Faculty Bibliography

OBJECTIVES/OBJECTIVE:Current treatments are effective only in 30% of lupus nephritis patients emphasizing the need for novel therapeutic strategies. To develop mechanistic hypotheses and explore novel biomarkers, we analyzed the longitudinal urinary proteomic profiles in patients with lupus nephritis undergoing treatment. METHODS:We quantified 1,000 urinary proteins in 30 patients with lupus nephritis at the time of the diagnostic renal biopsy and after 3, 6, and 12 months. The proteins and molecular pathways detected in the urine proteome were then analyzed with respect to baseline clinical features and longitudinal trajectories. The intrarenal expression of candidate biomarkers was evaluated using single cell transcriptomics of renal biopsies from lupus nephritis patients. RESULTS:Our analysis revealed multiple biological pathways including chemotaxis, neutrophil activation, platelet degranulation, and extracellular matrix organization that could be noninvasively quantified and monitored in the urine. We identified 237 urinary biomarkers associated with lupus nephritis as compared to controls without SLE. IL-16, CD163, and TGF-β mirrored intrarenal nephritis activity. Response to treatment was paralleled by a reduction of urinary IL-16, a CD4 ligand with proinflammatory and chemotactic properties. Single cell RNA sequencing independently demonstrated that IL16 is the second most expressed cytokine by most infiltrating immune cells in lupus nephritis kidneys. IL-16 producing cells were found at key sites of kidney injury. CONCLUSION/CONCLUSIONS:Urine proteomics may profoundly change the diagnosis and management of lupus nephritis by noninvasively monitor active intrarenal biological pathways. These findings implicate IL-16 in lupus nephritis pathogenesis designating it as a potentially treatable target and biomarker.

OBJECTIVE:Previous studies suggest a link between high serum type I interferon (IFN) and lupus nephritis (LN). We determined whether serum IFN activity is associated with subtypes of LN and studied renal tissues and cells to understand the impact of IFN in LN. METHODS:). Podocyte cell line gene expression was measured by real-time PCR. RESULTS:expression was not closely co-localized with pDCs. IFN directly activated podocyte cell lines to induce chemokines and proapoptotic molecules. CONCLUSION/CONCLUSIONS:Systemic high IFN is involved in the pathogenesis of severe LN. We do not find co-localization of pDCs with IFN signature in renal tissue, and instead observe the greatest intensity of IFN signature in glomerular areas, which could suggest a blood source of IFN.

OBJECTIVE:To evaluate seroreactivity and disease flares after COVID-19 vaccination in a multi-ethnic/racial cohort of patients with systemic lupus erythematosus (SLE). METHODS:90 SLE patients and 20 healthy controls receiving a complete COVID-19 vaccine regimen were included. IgG seroreactivity to the SARS-CoV-2 spike receptor-binding domain (RBD) and SARS-CoV-2 microneutralization were used to evaluate B cell responses; IFN-γ production to assess T cell responses was measured by ELISpot. Disease activity was measured by the hybrid SLE disease activity index (SLEDAI) and flares were assigned by the SELENA/SLEDAI flare index. RESULTS:Overall, fully vaccinated SLE patients produced significantly lower IgG antibodies against SARS-CoV-2 spike RBD than controls. Twenty-six SLE patients (28.8%) generated an IgG response below that of the lowest control (<100 units/ml). In logistic regression analyses, the use of any immunosuppressant or prednisone and a normal anti-dsDNA level prior to vaccination associated with decreased vaccine responses. IgG seroreactivity to the SARS-CoV-2 Spike RBD strongly correlated with the SARS-CoV-2 microneutralization titers and antigen-specific IFN-γ production determined by ELISpot. In a subset of patients with poor antibody responses, IFN-γ production was likewise diminished. Pre-/post-vaccination SLEDAI scores were similar. Only 11.4% of patients had a post-vaccination flare; 1.3% were severe. CONCLUSION/CONCLUSIONS:In a multi-ethnic/racial study of SLE patients 29% had a low response to the COVID-19 vaccine which was associated with being on immunosuppression. Reassuringly, disease flares were rare. While minimal protective levels remain unknown, these data suggest protocol development is needed to assess efficacy of booster vaccination.

Anti-SSA/Ro antibodies, while strongly linked to fetal cardiac injury and neonatal rash, can associate with a spectrum of disease in the mother, ranging from completely asymptomatic to overt Systemic Lupus Erythematosus (SLE) or Sjögren's Syndrome (SS). This study was initiated to test the hypothesis that the microbiome, influenced in part by genetics, contributes to disease state. The stool microbiome of healthy controls (HC) was compared to that of anti-SSA/Ro positive women whose children had neonatal lupus. At the time of sampling, these women were either asymptomatic (Asym), had minor rheumatic symptoms or signs considered as an undifferentiated autoimmune syndrome (UAS), or were diagnosed with SLE or SS. Differences in microbial relative abundances among these three groups were tested assuming an ordering in clinical severity (HC<Asym/UAS<SS/SLE) and then again without the ordinal assumption. Those taxa that showed differential relative abundances were then tested for whether the effect size differed depending on the women's HLA SLE-risk allele genotype (DRB1*03:01, DRB1*15:01, DQB1*02:01 and DQB1*06:02) or anti-SSA/Ro autoantibody levels. Multiple genera within the families Ruminococcaceae and Lachnospiraceae showed evidence of an HLA-by-genus interaction (P < .05). Four genera exhibited evidence of an interaction with anti-Ro52 IgA: Lachnoclostridium, Romboutsia, Bacteroides and Actinomyces (P < .01). In addition to documenting differences in microbial relative abundances across clinical severity of disease, these data provide a first-time demonstration that microbial differences are correlated with HLA SLE-risk alleles. Taken together, these data suggest that the clinical spectrum from benign to overt clinical autoimmunity may partially result from or trigger a complex interplay among specific microbial profiles, anti-Ro autoantibodies, and genetics.

Background Mitochondria are intracellular organelles derived from the endosymbiosis between an a-proteobacterium and a primitive eukaryotic cell. Mitochondria thus display proinflammatory and antigenic properties, when released into the extracellular milieu. Several cross-sectional studies reported increased levels of anti-mitochondrial antibodies (AMAs) in patients with systemic lupus erythematosus (SLE) and the antiphospholipid syndrome (APS). These autoantibodies also displayed correlations with the SLE disease activity index 2000 (SLEDAI-2K) and associations with various clinical manifestations (e.g. lupus nephritis, thromboses, carotid plaque). In the present study, we aim to detect AMAs against either whole organelles (AwMA), mitochondrial DNA (mtDNA) or RNA (mtRNA) through time in samples from patients included in the SLICC cohort. Methods Clinically relevant variables (e.g., sociodemographic variables, disease-specific outcomes including death and arterial vascular events (AVE)) were documented and biosamples were harvested upon patient enrolment in the SLICC cohort, as well as at each follow-up visit. AMA levels were measured by in-house direct ELISAs whereas SLE autoantibodies were detected by clinical laboratories. Healthy individuals, defined as having no known illnesses and infectious symptoms at the time of the blood draw, were recruited. 90% confidence intervals were calculated for both limits of the 95% nonparametric two-sided reference intervals for values measured in healthy donors. AMA values were segregated into 3 categories: Normal values were determined as within the inner limits of the range while values outside this range were characterized as abnormal, either lower or higher than the reference interval. (figure 1). Marginal Cox models with AMAs in 3 categories were adjusted for covariables and are presented as [hazard ratio (95% CI)]. Interactions with sex were tested in models with the AMAs as continuous variables. Results Sera from healthy individuals (n=126) or SLE patients included in the SLICC cohort, from their inclusion, up to 7 years of follow-up (n=1114 patients at baseline, 3577 samples in total). AwMA displayed lower correlations with antibodies to mitochondrial nucleic acids (versus AmtDNA: rs=0.37, and vs AmtRNA: rs=0.38), while antibodies to mitochondrial DNA or RNA shown higher correlations (rs=0.59). During our preliminary analyses on the distribution of the variables, We made intriguing observations regarding patients with AMA levels that were either lower or higher than those of healthy individuals. This information led us to categorize SLE patients as described in the methods and in figure 1. For each of the three antibodies assessed, SLE patients displayed more abnormal AMA levels at baseline than controls. The percentage of patients with higher levels of AwMA and AmtRNA increased at subsequent follow-up visits, while a slight decrease was observed for AmtDNA (figure 2). SLE patients with higher levels of AwMA showed higher risks of death [2.12 (1.18-3.83)]. It is of interest that an inverse relationship was found between AmtRNA and AVEs, with a small subset of patients with low levels of AmtRNA (n = 4), this autoantibody was associated with increased risks of this manifestation [4.46 (1.71-11.66)]. Additionally, patients with higher levels of AmtDNA and AmtRNA displayed increased risks of lupus nephritis [respectively: 3.05(2.05-4.54), and 1.56(1.12-2.18)]. Interestingly, there was an interaction with sex for AmtRNA levels effect on AVEs [males: 0.32 (0.11-0.99). Females: 1.56 (1.11-2.19)], and AmtDNA association with nephritis was only significant in female patients [4.00 (2.51-6.36)] (table 1). Conclusion These results show that AMAs display different associations with disease manifestations in various clusters of patients. These results prompt for further analyses by machine-learning in order to delineate clusters of clinical interests by adding AMAs in the routine serological assessment of SLE autoantibodies. Acknowledgements We acknowledge the contribution of the study participants, individual center support staff as well as investigators of the Systemic Lupus International Collaborating Clinics (SLICC) Inception Cohort project who for the past 20 years have made this study possible. LAY ABSTRACT The mitochondrion is a part of the cell that controls various biological mechanisms (e.g., energy supply, whether the cell should live or die, control, or produce various cellular components). They are derived, through evolution, from a microbe. Mitochondria may sometimes be jettisoned out of their host cell and subsequently elicit immune reactions - including the production of antibodies. Previous studies indicated that patients with autoimmune conditions such as systemic lupus erythematosus (SLE) and the antiphospholipid syndrome (APS) have antibodies against mitochondria in their blood stream. Presence of these antibodies was associated with increased disease activity and clinical manifestations of these diseases (e.g. kidney disease, arterial vessel disease). In this study, we studied blood samples harvested by an international group dedicated to the study of SLE [i.e., the SLE International Collaborating Clinics (SLICC) cohort] and observed that patients may be clustered into groups, upon their levels of antibodies and/or sex, allowing to have a better appreciation of their risks of death, vascular events, and kidney disease. These results might lead to improved diagnosis and/or prognosis in SLE and thus, in improved care and quality of life for the people living with lupus

Introduction Fetal cardiac disease is strongly associated with maternal anti-SSA/Ro antibodies, but gaps in our knowledge include the influence of antibody specificity and titer, maternal diagnosis, overall non-cardiac adverse pregnancy outcomes (APOs), optimal surveillance protocols, and efficacy of rapid treatment. Methods The multi-center Surveillance and Treatment To Prevent Fetal AV Block Likely to Occur Quickly (STOP BLOQ) study recruited pregnant women with commercially positive anti-Ro antibodies and stratified them into high and low titers of anti-Ro60 and Ro52 based on a research ELISA, using a cutoff defined by that obtained for 50 mothers with previous AVB offspring. Mothers with anti-Ro60 and/or 52 antibodies at or above 1,000 I.U. were trained to perform FHRM. From 17-25 weeks of gestation, FHRM was completed 3x/day in addition to weekly or biweekly fetal echocardiograms (echo). Mothers texted all audio sounds to the coordinating center. Texts deemed abnormal by mothers 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. Results 250 anti-Ro pregnant women (22% Hispanic, 50% white, 12% Black, 12% Asian, 4% other) have been consented, including 28 whose previous child had AVB. Of mothers tested to date, 153 were provided home monitors given high titer anti-Ro60 and/or 52 antibodies (26 high titer anti-Ro60 alone, 21 high titer anti-Ro52 alone,105 high titer antibodies to both antigens). The 83 patients with low titers were surveilled with echos per local standard of care. Regarding maternal diagnosis, of 161 assessed to date, 39% were asym/UAS, 11% RA, 31% SS, 19% SLE. Antibody titers did not significantly differ by ethnicity, race or diagnosis (table 1). Non-AVB APOs occurred in 18% and were not predicted by Ro60 or 52 titers but rather SLE diagnosis (table 2). In total, 24,759 FHRM audiotexts were received from 131 patients (90 of whom have delivered) during the monitoring period. Of these, 22 were evaluated by the on-call pediatric cardiologist, who prompted an emergency echo (all completed in < 6 hrs). In 11 cases, the emergency echo was normal. In 9, there were premature atrial contractions, confirming the mother's perception. In 2 with 2degree block on urgent echo (both treated per protocol with IVIG and dexamethasone), 1 reverted to normal sinus rhythm and the other progressed to 3degree block. In 2 others, the mother did not perceive abnormal FHRM for > 24 hrs, echo identified 3degree block, and retrospective cardiology review of FHRM audio captures identified an abnormality prior to obtaining the echo. All 4 AVB developed in fetuses of mothers with high titer antibodies to both Ro60 and 52 (mean 32,451 and 34,991 respectively). Of the 18 mothers with a previous AVB child who followed the 400mg hydroxychloroquine PATCH protocol, 1 developed AVB in accord with the results of Step 1 in that study. Conclusion These data support that APOs in this clinically diverse group of mothers are not influenced by anti-Ro titer or specificity, but rather SLE diagnosis. All conduction defects were initially identified by FHRM and in mothers with high titer anti-Ro60 and 52. Hydroxychloroquine continues to show efficacy in reducing the AVB recurrence rate with rapid intervention of emergent block being promising

Background Nearly 20% of pregnancies in patients with Systemic lupus erythematosus (SLE) result in an adverse pregnancy outcome (APO); early identification of women with SLE who are at high risk of APO is vital. We previously examined several regression and machine learning (ML) predictive models for APO using data from the PROMISSE Study, a large multi-center, multi-ethnic/racial study of APO in women with mild/moderate SLE and/or aPL. Penalized logistic regression (LASSO), as well as several black box ML algorithms (Random Forest, Support Vector Machine, and Super Learner) each achieved good internal cross-validated performance, with area under the receiver operating curve (AUC) of 0.77-0.78. The goal of this study was to externally validate the performance of these promising APO risk models using three independent, external cohorts. Methods The PROMISSE data set used to develop the initial APO prediction models consisted of N=385 pregnancies, 71 APO events (18.4%), and 32 known or potential APO risk factors that are routinely measured in clinical practice early in pregnancy. APO was defined as preterm delivery due to placental insufficiency or preeclampsia, fetal or neonatal death, or fetal growth restriction. Three independent prospective cohorts were provided by a team of international investigators with expertise in SLE pregnancy (Bronx, NY: N=96; NYC, NY: N=62; Pisa, Italy: N=152). Patient demographics were summarized for each cohort and missing data handled using multiple imputation with chained equations. Using the APO risk models developed with the PROMISSE data, we computed for each cohort: 1) the standard deviation (SD) of predicted risk scores to summarize the degree of heterogeneity in patient characteristics and 2) the area under the receiver operating curve (AUC) to summarize the ability of each model to discriminate patients with and without APO. Results The three external cohorts and the PROMISSE development cohort showed distributional differences in previously identified APO risk factors (table 1). Non-Hispanic White comprised 49.3% of the PROMISSE, compared to 98.7% in Pisa, 27.4% in NYC, and 0% in the Bronx. LAC positivity varied from 8.1% in PROMISSE to 22.6% in the NYC cohort, while PGA > 1 varied from 10.6% in the development cohort to 4.4% in the Bronx, NY cohort. Current antihypertensive use was 8.6% in PROMISSE, higher in the Bronx cohort (12.6%), and lower in the NYC (4.8%) and Pisa (5.3%) cohorts. APO rates were the same in PROMISSE and Pisa (18.4%) and higher in the Bronx (24%) and NYC cohorts (25.8%). Prediction risk score SD indicated similar levels of heterogeneity within each external cohort compared to the PROMISSE cohort. Model performance in external validation cohorts varied depending on the algorithm used. As expected, AUCs in the external cohorts were generally lower than cross-validated internal estimates, but still indicated satisfactory performance of the different models with the independent data sets (table 2). Super Learner, the highest performing algorithm in PROMISSE, performed well across all three external cohorts, with a minimum AUC of 0.63 in the NYC cohort and a maximum of 0.71 in the Pisa cohort (table 2). LASSO also maintained consistent external performance with minimum AUC of 0.60 and maximum of 0.66. Overall, performance was highest using data from the Pisa cohort, which was the largest and most complete of the three external validation data sets. Conclusions Penalized regression and ML approaches using variables obtained early in pregnancy show potential in discriminating pregnancies with high APO risk from those pregnancies with lower risk. This study provides confirmation of the geographic transportability of the best performing algorithms developed with PROMISSE. While Super Learner showed the most satisfactory performance across external cohorts, LASSO also performed well and yielded a parsimonious model that may be easier and more efficient to use as a risk assessment tool in practice. Data from additional external cohorts from the US and abroad will be obtained in the future for further validation and refinement of our APO prediction models