Faculty Bibliography

OBJECTIVE:The Systemic Lupus International Collaborating Clinics (SLICC) 2012 SLE classification criteria and the revised American College of Rheumatology (ACR) 1997 criteria are list-based, counting each SLE manifestation equally. We derived a classification rule based on giving variable weights to the SLICC criteria, and compared its performance to the revised ACR 1997, unweighted SLICC 2012 and the newly reported European League Against Rheumatism (EULAR)/ACR 2019 criteria. METHODS:The physician-rated patient scenarios used to develop the SLICC 2012 classification criteria were re-employed to devise a new weighted classification rule using multiple linear regression. The performance of the rule was evaluated on an independent set of expert-diagnosed patient scenarios and compared to the performance of the previously reported classification rules. RESULTS:Weighted SLICC criteria and the EULAR/ACR 2019 criteria had less sensitivity but better specificity compared to the list-based revised ACR 1997 and SLICC 2012 classification criteria. There were no statistically significant differences between any pair of rules with respect to overall agreement with the physician diagnosis. CONCLUSION/CONCLUSIONS:The two new weighted classification rules did not perform better than the existing list-based rules in terms of overall agreement on a dataset originally generated to assess the SLICC criteria. Given the added complexity of summing weights, researchers may prefer the unweighted SLICC criteria. However, the performance of a classification rule will always depend on the populations from which the cases and non-cases are derived, and whether the goal is to prioritize sensitivity or specificity.

Background/Purpose: The Accelerating Medicines Partnership (AMP) Lupus Network was established with the goal of applying novel technologies to the interrogation of blood and tissue samples from patients with lupus nephritis (LN). In contrast to global LN clinical trials, the AMP LN cohort affords an opportunity to generate outcome data representative of a US multicenter multi-ethnic real-world experience. In this analysis, the AMP clinical dataset was investigated to determine the percentages of patients who attained prespecified definitions of partial or complete responses at 52 weeks. In addition, incorporation of response rates at weeks 12 and 26 to the analysis provided longitudinal patterns of response to standard of care.
Method(s): Patients with LN who were undergoing kidney biopsies as part of standard of care were eligible to enroll in the AMP LN study. Response definitions were only applied to cases whose baseline spot urine protein/creatinine (UPCR) ratios were > 1.0. Complete response (CR) required: 1) UPCR < 0.5; and 2) normal creatinine (< 1.3 mg/dL) or, if abnormal at baseline, < 125% of baseline; and 3) prednisone < 10 mg/day at the time of the study visit. Partial response required: 1) >50% reduction in UPCR without meeting UPCR criterion for CR; and 2) normal creatinine (< 1.3 mg/dL) or, if abnormal, < 125% of baseline; and 3) prednisone dose < 15 mg/day at the time of the study visit. Patients who did not achieve a CR or PR at the specific timepoints were considered non-responders (NR). Only patients with renal biopsies that demonstrated ISN/RPS classes III, IV, V or combined III or IV with V and data available at all four timepoints (baseline, weeks 12, 26 and 52) were included in this analysis. Cross-sectional and longitudinal analyses of responses were performed, and heat maps were generated to graphically display response patterns.
Result(s): Data on 121 patients with LN enrolled in AMP were included in this analysis. Cross-sectional response rates at 52 weeks were: CR: 28.1%; PR: 23.1%; NR: 48.8% (Table 1). Response rates at weeks 12 and 26 are additionally displayed in Table 1, and Figure 1 is a heat map demonstrating longitudinal responses of our patients. All patients were considered NR at baseline. Only 7.4% of patients had week 12 CR responses sustained through week 52, whereas 19% had attained PR or CR at all 3 visits. An additional 14.9% achieved a PR or CR at 26 weeks which was sustained at 52 weeks. Overall, 36.4% of patients were NR at all time points.
Conclusion(s): Clinical data from the AMP Lupus Network revealed rates of 52-week CR and PR that were consistent with placebo response data from recently conducted LN trials. Low sustained CR rates not only underscore the need for more efficacious therapies but highlight how critically important it is to understand the molecular pathways that are associated with response and non-response. (Figure Presented)

Background/Purpose: Anti-Ro autoantibody production often precedes the development of Systemic Lupus Erythematosus (SLE) or Sjogren's syndrome (SS) by years. For anti-Ro+ mothers enrolled in the Research Registry for Neonatal Lupus (RRNL), progression to SS or SLE occurs in about a quarter, while most remain asymptomatic or develop only minor rheumatic symptoms (Asym/UAS). Thus, RRNL mothers uniquely offer a promise to identify genotype-phenotype relationships that are important to preclinical autoimmunity. Since multiple SLE risk alleles from Class II HLA genes are present in anti-Ro+ mothers, we examined interactions of specific microbiome taxa with Class II HLA by independent analytic paths with the goal to identify HLA-related microbiome associations in Anti-Ro+ Mothers of Children with Neonatal Lupus.
Method(s): Subjects included 125 RRNL mothers and 23 healthy controls. Stool microbiomes of anti-Ro+ women in RRNL (Asym/UAS, SS/SLE), and healthy controls (HC) were processed using 16S ribosomal RNA sequencing. Sera/ plasma were evaluated for cytokines and autoantibody levels. Alleles from HLA Class II genes were genotyped using NextGen sequencing of HLA region or imputed (HIBAG) from GWAS data. Independent analytic paths sought to explore associations of specific taxa and class II HLA included: 1) use of a cumulative logit model to test interactions between FDR significant genera and HLA alleles and 2) assignment of SLE, SS, UAS patients and HC to molecular phenotype clusters by Random Forest (RF), an unsupervised machine learning tool using Z-score transformed cytokine soluble mediators and autoantibody values with settings and the gap statistic that were used to estimate the optimal number of patients and HC within clusters. The overlapping distribution of SS/SLE, HLA alleles and taxa at clusters were then examined.
Result(s): Findings related to DRB1*15:01 and an interaction with genera of the Ruminococcaceae family were tested. Oscillibacter, with FDR-adjusted significance was shown to exhibit evidence of an interaction (P=0.033 (OR=0.60 (0.37-0.96)). In order to authenticate that SLE HLA risk alleles modify the strength of the association, we examined the molecular phenotype clusters from RF clustering. Radar plots were used to visualize the distribution HLA alleles and the enrichment of microbiome taxa within these clinically relevant phenotypic clusters (Figure 1). DRB1*1501 shows enrichment at cluster 4. Interestingly, the distribution of Oscillibacter, but not Coprococcus 3 was nearly superimposable with the Class II HLA allele with enrichment at cluster 4. However, the distribution of DRB1*1501 was not enriched at cluster profiles representing evaluations of DRB1*0301 and SS/SLE disease classification (Figure 2) demonstrating a limitation of DRB1*1501 to predict risk for transition from benign to pathologic autoimmunity in anti-Ro+ mothers of children with neonatal lupus.
Conclusion(s): These data support the use of molecular phenotypes that are linked to genetic-environmental interactions to identify HLA-related microbiome associations

Background/Purpose: The Accelerating Medicines Project (AMP) has enabled significant increases in understanding of SLE nephritis pathology, providing a profile of dozens of leukocyte subsets within affected kidneys by single-cell RNA sequencing of nephritis biopsies. While these results suggest a complex network of interactions between cell populations during nephritis, the spatial positioning of these cells is lost during the sequencing process. Inferred interactions between the diverse identified cell types would be greatly strengthened by detailed spatial information, placing these cells in context with each other and with the surrounding structures of the kidney.
Method(s): In consultation with AMP, we have used CODEX, a multicycle imaging technology allowing for staining of up to 40 targets on a single tissue sample without tissue degradation, to capture preliminary images of the AMP tissue biopsies available at New York University. Extensive antibody screening, sample preparation, optimization of antigen retrieval, and imaging steps are required, which remain under active optimization to allow for imaging the entirety of the AMP biopsy cohort available at the Grossman School of Medicine, which has been fully processed for future staining.
Result(s): At present we are able to image sixteen targets capturing dense interstitial T and B cell infiltrates, intratubular and interstitial myeloid populations, and sparser glomerular infiltrating cells in our demonstration cohort, with clear imaging of the glomeruli, tubules, and interstitial spaces. Further targets will be added as they are optimized, further allowing subsetting of T, B, and myeloid populations, with the goal of capturing the populations identified previously in single-cell sequencing.
Conclusion(s): CODEX imaging of renal biopsy samples provides spatial context for prior observations across a range of SLE nephritis samples, with complex interstitial populations found around glomeruli and tubules in active disease. Deeper profiling with expanded antigen targets to enable further sub-population phenotyping and activation states and imaging of the full cohort of biopsies available at NYU will provide a spatial atlas to SLE nephritis and further reveal underlying mechanisms of disease

Background/Purpose: The clinical heterogeneity of SLE with its complex pathogenesis remains challenging as we strive to provide optimal management. The contribution of platelets to endovascular homeostasis, inflammation and immune regulation highlights their potential importance in SLE. Prior work from our group showed that the Fcgamma receptor type IIa (FcgammaRIIa)-R/H131 biallelic polymorphism is associated with increased platelet activity and cardiovascular risk in SLE. The study was initiated to investigate the platelet transcriptome in patients with SLE and evaluate its association across FcgammaRIIa genotypes and distinct clinical features.
Method(s): RNA-sequencing was done on platelets isolated from 51 patients fulfilling criteria for the classification of SLE based on recent EULAR/ACR definitions, and 18 healthy controls matched on age, sex, and race. Unsupervised clustering, differential gene expression, and gene set enrichment analysis (GSEA) were used to analyze differences between SLE patients and controls, and SLE subpopulations, based on SELENA SLEDAI Hybrid disease activity, specific organ manifestations, and FcgammaRIIa genotype. Weighted Gene Correlation Network Analysis (WGCNA) was performed to create a modular transcriptomic framework.
Result(s): Our cross-sectional SLE cohort (N=51, age = 41.1+/-12.3, 100% female, 45% Hispanic, 24% black, 22% Asian, 51% white, SLEDAI = 4.4+/-4.2) was comprised of patients consecutively enrolled excluding those on aspirin or anticoagulants. Compared to the 18 controls, there were 2290 (p.adj < 0.05) differentially expressed genes. ( Figure 1 A, B) GSEA revealed positive enrichment for pathways related to interferon response, TNFa signaling, and coagulation in SLE. ( Figure 1C) WGCNA was used to create a modular transcriptomic framework. ( Figure 2A ) Modules enriched for platelet activity, immune response, and WNT signaling were significantly increased in SLE versus controls. Moreover, modules enriched for interferon response and WNT signaling paralleled increases in disease activity. ( Figure 2B) When analyzing patients with proteinuria, modules associated with oxidative phosphorylation and platelet activity were unexpectedly decreased. (Figure 2C) Analyzing the ratio of fold changes between SLE/Control vs SLE Proteinuria/SLE No Proteinuria, genes increased in SLE and those with proteinuria were enriched for immune effector processes, while genes increased in SLE but decreased in proteinuria were enriched for coagulation and cell adhesion. (Figure 2D) The module enriched for FCR activation was decreased in SLE and was affected by the FcgammaRIIa genotype. (Figure 3A) FcgammaRIIa R131 and H131 patients showed significantly different platelet transcriptomes. (Figure 3B) The combination of SLE with an FcgammaRIIa R131 variant leads to a significant increase in the platelet activity module not seen in controls. (Figure 3C)
Conclusion(s): These analyses reveal that SLE patients have a significantly different platelet transcriptome from controls, different phenotypic presentations of SLE patients associate with distinct platelet transcriptomic signatures, and FCGR2a variants may differentially influence the role of platelets in the contribution to SLE disease activity

Background/Purpose: Lupus nephritis (LN) is a leading cause of morbidity and mortality in systemic lupus erythematosus (SLE) patients. While LN pathogenesis has yet to be fully elucidated, T cells have been strongly implicated in mechanisms of disease. CD6 is a co-stimulatory receptor on T cells, that binds to activated leukocyte cell adhesion molecule (ALCAM), a ligand expressed on antigen presenting cells and epithelial and endothelial tissues. The CD6-ALCAM pathway plays an integral role in modulating T cell activation and trafficking and is central to immune-mediated inflammation. Previously, we reported that soluble urine ALCAM is a potential biomarker of disease in LN. Here, we evaluated the correlation of serum and urine ALCAM and CD6 with disease activity over time.
Method(s): Patient samples were acquired through the Accelerating Medicines Partnership (AMP), a public-private partnership to accelerate development of therapeutics for diseases such as LN. Serum and urine samples were obtained from patients with biopsy proven LN (n=345) and living kidney donor controls (n=68). Follow-up longitudinal sampling (3, 6, and 12 months) was available for 143 LN patients. ALCAM levels were quantified by ELISA, while CD6 levels were quantified by an electrochemiluminescent assay. Levels were analyzed cross-sectionally (first visit) and longitudinally against disease measures that included proteinuria, SLEDAI, the renal components of the SLEDAI score (R-SLEDAI), ISN-RPS histological class of the lesion, serological parameters, and patient characteristics.
Result(s): Consistent with our previous findings, cross-sectional analysis showed that urinary ALCAM was significantly elevated in LN patients (mean 4333.5 pg/mL, 95% CI [3614.0, 5053.0]) compared to control subjects (mean 214.4 pg/ mL, 95% CI [152.9, 276.0]) (p< 0.001), but that there were no differences in serum ALCAM levels. Urinary ALCAM levels significantly correlated with SLEDAI and R-SLEDAI scores (but did not correlate to the non-renal portion of SLEDAI (SLEDAI -R-SLEDAI) (Figure 1), suggesting that ALCAM level is associated with the renal activity. This was supported by near-significant correlations with C3 (p=0.07) and C4 levels (p=0.05). Serum and urine levels of CD6 were similar between cases and control subjects and did not change with disease activity, suggesting that the differences observed in urinary ALCAM levels are not due to hemodynamic changes or non-specific loss of glomerular permeability. In patients followed with longitudinal sampling, urinary ALCAM reflected changes in SLEDAI and R-SLEDAI. Furthermore, in preliminary analysis of a subset of patients who exhibited significant changes in R-SLEDAI across visits, intra-patient comparison of the respective timepoints reflected concomitant significant changes in urinary ALCAM levels (Figure 2).
Conclusion(s): Here, we expand upon previous studies and provide additional support in a large multi-center cohort, by showing that urinary ALCAM levels are elevated in SLE patients with active LN and decline with clinical improvement. Studies in progress are evaluating the implications of these findings in predicting therapeutic responses in LN, as well as longer term disease outcomes and prognosis

Background/Purpose: Systemic Lupus Erythematosus (SLE) is a complex chronic heterogeneous autoimmune disease, which increases the risk of atherothrombosis. In addition to their well described role in thrombosis and hemostasis, platelets are key mediators of inflammation and have immune effector cell properties. This study was initiated to investigate the role of platelet associated Lectin Galactoside-binding Soluble 3 Binding Protein (LGALS3BP), which binds to macrophage-associated lectin Mac-2, as a mediator of inflammation in SLE and potential biomarker associated with clinical phenotypes.
Method(s): RNA transcriptome analysis was performed on platelets isolated from 51 patients with SLE (not taking aspirin or anticoagulants) and 18 age, sex and race/ethnicity matched controls. LGALS3BP protein expression was determined in platelet releasates by ELISA and western blot analysis. Gene and protein expression of LGALS3BP in Megakaryocyte cell line (MEG-01) was investigated upon stimulation with IFN-alpha. Correlations between circulating serum LGALS3BP and LGALS3BP platelet mRNA and releasates were assessed. Subsequently, correlation analysis between clinical features of SLE and circulating serum LGLAS3BP was performed. Finally, the effects of platelets and LGALS3BP on macrophage inflammatory response were studied in vitro.
Result(s): Platelet transcriptome analysis revealed that LGALS3BP was one of the most differentially expressed transcripts in SLE versus matched-healthy controls (Fold change, 3.9, adjusted P-value = 2.5 x 10^-11) (Figure1A). Consistently, LGALS3BP in platelet releasates was significantly higher in 40 patients with SLE than 20 controls (p = 0.002) (Figure1B). Platelet LGALS3BP gene and protein expression were highly correlated with circulating LGALRS3BP in serum (r² = 0.370, p = 0.003 and r² = 0.689, p < 0.0001 respectively) (Figure1E and F). LGALS3BP measured in serum of 115 patients with SLE correlated with the SELENA SLEDAI hybrid disease activity index (r²= 0.322, p = 0.0005) (Figure1G). In particular, higher serum LGALS3BP levels were observed in SLE patients with lupus nephritis compared to those with SLE and inactive disease (P=0.0001) (Figure1H). In longitudinal analysis of 22 patients without proteinuria at baseline who went on to develop proteinuria over time, circulating plasma LGALS3BP tracked with flares of nephritis (p=0.06). In vitro, IFN-alpha induced the expression and production of LGALS3BP in MEG-01 cells in a dose dependent manner (Figure2A, B and C), which was completely inhibited by IFN-alpha neutralizing antibody (Figure2D, E and F). Recombinant LGALS3BP (Figure 3A and B) and Platelet releasates from SLE (Figure 3C) induced the production of pro-inflammatory cytokines such as IL-8 (p=0.04) and IL-6 (p=0.073) by macrophages.
Conclusion(s): These data show that platelets isolated from patients with SLE highly express and secrete LGALS3BP which induces a proinflammatory macrophage and is associated with SLE disease clinical phenotype. LGALS3BP may contribute to pathogenesis and serve as a novel biomarker of SLE disease activity

Background/Purpose: Diagnosis of lupus nephritis (LN) relies on a kidney biopsy obtained in SLE with proteinuria. Delayed access to kidney biopsies may delay diagnosis and treatment, and can be limited by rapid access to biopsy, antithrombotic and anticoagulation treatments, thrombocytopenia, and in resource poor settings. Here, we employed urine proteomics to develop a non-invasive biomarker to predict proliferative LN.
Method(s): We quantified 1200 biomarkers (Kiloplex, RayBiotech) in urine samples collected on the day of (73%) or within 3 weeks (27%) of kidney biopsy in SLE patients with proteinuria >= 500mg/d and compared their abundance between patients with or without a subsequent biopsy with proliferative LN (ISN class III or IV +/- V). Prospective urine proteomic profiles were obtained in patients with class III, IV, or V at baseline and week 12, 24, or 52.
Result(s): A total of 237 patients were included: 138 (58%) with proliferative LN, 57 (24%) pure membranous LN, 21 (9%) ISN class I or II LN, 9 (4%) ISN class VI, and 12 (5%) did not have LN. Forty urinary proteins were differentially abundant in patients with proliferative LN, topped by CD163 (Figure 1). Urinary CD163 (uCD163) was significantly elevated in proliferative LN compared to all other groups (Figure 2). Longitudinal analysis revealed that uCD163 selectively declined in patients that achieved renal response at 12 months (Figure 3).
Conclusion(s): Urinary CD163, a cleaved M2c macrophage receptor, can help to identify proliferative LN in SLE patients with proteinuria. Noninvasive monitoring of uCD163 may lead to early diagnosis and treatment of proliferative LN, thus reducing irreversible kidney damage

Background/Purpose: The Manhattan Lupus Surveillance Program (MLSP) is a multi-racial/ ethnic population-based registry with the primary goal to determine the prevalence and incidence of Systemic Lupus Erythematosus (SLE). In this study, we compare the three most commonly used classification criteria for SLE (1997 revised ACR, Systemic Lupus International Collaborating Clinics (SLICC) and the recent EULAR/ACR classification criteria) to identify cases that fulfilled only one of the classification criteria and explore each criteria set's unique cases. In addition, we used the EULAR/ACR criteria to determine the incidence and prevalence of SLE in Manhattan.
Method(s): MLSP cases were identified from Manhattan-based hospitals and rheumatologists, and state population databases. For this analysis, SLE cases were defined as fulfilling 1) the 1997 ACR classification criteria, 2) the SLICC criteria or 3) EULAR/ACR classification criteria. We quantified the number of cases that uniquely associated with each classification criteria and the number that fulfilled all three classifications. Prevalence (2007) and incidence rates (2007-2009) using the EULAR/ACR classification criteria and associated 95% confidence intervals (CI) were calculated using denominators obtained from the US Census data (revised 2000-2009 intercensal population files) for Manhattan.
Result(s): Overall 1,568 cases fulfilled at least one of the three classification criteria. Of those, 1008 (64.3%) cases fulfilled all three classification criteria, 166 (10.5%) fulfilled only the SLICC criteria, 50 (3.2%) fulfilled only the 1997 ACR criteria and 36 (2.3%) fulfilled the EULAR/ACR criteria with the remaining cases fulfilling a combination of two classification criteria. Cases that only met one of the classification criteria, and the reasons why they did not meet the other two classification criteria with example cases, are detailed in Tables 1-3. Based on the EULAR/ACR classification criteria, the age-adjusted overall prevalence and incidence rates of SLE in Manhattan were 59.8 (n=1,029, 95%CI:56.1-63.6) and 4.9 (n=245, 95%CI 4.3-5.5) per 100,000 population. Prevalence was 9 times higher and incidence was 6.9 times higher among females compared to males. The age-adjusted prevalence per 100,000 was highest among non-Hispanic Black females (198.9), followed by Hispanic females (133.1), non-Hispanic Asian/Pacific Islander females (97.7) and non-Hispanic White females (59.8). Age-adjusted incidence rates per 100,000 were highest in non-Hispanic Black females (15.8), followed by Hispanic females (7.5), non-Hispanic Asian/Pacific Islander females (7.3) and non-Hispanic White females (6.3). Prevalence and incidence rates for males followed a similar pattern.
Conclusion(s): Applying the three commonly used classification systems to a multi-racial/ ethnic population-based registry allowed for identifying unique cases of SLE who only fulfilled one classification system. The EULAR/ACR classification criteria revealed similar prevalence and incidence estimates and gender and racial/ethnic disparities to the previously published results from the MLSP using the 1997 revised ACR and SLICC classification criteria

Background/Purpose: Congenital Heart Block (CHB) complicates 2% of anti-Ro/ SSA antibody positive pregnancies and carries substantial perinatal morbidity and mortality. Almost all survivors require lifelong pacing. Data suggests the potential of anti-inflammatory treatment of 1degree and 2degree CHB in preventing progression to immutable complete block. However, the optimal surveillance strategy to detect rapidly transitioning and potentially reversible conduction disease is unknown. This study addresses the feasibility, acceptance and accuracy of the fetal heart rate and rhythm technique (FHRM) in high risk mothers.
Method(s): Prospective data from the Surveillance To Prevent AV Block Likely to Occur Quickly (STOP BLOQ) study were leveraged. Mothers referred to the study all had commercially positive anti-Ro/ SSA antibodies and were stratified into high and low titers of anti-Ro60 and Ro52 based on a research ELISA which used a threshold cutoff defined as the titer above or below that obtained for 50 mothers with a previous CHB offspring. Mothers with anti-Ro60 or 52 antibodies at or above 1,000 I.U or with a previous CHB offspring, were trained to perform FHRM with an educational video and personal instruction from a pediatric cardiologist. From 17-25 weeks of gestation, FHRM was completed 3x/day in addition to weekly or biweekly fetal echocardiograms (echo). Mothers texted all FHRM sounds to the study's data coordinating center. For those FHRM deemed abnormal by the mothers, texts were immediately sent to an on call pediatric cardiologist who either reassured if FHRM was normal or referred for emergency fetal echo in < 6 hours if abnormal. Postnatal electrocardiograms were evaluated for CHB.
Result(s): Fifty-six mothers with commercial anti-Ro/ SSA positivity were consented to the study. Of these, 37 (inclusive of 6 with previous CHB) performed FRHM since they had high titer anti-Ro60 (n=8) or 52 antibodies (n=7) or both (n=21), albeit one mother had unexpectedly low titer antibodies to both Ro60 and 52 and a child with incomplete CHB 4 yrs prior to enrollment. In total 3,360 FHRM audiotexts were received during the monitoring period. Of these, 39 recordings from 5 concerned mothers prompted an immediate call with the cardiologist. All but 2 recordings were deemed to be normal based on review of the audiotext alone; the cardiologist requested that the patient send repeat recordings after review as part of re-training and to provide additional reassurance. In the 2 cases an emergency echo was completed in < 6 hrs. In both there were premature atrial contractions which confirmed the mother's perception of the FHRM abnormality. However, there was no evidence of conduction disease. All surveillance echoes were normal. Thus, the overall rate of false positive recordings for the concern of a conduction defect perceived by the mothers was 1.1% (38/3360). There were no cases of CHB at birth.
Conclusion(s): These data support that FHRM is feasible and accurate. Mothers can be empowered to detect rhythm abnormalities with very few false perceptions thus supporting this technique to substantially enhance the management of anti-Ro/ SSA pregnancies