Faculty Bibliography

Background/Purpose: Both plasmacytoid dendritic cells (pDCs) and switched memory B cells (SMBCs) are considered to be key effector cells in systemic lupus erythematosus. It seems likely that within these classical cell lineages, additional diversity of function will exist that will contribute to disease pathogenesis. To explore this question, we performed single-cell RNA sequencing in pDCs and SMBCs from SLE patients and controls to assess gene expression patterns and cellular sub-groupings within these lineages. Methods : pDCs and SMBCs from SLE patients (n=10) and Healthy controls (n=5) were purified by magnetic separation. For deep sequencing, we used the Fluidigm C1 HT system with 800 capture site chips to capture single cells. Single cell capture was verified by direct visualization using the Array Scan system, allowing us to remove empty wells and wells with multiple cells. After quality control and adaptor trimming, the data was analyzed using SeqGeq software. pDCs and SMBCs were clustered using UMAP and pseudo-time analysis was performed using the Monocle program. Type I IFN activity in SLE plasma was measured using reporter cell assay. Results : A total of 2774 pDCs and 2578 SMBCs from SLE and healthy controls passed the quality control and were used for further analysis. In pDCs, we observed unique clusters for patients with high interferon, low interferon, and controls, indicating that the IFN response is a major determinant of overall gene expression patterns in SLE patient pDCs. IFN signature in pDCs correlated with circulating type I IFN activity in the SLE patients measured at the same time. Other genes upregulated in pDCs included the type I interferon regulator AXL and MACC1. The SMBCs were heterogeneous in patients and controls, and in contrast to the pDCs, the overall clustering pattern was independent of the IFN score. SMBC clusters were predominantly defined by genes indicating cellular activation or proliferation such as HLA-DRs and CREB1, or genes associated with nucleic acid processing such as DNASE1 and SNORD3B-1. Conclusion : We find distinct clusters of cells defined transcriptionally within the pDC and SMBC lineages, and the transcripts which define these subgroups differ between cell lineages. Type I IFN induced transcripts are important to pDC diversity, while in SMBCs transcripts related to cellular activation and nucleic acid processing are critical markers of transcriptional heterogeneity

Background/Purpose : SLE diagnostic criteria are important for reliable epidemiologic data. The prevalence of SLE in West Africa is falsely low due to barriers including limited access to both resource and labor-intensive diagnostic testing. Recently, the ACR and EULAR have proposed a weighted classification tool which is thought to improve diagnostic sensitivity and specificity compared to the established ACR and SLICC criteria. Here we aim to investigate the performance of each classification criteria in two West African cohorts--Korle bu Teaching Hospital, Accra Ghana (GH); and Lagos University Teaching Hospital, Lagos, Nigeria (N)--compared to an NYU Langone-African American (AA) cohort. Methods : We collected data on a total of 355 SLE patients: AA: n=151, GH: n=110, and N: n=94, diagnosed by expert clinicians. Clinical information including demographics, SLE criteria, SLEDAI scores, SLICC damage indexes, vital signs, and laboratory values as available was obtained at the initial patient encounter. Longitudinal data was collected over the course of at least 1 year at 6 month intervals during routine clinical visits. Where necessary, clinical charts were retrospectively reviewed, and the proportion of patients in each cohort meeting ACR, SLICC and the ACR/EULAR classification criteria was calculated. Results : The demographics per cohort were as follows: Age (in yrs): AA=43.1, GH=32.4yrs, N=35.5; percent female: AA=90, GH=100, N=97; Mean SLE disease duration (yrs): AA=14.3, GH=2.2, N=4.4. In each cohort, the percentage of patients meeting ACR, SLICC, and ACR/EULAR criteria were AA=96%, 96%, and 95%; GH=85%, 84%, 62%; N=90%, 87%, 61%. This discrepancy was largely due to missing laboratory data particularly with regard to immunologic and hematologic studies. ANA was missing in 0% of the AA cohort, 26% of the GH cohort, and 33% of the N cohort respectively. Compared to the GH and N cohorts, the reference AA cohort was more likely to meet ACR, SLICC, and ACR/EULAR criteria with likelihood ratios (LR) of GH=10.2 p< 0.001 and N=3.0 p=0.08; GH=11.5, p< 0.001 and N=6.3, p=0.01; and GH=46.1 P< 0.001 and N=44.9, p< 0.001 respectively. On average, the mean number of ACR/EULAR points by cohort was AA: 26.1+/-11.8, GH: 21.3+/-8.1, and N: 19.0+/-6.2. While the ANA entry criteria greatly diminished the new ACR/EULAR diagnostic utility in the GH and N cohorts, the weighted point system performed better than either of the ACR or SLICC criteria with 96% of the AA cohort, 92%of the GH, and 95% of the N cohort meeting criteria (LR: AA vs GH=1.9, p=0.2; AA vs N=0.23, p=0.6). Conclusion : Due to a relative lack of resources, supportive laboratory assays including an ANA may be more difficult to attain in developing nations. SLE is a clinical syndrome that may be efficiently diagnosed using the new weighted ACR/EULAR criteria. The entry criteria of ANA 1:80 greatly diminished the diagnostic utility of this classification system in the Ghanaian and Nigerian cohorts compared to the African American cohort. Clinical trials should consider offering wide ANA testing to cohorts in the developing world

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 : In SLE Apolipoprotein L1 (APOL1) risk variants associate with cardiovascular and kidney damage. APOL1 is both a secreted and tissue intrinsic protein; the latter role mediates organ injury. Expression is driven by inflammatory stimuli which initially promotes survival through autophagy. At higher expression, APOL1 contributes to cell death partially by compromising mitochondria. The RV protein structure favors toxicity at lower thresholds. Macrophages express APOL1 and use metabolic plasticity to perform effector functions. We hypothesized that in activated macrophages, APOL1 expression impairs mitochondrial Methods : Healthy controls were genotyped for APOL1 reference allele (G0) risk variants (RV) (n=15; G0/G0=8, RV/ G0=4, RV/RV=3). Monocytes were isolated from PBMCs using a Miltenyi Biotec Pan Monocyte Isolation kit and differentiated into macrophages using GM-CSF. Cells were treated with SLE-relevant agonists ssRNA hY3 or IFNgamma; and APOL1 expression was observed by qPCR. As in-vivo correlates, APOL1 expression relative to IFN response gene, Siglec 1, in SLE patient monocytes (n=17); and expression in coronary artery tissue macrophages with (n=3) or without (n=3) atherosclerotic plaque were assessed through RNA seq data and immunohistochemistry respectively. To test mitochondrial respiration, cultured HC macrophages were left untreated or IFNgamma treated, and bioenergetics were measured by the Seahorse assay. Confirmatory fluorescent microscopy was done by staining cells with Mitoprobe (polarized mitochondria) and Mitotracker (all mitochondria) and the ratio of Mitoprobe to Mitotracker staining was quantified using ImageJ software. Results : Across the genotypes,hY3 and IFNgamma increased APOL1 mRNA expression 29.1+/-18.4 and 31.6+/-14.9 fold compared to untreated (p< 0.001 in each). In SLE monocytes, APOL1 significantly correlated with Siglec1 expression (R=0.64; P=0.005). APOL1 stained 4% of non-plaque containing and 18% of plaque-containing coronary arteries (p=0.05). APOL1 was apparent in multiple cell types including invading tissue macrophages (fig1). On the seahorse assay, there were genotype-dependent differences in Basal OCR (BO pmol/min), Spare Capacity (SC pmol/min), and total ATP production (ATP pmol/min) (G0/G0: BO: 99.4+/-11.3, SC:150.9+/-16.6, ATP: 88.1+/-9.5; RV/G0: BO: 46.1+/-4.5, SC: 52.1+/-8.8, ATP: 40.7+/-3.4; RV/RV: BO: 46+/-17.4, SC: 14.9+/-11.6, ATP: 36.7+/-9.5 each p< 0.001). Across genotype, these values fell with IFNgamma (G0/G0: BO: 73.9+/-6, SC: 129.4+/-17.3, ATP: 67.6+/-5.4; RV/G0: BO: 46+/-5.1, SC: 27.9+/-8.1, ATP: 39.5+/-3.9; RV/RV: BO: 42.1+/-8.6, SC: 9.5+/-8.3, ATP: 35.8+/-6.9) (fig2). Fluorescent microscopy confirmed findings with the mean respective MitoProbe/Mitotracker ratios in G0/G0, RV/G0, and RV/RV macrophages at rest 1.5+/-0.5, 0.86+/-0.3, and 0.89+/-0.3 and with IFNgamma 1.3+/-0.4, 0.74+/-0.3, and 0.6+/-0.2 (fig3). Conclusion : Inflammation both in vitro and in vivo due to hY3, IFNgamma, and ischemia increase macrophage APOL1 expression across genotypes. In RV carrying macrophages, this results in diminished mitochondrial energy production-a potential underpin of variant-mediated toxicity. (Figure Presented)

Background/Purpose : Subjects with Systemic Lupus Erythematosus (SLE) are at elevated risk for end-organ damage. Lupus nephritis continues to be the complication with the highest standardized mortality ratio in SLE, yet clinicians have few tools to identify patients at risk. A complete blood count is a readily available test but little is known about its usefulness in tracking lupus nephritis and activity. In recent years, neutrophil/lymphocyte (NLR), monocyte/ lymphocyte (MLR), and platelet/lymphocyte (PLR) ratios have emerged as markers of systemic inflammation. This study sought to evaluate the association between NLR, MLR, and PLR and its individual components and lupus disease activity and lupus nephritis. Methods : 25 matched healthy controls and 85 patients fulfilling ACR or SLICC criteria for SLE were enrolled in the study and demographics, disease activity, as measured by the Hybrid SLEDAI, medications, and clinical manifestations were recorded. 20 lupus patients included in the study had active lupus nephritis, as defined by proteinuria greater than 500 mg/g creatinine. A complete blood cell count was assessed on all patients and healthy controls. Patients with platelet counts less than 100K or on nonsteroidal anti-inflammatory drugs were excluded from the study. Results : Overall, SLE patients had a significantly higher PLR (p=0.0001), NLR (p=0.0003), and MLR (p=0.0035) compared to healthy controls. Lymphocyte counts alone negatively associated with SLEDAI (beta=-0.31, p=0.006) but monocyte, neutrophil, or platelet counts did not show a significant association with SLEDAI. All three ratios showed a significant positive association with SLEDAI in linear regression analysis with PLR being a better predictor than lymphocyte counts alone (beta=0.38, p< 0.0001). The associations between PLR or MLR but not NLR and SLEDAI remained significant in a multivariate linear regression model adjusting for age, race, sex, ethnicity, and medications. Specifically, the dose of glucocorticoids did not explain the clinical associations with these cellular ratios. When evaluating active lupus nephritis, PLR (p=0.118) was not significant in a logistic regression and NLR (p=0.007) and MLR (p=0.007) performed equally well. These associations between NLR or MLR and active lupus nephritis persisted in a multivariate logistic regression model adjusting for age, race, sex, ethnicity, and medications. Interestingly, lymphocyte, monocyte, neutrophil, or platelet counts alone did not associate with active lupus nephritis. Conclusion : These data suggest that by using standard clinical labs to calculate NLR, MLR, and PLR clinicians may be able to better characterize lupus activity and current lupus nephritis

Background/Purpose : Compared to Caucasian, African-American ethnicity is associated with a higher risk of developing systemic lupus erythematosus, lupus nephritis, high-risk histological features, resistance to treatment, and mortality. In phase 1 of the Accelerating Medicines Partnership (AMP), we used single-cell genomics to identify ethnicity associated features. Methods : Single cell RNA sequencing was performed on renal biopsies obtained for clinical purpose; one pipeline applying CEL-Seq2 in a leukocyte enriched sample and the other Fluidigm C1 800 in an agnostic approach to dissociated renal cells. Differential abundance of cell populations was determined using a logistic mixed model. Then, the differential expression profile was determined for each cell cluster and interpreted using pathway enrichment analysis. Results : Samples from 19 African-American and 20 Caucasian patients were obtained. We identified 30 cell clusters. Type I and II interferon inducible genes were upregulated in most cell populations. A cluster of T cells with exceptionally high interferon signature was found to be increased in African-Americans (OR 4.8). Macrophages and DC4-like dendritic cells were instead less abundant (OR 0.3). In African-Americans, type I and II interferon response pathways were enriched in several cell types including T cells, B cells, plasma cells, and activated monocytes. The majority of the differentially expressed genes was specifically inducible by type II interferon. In addition, while there was no local expression of type I interferons, interferon gamma was abundantly expressed by infiltrating NK and CD8 T cells. Conclusion : African-American patients with lupus nephritis have a stronger interferon response pathway activation, especially type II. Our findings suggest an intrinsic biological factor underlying the outcome gap and highlight the role of interferon gamma in lupus nephritis, implicating this pathway as a potential therapeutic target in SLE. Further work in Phase 2 of AMP is being pursued to validate and extend these findings

Background/Purpose : The impact of glucocorticoid (GC) use on major organ damage in SLE patients has not been formally studied by amalgamating the relevant data published in the literature over the past 40 years. We aimed to study the association between GC use and the occurrence of major organ damage in SLE patients by performing meta-analyses of observational studies published between 1970 and December 2018. Methods : Literature search on PubMed (from 1966 to December 2018) for prevalence and longitudinal studies which reported GC exposure (proportion of GC users in the cohort [%GC use] and/or GC use in defined doses) and the occurrence (prevalence/incidence) of major organ damage in SLE patients using the keywords cataract, cerebrovascular (CVA), stroke, cardiovascular (CVS), angina, myocardial infarction (MI), coronary artery bypass, osteoporosis, avascular necrosis (AVN) and osteonecrosis in respective combinations with lupus was conducted. Studies with sample size < 50 and observation duration < 12 months were excluded. The logit of the proportion of patients with disease damage was modelled as a random effect in the meta-analysis, which was employed to study the association between the proportion of patients with organ damage and variables of GC use (mean daily [mg/day] and cumulative [gm] prednisone [PDN] doses and %GC use). A 2-stage estimation of the random-effects logistic regression models was used with restricted maximum likelihood estimation. Univariate associations between organ damage and moderators were examined for statistical significance, and variables related to GC use were adjusted for SLE disease duration in multivariate models if their univariate P values were < 0.2. Results : Out of 8,882 publications screened, 212 articles involving 205,619 SLE patients were eligible for the metaanalyses (Figure 1), of which 97 were prevalence and 115 were longitudinal studies. Univariate analyses of prevalence studies revealed that mean daily PDN dose (odds ratio [OR]=1.10, p=0.007) and lower proportion of female in the cohort (OR=0.002, p=0.002) were associated with the prevalence of overall CVS events. Mean daily PDN dose (OR=1.52, p< 0.001) and %GC use (OR=2,255.2, p< 0.001) were associated with the prevalence of AVN. A significant association between cumulative PDN dose and prevalence of CVA was found after multivariate adjustment for SLE disease duration (OR=1.07, p=0.017). In longitudinal studies, a significant association was identified between cumulative PDN dose and incidence of cataracts after adjustment for SLE disease duration (OR=1.04, p=0.013). While the incidence of MI in SLE patients has dropped over the past 40 years (OR=0.94, p=0.002), it was associated with % GC use after adjustment for SLE disease duration (OR=8.18, p=0.012). Interestingly, significant univariate associations were found between antimalarial use and lower prevalence of MI (OR=0.05, p=0.002) and lower incidence of CVA (OR=0.20, p=0.032). Conclusion : Independent of SLE disease duration, cumulative PDN dose was associated with higher prevalence of CVA and incidence of cataracts, and higher incidence of MI was associated with overall GC use

Background/Purpose : Different autoimmune diseases can co-exist in an individual and share similar genetic associations, autoimmune signaling pathways, and clinical manifestations. However, autoimmune diseases present varied cellular heterogeneities and may be distinguished by their primary target organs or tissues. The immune mechanisms that are shared between similar autoimmune diseases remain poorly understood due to limited access to affected human tissues and computational scalability. Recently, high resolution single-cell RNA-seq profiles have provided the opportunity for study of the contribution of diverse cell populations to disease pathogenesis. This advance has enabled unbiased comparison of disease across affected tissues with the goal of understanding autoimmune similarities. Methods : We have analyzed and integrated ~80,000 cells from 176 donors from publicly available single-cell RNAseq datasets generated from rheumatoid arthritis (RA) and osteoarthritis (OA) synovium 1 , pulmonary fibrosis and healthy lung, systemic lupus erythematosus (SLE) and healthy kidney and skin 2,3 , inflammatory bowel disease (IBD) and healthy colon, and Crohn intestinal mucosal biopsies. We use a robust integrative strategy 4 to cluster and project all the cells into two dimensional-space by correcting technical batch effect across tissue, donor, and single-cell platform (10X Genomics, Celseq2, Dropseq, Fluidigm, and Smartseq). Results : We identify 21 diverse cell type populations across multiple tissue sources (Figure 1A). In the myeloid cell population, we observed four distinct subsets including VSIG4+ M2-like macrophages, S100A8+ macrophages, SPP1+ MMP9+ inflammatory macrophages, and dendritic cells (DC). The SPP1+ MMP9+ inflammatory macrophage population with high expression of matrix metalloproteinases genes is co-localized between macrophages in RA synovium, SLE kidney, and alveolar from pulmonary fibrosis lung, and is absent in healthy lung tissue (Figure 1B). For CD8 T cells and nature killer cells, we identified a shared transcriptional gradient of granzyme-expressing cytotoxic effectors between RA synovium, SLE kidney, and fibrotic lung. Interestingly, the GzmK+ CD8 T cell population is absent in the healthy lung (Figure 1C). The patterns of cytotoxic effector states may suggest similarities between theprimary sites of inflamed RA and inflamed fibrotic lung, including potential common active pathways. In the stromal cell compartment, we observed distinct populations across different diseases and tissues, including fibroblasts, pericytes, mesangial, and tubular cells. Conclusion : We demonstrate that integrative analyses between disease tissues by single-cell transcriptomics is capable to discovering shared and unique disease-specific gene expression modules and cell states, and may help predict potential therapeutic targets for inflammatory and fibrotic diseases

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

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