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Rheumatoid arthritis and Type I Diabetes are autoimmune disease causing a disabling inflammatory polyarthritis that is the result of complex genetic and environmental factors. Genetic studies have now defined >100 loci for these diseases outside of the major histocompatability complex. Only a handful of these loci implicate coding variation. Because of the difficulty in characterizing non-coding variation, investigators have only in rare instances mapped RA loci to causal alleles. This is a critical bottleneck in linking genetic risk factors to underlying disease mechanisms. If we could define causal alleles it might become possible to identify disease mechanisms, and then we might be better able to target disease therapeutically and to define biomarkers that track with disease activity. Here we first demonstrate that rheumatoid arthritis and type I diabetes risk alleles overlap gene regulatory regions specifically in CD4+ effector and 885 regulatory T cells. We then go on to lay out a fine-mapping strategy based on these results to identify causal variation within 55 Autoimmune disease loci.Disclosure of InterestNone declared

In the coming years the possibility of having access to a patient's whole genome in the context of clinical care is becoming a real possibility. Recent discoveries in human genetics have begun to suggest that this data might have the potential to influence clinical management in the appropriate setting. Here we will discuss how personal genetic data might play an important role in the care of early rheumatic disease. We will also discuss how human genetic findings might influence the production of novel predictive biomarkers that might play an important role in the care of rheumatic diseases. Disclosure of Interest None declared DOI 10.1136/annrheumdis-2014-eular.6305

ObjectivesJuvenile idiopathic arthritis (JIA) is a heterogeneous group of diseases, comprising seven categories. Genetic data could potentially be used to help redefine JIA categories and improve the current classification system. The human leucocyte antigen (HLA) region is strongly associated with JIA. Fine-mapping of the region was performed to look for similarities and differences in HLA associations between the JIA categories and define correspondences with adult inflammatory arthritides.MethodsDense genotype data from the HLA region, from the Immunochip array for 5043 JIA cases and 14 390 controls, were used to impute single-nucleotide polymorphisms, HLA classical alleles and amino acids. Bivariate analysis was performed to investigate genetic correlation between the JIA categories. Conditional analysis was used to identify additional effects within the region. Comparison of the findings with those in adult inflammatory arthritic diseases was performed.ResultsWe identified category-specific associations and have demonstrated for the first time that rheumatoid factor (RF)-negative polyarticular JIA and oligoarticular JIA are genetically similar in their HLA associations. We also observe that each JIA category potentially has an adult counterpart. The RF-positive polyarthritis association at HLA-DRB1 amino acid at position 13 mirrors the association in adult seropositive rheumatoid arthritis (RA). Interestingly, the combined oligoarthritis and RF-negative polyarthritis dataset shares the same association with adult seronegative RA.ConclusionsThe findings suggest the value of using genetic data in helping to classify the categories of this heterogeneous disease. Mapping JIA categories to adult counterparts could enable shared knowledge of disease pathogenesis and aetiology and facilitate transition from paediatric to adult services.

BackgroundGuselkumab (GUS) is a fully human, selective interleukin (IL)-23p19 subunit inhibitor. In the phase 3 DISCOVER-2 study of biologic-naïve patients (pts) with active psoriatic arthritis (PsA), GUS significantly reduced the signs and symptoms of disease and radiographic progression vs placebo (PBO),[1] with durable response across multiple disease domains through 2 years.[2] GUS also significantly decreased serum levels of collagen turnover markers,[3] which are elevated in PsA pts vs healthy controls, consistent with diminished progression of structural damage. Further, changes in these and other serum cytokine levels through Week 24 (W24) of GUS treatment are associated with clinical response through 2 years.[4]ObjectivesFurther assess effects of GUS on serum cytokine and collagen turnover biomarkers from W24 through W100 (2 years) and explore associations between biomarker levels and longer-term clinical response (W100).MethodsIn DISCOVER-2, biologic-naïve adults with active PsA (swollen joint count ≥5, tender joint count ≥5, C-reactive protein [CRP] ≥0.6 mg/dL) were randomized 1:1:1 to GUS 100 mg every 4 weeks (Q4W); GUS 100 mg at W0, W4 and then Q8W; or PBO with crossover to GUS Q4W at W24. Blood samples from consenting GUS-treated pts (Q4W and Q8W pooled) were assessed for serum cytokine levels (N=100), including Th17-related effector molecules (IL-17A, IL-17F, IL-22), β-defensin 2 (BD-2), acute phase proteins (CRP, serum amyloid A [SAA], IL-6), and serum collagen turnover biomarkers (N=174; C1M, C3M, C4M, C6M). Using Spearman linear regression and general linear models, pooled changes from baseline (BL) in biomarkers during GUS treatment, correlations between changes in biomarker levels and reductions from BL at three time points (W24, W52, W100) in disease activity (measured by changes in Disease Activity in Psoriatic Arthritis [DAPSA] score, Psoriatic Arthritis Disease Activity Score [PASDAS], Psoriasis Area and Severity Index [PASI] score) were assessed. Associations between biomarker changes and achievement of American College of Rheumatology (ACR)50 response at W100 were also assessed.ResultsContinued treatment with GUS led to significant and sustained reductions in serum cytokines from W24 through W100. Reductions in CRP and IL-6 were associated with changes in DAPSA score, with a similar trend observed for PASDAS. Reductions in BD-2, IL-17A, IL-17F and IL-22 from BL correlated with improvements in the PASI score, and reductions in collagen turnover biomarkers correlated with changes in the PASDAS (Table 1). Continued disease improvement with long-term GUS treatment, assessed clinically using ACR50 response, was supported by the further reductions in CRP, SAA, IL-6 and collagen turnover biomarkers in ACR50 responders at W100 who were ACR50 nonresponders at W24 (Figure 1). Among ACR50 responders at W24, mean reductions in CRP, SAA and IL-6 were sustained through W100.ConclusionThese results provide molecular evidence that sustained reductions in serum acute phase proteins and collagen turnover biomarkers may contribute to the continuous, durable improvements in joint symptoms and that reductions in Th17-related effector molecules contribute to improvements in skin symptoms seen in PsA pts receiving GUS.References[1]Mease P, et al. Lancet. 2020;395:1126-36.[2]McInnes IB, et al. Arthritis Rheumatol. 2022;74:475-85.[3]Schett G, et al. Rheumatol Ther. 2022;9:1017-30.[4]Siebert S, et al. Arthritis Rheumatol. 2022:74(suppl 9).Table 1.Correlation of Change in Serum Biomarker Levels With Change in PsA Disease Activity From BL Through 24, 52 or 100 Weeks of GUS TreatmentDAPSAPASDASPASIBD-20.080.160.58aCRP0.30a0.240.08IL-17A0.080.210.46aIL-17F0.000.110.41aIL-220.170.220.34aIL-60.26a0.17-0.03SAA0.200.200.14TNF-α0.160.190.14C1M0.27a0.27a0.07C3M0.240.27a0.06C4M0.230.27a0.06C6M0.30a0.31a0.04aSignificant correlation between biomarker expression and disease activity;r>0.25 and P<0.05.Acknowledgements:NIL.Disclosure of InterestsStefan Siebert Speakers bureau: AbbVie, Amgen, Eli Lilly, GlaxoSmithKline, Janssen, and UCB, Grant/research support from: Amgen, Boehringer Ingelheim, Bristol Myers Squibb, Eli Lilly, GlaxoSmithKline, Janssen, and UCB, Georg Schett Speakers bureau: Amgen, AbbVie, Bristol Myers Squibb, Eli Lilly, Gilead, Janssen, Novartis and UCB, Siba P Raychaudhuri Speakers bureau: AbbVie, Amgen, Celgene, Eli Lilly, Janssen, Novartis, Pfizer, SUN Pharma, and UCB, Consultant of: AbbVie, Amgen, Celgene, Eli Lilly, Janssen, Novartis, Pfizer, SUN Pharma, and UCB, Grant/research support from: AbbVie, Amgen, Celgene, Eli Lilly, Janssen, Novartis, Pfizer, SUN Pharma, and UCB, Monica Guma Consultant of: Novartis, Pfizer, Gilead, Genentech, and Sonoma Biotherapeutics, Grant/research support from: Novartis, Pfizer, Gilead, Genentech, and Sonoma Biotherapeutics, Warner Chen Employee of: Janssen Research & Development, LLC, Sheng Gao Employee of: Janssen Research & Development, LLC, Soumya D Chakravarty Shareholder of: Johnson & Johnson, Employee of: Janssen Scientific Affairs, LLC, May Shawi Shareholder of: Johnson & Johnson, Employee of: Immunology Global Medical Affairs, Janssen Pharmaceutical Companies of Johnson & Johnson, Proton Rahman Consultant of: AbbVie, Amgen, Bristol Myers Squibb, Celgene, Eli Lilly, Janssen, Merck, Novartis, Pfizer, and UCB, Grant/research support from: Janssen and Novartis.

The oxysterol-binding-protein (OSBP)-related proteins (ORPs) are conserved from yeast to humans 1 , 2 , and are implicated in the regulation of sterol homeostasis 3 , 4 and in signal transduction pathways 5 . Here we report the structure of the full-length yeast ORP Osh4 (also known as Kes1) at 1.5–1.9 Å resolution in complexes with ergosterol, cholesterol, and 7-, 20- and 25-hydroxycholesterol. We find that a single sterol molecule binds within a hydrophobic tunnel in a manner consistent with a transport function for ORPs. The entrance is blocked by a flexible amino-terminal lid and surrounded by basic residues that are critical for Osh4 function. The structure of the open state of a lid-truncated form of Osh4 was determined at 2.5 Å resolution. Structural analysis and limited proteolysis show that sterol binding closes the lid and stabilizes a conformation favouring transport across aqueous barriers and signal transmission. The structure of Osh4 in the absence of ligand exposes potential phospholipid-binding sites that are positioned for membrane docking and sterol exchange. On the basis of these observations, we propose a model in which sterol and membrane binding promote reciprocal conformational changes that facilitate a sterol transfer and signalling cycle.

Background:The exact origin and precursor differentiation route of tissue macrophages remains controversial. Deep characterisation of myeloid cell subsets by single cell RNA sequencing (scRNA-seq) across healthy and inflamed tissues in rheumatoid arthritis (RA) has led to the identification of new pathogenic cell states and subsets in five recent large-scale studies ([1-5] including from the Accelerating Medicines Partnership (AMP) RA Consortium [4,5]). However, subset overlap across studies and compartments (blood versus synovial tissue) has not yet been systematically investigated.Objectives:To map monocyte subsets and states across studies and compartments to identify blood monocyte precursors of inflammatory synovial macrophage subsets observed in RA.Methods:First, peripheral blood mononuclear cells (PBMCs) from healthy volunteers and RA patients with clinically well-controlled disease (quiescent PBMCs) were enriched for monocytes by negative selection and subjected to scRNA-seq (10X Genomics). Clustering of 20,746 cells was performed in Seurat (generation of a Uniform Manifold Approximation and Projection (UMAP) template). Second, published myeloid cell subsets (comprising a total number of 110,351 myeloid cells from 5 scRNA-seq studies [1-5]) were mapped onto this template based on the similarity of their expression scores. Hierarchical clustering was applied to merge similar clusters to create a consensus map. Third, random forests were used as a novel method of merging over-clustered data to identify novel myeloid cell states and generate a final taxonomy of monocyte states in human healthy blood (Figure 1, left panel, with CD14high classical monocytes in dark blue at the bottom, CD16+ non-classical monocytes in magenta at the top, intermediate monocytes in the middle). Finally, to provide experimental validation at the protein level, PBMCs from 19 RA patients with uncontrolled inflammation (DAS > 5.1 and treatment failure with conventional Disease Modifying Anti-Rheumatic Drugs) were deeply immunophenotyped with a 23-marker myeloid panel by mass cytometry (CyTOF). Inflammatory cell states with increased abundance in RA were identified with Co-varying Neighborhood Analysis (CNA) [6]. The CyTOF dataset was mapped back onto the scRNA-seq template (Figure 1 middle panel) using bridge integration implemented in Seurat v5, using the COvid-19 Multi-omics Blood ATlas (COMBAT) Consortium CITE-seq dataset [7] as a bridge.Results:We generated an exhaustive reference atlas comprising a total of 11 monocyte states across anatomical compartments relevant for RA (Figure 1, left panel). For example, we show that the CD11b+ CD64+ FOLR2+ ID2+ cluster in [3], the IL1B+ cluster in [4] and cluster M8 in [5] represent the same inflammatory synovial macrophage subset (first of the 4 examples featured in Table 1) and are transcriptionally similar to an IL1B+ monocyte subset present in quiescent peripheral blood. Next, we show that 4 quiescent monocyte states present in the peripheral blood of both patients and healthy individuals (IL1B+, CXCL10+, C1Q+, and IFN-activated, all originating from CD14+ CD16+ intermediate monocytes (Figure 1, left panel) expand in the blood of patients with uncontrolled RA (Figure 1, middle panel). The statistically significant cell clusters (FDR<0.05) are colour-coded in dark red on Figure 1, right panel.Conclusion:We define a new monocyte cell taxonomy relevant for RA comprising a total number of 11 continuous cell states dynamically transitioning into each other across anatomical compartments. We show that 4 quiescent peripheral blood intermediate monocyte states, sharing a transcriptional signature with inflammatory synovial macrophages, expand in uncontrolled RA and therefore likely represent blood precursors of pathogenic tissue macrophages.REFERENCES:[1] Villani AC, Science, 2017.[2] Kuo D, Sci Transl Med, 2019.[3] Alivernini S, Nat Med, 2020.[4] Zhang F, Nat Immunol, 2019.[5] Zhang F, Nature, 2023.[6] Reshef YA, Nat Biotechnol, 2022.[7] COMBAT Consortium, Cell, 2022.Table 1.Figure 1.Acknowledgements:BRAGGSS Collaborators.Disclosure of Interests:None declared.

In addition to its effect on the central nervous system, nerve growth factor (NGF) appears to play a key role in the initiation and maintenance of inflammation in many organs. NGF degranulates mast cells, recruits inflammatory cellular infiltrates and activates T cells. Extravascular migration of leukocytes is initially controlled by the interaction of cell surface adhesion molecules of leukocytes and endothelial cells. A marked upregulation of NGF in keratinocytes is also observed in conditions characterized by angiogenesis such as psoriasis and wound healing. In this study we investigated the role of NGF in inflammation by studying its effects on endothelial cell proliferation and intracellular adhesion molecule expression by endothelial cells. The effect of NGF on human dermal microvascular endothelial cell (HDMEC) proliferation was measured using the hexosaminidase assay. ICAM-1 expression on HDMEC was measured by ELISA. The function of ICAM-1 was assessed by adherence of peripheral blood mononuclear cells (PBMC) to HDMEC using 51Cr-labeled PBMC. There was a significant increase in proliferation of HDMEC stimulated with NGF as compared to unstimulated HDMEC (P < 0.001). NGF-neutralizing antibody decreased the mitogenic effect of NGF significantly (P < 0.05). NGF also increased ICAM expression on HDMEC as compared to unstimulated HDMEC (P < 0.05). NGF-neutralizing antibody decreased ICAM expression on NGF-stimulated HDMEC (P < 0.05). The percentage of PBMC adherence was higher in NGF-stimulated HDMEC (P < 0.001). Anti-ICAM antibody decreased PBMC adherence. In the study reported here, the role of NGF in two important aspects of inflammation, i.e. angiogenesis and inflammatory cell recruitment at the site of inflammation, was investigated.

Background:COPA syndrome is an autosomal dominant, severe, rare, monogenic autoimmune disorder, often affecting the lungs and joints, caused by loss-of-function mutations of COPA which are located in a specific locus (i.e., the COPA mutation hotspot, 7th to 10th exons). It is associated with autoimmune features and upregulation of both the type-1 interferon (IFN) pathway and T helper-17 cells. Clinical manifestations usually start during childhood, but late-onset symptoms have been described.Objectives:We aimed to identify additional novel non-synonymous variants (NSV) in COPA and to describe their associated phenotypes in two distinct adult biobanks.Methods:All individuals from two large institutional biobanks (Massachusetts General Brigham, [MGB] and Mayo Clinic Biobank) with available whole-exome sequencing (WES) data were included in this study. All NSV in the 7th, 8th, 9th, and 10th exons of COPA were identified and annotated according to allele frequency reported in GnomAD and functional predictive tools (SIFT, PLOYPHEN-2 and CADD score). Individuals with COPA NSV were matched to controls without COPA NSV from the same biobank by year of birth, sex, and race and ethnicity. Medical record review was performed in cases and controls to collect personal and familial medical history, results of autoantibodies, and chest computed tomography (CT) imaging results obtained through routine clinical care. Associations with the presence of COPA NSV were tested using logistic regression for categorical outcomes or an univariable linear regression for continuous outcomes. Functional impact of ten novel COPA NSV was tested by measuring type-1 IFN activity in cells transfected with mutant plasmids.Results:Among the 106,365 individuals with available WES data, 33 unique NSV were identified among a total of 85 individuals (0.08%); 59 were women (69.4%) and mean age at medical record review was 60.6 years (SD 18.5). Two individuals carried a NSV previously implicated in COPA syndrome (p.R281Q and p.R233H) but none of them had been clinically diagnosed with COPA syndrome. All other identified SNV were rare: 14 recorded rare variants (all with a frequency <0.0001%) and 19 have never been previously described. NSV were predicted as deleterious by both SIFT and POLYPHEN-2 for 16 variants (48%). A history of autoimmune or inflammatory disease was reported for 38/85 carriers (45%) including 12 with inflammatory arthritis (14%), Table 1. Interstitial lung disease was observed in 11/85 patients (13%). Median age at autoimmune/inflammatory disease onset was 50.3 years IQR [39.5 – 63.5] with only 2 patients having childhood onset. Antinuclear antibodies, anti-CCP, and rheumatoid factor were positive for 15/27, 3/13, and 5/22 patients, respectively. A family history of autoimmune/inflammatory disease was reported in 17/68 patients (25%). When compared to matched controls, having a COPA NSV was significantly associated with increased risk for any autoimmune or inflammatory disease (OR = 1.73, 95%CI 1.05 to 2.87, p=0.03), any inflammatory arthritis (OR = 2.83, 95%CI 1.24 to 6.40, p=0.01), any ILD (OR = 6.17, 95%CI 2.27 to 18.4, p<0.001), and having a family history of an autoimmune or an inflammatory disease (OR = 2.81, 95%CI 1.41 to 5.52, p=0.003), Table 1. Functional impact was confirmed for 2/10 of the novel COPA NSV, with a lower type-1 IFN activity compared to two COPA NSV previously as pathogenic mutations, Figure 1.Conclusion:We identified 31 novel NSV beyond the known causal mutations for COPA syndrome and described associations with autoimmune and/or inflammatory diseases, including ILD, most of which were adult-onset. In addition to the COPA syndrome, COPA variants could contribute to the genetic architecture of a spectrum of unrecognized adult-onset inflammatory and autoimmune diseases including ILD.REFERENCES:NIL.Acknowledgements:Société Française de Rhumatologie, NIH, NIAMS.Disclosure of Interests:None declared.

Background:RA-associated interstitial lung disease (ILD) and idiopathic pulmonary fibrosis (IPF) share the MUC5B rs35705950 genetic risk factor and a predilection for the usual interstitial pneumonia (UIP) pattern. The role of telomere-related genes (TRGs) in the RA-ILD genetic background is unclear. Previous work found an excess of TRG rare exonic variants in RA-ILD compared to healthy controls. However, lack of RA controls without ILD precluded an investigation of whether the enrichment for rare variants in TRGs was associated with the RA or ILD pattern.Objectives:To investigate the contribution of TRG rare variants to ILD vs. no ILD in patients with RA, and to IPF vs. healthy controls.Methods:For the RA analyses, this genetic case-control association study consisted of a derivation (France) and a replication (US) sample that included cases with RA-ILD and controls with RA without ILD (RA-noILD). For the IPF analyses, cases with IPF were compared to healthy controls without IPF. Whole exome or genome sequencing was performed in all participants. ILD status and pattern (UIP or non-UIP) was determined by review of clinically-indicated high-resolution computed tomography (HRCT) chest imaging. Exonic variants from 14 candidate TRGs previously associated with IPF or linked to familial pulmonary fibrosis (TERT, TERC, PARN, RTEL1, CTC1, TINF2, ACD, POT1, NAF1, ZCCHC8, NHP2, NOP10, WRAP53, and DKC1) were identified and annotated for their frequency by gnomAD database and their functional impact using predictive tools (SIFT, POLYPHEN-2, and CADD score). Telomere length (TL) was measured in RA cases and controls from the derivation sample, in IPF cases and in non-IPF healthy controls. TRG rare variants enrichment in cases and controls was compared using the classical burden test adjusted for sex, age at RA, RA duration, MUC5B rs35705950 genotype and principal component of ancestry. Derivation and replication results were combined and meta-analyzed. We performed sub-group analyses restricted to cases with TL < 10th percentile.Results:In the RA analyses, the derivation sample included 157 RA-ILD cases and 231 RA-noILD controls, and the replication sample included 85 RA-ILD cases and 305 RA-noILD controls; Table 1. In the derivation sample, we identified 19 distinct rare TRG variants carried by 13/157 RA-ILD cases and 8/231 RA-noILD controls (8.3% vs. 3.5%, OR 2.83, 95% CI 0.96-8.58; p=0.06); Table 2. In the replication sample, an enrichment of TRG rare variants was also observed in RA-ILD cases (9/85 [10.6%] compared to 18/305 [5.9%] in RA-noILD controls, Burden test p=0.20), reaching statistical significance in the meta-analysis analysis (OR 2.12, 95% CI 1.07-4.21, p=0.03). When restricting the analyses to RA-UIP cases, we found a greater enrichment of TRG rare variants in both derivation and replication samples (10.5% and 13.8%, respectively) leading to a significant association with RA-UIP (OR 3.17, 95% CI 1.37-7.32, p=0.007), whereas no association was detected with non-UIP RA-ILD (p=0.33).Similar to RA-ILD and RA-UIP, the analysis of 1277 IPF cases and 1874 non-IPF healthy controls, found a significant excess of rare variants in TRG comparing patients with IPF to healthy controls: 2.0% vs. 1.5%, OR 2.31, 95% CI 1.24-4.37, p=0.013. No interaction between TRG rare variants and smoking status nor MUC5B rs35705950 was detected.When restricting to patients with RA-ILD having a TL<10th percentile, we observed a significant enrichment of TRG rare variants with an increased risk: 10.0% vs. 3.5%, OR 5.93, 95% CI 1.28-26.30, p=0.04. Similar to that observed in RA-ILD, when restricting the analysis to the IPF cases having a TL<10th percentile, a significant excess of TRG rare variants was detected (5.5% vs. 1.5%, OR 6.09 95% CI 2.58-13.50, p=0.0002).Conclusion:In aggregate, our findings provide proof of a contribution of TRGs to ILD risk in RA. Like MUC5B rs35705950, the excess of TRG rare variants support the paradigm of a shared genetic background between RA-ILD and IPF. Similar to IPF, our results indicates that the short TL observed in RA-ILD can be partially attributed to TRG rare variants.REFERENCES:NIL.REFERENCES: NIL. Acknowledgements:Société Française de Rhumatologie.Disclosure of Interests:None declared.

BackgroundA decline of urine protein-to-creatinine ratio (UPCR) to < 0.5 is associated with better long-term preservation of kidney function in lupus nephritis (LN). UPCR < 0.5 defines complete response in guidelines and clinical trials when achieved after 1 or 2 years. Biomarkers of early response are needed to guide early treatment changes. We studied longitudinal urine proteomic profiles in LN to identify early predictors of proteinuric response.ObjectivesIdentify early predictors of proteinuric response in LN using longitudinal urine proteomic profiles.MethodsWe quantified 1200 biomarkers (Kiloplex, RayBiotech) in urine samples collected on the day of (73%) or within 3 weeks (27%) of kidney biopsy and week 12, 24, or 52 in LN patients (ISN class III, IV, V, or mixed) with proteinuria > 1 g/d. Response was defined at one year from renal biopsy: Complete = UPCR < 0.5, serum creatinine (sCr) < 125% of baseline, prednisone ≤ 10mg/d; Partial = UPCR < 50% from baseline but >0.5, sCr < 125% of baseline, but prednisone allowed to 15 mg/d; Non responder = not meeting previous definitions.ResultsA total of 127 patients were included: 48 (38%) with pure proliferative LN (class III or IV), 41 (32%) with mixed LN (III or IV +/- V), and 38% (30%) with pure membranous LN. Response was complete in 34 (27%), partial in 29 (23%), and none in 64 (50%). There were no urinary biomarkers at baseline that predicted response. We then analyzed the changes in urinary proteins at 3 months compared to baseline. Patients who responded at 1 year showed an early decline in 51 urinary proteins led by CD163, IL-16, and CD206 (macrophage mannose receptor) (Figure 1A) which matched the proteomic signature associated with histological activity (Figure 1B). No changes were observed in nonresponders. The decline of several urinary biomarkers at 3 months outperformed a decline in UPCR (clinical standard) in predicting the 1 year response. In particular, a decline of CD163 predicted 1 year response in ROC analysis with an area under the curve (AUC) of 83% compared to an AUC of 75% for UPCR decline. In proliferative LN, urinary biomarkers displayed superior performance with an AUC of 91%, 86%, and 78% for the decline of CD206, CD163, and UPCR, respectively (Figure 1C-D). Pathway enrichment analysis identified leukocyte activation, neutrophil degranulation, and matrix degradation as the main pathways reduced at 3 months in responders.Figure 1.ConclusionAn early decline in urinary biomarkers of histological activity is associated with proteinuric response at 1 year. These findings indicate that effective immunosuppression induces by three months an immunological response in the kidney that can be noninvasively monitored in the urine. Biomarkers of immunological response outperformed early decline of UPCR, the standard of care, in predicting 1-year proteinuric response, especially in proliferative LN. Because biomarkers of immunological response parallel intrarenal activity, they could detect early treatment response/failure and allow early treatment changes. They could serve as surrogate endpoints in clinical trials. Longitudinal studies are needed to confirm that this immunological response is a better predictor of long-term kidney function preservation than proteinuric responses.REFERENCES:NIL.Acknowledgements:NIL.Disclosure of InterestsNone Declared.