Microbiome based detection of endometriosis
A non-invasive method using genomic analysis and machine learning to detect endometriosis by analyzing phase-specific microbial signatures in the female reproductive tract addresses the challenge of delayed diagnosis, enabling early and accurate detection.
WO2026117762A1PCT designated stage Publication Date: 2026-06-04HERANOVA LIFESCIENCES INC
Patent Information
- Authority / Receiving Office
- WO · WO
- Patent Type
- Applications
- Current Assignee / Owner
- HERANOVA LIFESCIENCES INC
- Filing Date
- 2025-11-27
- Publication Date
- 2026-06-04
AI Technical Summary
Technical Problem
Current diagnostic methods for endometriosis are invasive and often lead to delayed diagnosis, causing unnecessary suffering and reduced quality of life, highlighting the need for non-invasive and early detection tools.
Method used
A non-invasive method integrating high-throughput genomic analysis and advanced computational modeling to detect phase-specific microbial signatures associated with endometriosis by quantifying bacterial taxa and calculating a Functional Dysbiosis Score (FDS) using a trained machine learning classifier.
Benefits of technology
Enables early and accurate detection of endometriosis through the analysis of the female reproductive tract microbiome, reducing diagnostic delays and improving treatment outcomes.
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Abstract
Provided herein are methods of assessing whether a subject has endometriosis or is predisposed to endometriosis based on microbiome-based biomarkers in a sample of the subject. Kits useful for performing such assessments are also provided. Methods of treating or preventing endometriosis guided by information obtained from methods disclosed herein are also provided.
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