Faculty Bibliography

Background Patients with Systemic Lupus Erythematosus (SLE) represent a unique population at risk for COVID-19 due to underlying immune abnormalities and regular use of immunosuppressant medications. This study was initiated to evaluate for the presence of SARS-CoV-2 IgG antibodies in SLE patients with and without prior COVID-19-related symptoms or COVID-19 RT PCR testing. Methods A total of 329 patients with SLE from two cohorts, one serially monitored for COVID-19 in Spring 2020 (the Web-based Assesment of Autoimmune, Immune-Mediated and Rheumatic Patients (WARCOV) and one undergoing routine surveillance (NYU Lupus Cohort) were tested for SARS-CoV-2 IgG via commercially available immunoassays processed through hospital or outpatient laboratories between April 29, 2020 and February 9, 2021. Results Overall, 16% of 329 patients had a reactive SARSCoV- 2 IgG antibody test. Seropositive patients were more likely to be Hispanic. Other demographic variables, lupus-specific factors and immunosuppressant use were not associated with reactivity. Of the 29 patients with prior RT-PCR confirmed COVID-19, 83% developed an antibody response despite 62% being on immunosuppressants. Six percent of patients who had symptoms suspicious for COVID-19 but negative concurrent RT-PCR testing developed an antibody response. Twenty-three percent of patients who had COVID- 19-related symptoms but no RT-PCR testing and 5% of patients who had no symptoms of COVID-19 developed an antibody response. Among patients initially SARS-CoV-2 IgG positive, the majority maintained reactivity serially. In COVID- 19-confirmed patients high percentages had antibody positivity beyond 30 weeks from disease onset, 88% up to 10 weeks, 83% up to 20 weeks, and 80% up to 30 weeks. Conclusions Most patients with SLE and confirmed COVID- 19 were able to produce a serologic response despite use of a variety of immunosuppressants. These findings provide reassurances regarding the efficacy of humoral immunity and possible reinfection protection in patients with SLE

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.

OBJECTIVES/OBJECTIVE:There is a paucity of data regarding healthcare costs associated with damage accrual in systemic lupus erythematosus (SLE). We describe costs associated with damage states across the disease course using multi-state modeling. METHODS:Patients from 33 centres in 11 countries were enrolled in the Systemic Lupus International Collaborating Clinics (SLICC) inception cohort within 15 months of diagnosis. Annual data on demographics, disease activity, damage (SLICC/American College of Rheumatology (ACR) Damage Index [SDI]), hospitalizations, medications, dialysis, and selected procedures were collected. Ten-year cumulative costs (Canadian dollars) were estimated by multiplying annual costs associated with each SDI state by the expected state duration using a multi-state model. RESULTS:1687 patients participated, 88.7% female, 49.0% of Caucasian race/ethnicity, mean age at diagnosis 34.6 years (SD 13.3), and mean follow up 8.9 years (range 0.6-18.5). Annual costs were higher in those with higher SDIs (SDI ≥ 5: $22 006 2019 CDN, 95% CI $16 662, $27 350 versus SDI=0: $1833, 95% CI $1134, $2532). Similarly, 10-year cumulative costs were higher in those with higher SDIs at the beginning of the 10-year interval (SDI ≥ 5: $189 073, 95% CI $142 318, $235 827 versus SDI=0: $21 713, 95% CI $13 639, $29 788). CONCLUSION/CONCLUSIONS:Patients with the highest SDIs incur 10-year cumulative costs that are almost 9-fold higher than those with the lowest SDIs. By estimating the damage trajectory and incorporating annual costs, damage can be used to estimate future costs, critical knowledge for evaluating the cost-effectiveness of novel therapies.

Background/Purpose: Lupus nephritis continues to be the complication with the highest standardized mortality ratio in Systemic Lupus Erythematosus (SLE), and a late diagnosis associates with worse outcomes. Clinicians traditionally rely on proteinuria to drive decisions regarding renal biopsy and subsequent management. Since threshold levels for such determinations are variable but critically important, this study leveraged the well-phenotyped multi-center multi- racial Accelerating Medicines Partnership (AMP) lupus nephritis cohort, to address whether urine protein to creatinine ratios (UPCR) between.5 and 1 differ from higher ratios with regard to clinical, serologic and histologic variables.
Method(s): 239 patients fulfilling ACR or SLICC criteria for SLE with a random or 24 hr uPCR > or =.5 and histologic biopsy Class III, IV, V, or mixed were consecutively enrolled in AMP at the time of renal biopsy and demographics, clinical history, medications, disease activity as assessed by the hybrid SELENA-SLEDAI were recorded. Patients with biopsy Classes I, II and VI were ineligible. Patients were followed at 3, 12, 26 and 52 weeks.
Result(s): At baseline, 38 patients had a UPCR < 1 (A), 113 had a UPCR 1-3 (B), and 88 had a UPCR > 3 (C). There were 14 additional patients with UPCR < 1, and 11 patients with UPCR > 1 who had biopsy class I or II. In group A, there were significantly more male patients (44% A; 23% B; 26% C, p=0.012) with no differences in age, race or ethnicity. Neither the SLEDAI nor serologic parameters (anti-dsDNA, C3, or C4) distinguished among the groups. Those in group C had a significantly increased creatinine and decreased hemoglobin and albumin compared to the other two groups (Table 1). Patients in group A trended toward having an increased frequency of proliferative histology (Table 2). This trend was not observed when considering patients for whom this was their first biopsy, but was significant for repeat biopsy patients (56% A; 41% B; 24% C, p=0.03). The activity index was independent of UPCR regardless of biopsy number. However, those in group C had a significantly higher chronicity index than those with lower UPCR. This correlation was shown for patients with a repeat biopsy (r=0.2299, p=0.003) but not first biopsy patients (r=0.0891, p=0.45). Although medications did not differ at baseline among the groups, at 12 weeks, for each group significantly more patients were taking Mycophenolate Mofetil than at the time of biopsy (Table 3).
Conclusion(s): A significant proportion of both first and recurrent biopsies in patients with a UPCR < 1 have proliferative histology and accompanying activity scores similar to that of patients with nephrotic range proteinuria. These results support renal biopsy at thresholds lower than a UPCR of 1 since histologic findings can inform therapeutic decisions

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: Patients with systemic lupus erythematosus (SLE) are at increased risk of premature atherosclerosis and thrombosis. Hydroxychloroquine (HCQ) is widely used in the treatment of SLE and has been considered of benefit for overall vascular health albeit studies to address this benefit at the cellular level have been limited. Accordingly, this study was initiated to investigate the relationship between HCQ use and dose with platelet activity, the platelet transcriptome, and vascular functional readouts.
Method(s): Patients fulfilling ACR or SLICC criteria for SLE were consecutively recruited for platelet evaluation with the only exclusion being on nonsteroidal anti-inflammatory medications, aspirin or anticoagulants. At enrollment, blood was collected for hematology analysis using the Sysmex XN-1000 analyzer, platelet aggregation via the Helena AggRAMTM system, and platelet RNA isolation and storage. Microvascular function was assessed via sublingual sidestream darkfield imaging. Brachial artery reactivity testing was used to evaluate large vessel function. Stored platelet RNA was isolated and analyzed by RNA sequencing (Illumina HiSeq4000 Sequencing).
Result(s): Among 132 SLE subjects, 108 were on HCQ. Mean age was 39.9 +/- 13.0 and 97% were female. Lupus disease activity at the time of blood draw assessed by the SELENA-SLEDAI activity index was 3.44 (range 0-20). Demographics and SLE disease activity did not differ between those on versus off HCQ (Table 1). Platelet count and size were not different between groups (Figure 1A). Platelet aggregation in response to submaximal ADP at multiple concentrations was lower in participants on HCQ (Figure 1B). Consistently, there was an inverse relationship between HCQ dosing and platelet aggregation in response to ADP (2uM: R=-0.213, P=0.037; 1uM: R=-0.310, P=0.0025; 0.4uM: R=-0.376, P=0.00018; Figure 1C). Since no subjects were on aspirin (or any other antiplatelet therapy at enrollment), aggregation in response to arachidonic acid (AA) was robust and similar between groups. However, after incubating platelets with aspirin (3mM) in vitro, platelet aggregation in response to AA was lower in the HCQ group compared to non-HCQ group (P=0.035, Figure 1B). To investigate the potential mechanisms of HCQ induced lower platelet aggregation, we evaluated platelet RNA sequencing in 49 subjects (8 no HCQ, 41 on HCQ). Positive regulation of pathways related to platelet activation (and in particular, P-selectin expression) was inversely related to HCQ, especially with higher doses (Figure 1E). In terms of vascular function, subjects on HCQ had improved microvascular function as noted by an increased proportion of sublingual capillaries filled with RBCs (P=0.011) and smaller perfused boundary region (PBR, P=0.010). HCQ dosing correlated with PBR (R=-0.599, P=0.002, Figure 1H) and RBC Filling (R=-0.592, P=0.002, Figure 1I). BART also trended positively with HCQ dose (R=0.385, P=0.094; Figure 1J).
Conclusion(s): These findings suggest that HCQ may provide benefit for vascular health in SLE as supported by ex vivo experiments demonstrating decreased platelet aggregation and downregulation of platelet functional pathways as well as improved vascular readouts

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: 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

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: 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