Faculty Bibliography

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:To develop new classification criteria for systemic lupus erythematosus (SLE) jointly supported by the European League Against Rheumatism (EULAR) and the American College of Rheumatology (ACR). METHODS:This international initiative had four phases. (1) Evaluation of antinuclear antibody (ANA) as an entry criterion through systematic review and meta-regression of the literature and criteria generation through an international Delphi exercise, an early patient cohort and a patient survey. (2) Criteria reduction by Delphi and nominal group technique exercises. (3) Criteria definition and weighting based on criterion performance and on results of a multi-criteria decision analysis. (4) Refinement of weights and threshold scores in a new derivation cohort of 1001 subjects and validation compared with previous criteria in a new validation cohort of 1270 subjects. RESULTS:The 2019 EULAR/ACR classification criteria for SLE include positive ANA at least once as obligatory entry criterion; followed by additive weighted criteria grouped in seven clinical (constitutional, haematological, neuropsychiatric, mucocutaneous, serosal, musculoskeletal, renal) and three immunological (antiphospholipid antibodies, complement proteins, SLE-specific antibodies) domains, and weighted from 2 to 10. Patients accumulating ≥10 points are classified. In the validation cohort, the new criteria had a sensitivity of 96.1% and specificity of 93.4%, compared with 82.8% sensitivity and 93.4% specificity of the ACR 1997 and 96.7% sensitivity and 83.7% specificity of the Systemic Lupus International Collaborating Clinics 2012 criteria. CONCLUSION/CONCLUSIONS:These new classification criteria were developed using rigorous methodology with multidisciplinary and international input, and have excellent sensitivity and specificity. Use of ANA entry criterion, hierarchically clustered and weighted criteria reflect current thinking about SLE and provide an improved foundation for SLE research.

OBJECTIVE:To develop new classification criteria for systemic lupus erythematosus (SLE) jointly supported by the European League Against Rheumatism (EULAR) and the American College of Rheumatology (ACR). METHODS:This international initiative had four phases. 1) Evaluation of antinuclear antibody (ANA) as an entry criterion through systematic review and meta-regression of the literature and criteria generation through an international Delphi exercise, an early patient cohort, and a patient survey. 2) Criteria reduction by Delphi and nominal group technique exercises. 3) Criteria definition and weighting based on criterion performance and on results of a multi-criteria decision analysis. 4) Refinement of weights and threshold scores in a new derivation cohort of 1,001 subjects and validation compared with previous criteria in a new validation cohort of 1,270 subjects. RESULTS:The 2019 EULAR/ACR classification criteria for SLE include positive ANA at least once as obligatory entry criterion; followed by additive weighted criteria grouped in 7 clinical (constitutional, hematologic, neuropsychiatric, mucocutaneous, serosal, musculoskeletal, renal) and 3 immunologic (antiphospholipid antibodies, complement proteins, SLE-specific antibodies) domains, and weighted from 2 to 10. Patients accumulating ≥10 points are classified. In the validation cohort, the new criteria had a sensitivity of 96.1% and specificity of 93.4%, compared with 82.8% sensitivity and 93.4% specificity of the ACR 1997 and 96.7% sensitivity and 83.7% specificity of the Systemic Lupus International Collaborating Clinics 2012 criteria. CONCLUSION/CONCLUSIONS:These new classification criteria were developed using rigorous methodology with multidisciplinary and international input, and have excellent sensitivity and specificity. Use of ANA entry criterion, hierarchically clustered, and weighted criteria reflects current thinking about SLE and provides an improved foundation for SLE research.

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.).

OBJECTIVE:Extant epidemiologic data of primary Sjögren's Syndrome (pSS) remains limited, particularly for racial/ethnic populations in the United States (US). The Manhattan Lupus Surveillance Program (MLSP), a population-based retrospective registry of cases with Systemic Lupus Erythematosus and related diseases including pSS in Manhattan, was used to provide estimates of the incidence and prevalence of pSS across major racial/ethnic populations. METHODS:MLSP cases were identified from hospitals, rheumatologists, and population databases. Three case definitions were used for pSS: physician diagnosis, rheumatologist diagnosis, and modified pSS criteria. Rates among Manhattan residents were age-adjusted, and capture-recapture analyses were conducted to assess case under-ascertainment. RESULTS:By physician diagnosis, age-adjusted overall incidence and prevalence rates of pSS among adult Manhattan residents were 3.5 and 13.1 per 100,000 person-years. Capture-recapture adjustment increased incidence and prevalence rates (4.1 and 14.2). Based on physician diagnosis, incidence and prevalence rates were approximately 6 times higher among women than men (p<0.01). Incidence of pSS was statistically higher among non-Latina Asian (10.5) and non-Latina White women (6.2) compared with Latina women (3.2). Incidence was also higher among non-Latina Asian women compared with non-Latina Black women (3.3). Prevalence of pSS did not differ by race/ethnicity. Similar trends were observed when more restrictive case definitions were applied. CONCLUSION/CONCLUSIONS:Data from the MLSP revealed disparities in pSS incidence and prevalence by sex among Manhattan residents and differences in pSS incidence by race/ethnicity among women. These data also provided epidemiologic estimates for the major racial/ethnic populations in the US.

The molecular and cellular processes that lead to renal damage and to the heterogeneity of lupus nephritis (LN) are not well understood. We applied single-cell RNA sequencing (scRNA-seq) to renal biopsies from patients with LN and evaluated skin biopsies as a potential source of diagnostic and prognostic markers of renal disease. Type I interferon (IFN)-response signatures in tubular cells and keratinocytes distinguished patients with LN from healthy control subjects. Moreover, a high IFN-response signature and fibrotic signature in tubular cells were each associated with failure to respond to treatment. Analysis of tubular cells from patients with proliferative, membranous and mixed LN indicated pathways relevant to inflammation and fibrosis, which offer insight into their histologic differences. In summary, we applied scRNA-seq to LN to deconstruct its heterogeneity and identify novel targets for personalized approaches to therapy.

Background Classification and treatment decisions in lupus nephritis (LN) are largely based on renal histology. Single-cell RNA sequencing (scRNAseq) analysis may accurately differentiate types of renal involvement at the transcriptomic level, and better inform treatment decisions and prognosis. Methods scRNAseq was performed on kidney and non-lesional skin tissue collected from 20 SLE patients undergoing a clinically indicated renal biopsy. Cell types were determined using principal component analysis and t-distributed stochastic neighbor embedding (tSNE) plotting, resulting in the definitive identification of keratinocytes, tubular cells, mesangial cells, fibroblasts, endothelial cells, and leukocytes. Results LN patients expressed upregulated IFN response genes in both their tubular cells and keratinocytes. This IFN response signature in tubular cells predicted poor response to therapy 6 months post-biopsy. Tubular cells of non-responder patients also expressed upregulated extracellular matrix proteins and fibrotic markers (figure 1A and 1B). Using logistic regression analysis, a 4-gene tubular fibrosis score was created and able to predict response to treatment with an area under curve of 0.9 (figure 1C). Keratinocytes of non-responders also upregulated certain extracellular matrix genes and this response was not observed in peripheral blood mononuclear cells. Differential expression analysis between histology classes indicated an upregulation of IFN and TNF signaling in the tubular cells of patients with proliferative LN compared with membranous. Conclusions scRNAseq from 2-10 mm of renal biopsy tissue in SLE can differentiate between the different classes of LN, and provide important insights into potential pathogenic mechanisms. Further, changes in the skin of LN patients can provide a useful source of biomarkers and may reflect important information concerning concurrent kidney pathological events