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<p>Endometriosis is a common yet often underdiagnosed condition, partly due to the lack of reliable diagnostics. This study examines the clinical feasibility of a blood-based, miRNA-driven test to diagnose endometriosis and address the challenges of translating next-generation sequencing (NGS) findings into clinical use. Serum from 20 patients and 20 controls underwent miRNA sequencing to identify diagnostic biomarkers. A machine learning model built on all NGS-based differentially expressed miRNA biomarkers achieved ≥90% accuracy. Validation by qPCR confirmed some but not all findings, underscoring the difficulty of adapting NGS discoveries for routine diagnostics. Nonetheless, serum miRNA biomarkers show strong promise for non-invasive endometriosis detection, with further optimization needed for clinical translation.</p>

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Translation of miRNA blood-based discovery to molecular testing for clinical diagnosis of endometriosis

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年12月1日

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  • Yanqin Yu,
  • Wing Hing Wong,
  • Yao Hu,
  • Yirong Shen,
  • Xiaochun Xu,
  • Shen Lu,
  • Libo Zhu,
  • Xinmei Zhang,
  • Farideh Z. Bischoff

摘要

Endometriosis is a common yet often underdiagnosed condition, partly due to the lack of reliable diagnostics. This study examines the clinical feasibility of a blood-based, miRNA-driven test to diagnose endometriosis and address the challenges of translating next-generation sequencing (NGS) findings into clinical use. Serum from 20 patients and 20 controls underwent miRNA sequencing to identify diagnostic biomarkers. A machine learning model built on all NGS-based differentially expressed miRNA biomarkers achieved ≥90% accuracy. Validation by qPCR confirmed some but not all findings, underscoring the difficulty of adapting NGS discoveries for routine diagnostics. Nonetheless, serum miRNA biomarkers show strong promise for non-invasive endometriosis detection, with further optimization needed for clinical translation.