Association of Combined Anti-Ro52/TRIM21 and Anti-Ro60/SSA Antibodies With Increased Sjögren Disease Severity Through Interferon Pathway Activation

The biologic diagnosis of primary Sjögren disease (SjD) mainly relies on anti-Ro60/SSA antibodies, whereas the significance of anti-Ro52/TRIM21 antibodies currently remains unclear. The aim of this study was to characterize the clinical, serological, biologic, transcriptomic, and interferon profiles of patients with SjD according to their anti-Ro52/TRIM21 antibody status.Patients with SjD from the European PRECISESADS (n = 376) and the Brittany Diagnostic Suspicion of primitive Sjögren's Syndrome (DIApSS); (n = 146) cohorts were divided into four groups: double negative (Ro52-/Ro60-), isolated anti-Ro52/TRIM21 positive (Ro52+), isolated anti-Ro60/SSA positive (Ro60+), and double-positive (Ro52+/Ro60+) patients. Clinical information; EULAR Sjögren Syndrome Disease Activity Index, a score representing systemic activity; and biologic markers associated with disease severity were evaluated. Transcriptome data obtained from whole blood by RNA sequencing and type I and II interferon signatures were analyzed for PRECISESADS patients.In the DIApSS cohort, Ro52+/Ro60+ patients showed significantly more parotidomegaly (33.3% vs 0%-11%) along with higher β2-microglobulin (P = 0.0002), total immunoglobulin (P < 0.0001), and erythrocyte sedimentation rate levels (P = 0.002) as well as rheumatoid factor (RF) positivity (66.2% vs 20.8%-25%) compared to other groups. The PRECISESADS cohort corroborated these observations, with increased arthritis (P = 0.046), inflammation (P = 0.005), hypergammaglobulinemia (P < 0.0001), positive RF (P < 0.0001), leukopenia (P = 0.004), and lymphopenia (P = 0.009) in Ro52+/Ro60+ patients. Cumulative EULAR Sjögren Syndrome Disease Activity Index results further confirmed these disparities (P = 0.002). Transcriptome analysis linked anti-Ro52/TRIM21 antibody positivity to interferon pathway activation as an underlying cause for these clinical correlations.These results suggest that the combination of anti-Ro52/TRIM21 and anti-Ro60/SSA antibodies is associated with a clinical, biologic, and transcriptional profile linked to greater disease severity in SjD through the potentiation of the interferon pathway activation by anti-Ro52/TRIM21 antibodies

Association of combined anti-Ro52/TRIM21 and anti-Ro60/SSA antibodies with increased Sjögren disease severity through interferon pathway activation

Objective: The biologic diagnosis of primary Sjögren disease (SjD) mainly relies on anti-Ro60/SSA antibodies, whereas the significance of anti-Ro52/TRIM21 antibodies currently remains unclear. The aim of this study was to characterize the clinical, serological, biologic, transcriptomic, and interferon profiles of patients with SjD according to their anti-Ro52/TRIM21 antibody status. Methods: Patients with SjD from the European PRECISESADS (n = 376) and the Brittany Diagnostic Suspicion of primitive Sjögren's Syndrome (DIApSS); (n = 146) cohorts were divided into four groups: double negative (Ro52‾/Ro60‾), isolated anti-Ro52/TRIM21 positive (Ro52+), isolated anti-Ro60/SSA positive (Ro60+), and double-positive (Ro52+/Ro60+) patients. Clinical information; EULAR Sjögren Syndrome Disease Activity Index, a score representing systemic activity; and biologic markers associated with disease severity were evaluated. Transcriptome data obtained from whole blood by RNA sequencing and type I and II interferon signatures were analyzed for PRECISESADS patients. Results: In the DIApSS cohort, Ro52+/Ro60+ patients showed significantly more parotidomegaly (33.3% vs 0%?11%) along with higher β2-microglobulin (P =0.0002), total immunoglobulin (P <0.0001), and erythrocyte sedimentation rate levels (P =0.002) as well as rheumatoid factor (RF) positivity (66.2% vs 20.8%?25%) compared to other groups. The PRECISESADS cohort corroborated these observations, with increased arthritis (P =0.046), inflammation (P =0.005), hypergammaglobulinemia (P <0.0001), positive RF (P <0.0001), leukopenia (P =0.004), and lymphopenia (P =0.009) in Ro52+/Ro60+ patients. Cumulative EULAR Sjögren Syndrome Disease Activity Index results further confirmed these disparities (P =0.002). Transcriptome analysis linked anti-Ro52/TRIM21 antibody positivity to interferon pathway activation as an underlying cause for these clinical correlations. Conclusion: These results suggest that the combination of anti-Ro52/TRIM21 and anti-Ro60/SSA antibodies is associated with a clinical, biologic, and transcriptional profile linked to greater disease severity in SjD through the potentiation of the interferon pathway activation by anti-Ro52/TRIM21 antibodies.Funding: Supported by the Innovative Medicines Initiative Joint Undertaking (grant 115565 [PRECISESADS project]), resources of which include financial contribution from the European Union’s Seventh Framework Program (grant FP7/2007–2013) and EFPIA companies’ in-kind contribution. LBAI laboratory (Lymphocytes B, Auto-immunité et Immunothérapies) was supported by the Agence Nationale de la Recherche under the “Investissement d’Avenir” program (reference ANR-11-LABX-0016-001 [Labex IGO])

A new molecular classification to drive precision treatment strategies in primary Sjögren’s syndrome

There is currently no approved treatment for primary Sjögren's syndrome, a disease that primarily affects adult women. The difficulty in developing effective therapies is -in part- because of the heterogeneity in the clinical manifestation and pathophysiology of the disease. Finding common molecular signatures among patient subgroups could improve our understanding of disease etiology, and facilitate the development of targeted therapeutics. Here, we report, in a cross-sectional cohort, a molecular classification scheme for Sjögren's syndrome patients based on the multi-omic profiling of whole blood samples from a European cohort of over 300 patients, and a similar number of age and gender-matched healthy volunteers. Using transcriptomic, genomic, epigenetic, cytokine expression and flow cytometry data, combined with clinical parameters, we identify four groups of patients with distinct patterns of immune dysregulation. The biomarkers we identify can be used by machine learning classifiers to sort future patients into subgroups, allowing the re-evaluation of response to treatments in clinical trials

LUPUCE SLE BloodGen3 App - Screencast 1

This short video demonstrates a functionality of the LUPUCE SLE BloodGen3 application, that is accessible via this link: https://immunology-research.shinyapps.io/LUPUCE/ The “aggregate annotation” tab lists the 28 module aggregates that are used to generate fingerprint grid heatmaps or boxplots. Each module aggregate comprises several modules. Clicking on the links provided, an interactive Prezi presentation can be opened in a new browser window; for instance, in the case of module aggregate A28: https://prezi.com/view/sSTVHAGUMNgkGiNhSbgD/ . Clicking on individual modules will permit to zoom in and access background information about the module (gene composition), functional profiling information (ontology profiling, pathway and literature enrichment tools, transcription factor binding motif enrichment) and transcriptional profiles for the gene set constituting the module across several reference datasets (isolated leukocyte populations and hematopoietic precursors).</p

LUPUCE SLE BloodGen3 App - Screencast 3

This short video demonstrates a functionality of the LUPUCE SLE BloodGen3 application, that is accessible via this link: https://immunology-research.shinyapps.io/LUPUCE/ The “modules X studies” tab provides users access to fingerprint heatmap plots, for each of the aggregates and across the LUPUCE study. The position of the modules is set according to similarities in abundance patterns through hierarchical clustering. In this case, columns on the heatmap correspond to study groups, namely DA1, DA2 and DA3 as mentioned in screencast 2, and rows correspond to individual modules. The proportion of transcripts for which abundance is significantly changed is displayed using gradated red and blue dots, as previously detailed. Users can access heatmaps for each aggregate by using the drop-down list above the plot (“Choose aggregate”). Additionally, the zoom in/out function of the web browser can be used to increase the size of the image, thus improving its resolution. The image can then be saved for used in reports or manuscript preparation. </p

LUPUCE SLE BloodGen3 App - Screencast 4

This short video demonstrates a functionality of the LUPUCE SLE BloodGen3 application, that is accessible via this link: https://immunology-research.shinyapps.io/LUPUCE/ The “modules X individuals” tab provides users with the opportunity to generate custom fingerprint heatmap plots. Rows represent modules for a chosen aggregate, but this time columns represent individual subjects instead of study groups as in the previous tab. Users have the possibility to combine multiple module aggregates by typing in the IDs of the modules of interest (for example, A28 is the ID for module aggregate A28) into the designated box, and can also choose to classify patients according to various clinical and biological features, for example SLEDAI, an international scoring system stratifying SLE patients based on disease severity, but also renal involvement, daily dose of corticosteroid taken by patients, or auto-antibody serological status. </p

LUPUCE SLE BloodGen3 App - Screencast 6

This short video demonstrates a functionality of the LUPUCE SLE BloodGen3 application, that is accessible via this link: https://immunology-research.shinyapps.io/LUPUCE/ The “BOXPLOT (% Module Response)” tab provides access to box plots showing the percentage response for individual modules as well as normalized counts of any transcript across study groups of the LUPUCE dataset. In the first section, every module can be selected from a drop-down menu. On the second section, transcripts can be selected from a drop-down menu called “Gene symbol”. To facilitate the search for a particular transcript, it is possible to type the first letters of the transcript to get a suggestion from the tool. Results are generated systematically based on (i) IFN groups, which include “absent”, “mild”, “moderate” and “strong”; and (ii) disease activity groups, which include DA1, DA2 and DA3 as presented in screencast 2. </p

LUPUCE SLE BloodGen3 App - Screencast 2

This short video demonstrates a functionality of the LUPUCE SLE BloodGen3 application, that is accessible via this link: https://immunology-research.shinyapps.io/LUPUCE/ The “Fingerprint grid” tab provides access to fingerprint grid plots which indicate changes in transcript abundance of SLE patients across the LUPUCE dataset based on their disease activity, with the designation DA1 corresponding to no flare, DA2 to mild flare and DA3 to severe flare, in comparison to healthy controls. The position of the modules on the grid is fixed, with the modules in the same row belonging to the same aggregate. The number of modules per aggregate varies between two (aggregate A16) and 42 (aggregate A2). Red spots indicate that a proportion of the transcripts constitutive of the corresponding module have significantly higher abundance levels in SLE patients compared to healthy controls, while blue spots indicate the opposite. The colors are gradated to indicate the relative proportion of transcripts showing significant changes, with values ranging from +100% (all constitutive transcripts are increased) to -100% (all constitutive transcripts are decreased). An annotated map is provided below that uses a color code to represent the functional annotations associated with each of the modules on the map (no color means that functional associations for these modules have not yet been identified yet).</p

LUPUCE SLE BloodGen3 App - Screencast 5

This short video demonstrates a functionality of the LUPUCE SLE BloodGen3 application, that is accessible via this link: https://immunology-research.shinyapps.io/LUPUCE/ The "Heatmap transcript X individuals” tab provides users access to fingerprint heatmap plots of each transcript contained in modules from a selected module aggregate and according to individual subjects. A drop-down menu called “aggregate” allows the user to choose between each module aggregate (e.g. A28 for the module aggregate A28) in order to display the level of activation of transcripts that compose each constitutive module of the given module aggregate. In this tab, each patient is already clustered according to their IFN subgroup, i.e. “absent”, “mild”, “moderate” or “strong” IFN signature, based on previous work. This feature enables users to gain deeper insight into the characterization of individual patients based on their interferon signature, that is linked to many clinical manifestations occurring in SLE patients. </p

News and meta-analysis regarding anti-Beta 2 glycoprotein I antibodies and their determination

International audienceRecent advances allow us to propose antibodies targeting beta-2-glycoprotein I (β2-GPI) as the most specific antibodies associated with anti-phospholipid syndrome (APS). Therefore, there is now a crucial need for powerful biological assays to adequately monitor them. It is well established that these antibodies recognize mainly cryptic epitopes, which requires a great deal of consideration in the choice of laboratory tests to identify these antibodies. To this end, an update on the pathophysiological role of β2-GPI and a meta-analysis were conducted providing an overview of the current progress towards anti-β2-GPI detection