Screening biomarkers for Sjogren's Syndrome by computer analysis and evaluating the expression correlations with the levels of immune cells.

ABSTRACT:

Background

Sjögren's syndrome (SS) is a systemic autoimmune disease that affects about 0.04-0.1% of the general population. SS diagnosis depends on symptoms, clinical signs, autoimmune serology, and even invasive histopathological examination. This study explored biomarkers for SS diagnosis.

Methods

We downloaded three datasets of SS patients' and healthy pepole's whole blood (GSE51092, GSE66795, and GSE140161) from the Gene Expression Omnibus (GEO) database. We used machine learning algorithm to mine possible diagnostic biomarkers for SS patients. Additionally, we assessed the biomarkers' diagnostic value using the receiver operating characteristic (ROC) curve. Moreover, we confirmed the expression of the biomarkers through the reverse transcription quantitative polymerase

SUBMITTER: Zhong Y 

PROVIDER: S-EPMC10294232 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature