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

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.

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Publication Details

Journal
npj Women s Health
Published
2025-12-01
DOI
https://doi.org/10.1038/s44294-025-00116-5
Citations
1
Primary Topic
Endometriosis Research and Treatment
Type
article
Field-Weighted Citation Impact
1.70
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article

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

Yirong Shen, Farideh Z. Bischoff, Yao Hu, Winghing Wong et al.
1 citations
npj Women s Health
Endometriosis Research and Treatment
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article

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

Yirong Shen, Farideh Z. Bischoff, Yao Hu, Winghing Wong, Lu Shen, Xinmei Zhang, Libo Zhu, Xiaochun Xu, Yanqin Yu
article en
1 citations

Abstract

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.

npj Women s HealthVol. 3(1)
Women's Hospital, School of Medicine, Zhejiang University (CN), Edwards Lifesciences (Switzerland) (CH)
Openalex Percentile: Top 11%
Endometriosis Research and Treatment
1.70
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Translation of miRNA blood-based discovery to molecular testing for clinical diagnosis of endometriosis — Yirong Shen, Farideh Z. Bischoff, et al. · npj Women s Health (2025) | TGRS Research Map | TGRS