Consensus gene modules strategy identifies candidate blood-based biomarkers for primary Sjögren's disease

Cheïma Boudjeniba, Perrine Soret, Diana Trutschel, Antoine Hamon, Valentin Baloche, Bastien Chassagnol, Emiko Desvaux, Antoine Bichat, Audrey Aussy, Philippe Moingeon, Céline Lefebvre, Sandra Hubert, Marta Alarcon-Riquelmé, Wan Fai Ng, Jacques Eric Gottenberg, Benno Schwikowski, Michele Bombardieri, Joel A.G. van Roon, Xavier Mariette, Mickaël GuedjEtienne Birmele, Laurence Laigle, Etienne Becht*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

Primary Sjögren disease (pSD) is an autoimmune disease characterized by lymphoid infiltration of exocrine glands leading to dryness of the mucosal surfaces and by the production of autoantibodies. The pathophysiology of pSD remains elusive and no treatment with demonstrated efficacy is available yet. To better understand the biology underlying pSD heterogeneity, we aimed at identifying Consensus gene Modules (CMs) that summarize the high-dimensional transcriptomic data of whole blood samples in pSD patients. We performed unsupervised gene classification on four data sets and identified thirteen CMs. We annotated and interpreted each of these CMs as corresponding to cell type abundances or biological functions by using gene set enrichment analyses and transcriptomic profiles of sorted blood cell subsets. Correlation with independently measured cell type abundances by flow cytometry confirmed these annotations. We used these CMs to reconcile previously proposed patient stratifications of pSD. Importantly, we showed that the expression of modules representing lymphocytes and erythrocytes before treatment initiation is associated with response to hydroxychloroquine and leflunomide combination therapy in a clinical trial. These consensus modules will help the identification and translation of blood-based predictive biomarkers for the treatment of pSD.

Original languageEnglish
Article number110241
Number of pages12
JournalClinical Immunology
Volume264
DOIs
Publication statusPublished - Jul 2024

Keywords

  • Integrated analysis
  • Precision medicine
  • Sjögren disease
  • Unsupervised learning

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