Faculty Bibliography

Background/Purpose : The EULAR/ACR 2019 Classification Criteria for SLE have been validated in an international cohort of 696 SLE patients and 574 non-SLE patients with a sensitivity of 96.1% and a specificity of 93.4%. We comparatively evaluated the performance characteristics of the SLE classification systems in subsets of the validation cohort with regard to gender, race/ethnicity, and disease duration. Methods : 21 SLE expert centers from 16 countries submitted up to 100 SLE cases and 100 SLE mimicking controls each, using a standardized form without knowledge of the new criteria system to form the validation cohort. Cases and control diagnosis (SLE or not SLE) were independently verified by 3 SLE experts. The EULAR/ACR 2019 classifi-cation criteria validation cohort consisted of female (n=1,098) and male (n=172) patients; Asian (n=118), Black (n=68), Hispanic (n=124) and White (n=941) patients; and patients with an SLE duration of less than 1 year (n=34), 1-3 years (n=196), 3-5 years (n=157), and 5 or more years (n=879). Sensitivity and specificity with 95% confidence intervals (CI) were estimated for the EULAR-ACR 2019 criteria, the SLICC 2012 criteria and the ACR 1997 criteria. Results : As shown in Table 1, most of the point estimates for sensitivity and specificity in subsets lay within the 95% confidence intervals of the sensitivity and specificity of the EULAR/ACR 2019 criteria validation. In particular, sensitivity and specificity for all race/ethnicity groups were within the confidence intervals or even higher. Formally, the sensitivity was slightly lower for male patients, corresponding to a higher specificity, but the male 95% confidence intervals (0.86-0.98 for sensitivity, 0.90-0.99 for specificity) overlapped with those of the full cohort. Sensitivity appeared independent of disease duration at least from year 1 on, with all 95% confidence intervals overlapping (for the first year after diagnosis 0.52-1.00 for sensitivity, 0.69-0.97 for specificity). Conclusion : The point estimates of sensitivity and specificity suggest that the EULAR/ACR 2019 SLE classification criteria perform well in diverse race/ethnicity groups, in men and in early disease. These results now need to be independently validated in larger groups of African American/Black, Asian, and Hispanic patients, male patients and in early disease

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

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 : 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 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 : Based on encouraging bench to bedside results including experimental evidence supporting Toll-like receptor signaling in the pathogenesis of CHB, a case control study demonstrating CHB risk reduction in hydroxychoroquine (HCQ) exposed fetuses of anti-Ro positive SLE women, and a historical cohort study supporting a reduction in recurrence rate, an open label single arm Phase 2 clinical trial was initiated to evaluate whether HCQ reduces the CHB recurrence rate (pi) below the historical recurrence rate of 18%. Methods : A two-stage trial design (N=19 first stage; N=54 second stage) using Simon's optimal approach was employed to allow for early stopping due to absence of treatment efficacy. The null hypothesis, H 0 :pi <= 18%, would be rejected and HCQ considered efficacious at the end of the trial if <= 5 of 54 mothers with anti-Ro and a previous CHB child had a subsequent child with 2 nd or 3 rd degree block (primary outcome). The protocol required HCQ initiation or maintenance at 400mg by 10 wks gestation. Mothers underwent serial echocardiograms, with bloods drawn each trimester and delivery for cord blood to measure antibody and HCQ levels. Results : Sixty five mothers (all with previous CHB child and anti-Ro52 or Ro60 > 1,000 EU; 47.9% with anti-La; 71.4% White; 47.6% SLE and/or SS; 42.9% started HCQ solely for CHB prevention; 41% prior CHB child died, 3.2% had > 1 CHB child) signed consent. Ten were considered screen failures (2 miscarriages < 12 wks, 7 wherein dating of conception placed HCQ initiation at > 10 wks, 1 given dexamethasone (dex) 1mg at 10 wks) and 1 was lost to follow up before delivery leaving 54 pregnancies evaluable with serial fetal echos and birth or one yr EKG or echo results known. In Stage I, 2/19 fetuses had CHB, and the study proceeded to Stage II. By intention to treat analysis, 4/54 pregnancies resulted in CHB (7.4%; p = 0.02 for H 0 ), all at 19-20 wks. Three presented with 2 nd degree block, one reverted to NSR at birth following dex and two progressed to 3 rd degree despite dex and IVIG (one electively terminated). One presenting with 1 st degree was treated with dex prophylactically (eliminating this case from evaluating HCQ exposure alone), progressed to 2 nd but reverted to NSR at birth. At 2 yrs, the 2 in NSR had intermittent 2 nd degree on Holter monitor. In 8 mothers potentially confounding medications, IVIG and/or dex, were prescribed after enrollment for lupus flare, cardiac concerns apart from advanced block (APCs, echo brightness, 1 st degree block), and/or physician decision to consider additional prophylaxis. To evaluate HCQ alone, 9 additional mothers were enrolled, one whose fetus developed 3 rd degree block at 19 wks. Including only pregnancies exposed to HCQ alone prior to confirmed 2 nd or 3 rd degree block, 4/54 developed CHB (7.4%; p = 0.02). In total 5/63 pregnancies (7.9%) resulted in advanced block. HCQ levels in the second trimester confirmed a 98% adherence rate. Anti-Ro levels remained > 1,000 EU (considered vulnerable for CHB) throughout pregnancy. No CHB developed in any of the 7 mothers screened out because of low dose or delayed start of HCQ. Conclusion : These prospective data from a single-arm clinical trial support that HCQ significantly reduces the recurrence of CHB below the historical rate

Background/Purpose : Autoantibody production precedes SLE or SS by years, including anti-Ro. Anti-Ro + mothers of children with congenital heart block (CHB) are a unique population at risk for pathologic autoimmunity, as many are asymptomatic (Asym/UAS) and become aware of autoantibodies due to fetal disease and yet have a 10-year progression rate to SS/SLE of 20%-30%. We hypothesized that variation in the oral microbiome correlates with transition to SLE or SS and pathogenicity involves sequence homology between Ro60 and bacterial von Willebrand factor type A domain protein (vWFA).
Method(s): The oral microbiome of 25 anti-Ro + mothers of CHB children (Asym/UAS, N=9; SS/SLE, N=16) and 7 healthy controls (HC) were processed using 16S ribosomal RNA sequencing. Analysis of variance methods compared the centered log ratio transformed relative abundances for 1) HC vs. anti-Ro + mothers, and 2) assuming an ordering of severity from HC < Asym/UAS < SS/SLE. To adjust for multiple comparisons, a taxonomic stepdown method coupled with false discovery rate (FDR) was used. The Basic Local Alignment Search Tool evaluated homology of Ro60 at aa 371-381 and peptides of vWFA. Results : Sequencing 16S rRNA identified microorganisms from 2 kingdoms, 16 phyla, 25 classes, 41 orders, 70 families, 164 genera, and 166 species. The Shannon Index (H) revealed that for each taxonomic level except species, there were significant reductions in diversity in the anti-Ro + mothers relative to HC (P <= 0.05). There were global differences in the microbiota of these mothers relative to HC (perMANOVA P=0.00049). The phylum Actinobacteria was more abundant in the anti-Ro + mothers vs HC (P FDR =0.0231). Within Actinobacteria , the class Coriobacteriia and subsequent lower taxonomic levels down to Atopobium parvulum , all exhibited increases in relative abundance in the anti-Ro + mothers compared to HC. There was a significant reduction in the relative abundance as clinical severity increased within one of the most frequent phyla, Proteobacteria (P FDR =0.030; mean+/-SD; HC 0.24+/-0.07; Asym/UAS 0.19+/-0.12; SS/SLE 0.11+/-0.08). The difference in the relative abundances between Asym/UAS and SS/SLE within Proteobacteria was significant (P=0.042). Within Proteobacteria , the common class Betaproteobacteria also showed reduced relative abundance with increasing clinical severity (P FDR =0.0037; HC 0.11+/-0.04; Asym/UAS 0.072+/-0.07; SS/ SLE 0.031+/-0.04). These ordered differences were maintained down the taxonomic hierarchy to the genus ( Lautropia , P FDR =0.0072) and species within this genus ( L. mirabilis , P FDR =0.012). Next, sequences of vWFA secreted by these taxa were evaluated. For a comparison of Ro60 T cell epitope, FLLAVDVSASMNQ, the vWFA, VLVVFDNSSSMTA vWFA of A. parvulum was not a fit due to the aromatic and polar aa at positions 5 and 9, respectively. In contrast, the vWFA of L. mirabilis , LLLLLDVSGSMAG, was identical at 7 of the first 11 aa. Conclusion : These data provide evidence that the microbiome differs along a clinical spectrum of autoimmunity. In part, the data refiect a path involving depletion of L. mirabilis , which is secondary to a pathologic role of anti-Ro along with an expansion of A. parvulum , an opportunistic taxon

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 : 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 : Osteoporosis and bone fractures are a frequent cause of morbidity in systemic lupus erythematosus (SLE), and are felt to be related both to disease activity and glucocorticoid (GC) exposure. Dual energy X-ray absorptiometry (DEXA) is the standard tool to assess bone density, but it does not measure bone quality or strength and is not a robust predictor of fractures in SLE. Clinical 3T MRI scans have been shown to assess information about bone not captured by DEXA. This study aims to evaluate factors associated with bone structure measured by DEXA and MRI in an SLE cohort. Methods : DEXAs were performed on 31 women with SLE and 3T MRI of the non-dominant hip were performed on 29 of these cases. Results were associated with multiple demographic, clinical and laboratory measures. MRI parameters measured included trabecular plate width (PW), trabecular plate to rod ratio (PRR), plate volume fraction (PVF), rod volume fraction (RVF), trabecular bone thickness (Tb.Th), trabecular spacing (Tb.Sp) and trabecular network area (TNA). DEXA BMD was measured, and osteoporosis (OP) was defined as hip, spine or femoral neck Z score < -2.0 in premenopausal women, and T score < -2.5 in others, and low bone density (LBD) as Z score < -2.0 in premenopausal women and T score < -1.0 in others. Results : By DEXA, 8/31 (25.8%) had OP and 12 (38.7%) had LBD. History of lymphopenia (75.0% vs. 31.8%, p=0.049) and lower concurrent HCQ dose (340 vs. 400 mg, p=0.006) associated with DEXA OP, while older age (48.3 vs. 36.3 y, p=0.024) associated with LBD. Higher ESR was inversely correlated with favorable bone structure (PW r(22) = -.49, p=0.025, PRR rs = -.51, p=0.018, PVF rs = -.51, p=0.018, RVF rs = .51, p=0.018, Tb.Th rs = -.58, p=0.005, Tb.Sp rs = .44, p=0.046, TNA rs = -.50, p=0.022). Higher CRP was likewise inversely correlated with favorable bone structure (PW r(20) = -.61, p=0.004, PRR rs = -.57, p=0.009, PVF rs = -.57, p=0.009, RVF rs =.57, p=0.009, Tb.Th rs = -.56, p=.011, Tb.Sp rs =.67, p=0.001, TNA rs = -.64, p=0.002). A history of lupus nephritis was associated with unfavorable bone structure (PW 705.3 vs. 833.3 mum, p=0.048, PRR 6.6 vs. 8.1, p=0.024, PVF 0.83 vs. 0.89, p=0.024, RVF 0.17 vs. 0.11, p=0.024, Tb.Th 178.1 vs. 193.4 mm, p=0.012, Tb.Sp 358.6 vs. 296.5 mm, p=0.056, TNA 0.41 vs. 0.54 (1/mm), p=0.009). ESR, CRP and history of lupus nephritis were not significantly associated with DEXA hip BMD, OP or LBD. MRI parameters for favorable bone structure were inversely correlated with DEXA hip BMD (PW r(28) = -.47, p=0.011, Tb.Th rs = -.53, p=0.003) and BMI (PW r(28) = -.54, p=0.003, TbTh rs = -.72, p< 0.001, TNA rs = -.44, p=0.017). Conclusion : Higher ESR and CRP and a history of lupus nephritis associated with MRI parameters of unfavorable bone structure, but did not associate with DEXA abnormalities in SLE patients. MRI may be a more sensitive tool than DEXA to measure inflammatory effects on bone and potentially cumulative dose of steroid exposure. There were inverse correlations of MRI parameters with traditional osteoporosis risk factors and BMD measures on DEXA, and it is possible that each tool evaluates different aspects of bone health. Further evaluation of MRI screening for fracture risk in SLE and GC exposed individuals is warranted to better quantify risk and guide treatment