An Anti-Metabolic Prodromal Phenotype in Endometriosis

Laurence A Jacobs, Carlos A. Aguilar-Salinas
2026 · doi:10.5281/zenodo.22762765 · W7213289972
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This UK Biobank cohort study identified an anti-metabolic prodromal phenotype in endometriosis, characterized by lower metabolic dysfunction and lean body composition, using a machine learning pipeline on 233 candidate features.

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This prospective cohort study analyzed data from 273,043 female participants in the UK Biobank to identify prodromal biomarkers for incident endometriosis using a multi-stage machine learning pipeline. The researchers found that endometriosis is associated with an anti-metabolic phenotype characterized by lower metabolic dysfunction, reduced pulse pressure, and lean body composition. This profile stands in sharp contrast to the pro-metabolic signatures typically observed in cardiovascular, renal, and hepatic diseases. This paper is centrally about endometriosis — specifically characterizing its unique anti-metabolic prodromal phenotype distinct from other chronic conditions.

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Abstract

Endometriosis exhibits an anti-metabolic prodromal phenotype: lower metabolic dysfunction, lower pulse pressure, and a lean body composition, in sharp contrast to the pro-metabolic signatures of cardiovascular, renal, and hepatic disease. Endometriosis affects approximately 10% of reproductive- age women and is associated with chronic pelvic pain, infertility, and reduced quality of life. Epidemiological studies have reported inverse associations between endometriosis and cardiovascular risk factors, but no study has characterized a comprehensive prodromal biomarker signature or framed the condition within a multi-disease prediction architecture. This was a prospective cohort study of 273,043 female UK Biobank participants (enrollment 2006–2010; median follow-up 14.1 years). Incident endometriosis was identified from Hospital Episode Statistics (ICD-10 N80). A four- stage machine learning pipeline (literature priors, univariate screening, gradient-boosted feature selection, logistic regression) using 233 candidate features was applied with 5- fold cross-validation.
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An Anti-Metabolic Prodromal Phenotype in Endometriosis Authors/Creators - 1. Center for Molecular Cardiology, University of Zurich - 2. Center for Complexity Sciences, National University of Mexico - 3. Instituto Nacional de Ciencias Medicas y Nutricion Salvador Zubiran Description Endometriosis exhibits an anti-metabolic prodromal phenotype: lower metabolic dysfunction, lower pulse pressure, and a lean body composition, in sharp contrast to the pro-metabolic signatures of cardiovascular, renal, and hepatic disease. Endometriosis affects approximately 10% of reproductive- age women and is associated with chronic pelvic pain, infertility, and reduced quality of life. Epidemiological studies have reported inverse associations between endometriosis and cardiovascular risk factors, but no study has characterized a comprehensive prodromal biomarker signature or framed the condition within a multi-disease prediction architecture. This was a prospective cohort study of 273,043 female UK Biobank participants (enrollment 2006–2010; median follow-up 14.1 years). Incident endometriosis was identified from Hospital Episode Statistics (ICD-10 N80). A four- stage machine learning pipeline (literature priors, univariate screening, gradient-boosted feature selection, logistic regression) using 233 candidate features was applied with 5- fold cross-validation. Files An Anti-Metabolic Prodromal Phenotype in Endometriosis [draft v6].pdf Files (742.7 kB) | Name | Size | Download all | |---|---|---| | md5:acf1c94eb6b00620838c26fd637f7b6f | 742.7 kB | Preview Download |

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