Earlier vs. later time period of COVID-19 infection and emergent autoimmune signs, symptoms, and serologies.

OBJECTIVE: Autoantibodies and autoimmune diseases after SARS-CoV-2 infection are widely reported. Given evolving variants, milder infections, and increasing population vaccination, we hypothesized that SARS-CoV-2 infection earlier in the pandemic would be associated with more autoimmune connective tissue disease (CTD) symptoms and immunologic abnormalities. METHODS: Patients ≥18 years old with COVID-19 3/1/2020-8/15/2022 completed the CTD Screening Questionnaire and were tested for 27 autoimmune serologies, SARS-CoV-2 serologies, cell-bound complement activation products (CB-CAPs), and T and B lymphocyte immunophenotypes by flow cytometry. We assessed relationships between symptoms, serologies, and immunophenotypes in earlier (3/1/2020-1/31/2021) vs. later (2/1/2021-8/15/2022) periods, with different predominating SARS-CoV-2 viruses. RESULTS: 57 subjects had earlier and 23 had later pandemic COVID-19. 35 % of earlier vs. 17 % of later pandemic patients had CTD symptoms (p 0.18). More patients were antinuclear antibody (ANA) positive (44 % vs. 13 %, p 0.01) and had lupus anticoagulant (11 % vs. 4 %, p 0.67). After adjustment for age, race, and sex, earlier (vs. later) COVID-19 was associated with increased ANA positivity (OR 4.60, 95%CI 1.17, 18.15). No subjects had positive CB-CAPs. T and B cell immunophenotypes and SARS-CoV-2 serologies did not differ by group. In heatmap analyses, higher autoantibody variety was seen among those with infection in the early pandemic. CONCLUSION: In this sample, having COVID-19 infection in the earlier (pre-2/1/2021) vs. later pandemic was associated with more CTD symptoms, ANA positivity, and autoantibody reactivities. Earlier SARS-CoV-2 variants circulating in a less vaccinated population with less natural immunity may have been more immunogenic.

Towards an understanding of the biopsychosocial determinants of CVD in SLE: a scoping review.

OBJECTIVE: Systemic lupus erythematosus (SLE) is a chronic autoimmune condition with significant physical, mental, psychosocial and economic impacts. A main driver of SLE morbidity and mortality is cardiovascular disease (CVD). Both SLE and CVD exhibit disparities related to gender, race and other social dimensions linked with biological outcomes and health trajectories. However, the biospsychosocial dimensions of CVD in SLE populations remain poorly understood. The objective of this study was to systematically investigate the existing literature around known social factors influencing the development of CVD in SLE. METHODS: A scoping review protocol was developed according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping reviews guidelines. The search strategy encompassed three main concepts: SLE, CVD and social factors. Four databases were searched (PubMed, SCOPUS, PsychINFO and CINAHL). 682 studies were identified for screening. Articles were screened in two phases (title/abstract and full text) to determine whether they fulfilled the selection criteria. RESULTS: Nine studies were included after screening. All were conducted in the USA between 2009 and 2017. Six studies (67%) were cross-sectional and three (33%) were longitudinal. Most employed SLE cohorts (n=7, 78%) and two drew from healthcare databases (n=2; 22%). We identified five main themes encompassing social factors: socioeconomic status and education (n=5; 56%), race and/or ethnicity (n=7; 78%), mental health (n=2; 22%), gender (n=3; 33%) and healthcare quality and/or insurance (n=2; 22%). Overall, low income, fewer years of education, black race and/or ethnicity, depression, male gender, lack of insurance and healthcare fragmentation were all associated with CVD risk factors and outcomes in SLE. CONCLUSIONS: While several social factors contribute to CVD in SLE populations, considerable gaps remain as many social determinants remain un(der)explored. There is rich opportunity to integrate social theory, advance conceptualisations of race and/or ethnicity and gender, expand investigations of mental health and explore novel geographical contexts. In healthcare policy and practice, identified social factors should be considered for SLE populations during decision-making and treatment, and education resources should be targeted for these groups.

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.

Personalizing cardiovascular risk prediction for patients with systemic lupus erythematosus.

OBJECTIVE: Cardiovascular disease (CVD) risk is increased in SLE and underestimated by general population prediction algorithms. We aimed to develop a novel SLE-specific prediction tool, SLECRISK, to provide a more accurate estimate of CVD risk in SLE. METHODS: We studied patients in the Brigham and Women's Hospital SLE cohort. We collected one-year baseline data including the presence of traditional CVD factors and SLE-related features at cohort enrollment. Ten-year follow-up for the first major adverse cardiovascular event (MACE; myocardial infarction (MI), stroke, or cardiac death) began at day +1 following the baseline period (index date). ICD-9/10 codes identified MACE were adjudicated by board-certified cardiologists. Least absolute shrinkage and selection operator regression selected SLE-related variables to add to the American College of Cardiology/American Heart Association (ACC/AHA) Pooled Cohort Risk Equations 10-year risk Cox regression model. Model fit statistics and performance (sensitivity, specificity, positive/negative predictive value, c-statistic) for predicting moderate/high 10-year risk (≥7.5 %) of MACE were assessed and compared to ACC/AHA, Framingham risk score (FRS), and modified FRS (mFRS). Optimism adjustment internal validation was performed using bootstrapping. RESULTS: We included 1,243 patients with 90 MACEs (46 MIs, 36 strokes, 19 cardiac deaths) over 8946.5 person-years of follow-up. SLE variables selected for the new prediction algorithm (SLECRISK) were SLE activity (remission/mild vs. moderate/severe), disease duration (years), creatinine (mg/dL), anti-dsDNA, anti-RNP, lupus anticoagulant, anti-Ro positivity, and low C4. The sensitivity for detecting moderate/high-risk (≥7.5 %) of MACE using SLECRISK was 0.74 (95 %CI: 0.65, 0.83), which was better than the sensitivity of the ACC/AHA model (0.38 (95 %CI: 0.28, 0.48)). It also identified 3.4-fold more moderate/high-risk patients than the ACC/AHA. Patients who were moderate/high-risk according to SLECRISK but not ACC/AHA, were more likely to be young women with severe SLE and few other traditional CVD risk factors. Model performance between SLECRISK, FRS, and mFRS were similar. CONCLUSION: The novel SLECRISK tool is more sensitive than the ACC/AHA for predicting moderate/high 10-year risk for MACE and may be particularly useful in predicting risk for young females with severe SLE. Future external validation studies utilizing cohorts with more severe SLE are needed.

Anti-KIF20B autoantibodies are associated with cranial neuropathy in systemic lupus erythematosus.

BACKGROUND: Cranial neuropathies (CN) are a rare neuropsychiatric SLE (NPSLE) manifestation. Previous studies reported that antibodies to the kinesin family member 20B (KIF20B) (anti-KIF20B) protein were associated with idiopathic ataxia and CN. We assessed anti-KIF20B as a potential biomarker for NPSLE in an international SLE inception cohort. METHODS: Individuals fulfilling the revised 1997 American College of Rheumatology (ACR) SLE classification criteria were enrolled from 31 centres from 1999 to 2011 and followed annually in the Systemic Lupus Erythematosus International Collaborating Clinics inception cohort. Anti-KIF20B testing was performed on baseline (within 15 months of diagnosis or first annual visit) samples using an addressable laser bead immunoassay. Logistic regression (penalised maximum likelihood and adjusting for confounding variables) examined the association between anti-KIF20B and NPSLE manifestations (1999 ACR case definitions), including CN, occurring over the first 5 years of follow-up. RESULTS: Of the 1827 enrolled cohort members, baseline serum and 5 years of follow-up data were available on 795 patients who were included in this study: 29.8% were anti-KIF20B-positive, 88.7% female, and 52.1% White. The frequency of anti-KIF20B positivity differed only for those with CN (n=10) versus without CN (n=785) (70.0% vs 29.3%; OR 5.2, 95% CI 1.4, 18.5). Compared with patients without CN, patients with CN were more likely to fulfil the ACR haematological (90.0% vs 66.1%; difference 23.9%, 95% CI 5.0%, 42.8%) and ANA (100% vs 95.7%; difference 4.3%, 95% CI 2.9%, 5.8%) criteria. In the multivariate analysis adjusting for age at baseline, female, White race and ethnicity, and ACR haematological and ANA criteria, anti-KIF20B positivity remained associated with CN (OR 5.2, 95% CI 1.4, 19.1). CONCLUSION: Anti-KIF20B is a potential biomarker for SLE-related CN. Further studies are needed to examine how autoantibodies against KIF20B, which is variably expressed in a variety of neurological cells, contribute to disease pathogenesis.

Systemic lupus in the era of machine learning medicine.

Artificial intelligence and machine learning applications are emerging as transformative technologies in medicine. With greater access to a diverse range of big datasets, researchers are turning to these powerful techniques for data analysis. Machine learning can reveal patterns and interactions between variables in large and complex datasets more accurately and efficiently than traditional statistical methods. Machine learning approaches open new possibilities for studying SLE, a multifactorial, highly heterogeneous and complex disease. Here, we discuss how machine learning methods are rapidly being integrated into the field of SLE research. Recent reports have focused on building prediction models and/or identifying novel biomarkers using both supervised and unsupervised techniques for understanding disease pathogenesis, early diagnosis and prognosis of disease. In this review, we will provide an overview of machine learning techniques to discuss current gaps, challenges and opportunities for SLE studies. External validation of most prediction models is still needed before clinical adoption. Utilisation of deep learning models, access to alternative sources of health data and increased awareness of the ethics, governance and regulations surrounding the use of artificial intelligence in medicine will help propel this exciting field forward.

Serum S100A8/A9 and MMP-9 levels are elevated in systemic lupus erythematosus patients with cognitive impairment.

Objective: Cognitive impairment (CI) is one of the most common manifestations of Neuropsychiatric Systemic Lupus Erythematosus (NPSLE). Despite its frequency, we have a limited understanding of the underlying immune mechanisms, resulting in a lack of pathways to target. This study aims to bridge this gap by investigating differences in serum analyte levels in SLE patients based on their cognitive performance, independently from the attribution to SLE, and exploring the potential for various serum analytes to differentiate between SLE patients with and without CI. Methods: Two hundred ninety individuals aged 18-65 years who met the 2019-EULAR/ACR classification criteria for SLE were included. Cognitive function was measured utilizing the adapted ACR-Neuropsychological Battery (ACR-NB). CI was defined as a z-score of ≤-1.5 in two or more domains. The serum levels of nine analytes were measured using ELISA. The data were randomly partitioned into a training (70%) and a test (30%) sets. Differences in the analyte levels between patients with and without CI were determined; and their ability to discriminate CI from non-CI was evaluated. Results: Of 290 patients, 40% (n=116) had CI. Serum levels of S100A8/A9 and MMP-9, were significantly higher in patients with CI (p=0.006 and p=0.036, respectively). For most domains of the ACR-NB, patients with CI had higher S100A8/A9 serum levels than those without. Similarly, S100A8/A9 had a negative relationship with multiple CI tests and the highest AUC (0.74, 95%CI: 0.66-0.88) to differentiate between patients with and without CI. Conclusion: In this large cohort of well-characterized SLE patients, serum S100A8/A9 and MMP-9 were elevated in patients with CI. S100A8/A9 had the greatest discriminatory ability in differentiating between patients with and without CI.