Metabolism-related proteins as biomarkers for predicting prognosis in polycystic ovary syndrome.

ABSTRACT:

Objective

The study aimed to explore the role of metabolism-related proteins and their correlation with clinical data in predicting the prognosis of polycystic ovary syndrome (PCOS).

Methods

This research involves a secondary analysis of proteomic data derived from endometrial samples collected from our study group, which includes 33 PCOS patients and 7 control subjects. A comprehensive identification and analysis of 4425 proteins were conducted to screened differentially expressed proteins (DEPs). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were subsequently performed on the DEPs. To identify independent prognostic metabolism-related proteins, univariate Cox regression and LASSO regression were applied. The expression levels of

SUBMITTER: Ding N 

PROVIDER: S-EPMC11660692 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature