Welcome to the 2021 LUPUS CORA Meeting Program Scheduling
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LUPUS Topics || ASC03 BIOMARKERS IN SLE, LUPUS Topics || ASC14 PATHOGENETIC AND PROTECTIVE AUTOANTIBODIES, LUPUS Topics || ASC18 PERSONALISED MEDICINE IN SLE, No Topic Needed
- Chaim Putterman (United States of America)
- George Bertsias (Greece)
Stratification of Lupus and Systemic Autoimmune Diseases: Clinical Utility
- Marta E. Alarcón Riquelme (Spain)
Live Q&A
How far away is precision medicine for SLE?
- Joan T. Merrill (United States of America)
Live Q&A
How close are we to personalised medicine for SLE?
- Ian Bruce (United Kingdom)
Live Q&A
PERSONALIZED MOLECULAR PORTRAITS OF SYSTEMIC LUPUS ERYTHEMATOSUS PATIENTS AS KEY FOR PROGNOSIS AND THERAPEUTIC DECISIONS
- Daniel Toro-Domínguez (Spain)
Abstract
Background and Aims
Systemic Lupus Erythematosus is a complex autoimmune disease that leads to important worsening of the quality of life and significant suffering to those affected. Currently, therapies used are partially inefficient, mainly due to the molecular heterogeneity of the disease, being personalized medicine the big promise for the future of autoimmunity. With this work we intend to take a step further in that direction by developing MyPROSLE, a system capable of measuring the molecular portrait of individual patients.
Methods
We defined co-expressed and functionally annotated gene-modules conserved across two longitudinal datasets with 158 and 301 patients. The dysregulation magnitude for each gene-module was calculated at the patient level using averaged z-scores. We analyzed the association between gene-modules, clinical manifestations and the evolution of the disease by ANOVA, Student’s t-test and Cox proportional-hazard models. Drug response to hydroxychloroquine and mycophenolate was analyzed comparing molecular portraits. A third dataset of 1760 patients was used to measure the response to Tabalumab.
Results
The system allows to quantify the dysregulation of 30 gene-modules in individual patients with respect to healthy distributions. We show that dysregulation of certain gene-modules is strongly associated with different clinical manifestations and with predicting the time when remissions and relapses of the disease are to occur in the short time. We also demonstrate how the analyzed drugs act specifically on patients with gene-modules related with dysregulated plasma cells.
Conclusions
MyPROSLE allows to extract information from the patients useful for medical practice and may be a support for more precise therapeutic decisions in the future.
Live Q&A
DIFFERENTIAL GENE EXPRESSION OF GLYCOSYLATION-RELATED PROTEINS IN SLE PATIENTS FROM THE PRECISESADS COHORT
- László Kovács (Hungary)
Abstract
Background and Aims
We have previously revealed that the expression of various glycosylation enzymes is altered in patients with activeSLE. This finding could be linked to a decreased sensitivity of SLE activated T-cells to the immunoregulatory lectin Galectin-1. Herein, we wished to obtain an overview of the expression of a wide spectrum of glycosylation enzymes and lectins in patients with active SLE recruited within the multinational European PRECISESADS project.
Methods
Clinical data and RNA reads from PRECISEADS study were collected from 230 SLE patients and 444 controls. Total RNA was extracted from whole blood samples, RNASeq analysis was performed. In this study, the RNASeq data were investigated using a differential gene expression bioinformatics pipeline, and SLE subgroups stratified as those with high (SLEDAI≥6), moderate (SLEDAI=3-5) or low (SLEDAI=0-2) disease activity, and healthy controls were compared. The pathway and ontology enrichment of genes with significant expression change where investigated by Ingenuity Pathway Analysis software.
Results
Despite sporadic differences, glycosylation enzyme mRNA expression was not systematically different from controls in active SLE patients. However, Siglec-1, a sialic acid binding lectin was upregulated, whereas Collectin-12, a sialic acid containing scavenger receptor was downregulated in patients with high disease activity as compared with controls (Siglec-1) or with all other groups (Collectin-12) (p<0.05). Both substances are interferon-inducible. TUSC3, an enzyme participating in glycosylation was down-regulated. Pathway analysis revealed interferon (IF1H1)- and cytosolic pattern recognition receptor-related pathways to be most strongly involved.
Conclusions
Some participants in lectin-mediated immunoregulation with potential pathogenetic significance are differentially expressed in patients with active SLE.
Live Q&A
APPLICATION OF CLUSTER ANALYSIS TO IDENTIFY DISEASE PHENOTYPE ASSOCIATED WITH EROSIVE ARTHRITIS IN SYSTEMIC LUPUS ERYTHEMATOSUS
- Francesco Natalucci (Italy)
Abstract
Background and Aims
The definition of Systemic Lupus Erythematosus (SLE) related arthritis have been substantially changed due to the application of more sensitive imaging techniques. Thus, erosive arthritis could be identified in 40% of patients, suggesting the need for specific biomarkers. In this view, ACPA and anti-CarP have been associated with erosive damage; furthermore, the role of Dkk-1 was suggested. We used Cluster Analysis (CA) to identify different clinical and laboratory features associated with erosive arthritis.
Methods
We enrolled patients with a clinical history of joint involvement, evaluating the presence of erosive arthritis by hands ultrasound. Clinical and laboratory data were collected, including Rheumatoid Factor (RF), ACPA, anti-CarP, Dkk-1 levels. An unsupervised hierarchical CA was performed (SPSS 26 version) to identify the aggregation of patients into different subgroups sharing common features.
Results
One hundred twelve patients (M/F 6/106; median age 45 years, IQR 17; median disease duration 96 months, IQR 165) were analyzed. Erosive arthritis was identified in 25.9% of patients; RF was positive in 31.2% of patients, anti-CarP in 23.2%, ACPA in 8%, detectable Dkk-1 in 6.2%. CA for clinical characteristics identified four defined clusters (figure 1). Interestingly, in the same cluster were allocated ACPA and anti-CarP positivity, detectable Dkk-1 levels, erosive arthritis and renal manifestations. RF resulted allocated in a different cluster, including anti-SSA and anti-SSB.
Conclusions
CA identified a specific SLE phenotype with erosive arthritis, renal manifestations, anti-CarP and ACPA positivity and detectable Dkk-1. We could speculate about the presence of a shared pathogenic mechanism, involving NETosis, contributing to nephritis and erosive arthritis.