Screening of pathologically significant diagnostic biomarkers in tears of thyroid eye disease based on bioinformatic analysis and machine learning.

ABSTRACT:

Background

Lacrimal gland enlargement is a common pathological change in patients with thyroid eye disease (TED). Tear fluid has emerged as a new source of diagnostic biomarkers, but tear-based diagnostic biomarkers for TED with high efficacy are still lacking.

Objective

We aim to investigate genes associated with TED-associated lacrimal gland lesions. Additionally, we seek to identify potential biomarkers for diagnosing TED in tear fluid.

Methods

We obtained two expression profiling datasets related to TED lacrimal gland samples from the Gene Expression Omnibus (GEO). Subsequently, we combined the two separate datasets and conducted differential gene expression analysis and weighted gene co-expression network analysis (WGCNA) on the obtained integrated dataset. The g

SUBMITTER: Shu X 

PROVIDER: S-EPMC11561714 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature