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Endocrine-disrupting chemicals (EDCs) are ubiquitous environmental contaminants that interfere with hormonal signaling and have been linked to multiple diseases, yet their molecular contribution to migraine remains unclear. This study aims to identify EDC-related genes contributing to migraine risk and explore underlying mechanisms using an integrative multi-omics and causal inference framework.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We curated 181 EDCs and identified 1,116 EDC-related genes through chemical-gene interaction network analysis, followed by integration of multi-omics quantitative trait loci datasets (eQTL, sQTL, mQTL, and pQTL) to derive genetic instruments. Summary data-based Mendelian randomization (SMR) was performed to assess the effects of genetically predicted molecular traits on migraine risk using genome-wide association study (GWAS) data from the OpenGWAS and GWASCatalog. HEIDI testing and Bayesian colocalization analyses were conducted to distinguish pleiotropy from linkage and to prioritize genes with shared causal variants, followed by transcriptome-wide association study (TWAS) for validation. Multi-omics integration and differential gene expression analysis were used to characterize regulatory mechanisms. Finally, molecular docking and molecular dynamics simulations were performed to evaluate interactions between prioritized EDCs and molecular targets implicated in migraine pathophysiology.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Eight EDC-related genes were identified as significantly associated with migraine risk, of which\n                      <jats:italic>MEF2D<\/jats:italic>\n                      ,\n                      <jats:italic>OSBPL10<\/jats:italic>\n                      ,\n                      <jats:italic>B9D2<\/jats:italic>\n                      ,\n                      <jats:italic>HTRA1<\/jats:italic>\n                      and\n                      <jats:italic>PRDM16<\/jats:italic>\n                      were classified as high- or medium-evidence genes. Notably,\n                      <jats:italic>PNKP<\/jats:italic>\n                      and\n                      <jats:italic>B9D2<\/jats:italic>\n                      demonstrated consistent cross\u2011tissue evidence across multiple molecular layers, including TWAS, gene expression, DNA methylation, and alternative splicing.\n                      <jats:italic>PNKP<\/jats:italic>\n                      , prioritized through integrative analyses of EDC-related genes and migraine-associated omics datasets, exhibited limited individual differential gene expression but significant enrichment of pathways related to hypothalamic\u2013pituitary axis dysfunction, blood circulation, and pain signaling. Molecular docking and dynamics simulations further suggested stable binding between migraine-related target proteins and prioritized EDCs, including triphenyl phosphate (TPP), tris(1,3-dichloro-2-propyl) phosphate (TDCPP), and benzo(a)pyrene (B[a]P), providing preliminary connections between EDC exposure and migraine at the molecular level.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>This study provides integrative genetic and multi-omics evidence suggesting that EDC-related genes may be associated with to migraine susceptibility, highlighting the potential role of environmental factors to migraine risk. These findings identify a set of candidate EDCs and molecular targets that warrant further investigation, offering novel insights into migraine pathogenesis and informing future research on environmental determinants and preventive strategies for migraine.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1186\/s10194-026-02412-0","type":"journal-article","created":{"date-parts":[[2026,6,8]],"date-time":"2026-06-08T09:24:17Z","timestamp":1780910657000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Integrative multi-omics analysis identifies endocrine-disrupting chemical-related molecular mechanisms in migraine"],"prefix":"10.1186","volume":"27","author":[{"given":"Yinfan","family":"Ren","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ziqi","family":"Xu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zifei","family":"Xu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Guifang","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Huanjie","family":"Huang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chuhuai","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiao-Qian","family":"Hu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,6,8]]},"reference":[{"key":"2412_CR1","doi-asserted-by":"publisher","first-page":"1315","DOI":"10.1016\/S0140-6736(18)30478-1","volume":"391","author":"DW Dodick","year":"2018","unstructured":"Dodick DW (2018) Migraine. 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