An immuno-lipidomic signature revealed by metabolomic and machine-learning approaches in labial salivary gland to diagnose primary Sjögren’s syndrome

Aug 5, 2026

Primary Sjögren’s syndrome (pSS) is diagnosed using labial salivary gland (LSG) biopsy with focal lymphocytic sialadenitis and a focus score, but these findings often reflect advanced disease. A prospective cohort study combined targeted metabolomics with machine-learning to identify early biomarkers in LSG. Using linear models and random forests across training, validation, and test sets, a six-metabolite immuno-lipidomic signature discriminated early pSS from non-pSS sicca and linked components to lymphocytic infiltration and anti-SSA antibodies.

LanguageEnglish

CategoryResearch & Report

FormatPDF

Pages12

Reading Time30 min

AccessFree to download

Introduction

Biomarker rationale in labial salivary gland

Methods

Targeted metabolomics and machine-learning models

Results

Six-metabolite signature and biological associations

Conclusion

UCSF UC San Francisco Previously Published Works Title An immuno-lipidomic signature revealed by metabolomic and machine-learning approaches in labial salivary gland to diagnose primary Sjögrens syndrome. Permalink [https://escholarship.org/uc/item/7829d616](https://escholarship.org/uc/item/7829d616) Authors Chabrun, Floris Delattre, Estelle Lacout, Carole et al. Publication Date 2023 DOI 10.3389/fimmu.2023.1205616 Peer reviewed [eScholarship.org](eScholarship.org) Powered by the California Digital Library University of California TYPE Original Research PUBLISHED 14 July 2023 DOI 10.3389/fimmu.2023.1205616 OPEN ACCESS EDITED BY Efstathia K. Kapsogeorgou, National and Kapodistrian University of Athens, Greece REVIEWED BY Paola Perez, National Institute of Dental and Craniofacial Research (NIH), United States Nikolaos C. Kyriakidis, University of the Americas, Ecuador *CORRESPONDENCE Geoffrey Urbanski [urbanskigeoffrey@gmail.com](urbanskigeoffrey@gmail.com) †These authors have contributed equally to this work and share last authorship RECEIVED 14 April 2023 ACCEPTED 28 June 2023 PUBLISHED 14 July 2023 CITATION Urbanski G, Chabrun F, Delattre E, Lacout C, Davidson B, Blanchet O, Chao de la Barca JM, Simard G, Lavigne Cand Reynier P (2023) An immunolipidomic signature revealed by metabolomic and machine-learning approaches in labial salivary gland to diagnose primary Sjögren ’s syndrome. Front. Immunol. 14:1205616 . doi: 10.3389/fimmu.2023.1205616 COPYRIGHT © 2023 Urbanski, Chabrun, Delattre, Lacout, Davidson, Blanchet, Chao de la Barca, Simard, Lavigne and Reynier. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. An immuno-lipidomic signature revealed by metabolomic and machine-learning approaches in labial salivary gland to diagnose primary Sjögren’s syndrome Geoffrey Urbanski 1,2,3*, Floris Chabrun 2,4, Estelle Delattre 1, Carole Lacout 1, Brittany Davidson 3, Odile Blanchet 5, Juan Manuel Chao de la Barca 2,4, Gilles Simard 2,4, Christian Lavigne 1† and Pascal Reynier 2,4† 1 Department of Internal Medicine and Clinical Immunology, University Hospital, Angers, France, 2 Mitolab, MitoVasc Institute, CNRS 6015, INSERM U1083, University of Angers, Angers, France, 3 Department of Orofacial Sciences, University of California, San Francisco, San Francisco, CA, United States, 4 Department of Biochemistry and Molecular Biology, University Hospital, Angers, France, 5Centre de Ressources Biologiques, University Hospital, Angers, France Introduction: Assessing labial salivary gland exocrinopathy is a cornerstone in primary Sjögren ’ s syndrome . Currently this relies on the histopathologic diagnosis of focal lymphocytic sialadenitis and computing a focus score by counting lym=phocyte foci. However, those lesions represent advanced stages of primary Sjögren ’s syndrome, although earlier recognition of primary Sjögren’s syndrome and its effective treatment could prevent irreversible damage to labial salivary gland. This study aimed at ﬁnding early biomarkers of primary Sjögren’s syndrome in labial salivary gland combining metabolomics and machinelearning approaches. Methods: We used a standardized targeted metabolomic approach involving high performance liquid chromatography coupled with mass spectrometry among newly diagnosed primary Sjögren ’s syndrome (n=40) and non-primary Sjögren ’ s syndrome sicca (n=40) participants in a prospective cohort. A metabolic signature predictive of primary Sjögren ’ s syndrome status was explored using linear (logistic regressi

FAQs

Why is labial salivary gland assessment important in primary Sjögren’s syndrome?

LSG biopsy supports diagnosis by demonstrating focal lymphocytic sialadenitis and focus score calculation. However, these lesions are often linked to more advanced stages, motivating early biomarker discovery.

How was the metabolic signature built in this study?

Targeted metabolomics was performed using high-performance liquid chromatography coupled with mass spectrometry. Models included logistic regression with elastic-net regularization and random forests, evaluated via training, validation, and test splits.

Which metabolites composed the discriminant immuno-lipidomic signature?

The signature comprised six metabolites: kynurenine and five phospholipids (LysoPC C28:0; PCaa C26:0; PCaa C30:2; PCae C30:1; PCae C30:2).

What biological meaning did the signature components have?

The phospholipid component related to lymphocytic infiltrate intensity in salivary glands, while kynurenine was independently associated with anti-SSA antibodies in participant serum.

Aug 5, 2026

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