Primary Sjögren's syndrome (pSS) is one of the most widespread autoimmune diseases with unknown origin, characterized by a lymphocytic infiltrate of the exocrine glands and the production of anti-SSA/Ro and anti-SSB/La antibodies that cause dysfunction and destruction mainly of salivary and lachrymal glands, leading to dry eyes and dry mouth. In the absence of a standardized evidence-based screening tool to decide which patients with dry eye must be referred for study of this pathology, there is a tendency to have a continuous underdiagnosis of the disease, causing the calculation of its prevalence to be inaccurate.1 To improve our understanding of the underlying molecular nature, we analyzed public microarray-based gene expression profiles of salivary glands (GSE23117) and saliva (GSE7451) from primary Sjögren's syndrome (pSS) patients and controls. Unlike the two microarrays published before, we showed a specific common set of genes and an extensive study of biological pathways and networks showing a potential detonating factor. We included a machine learning model to distinguish pSS patients from controls, opening a possible means of detecting biomarkers to diagnose, monitor the response to treatment, and predict the prognosis of pSS.