Bioinformatics-driven identification and validation of hub genes regulating endometriosis-related infertility within human granulosa cells

Jiahuan Luo; Huawei Wang; Ling Zhou; Jinyuan Wang; Mengjie Song; Yulin Cheng; Meng Rao; Shuhua Zhao; Li Tang

doi:10.1016/j.rbmo.2025.104826

Bioinformatics-driven identification and validation of hub genes regulating endometriosis-related infertility within human granulosa cells

Reprod Biomed Online. 2025 Jan 14;51(2):104826. doi: 10.1016/j.rbmo.2025.104826. Online ahead of print.

Authors

Jiahuan Luo¹, Huawei Wang¹, Ling Zhou¹, Jinyuan Wang¹, Mengjie Song¹, Yulin Cheng¹, Meng Rao², Shuhua Zhao³, Li Tang⁴

Affiliations

¹ Department of Reproductive Genetics, First Affiliated Hospital of Kunming Medical University, Kunming, China.
² Department of Reproductive Genetics, First Affiliated Hospital of Kunming Medical University, Kunming, China. Electronic address: rm3816205@163.com.
³ Department of Reproductive Genetics, First Affiliated Hospital of Kunming Medical University, Kunming, China. Electronic address: kmshh1982@126.com.
⁴ Department of Reproductive Genetics, First Affiliated Hospital of Kunming Medical University, Kunming, China. Electronic address: tanglikm@163.com.

PMID: 40580573
DOI: 10.1016/j.rbmo.2025.104826

Abstract

Research question: Can bioinformatics-driven identification of hub genes in granulosa cells be used to predict oocyte developmental potential in patients with endometriosis (EMS)-related infertility?

Design: This was an exploratory cohort study on EMS-related infertility. An RNA sequencing dataset (GSE168214) related to EMS-related infertility was obtained from the Gene Expression Omnibus database to identify hub differentially expressed genes (DEG). Granulosa cell samples from 18 patients with EMS-related infertility and 76 patients with tubal-related infertility were further examined by quantitative real-time polymerase chain reaction (qRT-PCR) and analysed for their levels in relation to IVF/intracytoplasmic sperm injection outcomes.

Results: In total, 37 DEG and five hub genes (BTG2, FOSB, NR4A1, NR4A2 and NR4A3) were identified. BTG2 was selected as the preferred candidate hub gene for further validation. Expression levels of BTG2 detected by qRT-PCR were consistent with RNA sequencing results showing reduced expression in patients with EMS (P = 0.001). Moreover, BTG2 mRNA expression was negatively correlated with basal FSH [adjusted OR (aOR) 0.671, 95% CI 0.488-0.923; P = 0.014] and LH on the day of human chorionic gonadotrophin trigger (aOR 0.765, 95% CI 0.593-0.987; P = 0.039), and positively correlated with oocyte retrieval rate (aOR 1.012, 95% CI 1.004-1.021; P = 0.004), number of blastocysts formed (aOR 1.080, 95% CI 1.010-1.155; P = 0.024) and blastocyst formation rate (aOR 1.080, 95% CI 1.010-1.155; P = 0.001).

Conclusion: Bioinformatics-driven identification of BTG2, one of the hub genes in granulosa cells, has the potential to serve as a novel non-invasive biomarker for predicting the oocyte developmental potential of patients with EMS-related infertility.

Keywords: BTG2; Bioinformatics; Endometriosis-related infertility; Granulosa cells; Hub genes.