Endometriosis - on the intersection of modern environmental pollutants and ancient genetic regulatory variants

Anna Mantzouratou, Amelia Warren, Demetra Andreou, Dean Warren, Jack Wieland
In: Research Square · 2025 · doi:10.21203/rs.3.rs-6639771/v1 · W4411135393
preprint OA: green CC0
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⚙ AI-generated summary by claude@2026-06+body, 2026-06-07 ⓘ

This study investigated how ancient genetic variants, particularly those from Neanderthal and Denisovan introgression, interact with environmental pollutants to influence endometriosis risk by analyzing whole-genome sequencing data and regulatory databases.

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⚙ AI-generated deep summary by claude@2026-06, 2026-06-07 ⓘ

This preprint studied whether regulatory genetic variants, including variants attributed to ancient hominin introgression (Neanderthal and Denisovan), interact with modern endocrine-disrupting chemical (EDC) exposures to shape susceptibility to early-stage endometriosis. Using a dual-phase literature review, the authors selected five candidate genes (IL-6, CNR1, IDO1, TACR3, and KISS1R), then analyzed whole-genome sequencing data from 19 female participants with clinically confirmed endometriosis from the Genomics England 100,000 Genomes Project, performing variant enrichment, co-localisation, linkage disequilibrium, and functional interpretation with public regulatory databases. They report six regulatory variants significantly enriched in cases versus matched controls and the broader Genomics England population, including IL-6 variants rs2069840 and rs34880821 at a Neanderthal-derived methylation site with potential immune dysregulation, and variants in CNR1 and IDO1 (partly Denisovan origin) that overlap EDC-responsive regulatory regions. A major limitation is the very small cohort size (n=19) and stage estimation based on available clinical information because the database did not specify disease stage; This paper is centrally about endometriosis — it investigates gene-environment interactions between ancient regulatory variants and EDC-responsive regions to propose an endometriosis susceptibility model and potential early-stage biomarkers.

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endometriosis

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