Constructing a seventeen-gene signature model for non-obstructive azoospermia based on integrated transcriptome analyses and WGCNA.

ABSTRACT:

Background

Non-obstructive azoospermia (NOA) affects approximately 1% of the male population worldwide. The underlying mechanism and gene transcription remain unclear. This study aims to explore the potential pathogenesis for the detection and management of NOA.

Methods

Based on four microarray datasets from the Gene Expression Omnibus database, integrated analysis and weighted correlation network analysis (WGCNA) were used to obtain the intersected common differentially expressed genes (DESs). Differential signaling pathways were identified via GO and GSVA-KEGG analyses. We constructed a seventeen-gene signature model using least absolute shrinkage and selection operation (LASSO) regression, and validated its efficacy in another two GEO datasets. Three patients with NOA and

SUBMITTER: Chen Y 

PROVIDER: S-EPMC10029246 | biostudies-literature | 2023 Mar

REPOSITORIES: biostudies-literature