Faculty Bibliography

Background Epidemiologic data on systemic lupus erythematosus (SLE) are limited, particularly for racial/ethnic subpopulations in the United States (U.S.). This meta-analysis leveraged data from the Centers for Disease Control and Prevention (CDC) National Lupus Registry network of population-based SLE registries to estimate the general and by sex, race/ethnicity incidence of SLE in the U.S. Methods The CDC registries were established in Michigan, Georgia, California, New York and through the Indian Health Service (IHS). Registries used the 1997 revised ACR classification criteria for SLE as their case definition, and the surveillance time periods ranged from 2002-2009. Age-standardized incidence rates were stratified by sex and race/ethnicity from the state-based registries; the American Indian/Alaska Native (AI/AN) estimate was based only on the IHS registry that covered multiple states. For pooling data across the four sites with data on different racial/ethnic groups, we used Cochran's Q and I statistic to test for heterogeneity across sites. Due to significant heterogeneity, we used a random effects model to calculate pooled incidence, which allows for more variation across sites. We then extrapolated to the 2018 Census population data according to sex and race-stratified groups, including data from the IHS registry, and summed the stratum-specific estimates to provide a total population estimate of incident SLE cases in the U.S. Results The registries contributed 1,057 classified cases of SLE from a mix of urban and rural areas. From the meta-analysis of the four state-based registries, the overall incidence was 5.1 (95%CI4.6,5.6) per 100,000 person-years. The incidence among females was about 7 times higher than males (8.7 vs 1.2). In the meta-analysis, the incidence rate was highest among Black females (15.9,95%CI12.5,20.3), followed by Asian/Pacific Islander females (7.6,95%CI5.5,10.4), Hispanic females (6.8,95%CI6.2,7.6), and White females (5.7,95% CI4.9,6.7). Among males, the incidence rate was highest among Black males (2.4,95%CI1.8,3.0) followed by Hispanic males (0.9,95%CI0.4,1.9), White males (0.8,95%CI0.6,1.1), and Asian/Pacific Islander males (0.4,95%CI0.2,0.6). The AI/ AN incidence estimates, had the second highest rates of SLE among females (10.4,95%CI6.6,14.6) and highest for males (3.8, 95%CI1.6,7.8). Applying our sex- and race-specific incidence estimates to the corresponding population denominators from 2018 Census data, we estimated that 14,263 new persons (12,560 females and 1,703 males) in the U.S. were diagnosed with SLE and fulfill the ACR classification criteria, table 1. Conclusion A coordinated network of population-based SLE registries provided more accurate estimates of the incidence of SLE and the numbers of new individuals affected with SLE in the U.S. in 2018

OBJECTIVE:To characterize patients with Systemic Lupus Erythematosus (SLE) affected by COVID-19 and to analyze associations of comorbidities and medications on infection outcomes. METHODS:Patients with SLE and RT-PCR-confirmed COVID-19 were identified through an established New York University lupus cohort, query of two hospital systems, and referrals from rheumatologists. Data were prospectively collected via a web-based questionnaire and review of medical records. Baseline characteristics were obtained for all patients with COVID-19 to analyze risk factors for hospitalization. Data were also collected from asymptomatic patients and those with COVID-19-like symptoms who tested negative or were not tested. Statistical analyses were limited to confirmed COVID-19-positive patients. RESULTS:A total of 226 SLE patients were included: 41 patients with confirmed COVID-19; 19 patients who tested negative for COVID-19; 42 patients with COVID-19-like symptoms who did not get tested; and 124 patients who remained asymptomatic without testing. Of those SLE patients with COVID-19, 24 (59%) required hospitalization, four required intensive care unit-level of care, and four died. Hospitalized patients tended to be older, non-white, Hispanic, have higher BMI, history of nephritis, and at least one comorbidity. An exploratory (due to limited sample size) logistic regression analysis identified race, presence of at least one comorbidity, and BMI as independent predictors of hospitalization. CONCLUSION/CONCLUSIONS:In general, the variables predictive of hospitalization in our SLE patients were similar to those identified in the general population. Further studies are needed to understand additional risk factors for poor COVID-19 outcomes in patients with SLE.

OBJECTIVE:To characterize the hospitalization and death rates among patients with inflammatory arthritis affected by COVID-19 and to analyze the associations between comorbidities and immunomodulatory medications and infection outcomes. METHODS:Clinical, demographic, maintenance treatment, and disease course data and outcomes of individuals with inflammatory arthritis (IA; rheumatoid arthritis and spondylarthritis) with symptomatic COVID-19 infection were prospectively assessed via web-based questionnaire followed by individual phone calls and electronic medical record review. Baseline characteristics and medication use were summarized for hospitalized and ambulatory patients, and outcomes were compared for each medication class using multivariable logistic regression. RESULTS:A total of 103 patients with IA were included in the study (n=80 confirmed and n=23 highly suspicious for COVID-19). Twenty-six percent of participants required hospitalization, and 4% died. Patients who warranted hospitalization were significantly more likely to be older (P<0.001) and have comorbid hypertension (P=0.001) and chronic obstructive pulmonary disease (P=0.022). IA patients taking oral glucocorticoids had a higher likelihood of being admitted for COVID-19 (P<0.001) while those on maintenance anti-cytokine biologic therapies did not. CONCLUSION/CONCLUSIONS:In patients with underlying IA, COVID-19 outcomes were worse in those receiving glucocorticoids but not in patients on maintenance anti-cytokine therapy. Further work is needed to understand whether immunomodulatory therapies affect COVID-19 incidence.

Background/Purpose: Patients with systemic lupus erythematosus (SLE) represent a unique population in considering risk for coronavirus disease 2019 (COVID-19) with biologic, genetic, demographic, clinical and treatment issues all at play. By the nature of their chronic inflammatory autoimmune condition and regular use of immunosuppressive medications, these individuals would traditionally be considered at high risk of contracting the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and having a worse prognosis. Accordingly, we aimed to characterize patients with SLE affected by COVID-19 in New York City (NYC) and analyze associations of comorbidities and medications on outcomes.
Method(s): Patients with SLE and COVID-19 (confirmed by RT-PCR testing), were identified through a longitudinal survey of an established NYU lupus cohort, query of New York University Langone Health and Bellevue Hospitals systems and referrals from rheumatologists at those institutions. All patients were age 18 or older and met SLE classification criteria or carried a rheumatologist's diagnosis of SLE. Only English-, Spanish- or Mandarin-speaking patients were included in the study. Data were prospectively collected via a web-based questionnaire and review of electronic medical records. Baseline characteristics and medications were compared between the hospitalized and ambulatory patients with COVID-19. A logistic regression analysis was performed to identify independent predictors of hospital admission.
Result(s): A total of 41 SLE patients were confirmed COVID-19 positive by RT-PCR. The patients were predominantly female and encompassed the major racial/ethnic demographics seen in NYC. The most common symptoms of COVID-19+ patients were cough (78.4%), fever (64.9%), and shortness of breath (64.9%). Of those SLE patients with COVID-19, 24 (59%) were hospitalized, 4 required ICU level of care, and 4 died, all of hypoxic respiratory failure, Table 1. Hospitalized patients tended to be older, non-white, Hispanic, and have higher BMI, antiphospholipid syndrome, a history of lupus nephritis and at least one medical comorbidity, Table 2. There was no difference between the groups in use of hydroxychloroquine, systemic steroids or immunosuppressants. Logistic regression analysis identified the following independent predictors of being hospitalized with COVID-19: race (OR = 7.78 for non-white vs. white; 95% CI: 1.13 to 53.58; p=0.037), the presence of at least one comorbidity (OR=4.66; 95% CI: 1.02 to 21.20; p=0.047), and BMI (OR = 1.08 per increase in kg/m2; 95% CI: 0.99 to 1.18; p=0.096).
Conclusion(s): Patients with SLE and COVID-19 have a high rate of hospitalization but similar mortality rate to the general population in NYC. Risk factors such as non-white race, higher BMI, and the presence of one or more comorbidities were identified as independent predictors of hospitalization in SLE patients who develop COVID-19. The use of hydroxychloroquine and immunosuppressants did not appear to influence the outcomes of patients with SLE in the setting of COVID-19. Further studies are needed to understand additional risk factors for poor COVID-19 outcomes in patients with SLE

OBJECTIVES/OBJECTIVE:The European League Against Rheumatism (EULAR)/American College of Rheumatology (ACR) 2019 Classification Criteria for systemic lupus erythematosus (SLE) have been validated with high sensitivity and specificity. We evaluated the performance of the new criteria with regard to disease duration, sex and race/ethnicity, and compared its performance against the Systemic Lupus International Collaborating Clinics (SLICC) 2012 and ACR 1982/1997 criteria. METHODS:Twenty-one SLE centres from 16 countries submitted SLE cases and mimicking controls to form the validation cohort. The sensitivity and specificity of the EULAR/ACR 2019, SLICC 2012 and ACR 1982/1997 criteria were evaluated. RESULTS:The cohort consisted of female (n=1098), male (n=172), Asian (n=118), black (n=68), Hispanic (n=124) and white (n=941) patients; with an SLE duration of 1 to <3 years (n=196) and ≥5 years (n=879). Among patients with 1 to <3 years disease duration, the EULAR/ACR criteria had better sensitivity than the ACR criteria (97% vs 81%). The EULAR/ACR criteria performed well in men (sensitivity 93%, specificity 96%) and women (sensitivity 97%, specificity 94%). Among women, the EULAR/ACR criteria had better sensitivity than the ACR criteria (97% vs 83%) and better specificity than the SLICC criteria (94% vs 82%). Among white patients, the EULAR/ACR criteria had better sensitivity than the ACR criteria (95% vs 83%) and better specificity than the SLICC criteria (94% vs 83%). The EULAR/ACR criteria performed well among black patients (sensitivity of 98%, specificity 100%), and had better sensitivity than the ACR criteria among Hispanic patients (100% vs 86%) and Asian patients (97% vs 77%). CONCLUSIONS:The EULAR/ACR 2019 criteria perform well among patients with early disease, men, women, white, black, Hispanic and Asian patients. These criteria have superior sensitivity than the ACR criteria and/or superior specificity than the SLICC criteria across many subgroups.

Background - Based on inhibition of viral replication and limited reports on clinical efficacy, hydroxychloroquine (HCQ) is being considered as prophylaxis and treatment of COVID-19. Although HCQ is generally considered safe during pregnancy based on studies in patients with systemic lupus erythematous and other rheumatic conditions, there may still be reluctance to institute this antimalarial during pregnancy for the sole purpose of antiviral therapy. Methods - To provide data regarding any potential fetal/neonatal cardiotoxicity, we leveraged a unique opportunity in which neonatal electrocardiograms (ECGs) and HCQ blood levels were available in a recently completed study evaluating the efficacy of HCQ 400mg daily to prevent the recurrence of congenital heart block associated with anti-SSA/Ro antibodies. Results - Forty-five ECGs were available for QTc measurement, and levels of HCQ were assessed during each trimester of pregnancy and in the cord blood, providing unambiguous assurance of drug exposure. Overall, there was no correlation between cord blood levels of HCQ and the neonatal QTc (R = 0.02, P = 0.86) or the mean of HCQ values obtained throughout each individual pregnancy and the QTc (R = 0.04, P = 0.80). In total 5 (11%; 95% CI: 4% - 24%) neonates had prolongation of the QTc > 2SD above historical healthy controls (2 markedly and 3 marginally) but ECGs were otherwise normal. Conclusions - In aggregate, these data provide reassurances that the maternal use of HCQ is associated with a low incidence of infant QTc prolongation. However, if included in clinical COVID-19 studies, early postnatal ECGs should be considered.

Background/Purpose: Lupus nephritis (LN) is a major complication of systemic lupus erythematous (SLE) and affects ~60% of patients during the course of their disease, leading to significant morbidity and mortality. Previous studies examining the safety of percutaneous kidney biopsy to diagnose LN have found variable complication rates depending on disease type studied, ranging from 4-11% in autoimmune/SLE patients to 15-17% in safety studies of any kidney disease. The purpose of our study was to define the safety of obtaining additional tissue for research during clinically indicated renal biopsies in a SLE cohort.
Method(s): Patients were enrolled across 15 clinical US sites in the SLE Accelerating Medicines Partnership (AMP). Kidney biopsies were clinically indicated to evaluate proteinuria (urine protein creatinine ratio [uPCR] > 0.5). Patients with a history of renal transplant, use of rituximab within 6 months of biopsy, and current pregnancy were excluded. Ultrasound/CT-guided kidney biopsies were performed by interventional radiologists/nephrologists generally using an 18-gauge needle although technique, number of routine passes and core lengths varied. An additional core taken solely for research purposes, or a piece of core with sufficient glomeruli remaining from the routine passes and not required for clinical diagnosis, was collected. All adverse events (AEs) occurring within 30 days of biopsy were reported, including duration, severity, type, and resolution.
Result(s): 482 patients underwent a renal biopsy between 2014 and 2020. All patients met criteria for SLE (ACR or SLICC) and the majority were female (85%). Pathologic assessment of clinical biopsies revealed ISN/RPS Class I-VI for most biopsies, although 45 biopsies (9%) yielded a non-LN diagnosis (Table 1). Overall, 37 patients (8%) experienced an AE with several more than one, with a total of 41 AEs reported. Of these AEs, 8 (20%) were considered by the site investigator to be unrelated or unlikely to be related (included pain, shortness of breath, cardiac arrest, fall, and hemoglobin decrease due to sepsis) and 33 (80%) were deemed possibly, probably, or definitely related to the study procedure. Of these events, 9/33 (28%) were mild, 10 (30%) were moderate, and 12 (36%) were deemed severe. In 18 patients (4%) the AEs were considered serious as defined by inpatient or prolonged hospitalization, significant incapacity, or requiring intervention to prevent permanent impairment. The most common related AEs were bleed-related complications, including hematoma, hemorrhage, and hemoglobin decrease (N= 29). Of these, 18 required hospitalization, with 4 of these patients receiving a blood transfusion. All 29 bleed-related complications resolved. The length of the research biopsy did not associate with an AE.
Conclusion(s): Procurement of an additional kidney biopsy core for research purposes in SLE patients undergoing a clinically-indicated kidney biopsy did not result in an increase in adverse events compared to the adverse event rate in prior studies of the safety of percutaneous kidney biopsy. Accordingly, inclusion of a research core should be considered feasible for future studies to advance discovery of new therapeutic targets and prognostic indicators in LN

Background/Purpose: Treatment of lupus nephritis relies on renal histopathological features. However, renal biopsies do not capture patient-specific active biological pathways. Urine proteomic biomarkers could revolutionize the diagnosis and management of lupus nephritis by predicting active intrarenal biological pathways and can be noninvasively monitored over time.
Method(s): One thousand proteins were quantified (RayBiotech) in a total of 112 longitudinal urine samples from 30 SLE patients with active lupus nephritis and 7 healthy controls (HC). The proteins and molecular pathways detected in the urine proteome at the time of biopsy were then analyzed with respect to lupus nephritis class, response to treatment after 1 year, histopathological features (activity and chronicity indeces), and trajectory over time (baseline and week 12, 26, and 52). The intrarenal expression of candidate biomarkers was evaluated using single cell transcriptomics of renal biopsies from patients with active lupus nephritis.
Result(s): There were 237 proteins (FDR < 10%) enriched in the urine of patients with lupus nephritis reflecting several molecular pathways involving chemotaxis, extracellular matrix remodeling, and activation of neutrophils and platelets. Hierarchical clustering using urine proteomics segregated SLE patients into 2 groups, with 80% of complete responders clustering together. This finding could not be similarly reproduced using standard features including baseline proteinuria, creatinine, histologic activity or chronicity scores, or class, indicating unique informative features of urine proteomics (Fig. 1). Patients with proliferative lupus nephritis (class III or IV) had stronger activation of chemotaxis pathways. IL-16 was the urinary protein most significantly increased in proliferative disease compared to membranous (FC 6, p=0.002) (Fig. 2A). Assessment of urine proteins that correlated with histologic activity kidney highlighted IL-16 as the single most strongly correlated protein with histologic activity (r=0.69, p=9.5.10-5; Fig. 2B). IL-16 concentration was independent of the amount of proteinuria and progressively diminished over time in patients who were responding to immunosuppression (Fig. 2C). Single cell RNA sequencing revealed significant intrarenal expression of IL16 by all infiltrating immune cells and highlighted IL16 as the second most expressed cytokine in lupus nephritis kidneys out of a compendium of 236 cytokines (Fig. 3A-B).
Conclusion(s): Urine proteomics can noninvasively identify active and biologically relevant pathways in lupus nephritis. Integrated urine proteomics and renal single cell transcriptomics revealed that IL-16, a CD4 ligand with chemotactic and proinflammatory functions, was one of the most expressed cytokine in lupus nephritis. As a urine proteomic biomarker, IL-16 may predict renal histological activity and could be monitored over time to assess response to immunosuppression. Urinary IL-16 is independent of proteinuria thus potentially providing actionable clinical information that is not captured by currently used biomarkers. Further studies are ongoing to validate these findings

Background/Purpose: Current management of lupus nephritis (LN) is guided by histopathological features on kidney biopsy and measurement of proteinuria. Urine proteomics is a non-invasive source of novel biomarkers which may better reflect the complex dynamic immunobiology of LN in real time. Two composite measures include CKD273, which can predict the risk of progression of chronic kidney disease in the general population, and LN120, which was designed to diagnose LN. Both are multidimensional urine proteomic classifiers consisting of 273 or 120 peptides, respectively, with major components including collagen fragments, abundant blood-derived proteins, and proteins involved in inflammation. We investigated the ability of these classifiers to predict traditional biopsy features and disease response in LN.
Method(s): A total of 31 adults with biopsy-proven LN were included in this study. All participants met the SLICC and 2019 EULAR/ACR Classification Criteria for SLE based on a spot urine protein-to-creatinine ratio of >0.5 and class III, IV, and/or V LN on renal biopsy. Urine samples were collected at week 0 (at the time of renal biopsy) and week 12 and then subjected to peptidome analysis using a capillary electrophoresis-mass spectrometry (CE-MS) platform. This peptidome data was used to calculate CKD273 and LN120 classifiers at each time point. LN response status was determined at week 52 based on proteinuria, creatinine, and prednisone dosage (no more than 10 mg daily). Spearman's rank correlation and t-tests were used to compare proteomic classifiers with renal biopsy characteristics and response.
Result(s): At week 0, both CKD273 and LN120, but not proteinuria, exhibited a moderate to strong correlation with histological activity index on renal biopsy (Figure 1; rho = 0.65 with p = 0.00024 for CKD273; rho = 0.47 with p = 0.013 for LN120). CKD273 also correlated with chronicity index (rho = 0.54, p = 0.0037). Neither classifier significantly correlated with lupus nephritis ISN class. With respect to response, CKD273 and LN120 were not significantly different between groups at week 0. However, a reduction in LN120 was observed in 100% of complete responders, 60% of partial responders, and 50% of non-responders at week 12 (Figure 2). The magnitude of this change in LN120 in complete responders versus non-responders did not reach statistical significance (p = 0.13), though this is potentially because of the small number of responders with CE-MS data available at both time points (n = 4). CKD273 did not significantly change with time in any response group (Figure 3).
Conclusion(s): This work provides proof of concept that urine proteomic classifiers can noninvasively predict histological activity and chronicity in LN. Complete responders, but not partial responders or non-responders, exhibited an impressive numerical decrease in LN120 by week 12, suggesting that proteomic scores may track with and predict a durable treatment response. Larger studies are needed to validate these findings

Background/Purpose: Disparities have been reported during the coronavirus disease (COVID-19) outbreak. Systemic lupus erythematosus (SLE) patients represent a unique group that is affected by clinical, treatment, demographic, and socioeconomic (SES) risk factors for severe COVID-19 disease. The Neighborhood Deprivation Index has been associated with non-communicable disease as well as communicable disease outcomes. We conducted this study to identify neighborhood SES factors influencing SLE COVID-19 outcomes.
Method(s): Patients with SLE and COVID-19 (confirmed by RT-PCR testing), were identified through a longitudinal survey of an established NYU lupus cohort, query of NYU Langone Health and Bellevue Hospitals systems and referrals from rheumatologists at those institutions. All patients were age 18 or older and met SLE classification criteria or carried a clinical diagnosis of SLE. Baseline characteristics along with zip code neighborhood data including COVID-19 case rates and neighborhood characteristics were obtained using the Hopkins COVID database and the American Community Surveys (ACS 2014-2018) respectively. A principal component analysis was performed to identify contributory neighborhood characteristics. Then a logistic regression analysis identified predictors of testing positive for COVID-19 and COVID-19 hospitalization.
Result(s): A total of 59 SLE patients (41+ and 18-) were tested for COVID-19 by RT-PCR. The patients were predominantly female, aged 46+/-16, and racially/ethnically diverse. Roughly 140 neighborhood data points were recorded and categorized as follows: population density, race and ethnicity, household type, household size, education level, employment type and status, income and poverty, transportation method, and insurance status. COVID-19 positive patients tended to live in neighborhoods with more single parent households, households with >4 residents, higher unemployment rate, higher high school dropout rate, more public transit use, and more employment in retail, construction, and personal care services. These variables were directly proportional to principal component 1 (PC1) and accounted for 88% of the variance in neighborhood characteristics. A logistic regression model identified that PC1 (OR= 1.3; 95% CI: 1.0-1.8) and taking immune suppressants (IS) (taking vs not taking OR= 2.1; 95% CI: 1.5 to 23.3) independently correlated with having a positive COVID-19 test when controlling for hydroxychloroquine (HCQ), glucocorticoids (GC), and previous lupus nephritis (LN). Only PC1 independently correlated with COVID-19 hospitalization (OR= 1.4; 95% CI: 1.1-1.9) upon controlling for taking IS, HCQ, GCs, and LN. PC1 associated with African American (AA) or Hispanic patient race/ethnicity (OR= 1.6, 95% CI: 1.2-2.2).
Conclusion(s): In addition to SLE disease, neighborhood characteristics and SES are important risk factors both for contracting COVID-19 and developing severe disease. Neighborhood deprivation may mediate the reported relationship between AA and Hispanic race/ethnicity and COVID-19. Given that a plurality of SLE patients are of AA and/or Hispanic backgrounds, care teams must formulate strategies to address socioeconomic stress in our patients