Endometriosis is a chronic, hormone-dependent condition that affects 190 million women worldwide. There are no validated biomarkers for endometriosis and this delays diagnosis and treatment.

We performed serum steroid metabolome profiling in healthy controls (n=57) and women with laparoscopically-confirmed endometriosis (n=159) using liquid chromatography-tandem mass spectrometry. Women with endometriosis had a distinct steroid signature characterised by increased concentrations of classic and 11-oxygenated androgens, and altered metabolism associated with 11-ketotestosterone production.

Metabolomic data were used to generate a supervised machine learning model to predict diagnostic outcome. ROC curve analysis demonstrated robust discrimination between healthy controls and endometriosis patients (AUC=0.99) with 96.84% positive-, and 92.86% negative-predictive power. Data were partitioned into train and validation groups, and a refined model identified >95% of endometriosis patients in a blinded sample set.

These data reframe endometriosis as an androgen-dominant condition and present a unique opportunity to develop novel diagnostic approaches using 11-oxygenated androgens as biomarkers.

The authors have declared no competing interest.

This work was supported by the Wellcome Trust (Fellowship 220656/Z/20/Z to DAG, Investigator Award 209492/Z/17/Z to WA), Medical Research Council (Grant MRC/IAA/002 to DAG, program grant MR/N024524/1 to PTKS, and program grant MC_UP_1605/15 to WA) and the Institute for Regeneration and Repair Innovators award (funded by WT ITPA to DAG). Research conducted by the Edinburgh EXPPECT group that contributed to collection of biospecimens has been supported by grants from the MRC, Wellcome Trust, NIHR, CSO, and Wellbeing of Women.

I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.

Yes

The details of the IRB/oversight body that provided approval or exemption for the research described are given below:

Written informed consent was obtained prior to study participation from healthy volunteers identified through advertisement. Ethical approval was granted by the Science, Technology, Engineering and Mathematics Ethical Review Committees of the University of Birmingham, UK (ERN_17-0494, ERN_17-0494B). Written informed consent was obtained from all endometriosis study participants prior to surgery. Ethical approval was granted by the Lothian Research Ethics Committee (LREC 11/AL/0376), South Central-Hampshire A research ethics committee (IRAS:237815 REC reference 19/SC/0449) and Wales REC 6 A research ethics committee (IRAS 268806; REC ref: 19/WA/0271). Methods were carried out in accordance with Local Tissue Governance guidelines and international EPHect guidelines (https://endometriosisfoundation.org/ephect/).

I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals.

Yes

I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).

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I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable.

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All data produced in the present study are available upon reasonable request to the authors