Closing the evidence loop—membrane-lipid homeostasis and vesicular transport link DEHP exposure to endometriosis

Yonggang Dai, Lu Zhang, Tian Wang, Hao Liu, Wenyi Yang, Hongya Wang
Human genomics · 2025 · vol. 19(1) , pp. 156 · doi:10.1186/s40246-025-00881-z · PMID:41310859 · PMC12751832 · W4416739996
article OA: gold CC0
📄 Open PDF View on OpenAlex View on PubMed View at publisher
⚙ AI-generated summary by claude@2026-06, 2026-06-08 ⓘ

This study identifies a seven-gene signature involved in lipid metabolism and vesicular transport as a link between DEHP exposure and endometriosis, supported by computational modeling and molecular dynamics simulations.

One-sentence paraphrase of the abstract; not a substitute for reading it. No clinical advice. How this works

⚙ AI-generated deep summary by claude@2026-06, 2026-06-09 ⓘ

This study investigated how di(2-ethylhexyl) phthalate (DEHP) could connect environmental exposure to endometriosis biology by building an integrated pipeline from DEHP target prediction, multi-cohort endometriosis transcriptomics, and interpretable machine learning through structural/dynamical validation. Differential expression and WGCNA across three GEO endometriosis case–control datasets generated a high-confidence 229-gene set, whose intersection with DEHP-predicted targets yielded a 17-gene subnetwork enriched for a “membrane-lipid homeostasis → vesicular transport → detoxification/de-esterification” axis; a seven-gene signature (ELOVL6, LYPLA1, UGT8, SLC1A5, HMGCR, EPHX1, VAMP2) discriminated cases from controls with AUCs mostly >0.75 and molecular docking/100-ns MD supported stable DEHP binding for UGT8, ELOVL6, and HMGCR. The authors’ major caveat is that mechanistic conclusions are largely inferred from in silico target mapping and computational modeling rather than direct experimental exposure-to-effect validation in primary cells, organoids, or in vivo. This paper is centrally about endometriosis — it develops a DEHP-to-endometriosis regulatory framework anchored in membrane-lipid homeostasis, vesicular transport, and detoxification genes.

Read from the paper's body, not the abstract. Not a substitute for reading the paper. No clinical advice. How this works

Abstract

BACKGROUND: The causal bridge from environmental exposure to endometriosis (Ems) biology remains incompletely defined. Di(2-ethylhexyl) phthalate (DEHP) is repeatedly implicated in elevated Ems risk, yet actionable molecular anchors linking exposure to phenotype are scarce. METHODS: We established a multi-layered pipeline centered on DEHP. Comprehensive in silico target prediction across ChEMBL, PharmMapper, and SwissTargetPrediction yielded 1364 de-duplicated candidate proteins. Three transcriptomic cohorts (GSE51981, GSE6364, GSE7305) were integrated and analyzed using differential expression and Weighted Gene Co-expression Network Analysis (WGCNA) to derive a 229-gene, high-confidence Ems set. The intersection identified 17 overlapping genes, which were contextualized by protein-protein interaction (PPI) networks and Gene Ontology/Kyoto Encyclopedia of Genes and Genomes (GO/KEGG) enrichment. Interpretable machine learning with SHapley Additive exPlanations (SHAP) prioritized a core signature, followed by molecular docking and 100-ns molecular dynamics (MD) simulations to validate binding feasibility and temporal stability. RESULTS: The 17-gene overlap formed a compact functional subnetwork aligned with a "membrane-lipid homeostasis to vesicular transport to detoxification/de-esterification" axis. Classifiers showed robust discrimination across training and external cohorts (most area under the receiver operating characteristic curve [AUC] > 0.75), while single-gene receiver operating characteristic (ROC) analyses highlighted UGT8 (AUC = 0.869) and EPHX1 (0.853) as highly transferable. SHAP prioritized a seven-gene signature-ELOVL6, LYPLA1, UGT8, SLC1A5, HMGCR, EPHX1, and VAMP2-and revealed non-linear relationships, including ELOVL6-UGT8 synergy, HMGCR-LYPLA1 antagonism, and EPHX1-SLC1A5 context dependence. Docking supported pocket complementarity with ~ 2.2-3.3 Å hydrogen bonds plus extensive hydrophobic/π contacts; MD confirmed stable, compact, and persistent binding for UGT8-DEHP, ELOVL6-DEHP, and HMGCR-DEHP over 100 ns. CONCLUSIONS: This study establishes a comprehensive workflow spanning from chemical exposure identification to target discovery, disease network mapping, interpretable computational modeling, and structural/dynamical validation. We propose a DEHP-Ems regulatory framework underpinned by lipid metabolism, vesicular trafficking, and detoxification pathways. The resulting seven-gene signature provides a clinically applicable panel for diagnostic stratification and highlights potential therapeutic entry points, particularly along the HMGCR axis and via SLC1A5-mediated glutamine uptake. These findings lay the groundwork for future mechanistic studies in primary cell systems, organoid models, in vivo experiments, and prospective clinical validation.

My notes (saved in your browser only)

Condition tags

endometriosis

MeSH descriptors

Diethylhexyl Phthalate Diethylhexyl Phthalate Diethylhexyl Phthalate Diethylhexyl Phthalate Diethylhexyl Phthalate Diethylhexyl Phthalate Diethylhexyl Phthalate Diethylhexyl Phthalate Diethylhexyl Phthalate Diethylhexyl Phthalate Diethylhexyl Phthalate Diethylhexyl Phthalate Diethylhexyl Phthalate Diethylhexyl Phthalate Diethylhexyl Phthalate Diethylhexyl Phthalate Diethylhexyl Phthalate Endometriosis Endometriosis Endometriosis

Citation neighborhood

Papers in the corpus that this work cites (lower rings, blue) and that cite this one (upper rings, green). Dot size scales with the paper's in-corpus citation count — bigger dot = more influential within the endo/adeno field. Click a dot to open that paper. [ expand to 2 hops ] — adds papers reached through this work's immediate citers/citees. Heavier; up to 60 extra dots.

References (43)

Source provenance

europepmc
last seen: 2026-06-11T06:19:48.454388+00:00
openalex
last seen: 2026-06-10T17:14:06.276822+00:00
pmc
last seen: 2026-05-13T20:22:03.195721+00:00
pubmed
last seen: 2026-05-29T00:30:41.842162+00:00
License: CC0 · commercial use OK