Preventing the development of SLE: identifying risk factors and proposing pathways for clinical care

Systemic lupus erythematosus

Systemic lupus erythematosus (SLE) is a multisystemic autoimmune disease characterised by the presence of autoantibodies towards nuclear antigens, immune complex deposition, and chronic inflammation at classic target organs such as skin, joints, and kidneys. Despite substantial advances in the diagnosis and management of SLE, the burden of disease remains high. It is important to appreciate the typical presentations and the diagnostic process to facilitate early referral and diagnosis for patients. In most patients, constitutional, mucocutaneous, and musculoskeletal symptoms represent the earliest complaints; these symptoms can include fatigue, lupus-specific rash, mouth ulcers, alopecia, joint pain, and myalgia. In this Seminar we will discuss a diagnostic approach to symptoms in light of the latest classification criteria, which include a systematic evaluation of clinical manifestations (weighted within each domain) and autoantibody profiles (such as anti-double-stranded DNA, anti-Sm, hypocomplementaemia, or antiphospholipid antibodies). Non-pharmacotherapy management is tailored to the individual, with specific lifestyle interventions and patient education to improve quality of life and medication (such as hydroxychloroquine or immunosuppressant) adherence. In the last decade, there have been a few major breakthroughs in approved treatments for SLE and lupus nephritis, such as belimumab, anifrolumab, and voclosporin. However the disease course remains variable and mortality unacceptably high. Access to these expensive medications has also been restricted across different regions of the world. Nonetheless, understanding of treatment goals and strategies has improved. We recognise that the main goal of treatment is the achievement of remission or low disease activity. Comorbidities due to both disease activity and treatment adverse effects, especially infections, osteoporosis, and cardiovascular disease, necessitate vigilant prevention and management strategies. Tailoring treatment options to achieve remission, while balancing treatment-related comorbidities, are priority areas of SLE management.

Risk prediction models for incident systemic lupus erythematosus among women in the Nurses' health study cohorts using genetics, family history, and lifestyle and environmental factors

OBJECTIVE

Systemic lupus erythematosus (SLE) is a severe multisystem autoimmune disease that predominantly affects women. Its etiology is complex and multifactorial, with several known genetic and environmental risk factors, but accurate risk prediction models are still lacking. We developed SLE risk prediction models, incorporating known genetic, lifestyle and environmental risk factors, and family history.

METHODS

We performed a nested case-control study within the Nurses' Health Study cohorts (NHS). NHS began in 1976 and enrolled 121,700 registered female nurses ages 30-55 from 11 U.S. states; NHSII began in 1989 and enrolled 116,430 registered female nurses ages 25-42 from 14 U.S. states. Participants were asked about lifestyle, reproductive and environmental exposures, as well as medical information, on biennial questionnaires. Incident SLE cases were self-reported and validated by medical record review (Updated 1997 American College of Rheumatology classification criteria). Those with banked blood samples for genotyping (∼25% of each cohort), were selected and matched by age (± 4 years) and race/ethnicity to women who had donated a blood sample but did not develop SLE. Lifestyle and reproductive variables, including smoking, alcohol use, body mass index, sleep, socioeconomic status, U.S. region, menarche age, oral contraceptive use, menopausal status/postmenopausal hormone use, and family history of SLE or rheumatoid arthritis (RA) were assessed through the questionnaire prior to SLE diagnosis questionnaire cycle (or matched index date). Genome-wide genotyping results were used to calculate a SLE weighted genetic risk score (wGRS) using 86 published single nucleotide polymorphisms (SNPs) and 10 classical HLA alleles associated with SLE. We compared four sequential multivariable logistic regression models of SLE risk prediction, each calculating the area under the receiver operating characteristic curve (AUC): 1) SLE wGRS, 2) SLE/RA family history, 3) lifestyle, environmental and reproductive factors and 4) combining model 1-3 factors. Models were internally validated using a bootstrapped estimate of optimism of the AUC. We also examined similar sequential models to predict anti-dsDNA positive SLE risk.

RESULTS

We identified and matched 138 women who developed incident SLE to 1136 women who did not. Models 1-4 yielded AUCs 0.63 (95%CI 0.58-0.68), 0.64 (95%CI 0.59-0.68), 0.71(95% CI 0.66-0.75), and 0.76 (95% CI 0.72-0.81). Model 4 based on genetics, family history and eight lifestyle and environmental factors had best discrimination, with an optimism-corrected AUC 0.75. AUCs for similar models predicting anti-dsDNA positive SLE risk, were 0.60, 0.63, 0.81 and 0.82, with optimism corrected AUC of 0.79 for model 4.

CONCLUSION

A final model including SLE weighted genetic risk score, family history and eight lifestyle and environmental SLE risk factors accurately classified future SLE risk with optimism corrected AUC of 0.75. To our knowledge, this is the first SLE prediction model based on known risk factors. It might be feasibly employed in at-risk populations as genetic data are increasingly available and the risk factors easily assessed. The NHS cohorts include few non-White women and mean age at incident SLE was early 50s, calling for further research in younger and more diverse cohorts.

Longitudinal Immune Cell Profiling in Patients With Early Systemic Lupus Erythematosus

OBJECTIVES

To investigate the immune cell profiles of patients with systemic lupus erythematosus (SLE), and to identify longitudinal changes in those profiles over time.

METHODS

We employed mass cytometry with 3 different panels of 38-39 markers (an immunophenotyping panel, a T cell/monocyte panel, and a B cell panel) in cryopreserved peripheral blood mononuclear cells (PBMCs) from 9 patients with early SLE, 15 patients with established SLE, and 14 controls without autoimmune disease. We used machine learning-driven clustering, flow self-organizing maps, and dimensional reduction with t-distributed stochastic neighbor embedding to identify unique cell populations in early SLE and established SLE. We used mass cytometry data of PBMCs from 19 patients with early rheumatoid arthritis (RA) and 23 controls to compare levels of specific cell populations in early RA and SLE. For the 9 patients with early SLE, longitudinal mass cytometry analysis was applied to PBMCs at enrollment, 6 months after enrollment, and 1 year after enrollment. Serum samples were also assayed for 65 cytokines using Luminex multiplex assay, and associations between cell types and cytokines/chemokines were assessed.

RESULTS

Levels of peripheral helper T cells, follicular helper T (Tfh) cells, and several Ki-67+ proliferating subsets (ICOS+Ki-67+ CD8 T cells, Ki-67+ regulatory T cells, CD19intermediate Ki-67high plasmablasts, and PU.1high Ki-67high monocytes) were increased in patients with early SLE, with more prominent alterations than were seen in patients with early RA. Longitudinal mass cytometry and multiplex serum cytokine assays of samples from patients with early SLE revealed that levels of Tfh cells and CXCL10 had decreased 1 year after enrollment. Levels of CXCL13 were positively correlated with levels of several of the expanded cell populations in early SLE.

CONCLUSION

Two major helper T cell subsets and unique Ki-67+ proliferating immune cell subsets were expanded in patients in the early phase of SLE, and the immunologic features characteristic of early SLE evolved over time.

The Role of Autoantibody Testing in Modern Personalized Medicine

Personalized medicine (PM) aims individualized approach to prevention, diagnosis, and treatment. Precision Medicine applies the paradigm of PM by defining groups of individuals with akin characteristics. Often the two terms have been used interchangeably. The quest for PM has been advancing for centuries as traditional nosology classification defines groups of clinical conditions with relatively similar prognoses and treatment options. However, any individual is characterized by a unique set of multiple characteristics and therefore the achievement of PM implies the determination of myriad demographic, epidemiological, clinical, laboratory, and imaging parameters. The accelerated identification of numerous biological variables associated with diverse health conditions contributes to the fulfillment of one of the pre-requisites for PM. The advent of multiplex analytical platforms contributes to the determination of thousands of biological parameters using minute amounts of serum or other biological matrixes. Finally, big data analysis and machine learning contribute to the processing and integration of the multiplexed data at the individual level, allowing for the personalized definition of susceptibility, diagnosis, prognosis, prevention, and treatment. Autoantibodies are traditional biomarkers for autoimmune diseases and can contribute to PM in many aspects, including identification of individuals at risk, early diagnosis, disease sub-phenotyping, definition of prognosis, and treatment, as well as monitoring disease activity. Herein we address how autoantibodies can promote PM in autoimmune diseases using the examples of systemic lupus erythematosus, antiphospholipid syndrome, rheumatoid arthritis, Sjögren syndrome, systemic sclerosis, idiopathic inflammatory myopathies, autoimmune hepatitis, primary biliary cholangitis, and autoimmune neurologic diseases.

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.

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.

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.

Generating evidence to inform health technology assessment of treatments for SLE: a systematic review of decision-analytic model-based economic evaluations

This study aimed to understand and appraise the approaches taken to handle the complexities of a multisystem disease in published decision-analytic model-based economic evaluations of treatments for SLE. A systematic review was conducted to identify all published model-based economic evaluations of treatments for SLE. Treatments that were considered for inclusion comprised antimalarial agents, immunosuppressive therapies, and biologics including rituximab and belimumab. Medline and Embase were searched electronically from inception until September 2018. Titles and abstracts were screened against the inclusion criteria by two reviewers; agreement between reviewers was calculated according to Cohen’s κ. Predefined data extraction tables were used to extract the key features, structural assumptions and data sources of input parameters from each economic evaluation. The completeness of reporting for the methods of each economic evaluation was appraised according to the Consolidated Health Economic Evaluation Reporting Standards (CHEERS) statement. Six decision-analytic model-based economic evaluations were identified. The studies included azathioprine (n=4), mycophenolate mofetil (n=3), cyclophosphamide (n=2) and belimumab (n=1) as relevant comparator treatments; no economic evaluation estimated the relative cost-effectiveness of rituximab. Six items of the CHEERS statement were reported incompletely across the sample: target population, choice of comparators, measurement and valuation of preference-based outcomes, estimation of resource use and costs, choice of model, and the characterisation of heterogeneity. Complexity in the diagnosis, management and progression of disease can make decision-analytic model-based economic evaluations of treatments for SLE a challenge to undertake. The findings from this study can be used to improve the relevance of model-based economic evaluations in SLE and as an agenda for research to inform future health technology assessment and decision-making.

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.

Autoimmune markers for progression of Libby amphibole lamellar pleural thickening

Exposure to Libby Asbestiform Amphibole (LAA) is associated with asbestos-related diseases, including mesothelioma, pulmonary carcinoma, pleural fibrosis, and systemic autoimmune diseases. The pleural fibrosis can manifest as a rapidly progressing lamellar pleural thickening (LPT), which causes thoracic pain, dyspnea, and worsening pulmonary function tests (PFT). It is refractory to treatment and frequently fatal.Objective: Because of the immune dysfunction that has been described in the LAA-exposed population and the association of pleural manifestations with the presence of autoantibodies, this study tested whether specific immunological factors were associated with progressive LPT and whether they could be used as markers of progressive disease.Methods: Subjects were placed into three study groups defined as (1) progressive LPT, (2) stable LPT, (3) no LPT. Serum samples were tested for antinuclear autoantibodies, mesothelial cell autoantibodies, anti-plasminogen antibodies, IL1 beta, and IL17; which have all been shown to be elevated in mice and/or humans exposed to LAA.Results: Group 1 had significantly higher mean values for all of the autoantibodies, but not IL1 or IL-17, compared to the control Group 3. All three autoantibody tests had high specificity but low sensitivity, but ROC area-under-the-curve values for all three antibodies were over 0.7, statistically higher than a test with no value. When all LPT subjects were combined (Progressive plus Stable), no marker had predictive value for disease.Conclusion: The data support the hypothesis that progressive LPT is associated with immunological findings that may serve as an initial screen for progressive LPT.

Autoantibodies in SLE: prediction and the p value matrix

Autoantibodies (AA) and antinuclear antibodies (ANA) serve as key diagnostic and classification criteria for systemic lupus erythematosus (SLE). More than 200 different AA have been reported in SLE, although only a handful (<20) are considered "mainstream" because they are widely and routinely used in diagnostic, research and clinical medicine. Although the vast majority of AA have been relegated to the diminished status of "orphan" AA, some serve as predictors of SLE because they first appear in very early or subclinical SLE. Some AA are pathogenic, whereas others are thought to protect against or ameliorate disease progression and, hence, taken together can be used as predictive biomarkers of prognosis. Although studies have shown that specific AA are detected in the preclinical phase of SLE and are biomarkers of increased risk of developing the disease, AA are currently not widely used to predict very early SLE in individuals who have low pretest probability of disease. With the advent of multianalyte arrays with analytic algorithms, emerging evidence indicates that when certain combinations of biomarkers, such as the interferon signature and stem cell factor accompany AA and ANA, the predictive power for SLE is markedly increased.

Preclinical and early systemic lupus erythematosus

The challenge of early diagnosis and treatment is a timely issue in the management of systemic lupus erythematosus (SLE), as autoimmunity starts earlier than its clinical manifestations. Hence, growing efforts for stratification of patients according to the individual risk of developing specific clinical manifestations and/or predicting a better response to a given treatment have led to the proposal of several biomarkers, which require validation for use in clinical practice. In this viewpoint, we aim at distinguishing and discussing the features and the approach to asymptomatic immunological abnormalities potentially heralding the development of SLE, defined as preclinical lupus, and clinical manifestations consistent with SLE not yet fulfilling classification criteria, defined as early lupus. In case of preclinical SLE, careful surveillance using available screening tools is paramount, while patients with early lupus deserve an appropriate and timely diagnosis and, consequently, a proper treatment including hydroxychloroquine as the anchor drug.

Antinuclear Antibody-Negative Systemic Lupus Erythematosus in an International Inception Cohort

OBJECTIVE

The spectrum of antinuclear antibodies (ANAs) is changing to include both nuclear staining as well as cytoplasmic and mitotic cell patterns (CMPs) and accordingly a change is occurring in terminology to anticellular antibodies. This study examined the prevalence of indirect immunofluorescence (IIF) anticellular antibody staining using the Systemic Lupus International Collaborating Clinics inception cohort.

METHODS

Anticellular antibodies were detected by IIF on HEp-2000 substrate using the baseline serum. Three serologic subsets were examined: ANA positive (presence of either nuclear or mixed nuclear/CMP staining), anticellular antibody negative (absence of any intracellular staining), and isolated CMP staining. The odds of being anticellular antibody negative versus ANA or isolated CMP positive was assessed by multivariable analysis.

RESULTS

A total of 1,137 patients were included; 1,049 (92.3%) were ANA positive, 71 (6.2%) were anticellular antibody negative, and 17 (1.5%) had an isolated CMP. The isolated CMP-positive group did not differ from the ANA-positive or anticellular antibody-negative groups in clinical, demographic, or serologic features. Patients who were older (odds ratio [OR] 1.02 [95% confidence interval (95% CI) 1.00, 1.04]), of white race/ethnicity (OR 3.53 [95% CI 1.77, 7.03]), or receiving high-dose glucocorticoids at or prior to enrollment (OR 2.39 [95% CI 1.39, 4.12]) were more likely to be anticellular antibody negative. Patients on immunosuppressants (OR 0.35 [95% CI 0.19, 0.64]) or with anti-SSA/Ro 60 (OR 0.41 [95% CI 0.23, 0.74]) or anti-U1 RNP (OR 0.43 [95% CI 0.20, 0.93]) were less likely to be anticellular antibody negative.

CONCLUSION

In newly diagnosed systemic lupus erythematosus, 6.2% of patients were anticellular antibody negative, and 1.5% had an isolated CMP. The prevalence of anticellular antibody-negative systemic lupus erythematosus will likely decrease as emerging nomenclature guidelines recommend that non-nuclear patterns should also be reported as a positive ANA.

The Utilization of Autoantibodies in Approaches to Precision Health

Precision health (PH) applied to autoimmune disease will need paradigm shifts in the use and application of autoantibodies and other biomarkers. For example, autoantibodies combined with other multi-analyte “omic” profiles will form the basis of disease prediction allowing for earlier intervention linked to disease prevention strategies, as well as earlier, effective and personalized interventions for established disease. As medical intervention moves to disease prediction and a model of “intent to PREVENT,” diagnostics will include an early symptom/risk-based, as opposed to a disease-based approach. Newer diagnostic platforms that utilize emerging megatrends such as deep learning and artificial intelligence and close the gaps in autoantibody diagnostics will benefit from paradigm shifts thereby facilitating the PH agenda.

Incremental direct medical costs of systemic lupus erythematosus patients in the years preceding diagnosis: A general population-based study

Objective We estimated the incremental (extra) direct medical costs of a population-based cohort of newly diagnosed systemic lupus erythematosus (SLE) for five years before and after diagnosis, and the impact of sex and socioeconomic status (SES) on pre-index costs for SLE. Methods We identified all adults newly diagnosed with SLE over 2001-2010 in British Columbia, Canada, and obtained a sample of non-SLE individuals from the general population, matched on sex, age, and calendar-year of study entry. We captured costs for all outpatient encounters, hospitalisations, and dispensed medications each year. Using generalised linear models, we estimated incremental costs of SLE each year before/after diagnosis (difference in costs between SLE and non-SLE, controlling for covariates). Similar models were used to examine the impact of sex and SES on costs within SLE. Results We included 3632 newly diagnosed SLE (86% female, mean age 49.6 ± 15.9) and 18,060 non-SLE individuals. Over the five years leading up to diagnosis, per-person healthcare costs for SLE patients increased year-over-year by 35%, on average, with the biggest increases in the final two years by 39% and 97%, respectively. Per-person all-cause medical costs for SLE the year after diagnosis (Year + 1) averaged C$12,019 (2013 Canadian) with 58% from hospitalisations, 24% outpatient, and 18% from prescription medications; Year + 1 costs for non-SLE averaged C$2412. Following adjustment for age, sex, urban/rural residence, socioeconomic status, and prior year's comorbidity score, SLE was associated with significantly greater hospitalisation, outpatient, and medication costs than non-SLE in each year of study. Altogether, adjusted incremental costs of SLE rose from C$1131 per person in Year -5 (fifth year before diagnosis) to C$2015 (Year -2), C$3473 (Year -1) and C$6474 (Year + 1). In Years -2, -1 and +1, SLE patients in the lowest SES group had significantly greater costs than the highest SES. Unlike the non-SLE cohort, male patients with SLE had higher costs than females. Annual incremental costs of SLE males (vs. SLE females) rose from C$540 per person in Year -2, to C$1385 in Year -1, and C$2288 in Year + 1. Conclusion Even years before diagnosis, SLE patients incur significantly elevated direct medical costs compared with the age- and sex-matched general population, for hospitalisations, outpatient care, and medications.

Analysis of autoantibody profiles in two asbestiform fiber exposure cohorts

An increased risk for Systemic Autoimmune Diseases (SAID) was reported in the population of Libby, Montana, where extensive exposure to asbestiform amphiboles occurred through mining and use of asbestiform fiber-laden vermiculite. High frequencies of antinuclear autoantibodies (ANA) were detected in individuals and mice exposed to Libby Asbestiform Amphiboles (LAA). Among the 6603 individuals who have undergone health screening at the Center for Asbestos Related Diseases (CARD, Libby MT), the frequencies of rheumatoid arthritis, systemic lupus erythematosus, sarcoidosis, and systemic sclerosis are significantly higher than expected prevalence in the United States. While these data support the hypothesis that LAA can trigger autoimmune responses, evidence suggests that chrysotile asbestos does not. Serological testing was therefore performed in subjects exposed to LAA or predominantly chrysotile (New York steamfitters) using multiplexed array technologies. Analyses were performed in order to determine a) autoantibody profiles in each cohort, and b) whether the two populations could be distinguished through predictive modeling. Analysis using perMANOVA testing confirmed a significant difference between autoantibody profiles suggesting differential pathways leading to autoantibody formation. ANA were more frequent in the LAA cohort. Specific autoantibodies more highly expressed with LAA-exposure were to histone, ribosomal P protein, Sm/Ribonucleoproteins, and Jo-1 (histidyl tRNA synthetase). Myositis autoantibodies more highly expressed in the LAA cohort were Jo-1, PM100, NXP2, and Mi2a. Predictive modeling demonstrated that anti-histone antibodies were most predictive for LAA exposure, and anti-Sm was predictive for the steamfitters' exposure. This emphasizes the need to consider fiber types when evaluating risk of SAID with asbestos exposure.

Emerging technologies in autoantibody testing for rheumatic diseases

Testing for the presence of antinuclear antibodies (ANAs) is a key step in the diagnosis of systemic lupus erythematosus (SLE) and other systemic autoimmune rheumatic diseases (SARD). The standard slide-based indirect immunofluorescence (IIF) test is widely used, but is limited by a relative lack of specificity for SLE and not all SARD-ANAs are detected. Alternative immunoassays that might offer enhanced diagnostic and prognostic information have evolved, and some of these have entered clinical practice. This review summarizes the current state of ANA testing and multiplex techniques for detecting other autoantibodies, the possibility of point-of-care testing, and approaches for applications in early disease stages.

Pathogenesis of Human Systemic Lupus Erythematosus: A Cellular Perspective

Systemic lupus erythematosus (SLE) is a chronic autoimmune disease affecting multiple organs. A complex interaction of genetics, environment, and hormones leads to immune dysregulation and breakdown of tolerance to self-antigens, resulting in autoantibody production, inflammation, and destruction of end-organs. Emerging evidence on the role of these factors has increased our knowledge of this complex disease, guiding therapeutic strategies and identifying putative biomarkers. Recent findings include the characterization of genetic/epigenetic factors linked to SLE, as well as cellular effectors. Novel observations have provided an improved understanding of the contribution of tissue-specific factors and associated damage, T and B lymphocytes, as well as innate immune cell subsets and their corresponding abnormalities. The intricate web of involved factors and pathways dictates the adoption of tailored therapeutic approaches to conquer this disease.

Clinical and Immunologic Profiles in Incomplete Lupus Erythematosus and Improvement with Hydroxychloroquine Treatment

Objective. The study goals were to evaluate performance of SLE classification criteria, to define patients with incomplete lupus erythematosus (ILE), and to probe for features in these patients that might be useful as indicators of disease status and hydroxychloroquine response. Methods. Patients with ILE (N = 70) and SLE (N = 32) defined by the 1997 American College of Rheumatology criteria were reclassified using the 2012 Systemic Lupus International Collaborating Clinics criteria. Disease activity, patient reported outcomes, and levels of Type I interferon- (IFN-) inducible genes, autoantibodies, and cytokines were measured. Subgroups treated with hydroxychloroquine (HCQ) were compared to patients not on this drug. Results. The classification sets were correlated (R² = 0.87). ILE patients were older (P = 0.0043) with lower disease activity scores (P < 0.001) and greater dissatisfaction with health status (P = 0.034) than SLE patients. ILE was associated with lower levels of macrophage-derived cytokines and levels of expressed Type I IFN-inducible genes. Treatment of ILE with HCQ was associated with better self-reported health status scores and lower expression levels of Type I IFN-inducible genes than ILE patients not on HCQ. Conclusion. The 2012 SLICC SLE classification criteria will be useful to define ILE in trials. Patients with ILE have better health status and immune profiles when treated with HCQ.