Screening and verification of genes related to polycystic ovary syndrome.

ABSTRACT:

Objective

To identify key genes involved in occurrence and development of polycystic ovary syndrome (PCOS).

Methods

By downloading the GSE85932 dataset from the GEO database, we used bioinformatical analysis to analyse differentially expressed genes (DEGs) from blood samples of eight women with PCOS and eight matched controls. Following bioinformatic analysis, we performed a cross-sectional study of serum samples taken from 79 women with PCOS and 36 healthy controls.

Results

From the 178 DEGs identified by bioinformatical analysis, 15 genes were identified as significant, and of these, ORM1 and ORM2 were selected for further verification as potential biomarkers for PCOS. Serum ORM1 and ORM2 levels were significantly increased in women with PCOS, and had a high diagnos

SUBMITTER: Li X 

PROVIDER: S-EPMC9837284 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature