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Systemic sclerosis: a model for studying the immunity-fibrosis relationship

As a MD resident and then PhD student I have been learning immunology of autoimmune diseases and clinical aspects. During this period my work was dedicated to characterize autoantibodies in SSc and in particular to study their prevalence and clinical associations:
Sobanski V, Dauchet L, Lefèvre G, Lambert M, Morell-Dubois S, Sy T, Hachulla E, Hatron PY, Launay D, Dubucquoi S. Prevalence of anti-RNA polymerase III antibodies in systemic sclerosis: a new French cohort, systematic review and meta-analysis. Arthritis Rheum. 2014 66(2):407-417; doi: 10.1002/art.38219
⇒ To my knowledge, it was the first time that a systematic review and meta-analysis was performed on an autoantibody prevalence in SSc. At this time, anti-RNA polymerase III antibodies were not well characterized and different methods for screening resulted in high discrepancies between centres. My work showed that there was a high heterogeneity in their prevalence worldwide which remains largely unexplained (after adjustment for baseline SSc characteristics or methods testing) suggesting the implication of genetic background or environmental factors.
Sobanski V, Giovannelli J, Lynch BM, Schreiber BE, Nihtyanova SI, Harvey J, Handler CE, Denton CP, Coghlan JG. Characteristics and Survival of Anti-U1 RNP Antibody- Positive Patients With Connective Tissue Disease-Associated Pulmonary Arterial Hypertension. Arthritis Rheumatol. 2016;68(2):484-93;
doi: 10.1002/art.39432

⇒ During my fellowship in the Centre for Rheumatology and Connective Tissue Diseases at University College London, I set up a large database of >3,000 patients who underwent a right heart catheterization at this national reference centre for pulmonary hypertension. I thoroughly reviewed each case and identified >1,000 patients with a connective tissue disease. This work enabled to study specifically patients with anti-U1RNP antibodies (an autoantibody shared between patients with various connective tissue diseases) suggesting that there was a serological homogeneity in patients with pulmonary hypertension. I have been invited to present the results in different congresses (Pulmonary Hypertension forum and International Workshop on Scleroderma Research).

A highly heterogeneous disease

We conducted a study to identify and characterize homogeneous phenotypes of patients with ScS without any a priori assumptions using cluster analysis, and compare survival between the different identified groups:
Sobanski V, Giovannelli J , Allanore Y, Riemekasten G, Airò P, Vettori S, Cozzi F, Distler O, Matucci-Cerinic M, Denton C, Launay D, Hachulla E and EUSTAR collaborators. Phenotypes determined by cluster analysis and their survival in the prospective EUSTAR cohort of patients with systemic sclerosis. Arthritis Rheumatol 2019 Sep;71(9):1553-1570; doi: 10.1002/art.40906
⇒ This was a multicenter study (137 centers) of patients in the prospective EUSTAR cohort including ~7,000 patients. This study suggested that restricting the classification of patients to skin involvement does not capture the full heterogeneity of SSc. This article was commented on in a "News and Views" in the journal Nature Review Rheumatol by Hinchcliff et al. The authors have described the notable elements of our work and stressed the importance of using "new" statistical tools (such as cluster analysis) to better understand the "phenome" of scleroderma patients. I have presented the study in oral presentations at EULAR congress and Scleroderma World congress.

Identification of the need for high quality phenotypic data and implementation of actions

The prerequisite for any big data / artificial intelligence analysis is to have a large volume of data. I have funded our university hospital clinical data warehouse INCLUDE. We have obtained funding from the European Metropolitan Area of Lille (€1 million) and the I-SITE ULNE foundation (500k€), designed internal regulations and governance that have enabled us to obtain a GDPR-compliant CNIL authorization (security and confidentiality), and acquired a data storage solution. We have implemented all the data (clinical notes, laboratory results, imaging reports, anatomo-pathology reports, drug prescriptions, claims data) produced since 2008 (1.6 millions of patients). This transdisciplinary project brings together all the skills present on our campus (clinicians, researchers, health data specialists, artificial intelligence specialists). We constituted a true health data platform that is part of the national process of setting up regional hubs bringing together data producers and operating skills.
Ledoult E, Launay D, Béhal H, Mouthon L, Pugnet G, Lega JC, Agard C, Allanore Y, Jego P, Fauchais AL, Harlé JR, Berthier S, Aouba A, Mekinian A, Diot E, Truchetet ME, Boulon C, Duhamel A, Hachulla E, Sobanski V; French National Scleroderma Cohort Network. Early trajectories of skin thickening are associated with severity and mortality in systemic sclerosis. Arthritis Res Ther. 2020 Feb 18;22(1):30; doi: 10.1186/s13075-020-2113-6
⇒ This work showed that we could identify skin trajectories among the French national SSc database using latent class mixed modelling. It showed that longitudinal analysis of clinical data can be a relevant approach to decipher the heterogeneity of SSc.