-3 Zeta Autoantibody as a Biomarker for Predicting Hepatocarcinogenesis

Hepatocellular carcinoma (HCC) is a common malignancy worldwide. Alpha-fetoprotein (AFP) is still the only serum biomarker widely used in clinical settings. However, approximately 40% of HCC patients exhibit normal AFP levels, including very early HCC and AFP-negative HCC; for these patients, serum AFP is not applicable as a biomarker of early detection. Thus, there is an urgent need to identify novel biomarkers for patients for whom disease cannot be diagnosed early. In this study, we screened and identified novel proteins in AFP-negative HCC and evaluated the feasibility of using autoantibodies to those protein to predict hepatocarcinogenesis. First, we screened and identified differentially expressed proteins between AFP-negative HCC tissue and adjacent non-tumor liver tissue using SWATH-MS proteome technology. In total, 2,506 proteins were identified with a global false discovery rate of 1%, of which 592 proteins were expressed differentially with 175 upregulated and 417 downregulated (adjusted p-value <0.05, fold-change FC ≥1.5 or ≤0.67) between the tumor and matched benign samples, including 14-3-3 zeta protein. For further serological verification, autoantibodies against 14-3-3 zeta in serum were evaluated using enzyme-linked immunosorbent, Western blotting, and indirect immunofluorescence assays. Five serial serum samples from one patient with AFP-negative HCC showed anti-14-3-3 zeta autoantibody in sera 9 months before the diagnosis of HCC, which gradually increased with an increase in the size of the nodule. Based on these findings, we detected the prevalence of serum anti-14-3-3 zeta autoantibody in liver cirrhosis (LC) patients, which is commonly considered a premalignant liver disease of HCC. We found that the prevalence of autoantibodies against 14-3-3 zeta protein was 16.1% (15/93) in LC patient sera, which was significantly higher than that in patients with chronic hepatitis (0/75, p = 0.000) and normal human sera (1/60, 1.7%, p = 0.01). Therefore, we suggest that anti-14-3-3 zeta autoantibody might be a biomarker for predicting hepatocarcinogenesis. Further follow-up and research of patients with positive autoantibodies will be continued to confirm the relationship between anti-14-3-3 zeta autoantibody and hepatocarcinogenesis.

Immune checkpoints and the multiple faces of B cells in systemic lupus erythematosus

PURPOSE OF REVIEW

B-lymphocytes are crucial in the pathogenesis of systemic lupus erythematosus (SLE), including autoantibody production, antigen presentation, co-stimulation, and cytokine secretion. Co-stimulatory and co-inhibitory molecules control interactions between B and T cells during an inflammatory response, which is essential for an appropriate host protection and maintenance of self-tolerance. Here, we review recent findings about checkpoint molecules and SLE B cells including their potential therapeutic implications and experiences from clinical trials.

RECENT FINDINGS

Most prominent checkpoint molecules involved in pathologic B and T cell interaction in SLE are CD40/CD40L and inducible co-stimulator/ICOSL, both also intimately involved in the formation of germinal centers and ectopic lymphoid tissue. Dysregulations of inhibitory checkpoint molecules, like programmed death-1/programmed death-ligand 1 and B- and T-lymphocyte attenuator have been suggested to impair B cell functions in SLE recently.

SUMMARY

Accumulating evidence indicates that dampening immune responses by either blocking co-activating signals or enhancing co-inhibitory signals in different cell types is a promising approach to treat autoimmune diseases to better control active disease but may also allow resolution of chronic autoimmunity.

Systemic Lupus Erythematosus and Critical Illness

Systemic lupus erythematosus is a chronic autoimmune disorder that causes a wide range of mild to life-threatening conditions that require hospitalization and critical care. The morbidity and mortality of systemic lupus erythematosus are associated with the organ system damage caused by intermittent or chronic disease activity and with the complications of long-term and toxic immunosuppressant medication regimens. This article reviews the epidemiologic, clinical, diagnostic, and therapeutic information essential for critical care clinicians who provide care to patients with systemic lupus erythematosus.

Pregnancy Outcomes in Systemic Lupus Erythematosus Women: A single tertiary centre experience

Objectives

This study was conducted to assess pregnancy outcomes in women with systemic lupus erythematosus (SLE) in Oman.

Methods

A retrospective cohort study of 149 pregnancies in 98 women with SLE was conducted over 10 years to evaluate the impact of clinical and laboratory parameters in predicting adverse pregnancy outcomes.

Results

Mean maternal age was 30.6 ± 5 years ranging from 20–44 years, and the mean disease duration was 10 ± 5 years, ranging from 2–27 years. The most common maternal manifestations were joint pain in 36 (24.2%), lupus nephritis (LN) in 18 (12.08%), preeclampsia in 11 (7.4%), eclampsia in three (2%) and lupus flare in one pregnancy. The live birth rate was 139 (93.3%) with a mean gestational age of 36 ± 2 weeks ranging from 26–40 weeks. In total, 55 (39.6%) were preterm deliveries, six (4%) pregnancies ended in miscarriage, and four (2.7%) resulted in intrauterine fetal death. Intrauterine growth restriction was observed in 49 babies (35%). A significant association was found between hypertension (HTN) and miscarriage (P = 0.024) and preterm birth (P = 0.019). In addition, HTN was positively associated with preeclampsia (P = 0.004) and LN (P = 0.048). Antiphospholipid syndrome impacted preterm birth (P = 0.013) and postpartem haemorrhage (PPH) (P = 0.027) and was found to be a significant predictor for women developing deep vein thrombosis and pulmonary embolism (P <0.001 for both).

Conclusion

Despite potential complications, most pregnancies complicated by SLE in Oman result in good outcomes. Adverse pregnancy outcomes, however, may still occur in women with SLE. In women with SLE, pregnancy planning, careful antenatal monitoring and efficient SLE treatment need to be undertaken for successful pregnancy outcomes.

Autoantibody Discovery, Assay Development and Adoption: Death Valley, the Sea of Survival and Beyond

Dating to the discovery of the Lupus Erythematosus (LE) cell in 1948, there has been a dramatic growth in the discovery of unique autoantibodies and their cognate targets, all of which has led to the availability and use of autoantibody testing for a broad spectrum of autoimmune diseases. Most studies of the sensitivity, specificity, commutability, and harmonization of autoantibody testing have focused on widely available, commercially developed and agency-certified autoantibody kits. However, this is only a small part of the spectrum of autoantibody tests that are provided through laboratories world-wide. This manuscript will review the wider spectrum of testing by exploring the innovation pathway that begins with autoantibody discovery followed by assessment of clinical relevance, accuracy, validation, and then consideration of regulatory requirements as an approved diagnostic test. Some tests are offered as "Research Use Only (RUO)", some as "Laboratory Developed Tests (LDT)", some enter Health Technology Assessment (HTA) pathways, while others are relegated to a "death valley" of autoantibody discovery and become "orphan" autoantibodies. Those that achieve regulatory approval are further threatened by the business world's "Darwinian Sea of Survival". As one example of the trappings of autoantibody progression or failure, it is reported that more than 200 different autoantibodies have been described in systemic lupus erythematosus (SLE), a small handful (~10%) of these have achieved regulatory approval and are widely available as commercial diagnostic kits, while a few others may be available as RUO or LDT assays. However, the vast majority (90%) are orphaned and languish in an autoantibody 'death valley'. This review proposes that it is important to keep an inventory of these "orphan autoantibodies" in 'death valley' because, with the increasing availability of multi-analyte arrays and artificial intelligence (MAAI), some can be rescued to achieve a useful role in clinical diagnostic especially in light of patient stratification and precision medicine.

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.

Antinuclear Autoantibodies in Health: Autoimmunity Is Not a Synonym of Autoimmune Disease

The incidence of autoimmune diseases is increasing. Antinuclear antibody (ANA) testing is a critical tool for their diagnosis. However, ANA prevalence in healthy persons has increased over the last decades, especially among young people. ANA in health occurs in low concentrations, with a prevalence up to 50% in some populations, which demands a cutoff revision. This review deals with the origin and probable physiological or compensatory function of ANA in health, according to the concept of immunological clearance, theory of autoimmune regulation of cell functions, and the concept of functional autoantibodies. Considering ANA titers ≤1:320 as a serological marker of autoimmune diseases seems inappropriate. The role of anti-DFS70/LEDGFp75 autoantibodies is highlighted as a possible anti-risk biomarker for autoimmune rheumatic disorders. ANA prevalence in health is different in various regions due to several underlying causes discussed in the review, all influencing additive combinations according to the concept of the mosaic of autoimmunity. Not only are titers, but also HEp-2 IFA) staining patterns, such as AC-2, important. Accepting autoantibodies as a kind of bioregulator, not only the upper, but also the lower borders of their normal range should be determined; not only their excess, but also a lack of them or "autoimmunodeficiency" could be the reason for disorders.

Scleroderma-specific autoantibodies embedded in immune complexes mediate endothelial damage: an early event in the pathogenesis of systemic sclerosis

BACKGROUND

Consistently with their diagnostic and prognostic value, autoantibodies specific for systemic sclerosis (SSc) embedded in immune complexes (ICs) elicited a pro-inflammatory and pro-fibrotic cascade in healthy skin fibroblasts, engaging Toll-like receptors (TLRs) via their nucleic acid components. The objective of this study was to investigate the pathogenicity of SSc-ICs in endothelial cells.

METHODS

ICs were purified from the sera of SSc patients bearing different autoantibody specificities (antibodies against DNA topoisomerase I, centromeric proteins, RNA polymerase, and Th/To), patients with systemic lupus erythematosus (SLE) and primary anti-phospholipid syndrome (PAPS), or healthy controls (NHS) using polyethylene glycol precipitation. Human umbilical vein endothelial cells (HUVECs) were incubated with ICs, positive and negative controls. mRNA levels of endothelin-1 (et-1), collagenIα1 (colIα1), interferon (IFN)-α, and IFN-β were investigated by real-time PCR; et-1 and il-6 mRNA levels were assessed after pre-treatment with bafilomycin. ICAM-1 expression was evaluated by cell ELISA; secretion of IL-6, IL-8, and transforming growth factor (TGF)-β1 in culture supernatants was measured by ELISA. The expression of Fcγ receptors (CD64, CD32, and CD16) was assessed in endothelial cells at FACS analysis. Intracellular signaling pathways culminating with NFκB, p38MAPK, SAPK-JNK, and Akt were assessed by Western blotting. Healthy skin fibroblasts were stimulated with supernatants from HUVECs incubated with ICs, and TGF-β1 secretion and mRNA levels of colIα1 and matrix metalloproteinase (mmp)-1, protein expression of α smooth muscle actin (α-SMA), and IL-6 were evaluated by Western blotting; et-1 mRNA levels were assessed in fibroblasts pre-treated with IL-6 and TGF-β inhibitors and stimulated with ATA-ICs.

RESULTS

All SSc stimulated IL-6 secretion; ACA-ICs and anti-Th/To-ICs increased ICAM-1 expression; all SSc-ICs but anti-Th/To-ICs augmented IL-8 levels; all SSc-ICs but ACA-ICs and ARA-ICs upregulated et-1, and all SSc-ICs but ARA-ICs affected TGF-β1 secretion. colIα1, IFN-α, and IFN-β mRNA levels were not affected by any SSc-IC. FcγRII (CD32) and FcγRIII (CD16) were not detectable on HUVECs, while FcγRI (CD64) was minimally expressed. A differential modulation of tlr expression was observed: tlr2, tlr3, and tlr4 were upregulated by ATA-ICs and ACA-ICs, while anti-Th/To-ICs resulted in tlr9 upregulation. Pre-treatment with bafilomycin did not affect the upregulation of et-1 and il-6 induced by ATA-ICs, ACA-ICs, and anti-Th/To-ICs; a 23% reduction in both genes was reported for ARA-ICs. All SSc-ICs activated p38MAPK and Akt, and all SSc-ICs but ARA-ICs yielded the activation of NFκB; ATA-ICs and ACA-ICs increased the activation rate of both subunits of SAPK-JNK. When healthy skin fibroblasts were stimulated with supernatants from HUVECs incubated with SSc-ICs, TGF-β1 secretion, colIα1, α-SMA, and IL-6 expression levels were significantly modulated. Pre-treatment with IL-6 and TGF-β inhibitors prevented et-1 upregulation induced by ATA-ICs by 85% and 77%, respectively.

CONCLUSIONS

These data provide the first demonstration of the pathogenicity of ICs from scleroderma patients with different autoantibodies on the endothelium. Endothelial activation induced by SSc-ICs ultimately led to a pro-fibrotic phenotype in healthy skin fibroblasts.

Antibodies specific to ferritin light chain polypeptide are frequently detected in patients with immune‑related pancytopenia

Immuno-related pancytopenia (IRP) is characterized by pancytopenia resulting from bone marrow suppression or destruction mediated by auto-antibodies. In our previous study, a K562 cDNA library was established, which was used to screen for seven possible auto-antigens produced by hematopoietic cells in patients with IRP, including ferritin light chain (FTL). In the present study, FTL was expressed and purified, and the levels of the auto-antibodies specific to FTL were measured. Through ELISA, it was shown that the titer of anti-FTL antibodies was higher in patients with IRP without treatment compared with those who had recovered from IRP, those with severe aplastic anemia (SAA), those with myelodysplastic syndrome (MDS) and the healthy controls. Furthermore, the expression levels of FTL-mRNA were upregulated in patients with IRP without treatment compared with those who had recovered from IRP, those with MDS and the normal controls. The results suggest that FTL antibody expression is upregulated in patients with IRP. Detecting FTL antibodies may therefore have certain clinical value in differentiating between IRP, SAA and MDS. Furthermore, in specific patients with IRP, FTL as an auto-antigen may induce immune attack on hematopoietic stem cells.

Precision health: A pragmatic approach to understanding and addressing key factors in autoimmune diseases

The past decade has witnessed a significant paradigm shift in the clinical approach to autoimmune diseases, lead primarily by initiatives in precision medicine, precision health and precision public health initiatives. An understanding and pragmatic implementation of these approaches require an understanding of the drivers, gaps and limitations of precision medicine. Gaining the trust of the public and patients is paramount but understanding that technologies such as artificial intelligences and machine learning still require context that can only be provided by human input or what is called augmented machine learning. The role of genomics, the microbiome and proteomics, such as autoantibody testing, requires continuing refinement through research and pragmatic approaches to their use in applied precision medicine.