RT Journal Article
T1 A new molecular classification to drive precision treatment strategies in primary Sjögren's syndrome.
A1 Soret, Perrine
A1 Le-Dantec, Christelle
A1 Desvaux, Emiko
A1 Foulquier, Nathan
A1 Chassagnol, Bastien
A1 Hubert, Sandra
A1 Jamin, Christophe
A1 Barturen, Guillermo
A1 Desachy, Guillaume
A1 Devauchelle-Pensec, Valerie
A1 Boudjeniba, Cheïma
A1 Cornec, Divi
A1 Saraux, Alain
A1 Jousse-Joulin, Sandrine
A1 Barbarroja, Nuria
A1 Rodriguez-Pinto, Ignasi
A1 De Langhe, Ellen
A1 Beretta, Lorenzo
A1 Chizzolini, Carlo
A1 Kovacs, Laszlo
A1 Witte, Torsten
A1 Bettacchioli, Eleonore
A1 Buttgereit, Anne
A1 Makowska, Zuzanna
A1 Lesche, Ralf
A1 Borghi, Maria Orietta
A1 Martin, Javier
A1 Courtade-Gaiani, Sophie
A1 Xuereb, Laura
A1 Guedj, Mickaël
A1 Moingeon, Philippe
A1 Alarcon-Riquelme, Marta E
A1 Laigle, Laurence
A1 Pers, Jacques-Olivier
K1 Autoantibodies
K1 Biomarkers
K1 Chemokines
K1 Cohort studies
K1 Computational diology
K1 Computer simulation
AB 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.
PB Nature Publishing Group
YR 2021
FD 2021-06-10
LK http://hdl.handle.net/10668/17985
UL http://hdl.handle.net/10668/17985
LA en
NO Soret P, Le Dantec C, Desvaux E, Foulquier N, Chassagnol B, Hubert S, et al. A new molecular classification to drive precision treatment strategies in primary Sjögren's syndrome. Nat Commun. 2021 Jun 10;12(1):3523
NO The research leading to these results has received support from the Innovative Medicines Initiative Joint Undertaking under the Grant Agreement Number 115565 (PRECISESADS project), resources of which are composed of financial contribution from the European Union’s Seventh Framework Program (FP7/2007–2013) and EFPIA companies’ in-kind contribution. LBAI was supported by the Agence Nationale de la Recherche under the “Investissement d’Avenir” program with the Reference ANR-11-LABX-0016-001 (Labex IGO) and the Région Bretagne. The authors would like to particularly express their gratitude to the patients, nurses, technicians and many others who helped directly or indirectly in the consecution of this study. They are grateful to the Institut Français de Bioinformatique (ANR-11-INBS-0013), the Roscoff Bioinformatics platform ABiMS (http://abims.sb-roscoff.fr) for providing computing and storage resources and the Hypérion platform at LBAI (Brest, France) for flow cytometry facilities. Finally, this workis now supported by ELIXIR Luxembourg via its data hosting service.
DS RISalud
RD Apr 18, 2025