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

ABSTRACT:

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 machine-learning approaches.

Methods

We used a standardized targeted metabolomic approach involving high performance liquid chromatography coupled with mass spectrometry among n

SUBMITTER: Urbanski G 

PROVIDER: S-EPMC10375713 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature