Multi-omics integration of the vaginal microbiome and inflammatory proteome for non-invasive prediction of infertility: a machine learning approach
A vaginal microbiome-based SVM model achieved an AUC of 0.815 in distinguishing infertile women from healthy controls.
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Context
Female infertility diagnosis often relies on invasive and costly procedures. Non-invasive biomarkers derived from the vaginal microenvironment could enable earlier and less burdensome screening.
What the study showed
The microbiome-only SVM model (14 microbial features) outperformed the proteomic XGBoost model (AUC 0.629) and matched the combined multi-omics SVM model (AUC 0.799). SHAP analysis identified specific microbial genera as the primary predictive contributors, while only 4 inflammatory proteins were retained after feature selection.
How it was done
Cross-sectional study enrolling 205 women (76 infertile, 129 controls) between October 2025 and February 2026. Vaginal swabs underwent 16S rRNA sequencing and Olink Target 96 Inflammation panel profiling; eight ML algorithms were trained on 143 participants and validated on 62.
Risk of bias
Small sample size (n=205), a 4-month recruitment window, and a cross-sectional design preclude causal inference. This analysis is based on the abstract only; full methodological details were not available. The operational definition of infertility and exclusion criteria are not described in the abstract.
What this study does NOT prove
This study does not prove that the vaginal microbiome causes infertility, nor that the model performs reproducibly across clinically distinct populations.
In clinical practice
Findings are exploratory and insufficient to change current diagnostic practice. External validation in larger independent cohorts is required before any clinical translation.
Limitations
Small sample size (n=205), a 4-month recruitment window, and a cross-sectional design preclude causal inference. This analysis is based on the abstract only; full methodological details were not available. The operational definition of infertility and exclusion criteria are not described in the abstract.
Technical appendix
Version history
- 1.0 · 2026-11-05 — Auto-generated under Evidence Standard v1.0