Faculty Bibliography

Background/Purpose : Pregnancy counseling of all anti-Ro positive women includes advice regarding the development of congenital heart block (CHB), albeit the risk is only 2% for primigravida women or those with previously unaffected offspring. Despite this low risk, the prevailing surveillance recommendation is weekly echocardiography. While evidence from basic research laboratories support that high titers of antibodies confer clinically meaningful risk, unfortunately the majority of commercial laboratories use the BioPlex assay, which provides positive and negative values with limited information on actual levels because the sera or plasma are not diluted past a specified cutoffgiven cost (e.g. values of anti-Ro inclusive of Ro52 or Ro60 by laboratories such as Quest or LabCorp provide positive as 1-8 or > 8 units with no further information). The present study was initiated to assess whether the Bio-Plex assay used by many commercial laboratories provides adequate stratification of risk for counseling regarding management. Methods : The study group comprised healthy non-pregnant donors (N = 9), healthy pregnant donors (N = 62), women testing positive for anti-Ro by commercial BioPlex but without CHB children (N = 60 SLE and 2 SS), and women with CHB children (N = 83). Anti-Ro60 reactivity was assessed using native antigen and anti-Ro52 using recombinant protein. Sera were applied to coated microtiter plates at serial dilutions ranging from 1:1000 -1:50,000 for 1h at RT and run in duplicate. Tested samples were multiplied by the dilution factor which gives an OD in the range of 0.3-0.8. Results were considered positive at 123 ELISA units (EU) for Ro60 and 215 EU for Ro52 as this represented the mean +3 SD of the values obtained for healthy control sera. Results : Of the 83 CHB mothers tested, 74 had titers of Ro60 and Ro52 > 1000 EU, in 1 anti-Ro60 was > 1000 EU and anti-52 Ro between 215 -1000, in 3 anti-Ro52 was > 1000 EU and anti-Ro60 between 300 -1000, and 1 mother had anti-Ro60 > 1000 EU and was negative for anti-Ro52. Albeit all positive, the sera from 4 CHB mothers obtained 15 years after the birth of the affected child were < 1000 EU for both anti-Ro60 and Ro52. With these results setting thresholds ( > 1000 EU in either Ro60 or Ro52 for CHB risk), we assessed patients testing positive for anti-Ro based on the BioPlex assay. Of 42 patients with values of > 8 on BioPlex testing, 14 had titers > 1000 EU for both anti-Ro60 and Ro52, 7 had anti-Ro60 > 1000 EU, and 8 had anti-Ro52 > 1000 EU. Thus, 13 of 42 (25%) with commercial Ro > 8 did not meet the threshold EU for CHB risk. Of 20 patients considered positive for anti-Ro by BioPlex with values between 1-8, none had levels of either anti-Ro60 or Ro52 at 1000 EU. No patient or healthy control testing negative by the BioPlex assay was positive for CHB risk in our ELISA. Conclusion : These data suggest that commercial testing using the BioPlex assay may fall short of stratifying risk for CHB. Women with positive values < 8 are not likely at risk, obviating the cost and burden of weekly fetal echo surveillance. Moreover, even those considered high titer on commercial testing may be at low risk supporting the need for more quantitative commercial testing than is currently available. (Figure Presented)

Background/Purpose : The impact of renal injury in lupus nephritis (LN) is widespread with consequences to resident cells in other tissue beds, even non-lesional, non-sun exposed skin. Faithful reflection of a relevant renal tissue pathway in a more readily accessible compartment would allow for less invasive diagnostic alternatives. While ongoing studies are exploiting single cell RNA sequencing to link phenotype to biotype and identify cell specific pathways in the kidney, this study was initiated to address the hypothesis that these pathways may be reflected in uninvolved skin which is more likely to be serially biopsied. Methods : Single cell RNAseq was performed on cell suspensions prepared from ~2 mm punch biopsies of nonlesional, non-sun-exposed skin from the buttocks of 5 healthy controls, 4 SLE patients without LN and 18 SLE patients with proteinuria (with skin biopsies obtained within 24 hrs of the kidney biopsy). Histology revealed Class III ( n=6 ), Class III/V or IV/V mixed ( n=11 ), Class V ( n=1 ), and nephrosclerosis ( n=1 ). Dissociation of cryostored skin biopsies with collagenase and trypsin enzymes was followed by scRNA-seq using the 10x Genomics platform using V2 and V3 reagents. Results : We obtained 8,019 and 17,655 high-quality scRNA-seq profiles from single cell suspensions of control and SLE non-lesional, non-sun-exposed skin, respectively. A graph-based clustering method was applied and identified major clusters of cells as visualized by t-distributed stochastic neighbor embedding (tSNE). Differential gene expression analysis guided by established markers revealed these cell clusters as keratinocyte (KC), one smooth muscle cell cluster (SMC), fibroblast (FB), melanocyte (MEL), vascular endothelial cells (VEC), lymphatic endothelial cells (LEC), macrophages-dendritic cells (MAC-DC), T cells (TC) and sweat gland cells (SGC) (Figure 1A). Ranking cells by abundance, the result of the SLE skin cells was KC >FB >VEC >LEC, SMC, MAC-DC, TC, MEL and SGC. Overall, samples processed using the recent V3 single cell reagent kit showed higher genes and transcript captures compared to V2. However, these samples also captured more mitochondrial transcripts (Figure 1B). An analysis of gene expression changes in KC, SMC, and VSC from the LN patients versus controls demonstrated overexpression of interferon stimulated genes. However, the degree of interferon response varied in these cell types with KCs (basal KC, p=0.00312 and hair follicle KC, p=0.000012) showing the highest response followed by VECs (p=0.0043) and SMCs (p=0.0068). In addition to the interferon response signature, VECs from the LN patients also showed upregulation of MHC-II genes such as HLA-DRB5 and HLA-DRB1, suggesting increased antigen presentation capacity (Figure 1C). Conclusion : scRNA-seq identifies major skin cell types and further clustering identifies rarer cell populations. KCs, SMCs, and VECs from the skin of LN patients reveal diverse IFN response states and additionally VECs also show higher antigen presentation potential. The V3 upgrade of 10x Genomics single cell reagents capture more genes and UMIs per cell, but also higher mitochondrial content compared to the V2 version

Background/Purpose : Lupus nephritis (LN) complicates up to 60% of patients with systemic lupus erythematosus (SLE) and carries a high morbidity and mortality. The definitive diagnosis is based on kidney biopsy. This is invasive and not always readily available, thus delaying treatment. Sometimes multiple biopsies are required over the course of the disease. Importantly, while renal pathology is accurate at describing the morphology of renal disease, the underlying biology and molecular pathways are not thoroughly assessed. Urine proteomics is a non-invasive strategy that may provide insights regarding ongoing renal disease. Methods : One thousand proteins were quantified (RayBiotech Kiloplex assay) on a total of 112 longitudinal urine samples from 32 SLE patients with active LN and 7 healthy controls (HC) enrolled in the Accelerating Medicines Partnership (AMP). All patients underwent treatment as directed by their own physicians. Differentially excreted proteins at baseline (SLE vs HC, proliferative vs membranous LN, responders vs non responders) were identified using a linearmodel with moderated t statistic. Response to treatment was defined based on proteinuria at 1 year as complete (< 0.5g/24h) or partial (50% reduction but >0.5/24h). In the longitudinal analysis, a mixed model was employed to identify markers associated with proteinuria. Pathway enrichment analysis was performed using the genes coding for the differentially excreted analytes using Ingenuity Pathway Analysis (IPA) and other publicly available pathway libraries. Results : There were 186 proteins increased in SLE patients (Fig. 1). The most enriched pathway was TNFa (p< 0.001). We found 74 differentially excreted proteins comparing proliferative and pure membranous LN. CD4, MCP-1, MIP-1a, RANTES, IL-16, and IL-7, markers involved in CD4 T cell and monocyte biology, were enriched in proliferative disease. A few targets were exclusively identified in either class (i.e. CD4 in proliferative nephritis). We used a longitudinal model to identify specific urine proteins associated with worse proteinuria as a marker of severity. Proteinu-ria was associated with 105 markers (FDR < 0.05), the strongest association being CD163 (p = 10-9), a phagocyte marker. IPA implicated several pathways involving fibrosis, acute phase response, LPS/IL1, RXR, ICOS signaling and macrophage/fibroblasts (Fig. 2). Next, we identified 27 differentially excreted proteins in non-responders. IPA revealed that tretinoin, GM-CSF, TNF, and IL1 were among the top upstream regulators (Fig. 3). Conclusion : There is an inflammatory signature in the urine of patients with LN implicating monocyte and TNFa pathways. These signatures are associated with proliferative disease, worse proteinuria, and non-response to treatment. Of note, TNFa is involved in LN and has therapeutic potential. In phase 1 of AMP, monocytes were the main urine cell type identified by singe cell RNA sequencing in patients with LN. These results suggest that urine proteomics might identify and infer active pathological mechanisms in LN, paving the way for a more personalized approach to treatment. Further work in Phase 2 of AMP is being pursued to validate and extend these findings

Background/Purpose : The heterogeneity of the clinical manifestations of systemic lupus erythematosus (SLE) and lack of a diagnostic test make SLE difficult for epidemiologists to study. The Centers for Disease Control and Prevention (CDC) supported five population-based SLE surveillance registries, using harmonized methodology, to better estimate incidence and prevalence of SLE in diverse areas in the United States (US). Leveraging these data, we performed a meta-analysis to estimate the general prevalence of SLE in the US. Methods : The CDC registries were established in Michigan, Georgia, California, New York and the through the Indian Health Service (IHS). All registries used the 1997 revised ACR classification criteria for SLE as their primary case definition, and the surveillance time periods ranged from 2003 to 2009. Age-standardized prevalence was stratified by sex and race/ethnicity from the state-based registries; the American Indian/Alaska Native (AI/AN) estimate was based 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 I2 statistic to test for heterogeneity across sites. Due to significant heterogeneity, we used a random effects model to calculate pooled prevalence, which allows for more variation across sites. We then extrapolated to the 2017 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 SLE cases in the US. Results : The registries contributed 5,417 classified cases of SLE from a mix of urban and rural areas. From the metaanalysis of the four state-based registries, the overall prevalence was 72.8 (95%CI 65.3, 81.0) per 100,000 population. The prevalence among females was about 9 times higher than males (128.7 vs 14.6). In the meta-analysis, prevalence was highest among black females (230.9, 95%CI 178.2, 299.2), followed by Hispanic females (120.7, 95%CI 84.0, 173.4), white females (84.7, 95%CI 68.4, 104.8) and Asian/Pacific Islander females (84.4, 95%CI 48.3, 147.4). Among males, prevalence followed a similar pattern with the highest rates among black males (26.7, 95%CI 19.6, 36.4) followed by Hispanic males (18.0, 95%CI 15.6, 20.8), Asian/Pacific Islander males (11.2, 95%CI 5.7, 21.9), and white males (8.9, 95%CI 8.0, 10.1). The AI/AN prevalence estimates, which were not included in the meta-analysis, had the highest rates of SLE for both females (271, 95%CI 238, 307) and males (54, 95%CI 36, 77). Applying our sexand race-specific prevalence estimates to the corresponding population denominators from 2017 Census data, we estimated that 198,677 persons (179,186 females and 19,491 males) in the US fulfill ACR SLE classification criteria, Table 1. Conclusion : Using estimates from a coordinated network of population-based SLE registries, a more accurate prevalence estimate for the US was obtained. Our methods did not capture undiagnosed, incomplete, or other forms of lupus such as cutaneous lupus. Other case definitions may yield different results

Background/Purpose : Early treatment initiation in rheumatoid arthritis (RA) is fundamental to avoid chronic joint destruction and disability. Despite remarkable advances in RA therapeutics, oral methotrexate (MTX) remains the anchor drug and mainstay of treatment worldwide. However, MTX bioavailability has a wide inter-individual variability and >50% of patients with moderate or severe RA show no or suboptimal improvement in their symptoms in response to MTX. The reasons for these disparities in treatment response remain unclear. Prior studies have shown that the biotransformation of MTX is altered in germ-free and microbiome-depleted mice, prompting us to hypothesize that inter-individual differences in the human gut microbiome could impact drug bioavailability and thus clinical efficacy. We sought to determine differences in the microbiome of drug-naive, new onset RA (NORA) patients that could predict response to MTX therapy. Methods : We enrolled 27 drug-naive, NORA patients priori to MTX initiation (test cohort), and classified them as either MTX-responders (MTX-R; 39% of the cohort) or non-responders (MTX-NR; 61%) based on a stringent definition of clinical response (delta improvement of DAS28 >1.8 by month 4). We performed 16S rRNA gene and Shotgun Metagenomic sequencing on the baseline gut microbiomes of these NORA patients and confirmed the results in an independent validation cohort (n=31). NMR and LC-MS were performed in ex vivo incubations to measure the capacity of each NORA microbiome to metabolize MTX. Results : Our analysis revealed significant associations between the abundance of gut bacterial taxa and future MTX response. Patients that responded to therapy had significantly lower microbial diversity (p< 0.05). A significant difference in overall gut microbial community structure was also observed between groups (Bray-Curtis distance; PERMANOVA < 0.05). At the class level, we observed statistically higher abundance of Clostridia and lower abundance of Bacteroidia in MTX-NR (p< 0.05; q< 0.2). Furthermore, the baseline metagenome separated most MTX-R from MTX-NR (PCoA; PERMANOVA p< 0.05). We identified 8 microbial modules and 23 pathways, whose abundance significantly differed between groups (p< 0.05, q< 0.2), including genes related with purine and MTX metabolism, indicating a major difference in metabolic and biosynthetic potential between the microbiome of MTX-R and MTX-NR patients. Machine learning techniques were applied to this metagenomic data, resulting in a robust model based on bacterial gene abundance that accurately predicted response to MTX in an independent cohort. Finally, MTX available levels remaining after ex vivo incubation with distal gut samples from pre-treatment RA patients significantly correlated with the magnitude of future clinical response, suggesting a direct effect of the gut microbiome on MTX bioavailability and response to therapy. Conclusion : Together, these results provide the first step towards predicting response to oral MTX in NORA patients and support the utility of the gut microbiome as a prognostic tool and perhaps even as a target for manipulation in the treatment of rheumatic and autoimmune disease

Objective/UNASSIGNED:Epidemiological data for primary discoid lupus erythematosus (pDLE) remain limited, particularly for racial/ethnic populations in the USA. The Manhattan Lupus Surveillance Program (MLSP) is a population-based retrospective registry of cases with SLE and related diseases including pDLE in Manhattan and was used to provide estimates of the prevalence and incidence of pDLE across major racial/ethnic populations. Methods/UNASSIGNED:MLSP cases were identified from rheumatologists, hospitals and population databases. Two case definitions were used for pDLE: the primary case definition which was any physician diagnosis found in the chart and a secondary case definition which was limited to cases diagnosed by a rheumatologist and/or dermatologist. Rates among Manhattan residents were age-adjusted, and capture-recapture analyses were conducted to assess case under-ascertainment. Results/UNASSIGNED:Based on the primary definition, age-adjusted overall prevalence and incidence rates of pDLE among Manhattan residents were 6.5 and 0.8 per 100 000 person-years, which increased to 9.0 and 1.3 after capture-recapture adjustment. Prevalence and incidence rates were approximately two and six times higher, respectively, among women compared with men (p<0.0001). Higher prevalence was also found among non-Latino blacks (23.5) and Latinos (8.2) compared with non-Latino whites (1.8) and non-Latino Asians (0.6) (p<0.0001). Incidence was highest among non-Latino blacks (2.4) compared with all other racial/ethnic groups. Similar relationships were observed for the secondary case definition. Conclusion/UNASSIGNED:Data from the MLSP provide epidemiological estimates for pDLE among the major racial/ethnic populations in the USA and reveal disparities in pDLE prevalence and incidence by sex and race/ethnicity among Manhattan residents.

Mothers giving birth to children with manifestations of neonatal lupus (NL) represent a unique population at risk for the development of clinically evident pathologic autoimmunity since many are asymptomatic and only become aware of anti-SSA/Ro positivity (anti-Ro+) based on heart block in their fetus. Accordingly, we hypothesized that the microbiome in saliva is associated with the development of autoreactivity and in some cases the progression in health status from benign to overt clinical disease including Sjögren's syndrome (SS) and systemic lupus erythematosus (SLE). The study comprised a clinical spectrum of anti-Ro+ mothers, all of whom gave birth to a child with NL: 9 were asymptomatic or had an undifferentiated autoimmune disease (Asym/UAS) and 16 fulfilled criteria for SS and/or SLE. Microbial diversity was reduced across all levels from kingdom to species for the anti-Ro+ mothers vs healthy controls; however, there were no significant differences between Asym/UAS and SS/SLE mothers. Relative abundance of Proteobacteria and more specifically class Betaproteobacteria decreased with clinical severity (healthy controls < Asym/UAS < SS/SLE). These ordered differences were maintained through the taxonomic hierarchy to three genera (Lautropia, Comamonas, and Neisseria) and species within these genera (L. mirabilis, N. flavescens and N. oralis). Biometric analysis comparing von Willebrand Factor domains present in human Ro60 with L. mirabilis proteins support the hypothesis of molecular mimicry. These data position the microbiome in the development of anti-Ro reactivity and subsequent clinical spectrum of disease.

Objective/UNASSIGNED:A common problem in clinical trials is missing data due to participant dropout and loss to follow-up, an issue which continues to receive considerable attention in the clinical research community. Our objective was to examine and compare current and alternative methods for handling missing data in SLE trials with a particular focus on multiple imputation, a flexible technique that has been applied in different disease settings but not to address missing data in the primary outcome of an SLE trial. Methods/UNASSIGNED:Data on 279 patients with SLE randomised to standard of care (SoC) and also receiving mycophenolate mofetil (MMF), azathioprine or methotrexate were obtained from the Lupus Foundation of America-Collective Data Analysis Initiative Database. Complete case analysis (CC), last observation carried forward (LOCF), non-responder imputation (NRI) and multiple imputation (MI) were applied to handle missing data in an analysis to assess differences in SLE Responder Index-5 (SRI-5) response rates at 52 weeks between patients on SoC treated with MMF versus other immunosuppressants (non-MMF). Results/UNASSIGNED:The rates of missing data were 32% in the MMF and 23% in the non-MMF groups. As expected, the NRI missing data approach yielded the lowest estimated response rates. The smallest and least significant estimates of differences between groups were observed with LOCF, and precision was lowest with the CC method. Estimated between-group differences were magnified with the MI approach, and imputing SRI-5 directly versus deriving SRI-5 after separately imputing its individual components yielded similar results. Conclusion/UNASSIGNED:The potential advantages of applying MI to address missing data in an SLE trial include reduced bias when estimating treatment effects, and measures of precision that properly reflect uncertainty in the imputations. However, results can vary depending on the imputation model used, and the underlying assumptions should be plausible. Sensitivity analysis should be conducted to demonstrate robustness of results, especially when missing data proportions are high.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Nonadherence to treatment is a major cause of lupus flares. Hydroxychloroquine (HCQ), a major medication in systemic lupus erythematosus, has a long half-life and can be quantified by high-performance liquid chromatography. This international study evaluated nonadherence in 305 lupus patients with flares using drug levels (HCQ < 200 ng/ml or undetectable desethylchloroquine), and self-administered questionnaires (MASRI < 80%). Drug levels defined 18.4% of the patients as severely nonadherent. In multivariate analyses, younger age, nonuse of steroids, higher body mass index, and unemployment were associated with nonadherence by drug level. Questionnaires classified 23.4% of patients as nonadherent. Correlations between adherence measured by questionnaires, drug level, and physician assessment were moderate. Both methods probably measured two different patterns of nonadherence: self-administered questionnaires mostly captured relatively infrequently missed tablets, while drug levels identified severe nonadherence (i.e., interruption or erratic tablet intake). The frequency with which physicians miss nonadherence, together with underreporting by patients, suggests that therapeutic drug monitoring is useful in this setting. (Trial registration: ClinicalTrials.gov: NCT01509989.).