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Updated: Jun 29, 2026
A Neural Network-Based Identification of Developmentally Competent or Incompetent Mouse Fully-Grown Oocytes
Published on: March 3, 2018
Multiomics identification of programmed cell death-related characteristics for nonobstructive azoospermia based on a
Shuqiang Huang1, Cuiyu Tan1, Wanru Chen2
1Center for Reproductive Medicine, the Affiliated Qingyuan Hospital (Qingyuan People's Hospital), Guangzhou Medical University, Qingyuan, Guangdong 511518, China.
Background:
Abnormal programmed cell death (PCD) plays a central role in spermatogenic dysfunction. However, the molecular mechanisms and biomarkers of PCD in patients with nonobstructive azoospermia (NOA) remain unclear.
Methods:
The genetic conditions of NOA patients were analysed using bulk transcriptomic, single-cell transcriptomic, single nucleotide polymorphism (SNP), and clinical data from multiple centres. A total of 675 machine learning methods were applied to construct models from 12 different PCDs and to screen for distinctive genes. A new PCDscore system was created to measure the degree of PCD in patients. Using the NOA mouse model, TUNEL, qRT-PCR, Western blotting, and immunohistochemistry (IHC) were utilized to validate the PCD status in NOA testes and the expression levels of hub PCD-related genes (PCDRGs). Mouse testicular samples were used for sequencing of the whole transcriptome. The sequencing results were used to evaluate the correlation between PCD scores and expression of hub genes.
Results:
A PCDscore system was built using 12 characteristic PCDRGs chosen by machine learning. PCD scores correlated with gene interaction and immune activity changes. Leydig, Sertoli, and T cells were prominent in cell interactions with PCDscore changes. PCDscore in the NOA mouse testis was increased. Among the 12 PCDRGs, BCL2L14, GGA1, GPX4, PHKG2, and SLC39A8 were strongly linked to spermatogenesis. BCL2L14, GGA1, GPX4, and PHKG2 strongly correlated with PCD statuses. The changes in the expression of these genes may be due to the effects of SNPs, which may lead to the male reproductive system disorders.
Conclusions:
Our study provides new insights into PCD-related mechanisms in NOA patients via multiomics and proposes reliable models for the diagnosis of NOA via the use of PCD biomarkers. A deeper understanding of these mechanisms may aid in the clinical diagnosis and treatment of NOA.
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