Banca de DEFESA: NÍVEA MARIA SOBRAL ARRUDA CÂMARA

Uma banca de DEFESA de MESTRADO foi cadastrada pelo programa.
STUDENT : NÍVEA MARIA SOBRAL ARRUDA CÂMARA
DATE: 12/08/2026
TIME: 09:00
LOCAL: Sala de Aulas II GEP/MEJC
TITLE:

Analysis of gene expression profiles for the identification of candidate molecular biomarkers in the pathogenesis of Polycystic Ovary Syndrome

KEY WORDS:

Polycystic Ovary Syndrome, Bioinformatics, Biomarkers, Transcriptome.

PAGES: 101
BIG AREA: Ciências da Saúde
AREA: Saúde Coletiva
SUMMARY:

Polycystic Ovary Syndrome (PCOS) is an endocrine–metabolic disorder that affects approximately 6–20% of women of reproductive age and is typically characterized by chronic ovulatory dysfunction, hyperandrogenism, and polycystic ovarian morphology. Its etiology is multifactorial and complex, and the absence of specific biomarkers remains a challenge for accurate diagnosis and effective clinical management. In this context, the present study aimed to analyze gene expression profiles using bioinformatics approaches to identify candidate molecular biomarkers associated with PCOS. For this purpose, publicly available data from the Gene Expression Omnibus (GEO) database were used to identify differentially expressed genes (DEGs), evaluate their biological functions, signaling pathways, and protein–protein interaction (PPI) networks. The methodology consisted of an in silico analysis of three datasets (GSE138518, GSE155489, and GSE193123) derived from granulosa cells obtained from patients with PCOS and control subjects. Differential expression analysis was performed using the limma package via the GEO2R tool, considering |log2FC| > 1 and an adjusted p-value < 0.05. In addition, criteria such as biological relevance, participation in enriched pathways, and centrality within PPI networks were considered. Integration of the three datasets resulted in the identification of 28 shared differentially expressed genes (DEGs) associated with inflammatory, immune-related, and lipid metabolism processes, including potential candidates such as CFH, HLA-DQB1, and APOC1, which may contribute to the pathophysiology of PCOS. Although these genes have previously been associated with pathways involved in the syndrome, the main contribution of this study lies in the integration of multiple transcriptomic datasets, which provides greater robustness and consistency in DEG identification. The findings expand the current understanding of the molecular mechanisms underlying PCOS and establish a relevant scientific basis for future investigations aimed at developing more precise diagnostic and therapeutic strategies.

COMMITTEE MEMBERS:
Externa à Instituição - BARBARA ALVES CABRAL - EBSERH
Presidente - 2328351 - GUSTAVO MAFALDO SOARES
Interna - 1055045 - MARCELA ABBOTT GALVAO URURAHY