Integrative analysis of hub genes for recurrent pregnancy loss with antiphospholipid syndrome: integrated bioinformatics analysis, machine learning and experimental validation - Report - MDSpire

Integrative analysis of hub genes for recurrent pregnancy loss with antiphospholipid syndrome: integrated bioinformatics analysis, machine learning and experimental validation

  • By

  • Huan Zeng

  • Chengming Ding

  • Weilei Dong

  • Haochuan Long

  • Zhen Liu

  • Yulu Guo

  • Yuji Xiao

  • Wenyan Liao

  • June 4, 2026

  • 0 min

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Clinical Report: Key Genes in Recurrent Pregnancy Loss and Antiphospholipid Syndrome

Overview

This study identifies three hub genes associated with recurrent pregnancy loss (RPL) in patients with antiphospholipid syndrome (APS), enhancing understanding of their pathogenesis. The findings suggest potential biomarkers and therapeutic targets for RPL linked to APS.

Background

Recurrent Pregnancy Loss (RPL) significantly impacts reproductive health, affecting approximately 2.5% of women. Antiphospholipid Syndrome (APS) is a leading cause of immune-related RPL, with a prevalence of 7%–25% among affected women. Understanding the genetic underpinnings of RPL in the context of APS is crucial for developing targeted diagnostic and therapeutic strategies.

Data Highlights

GeneExpression Change
NAA30Hub Gene Identified
ARHGAP44Hub Gene Identified
SUGT1Downregulated in RPL with APS

Key Findings

  • Identified 10 common differentially expressed genes (DEGs) in RPL and APS.
  • Eight DEGs were downregulated and two were upregulated.
  • Imbalance of immune system-associated cells is a characteristic of both APS and RPL.
  • Machine learning techniques identified NAA30, ARHGAP44, and SUGT1 as hub genes.
  • SUGT1 influences the biological behavior of trophoblast cells.

Clinical Implications

The identification of hub genes provides potential biomarkers for diagnosing RPL in APS patients. Clinicians may consider these genes in developing targeted therapeutic strategies to improve pregnancy outcomes in affected women.

Conclusion

This study enhances the understanding of the molecular mechanisms underlying RPL associated with APS and highlights potential diagnostic and therapeutic targets.

Related Resources & Content

  1. Frontiers in Immunology, 2026 -- Multi-omics insights into immune tolerance at the maternal–fetal interface in recurrent pregnancy loss: mechanisms, integration challenges, and translational perspectives
  2. American Journal of Epidemiology, 2023 -- A novel approach for inferring effects on pregnancy loss
  3. JMIR Medical Informatics, 2026 -- Adverse Pregnancy Outcomes in Women With Immune Abnormalities: Machine Learning Model Development and Validation Using First-Trimester Sonographic Features
  4. Recurrent pregnancy loss: a committee opinion (2026) | American Society for Reproductive Medicine | ASRM
  5. Frontiers in Endocrinology — Bioinformatics and machine learning-driven discovery of candidate tissue diagnostic markers for endometriosis with experimental verification
  6. Guideline No. 464: Recurrent Pregnancy Loss - ScienceDirect
  7. Recurrent pregnancy loss: a committee opinion (2026) | American Society for Reproductive Medicine | ASRM
  8. Hydroxychloroquine and pregnancy outcomes in patients with anti-phospholipid syndrome: a systematic review and meta-analysis - PMC

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