Metabolic Profile of Whole Unstimulated Saliva in Patients with Sjögren’s Syndrome

Author:

Setti Giacomo1ORCID,Righi Valeria2ORCID,Mucci Adele3ORCID,Panari Lucia1,Bernardelli Giuditta4,Tarentini Elisabetta5,Gambini Anna5,Consolo Ugo1ORCID,Generali Luigi1ORCID,Magnoni Cristina5,Meleti Marco6,Sandri Gilda7ORCID,Bellini Pierantonio1ORCID

Affiliation:

1. Dentistry and Oral-Maxillofacial Surgery Unit, University of Modena and Reggio Emilia, Largo del Pozzo 71, 41125 Modena, Italy

2. Department for Life Quality Studies, University of Bologna, Corso d’Augusto 237, 47921 Rimini, Italy

3. Department of Chemical and Geological Sciences, University of Modena and Reggio Emilia, Via G. Campi 103, 41125 Modena, Italy

4. Pathology Unit, Azienda USL-IRCCS di Reggio Emilia, Viale Risorgimento 80, 42123 Reggio Emilia, Italy

5. Dermatology Unit, University of Modena and Reggio Emilia, Largo del Pozzo 71, 41125 Modena, Italy

6. Centro Universitario Odontoiatria, University of Parma, Via Gramsci 14, 43126 Parma, Italy

7. Rheumatology Unit, University of Modena and Reggio Emilia, Largo del Pozzo 71, 41125 Modena, Italy

Abstract

Primary Sjögren’s Syndrome (pSS) is a multi-system autoimmune disease that involves the exocrine glands. Lymphocytes infiltrate the gland tissue, leading to anatomical modification and hypofunction. Even if the prognosis of pSS is favorable, quality of life is typically reduced due to the diverse manifestations of the disease. The aim of this study is to compare the salivary metabolomes of pSS with healthy controls (HCs). Seven cases were selected from a cohort of pSS patients, and six age- and sex-matched HCs were recruited from a cohort of volunteers. Whole unstimulated saliva was collected for NMR analysis. Our metabolomic analysis focused on 360 ms total echo 1D 1H NMR CPMG spectra. Metabolites detected with CPMG NMR spectra were assigned through 2D NMR spectra (COSY, TOCSY, and HSQC). About 50 metabolites were detected and assigned. Unsupervised exploratory PCA returned partial clustering, and PLS-DA improved the separation between pSS and HCs, highlighting a pool of metabolites distinctly describing each group. Despite the limited number of samples, the presented preliminary data are promising. PLS-DA indicated well-defined group separation, suggesting that the application of 1H-NMR metabolomics is suitable for the study of pSS.

Publisher

MDPI AG

Subject

Molecular Biology,Biochemistry,Endocrinology, Diabetes and Metabolism

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