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

Toll-Like Receptors, Infections, and Rheumatoid Arthritis

International audienceToll-like receptors (TLR) that belong to the group of protein recognition receptor (PPR) provide an innate immune response following the sensing of conserved pathogen-associated microbial patterns (PAMPs) and changes in danger-associated molecular patterns (DAMPs) that are generated as a consequence of cellular injury. Analysis of the TLR pathway has moreover offered new insights into the pathogenesis of rheumatoid arthritis (RA). Indeed, a dysfunctional TLR-mediated response characterizes RA patients and participates in establishment of a chronic inflammatory state. Such an inappropriate TLR response has been attributed (i) to the report of important alterations in the microbiota and abnormal responses to infectious agents as part of RA; (ii) to the abnormal presence of TLR-ligands in the serum and synovial fluid of RA patients; (iii) to the overexpression of TLR molecules; (iv) to the production of a large panel of pro-inflammatory cytokines downstream of the TLR pathway; and (v) to genetic variants and epigenetic factors in susceptible RA patients promoting a hyper TLR response. As a consequence, the development of promising therapeutic strategies targeting TLRs for the treatment and prevention of RA is emerging

An elevated polyclonal free light chain level reflects a strong interferon signature in patients with systemic autoimmune diseases

The work described has received support from the Innovative Medicines Initiative Joint Undertaking under grant agreement No. 115565, the resources for which are composed of a financial contribution from the European Union's Seventh Framework Programme (FP7/2007-2013) and the European Federation of Pharmaceutical Industries and Associations (EFPIA) companies'in-kind contribution. We thank all the members of PRECISESADS Consortium and INSERM U1227 for their effort in the sample recruitment, distribution and assessment of the samples used in this study. We are grateful to Dr Wesley H Brooks (Tampa, USA) for editorial assistance and to Valerie Le Troadec for secretarial assistance.High amount of polyclonal free light chains (FLC) are reported in systemic autoimmune diseases (SAD) and we took advantage of the PRECISESADS study to better characterize them. Serum FLC levels were explored in 1979 patients with SAD (RA, SLE, SjS, Scl, APS, UCTD, MCTD) and 614 healthy controls. Information regarding clinical parameters, disease activity, medications, autoantibodies (Ab) and the interferon α and/or γ scores were recorded. Among SAD patients, 28.4% had raised total FLC (from 12% in RA to 30% in SLE and APS) with a normal kappa/ lambda ratio. Total FLC levels were significantly higher in SAD with inflammation, active disease in SLE and SjS, and an impaired pulmonary functional capacity in SSc, while independent from kidney impairment, infection, cancer and treatment. Total FLC concentrations were positively correlated among the 10/17 (58.8%) autoantibodies (Ab) tested with anti-RNA binding protein Ab (SSB, SSA-52/60 kDa, Sm, U1-RNP), anti-dsDNA/nucleosome Ab, rheumatoid factor and negatively correlated with complement fractions C3/C4. Finally, examination of interferon (IFN) expression as a potential driver of FLC overexpression was tested showing an elevated level of total FLC among patients with a high IFNα and IFNγ Kirou's score, a strong IFN modular score, and the detection in the sera of B-cell IFN dependent factors, such as TNF-R1/TNFRSF1A and CXCL10/IP10. In conclusion, an elevated level of FLC, in association with a strong IFN signature, defines a subgroup of SAD patients, including those without renal affectation, characterized by increased disease activity, autoreactivity, and complement reduction.Innovative Medicines Initiative Joint Undertaking 115565European Commission FP7/2007-2013European Federation of Pharmaceutical Industries and Associations (EFPIA)Institut National de la Sante et de la Recherche Medicale (Inserm)European Commission U122