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POS0421 COMBINED ANALYSIS OF METABOLIC AND TRANSCRIPTOMIC KIDNEY PROFILES OF NZW/B-F1 MURINE LUPUS UNCOVERS BIOLOGICAL MECHANISMS PRECEDING THE ONSET OF NEPHRITIS. Ann Rheum Dis 2021. [DOI: 10.1136/annrheumdis-2021-eular.4115] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
Abstract
Background:Metabolic pathways are important regulators of immune differentiation and activation in kidneys. Kidneys directly impact systemic metabolism, circulating metabolite levels, and express intrinsic metabolic activity. The integration of renal metabolomic and transcriptomic profiles may unravel unique gene-metabolite pairs of biological significance in lupus nephritis (LN).Objectives:To decipher gene-metabolite signatures at both pre-nephritic and nephritic stages of lupus.Methods:Kidneys were isolated and snap-frozen after perfusion from female NZB/NZW-F1 lupus mice at the pre-nephritic (3-month-old) and nephritic (6-month-old exhibiting ≥100 ng/dL of urine protein) stage of lupus (n=6/group). Age-matched female C57BL/6 mice were used as healthy controls. Sample extracts were used for RNA sequencing and 1H-NMR spectroscopy metabolic profiling. DESeq2 was used to identify differentially expressed genes. Univariate analysis was used to reveal metabolic differences characteristic for nephritis.Results:Comparative transcriptomic analyses uncovered multiple transcripts related to metabolic pathways: In pre-nephritic kidneys, lipid metabolism, cellular respiration, TCA cycle, amino acid metabolism processes were overrepresented in the upregulated genes while in nephritic kidneys, amino acid metabolism processes were overrepresented among the downregulated genes (Figure 1). 1H-NMR analysis revealed a total of 49 metabolites. Comparison of the metabolic levels of nephritic and pre-nephritic animals revealed that ADP, ATP, NAD+, Taurine and Myo-inositol decreased, while Thr increased significantly. The comparison to corresponding control animals, demonstrated that only myo-inositol increased significantly. Integration of kidney metabolomics and transcriptomics indicated the involvement of processes related to glutathione metabolism, leukocyte trans-endothelial migration and antigen presentation during the established renal disease stage.Conclusion:The combined transcriptomics and metabolomics analysis revealed metabolic derangements in lupus-affected kidneys both during subclinical and overt LN. Deregulated tissue-levels of taurine and myo-inositol at the subclinical stage of the disease suggest aberrant renal biochemistry preceding the development of overt LN that may directly impact systemic metabolism and circulating metabolite levels.Figure 1.Pathways linked to cell metabolism were overrepresented among 3-month upregulated and 6-month lupus mice (F1) downregulated DEGS (differentially expressed genes) compared to controls (C57BL/6).Acknowledgements:This project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No 742390).Disclosure of Interests:None declared
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THU0014 COMPARATIVE TRANSCRIPTOME ANALYSES ACROSS TISSUES AND SPECIES IDENTIFY TARGETABLE GENES FOR HUMAN SYSTEMIC LUPUS ERYTHEMATOSUS (SLE) AND LUPUS NEPHRITIS (LN). Ann Rheum Dis 2020. [DOI: 10.1136/annrheumdis-2020-eular.4102] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
Abstract
Background:Systemic Lupus Erythematosus (SLE) is a complex disease associated with the dysfunction of multiple tissues and cells. The causal tissue for each disease phenotype is not known a priori. Despite improvements in diagnosis and treatment, major organ involvement (such as the kidneys) contributes significantly to morbidity and mortality that still remain increased. There is an unmet need for timely targeted therapy.Objectives:RNA-sequencing was performed to investigate the patterns of transcription variation across tissues between healthy and lupus-prone mice at different stages of lupus, and how these patterns associate with human Systemic Lupus Erythematosus (SLE).Methods:NZB/W-F1 lupus prone mice were sacrificed at the pre-puberty, pre-autoimmunity and nephritic stage. Age-matched C57BL/6 were used as controls. An “effector” tissue (spleen) and “end-organs” (kidneys, brain) were collected. Total RNA was isolated, and mRNA-sequencing was performed. A time-series analysis was developed and differentially expressed genes (DEGs) were analyzed with DESeq. Hierarchical clustering and functional enrichment analysis were performed with gProfiler. Human orthologs of mouse tissue DEGs were identified in the whole-blood RNA-sequencing dataset comprised of 55 lupus-nephritis (LN), 65 non-LN SLE patients and 58 healthy individuals (HI). Human orthologs were compared to human DEGs. Using machine learning, human orthologs identified in the mouse dataset were used to predict kidney involvement in the human dataset, which was split in training and validation sets.Results:Lupus susceptibility and progression signatures at different tissues and different stages of the disease were identified. Tissue-specific signatures and a common cross-tissue signature were also described. Previously described and novel biological processes and pathways were revealed. The comparative murine-human transcriptome analysis identified human orthologs from the mouse spleen-signature (including CCL5, IFIT and HLA genes) that are involved in systemic autoimmunity. It also identified human orthologs from the kidney- and brain-signature (including FCGR2A, C1Q, JAK1 and APOA2) that are involved in major “end-organ” damage and response mechanisms. Using a neural network model, 193 human orthologs accurately predicted LN patients vs HI (accuracy=0.86, sensitivity=0.82, specificity=0.91 in the validation set). Using a support vector machine model, 30 human orthologs and age and gender were the best predictors of LN vs non-LN SLE patients (accuracy=0.71, sensitivity=0.73, specificity=0.69 in the validation set).Conclusion:Murine tissue gene signatures identified by RNA-sequencing analysis revealed biological processes and pathways that could be potentially used as biomarkers or therapeutic targets in human SLE. Comparison of the murine tissue-transcriptome with the whole-blood human-transcriptome revealed common gene signatures, demonstrating similar biological processes and pathways. Machine learning identified a murine kidney lupus signature that can accurately predict kidney involvement in human SLE. Validation in other datasets is ongoing.References:[1]Panousis NI, et al. Ann Rheum Dis 2019;78:1079Acknowledgments:This work was supported by FOREUM, SYSCID and ERC -Advanced GrantDisclosure of Interests:Eleni Frangou: None declared, Panayiotis Garantziotis: None declared, Maria Grigoriou: None declared, Aggelos Banos: None declared, Nikolaos Panousis: None declared, Emmanouil Dermitzakis: None declared, George Bertsias Grant/research support from: GSK, Consultant of: Novartis, Dimitrios Boumpas: None declared, Anastasia Filia: None declared
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OP0163 2019 UPDATE OF THE JOINT EUROPEAN LEAGUE AGAINST RHEUMATISM AND EUROPEAN RENAL ASSOCIATION–EUROPEAN DIALYSIS AND TRANSPLANT ASSOCIATION (EULAR/ERA-EDTA) RECOMMENDATIONS FOR THE MANAGEMENT OF LUPUS NEPHRITIS. Ann Rheum Dis 2020. [DOI: 10.1136/annrheumdis-2020-eular.3870] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
Background:Up to 40% of systemic lupus erythematosus (SLE) patients develop kidney disease, which represents a major cause of morbidity.Objectives:To update the 2012 EULAR/ERA-EDTA recommendations for the management of lupus nephritis (LN).Methods:We followed the EULAR standardised operating procedures for the publication of treatment recommendations. Delphi-based methodology led to 15 questions for systematic literature review (SLR), which was undertaken by three fellows.Results:The changes include recommendations for treatment targets, use of glucocorticoids and calcineurin inhibitors (CNI), and management of end-stage-kidney-disease (ESKD). The target of therapy is complete response (proteinuria <0.5-0.7gr/24h with [near-]normal glomerular filtration rate) by 12 months, but this can be extended in patients with baseline nephrotic-range proteinuria. Hydroxychloroquine is recommended with regular ophthalmological monitoring. In active proliferative LN, initial (induction) treatment with mycophenolate mofetil (MMF 2-3g/day, or mycophenolic acid at equivalent dose) or low-dose intravenous cyclophosphamide (CY; 500mg x6 biweekly doses), both combined with glucocorticoids (pulses of intravenous methylprednisolone, then oral prednisone 0.3-0.5mg/kg/day) is recommended. MMF/CNI (especially tacrolimus) combination and high-dose CY are alternatives, for patients with nephrotic-range proteinuria and adverse prognostic factors. Subsequent long-term maintenance treatment with MMF or azathioprine should follow, with no or low-dose (<7.5 mg/day) glucocorticoids. The choice of agent depends on the initial regimen and plans for pregnancy. In non-responding disease, switch of induction regimens or rituximab are recommended. In pure membranous LN with nephrotic-range proteinuria or proteinuria >1g/24h despite renin-angiotensin-aldosterone blockade, MMF in combination with glucocorticoids is preferred. Assessment for kidney and extra-renal disease activity, and management of comorbidities is lifelong with repeat kidney biopsy in cases of incomplete response or nephritic flares. In ESKD, transplantation is the preferred kidney replacement option with immunosuppression guided by transplant protocols and/or extra-renal manifestations.Conclusion:The updated recommendations intend to inform rheumatologists, nephrologists, patients, national professional societies, hospital officials, social security agencies and regulators about the treatment of LN based on most recent evidence.Disclosure of Interests:Antonis Fanouriakis Paid instructor for: Paid instructor for Enorasis, Amgen, Speakers bureau: Paid speaker for Roche, Genesis Pharma, Mylan, Myrto Kostopoulou: None declared, Kim Cheema: None declared, Hans-Joachim Anders: None declared, Martin Aringer Consultant of: Boehringer Ingelheim, Roche, Speakers bureau: Boehringer Ingelheim, Roche, Ingeborg Bajema Consultant of: GSK, John N. Boletis Grant/research support from: GSK, Pfizer, Paid instructor for: GSK, Abbvie, UCB, Enorasis, Eleni Frangou: None declared, Frederic Houssiau Grant/research support from: UCB, Consultant of: GSK, Jane Hollis: None declared, Alexandre Karras: None declared, Francesca Marchiori: None declared, Stephen Marks: None declared, Gabriela Moroni: None declared, Marta Mosca: None declared, Ioannis Parodis: None declared, Manuel Praga: None declared, Matthias Schneider Grant/research support from: GSK, UCB, Abbvie, Consultant of: Abbvie, Alexion, Astra Zeneca, BMS, Boehringer Ingelheim, Gilead, Lilly, Sanofi, UCB, Speakers bureau: Abbvie, Astra Zeneca, BMS, Chugai, GSK, Lilly, Pfizer, Sanofi, Josef S. Smolen Grant/research support from: AbbVie, AstraZeneca, Celgene, Celltrion, Chugai, Eli Lilly, Gilead, ILTOO, Janssen, Novartis-Sandoz, Pfizer Inc, Samsung, Sanofi, Consultant of: AbbVie, AstraZeneca, Celgene, Celltrion, Chugai, Eli Lilly, Gilead, ILTOO, Janssen, Novartis-Sandoz, Pfizer Inc, Samsung, Sanofi, Vladimir Tesar: None declared, Maria Trachana: None declared, Ronald van Vollenhoven Grant/research support from: AbbVie, Amgen, Arthrogen, Bristol-Myers Squibb, GlaxoSmithKline (GSK), Janssen Research & Development, LLC, Lilly, Pfizer, Roche, and UCB, Consultant of: AbbVie, AstraZeneca, Biotest, Bristol-Myers Squibb, Celgene, Crescendo Bioscience, GSK, Janssen, Lilly, Medac, Merck, Novartis, Pfizer, Roche, UCB and Vertex, Speakers bureau: AbbVie, AstraZeneca, Biotest, Bristol-Myers Squibb, Celgene, Crescendo Bioscience, GlaxoSmithKline, Janssen, Lilly, Merck, Novartis, Pfizer, Roche, UCB, Vertex, Alexandre Voskuyl: None declared, Y.K. Onno Teng Grant/research support from: GSK, Consultant of: GSK, Aurinia Pharmaceuticals, Novartis, Bernadette van Leeuw: None declared, George Bertsias Grant/research support from: GSK, Consultant of: Novartis, David Jayne Grant/research support from: ChemoCentryx, GSK, Roche/Genentech, Sanofi-Genzyme, Consultant of: Astra-Zeneca, ChemoCentryx, GSK, InflaRx, Takeda, Insmed, Chugai, Boehringer-Ingelheim, Dimitrios Boumpas: None declared
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