Humans are exposed daily to complex mixtures of chemical pollutants through their environment and diet, some of which have the potential to disrupt the bodies’ natural endocrine functions and contribute to reproductive diseases like endometriosis. Increasing epidemiological and experimental evidence supports the association between endometriosis and certain persistent organic pollutants (POPs) like dioxins; however, little is known about the underlying linking mechanisms. The main objective of this study is to proof the methodological applicability and discovery potential of integrating ultra-trace mass spectrometry (MS) profiling of POP biomarkers and endogenous biomarker profiling (MS metabolomics and cytokines) in a case-control study for the etiological research of endometriosis. The approach is applied in a pilot clinical-based study conducted in France where women with and without surgically confirmed endometriosis were recruited. Serum samples were analysed with high-resolution MS for about 30 polychlorinated biphenyls (PCBs), organochlorinated pesticides and perfluoroalkyl substances (PFAS). About 600 serum metabolites and lipids were identified with targeted metabolomics using tandem MS with the Biocrates MxP® Quant 500 Kit. A panel of 4 pro-inflammatory cytokines were analysed using ELISA-based 4-PLEX analyser. Statistical analysis included a battery of variable selection approaches, multivariate logistic regression for single-chemical associations, Bayesian kernel machine regressions (BKMR) to identify mixture effects of POPs and a multiblock approach to identify shared biomarker signatures among high risk clusters. The results showed the positive associations between some POPs and endometriosis risk, including the pesticide trans-nonachlor Odds Ratio (95% Confidence Interval) 3.38 (2.06–5.98), p < 0.0001 and PCB 114 OR (95% CI) 1.83 (1.17–2.93), p = 0.009. The BKMR approach showed a tendency of a positive cumulative effect of the mixture, however trans-nonachlor exhibited significant associations within the mixture and interacted with other PCBs, strengthening the effects at highest concentrations. Finally, the multiblock analysis, relating the various blocks of data, revealed a latent cluster of women with higher risk of endometrioma presenting higher concentrations of trans-nonachlor, PCB 114 and dioxin-like toxic equivalents from PCBs, together with an increased inflammatory profile (i.e. elevated interleukin-8 and monocyte chemoattractant protein-1). It was also highlighted a specific metabolic pattern characterized by dysregulation of bile acid homeostasis and lipase activity. Further research will be required with larger sample size to confirm these findings and gain insight on the underlying mechanisms between POPs and endometriosis.

人类每天都会通过环境和饮食接触到复杂的化学污染物混合物，其中一些有可能破坏身体的自然内分泌功能并导致子宫内膜异位症等生殖疾病。越来越多的流行病学和实验证据支持子宫内膜异位症与某些持久性有机污染物（POPs）如二恶英之间的关联；然而，人们对潜在的链接机制知之甚少。本研究的主要目的是证明在病例对照研究中整合 POP 生物标志物的超痕量质谱 (MS) 分析和内源性生物标志物分析（MS 代谢组学和细胞因子）的方法学适用性和发现潜力子宫内膜异位症。该方法应用于在法国进行的一项基于临床的试点研究，该研究招募了有和没有手术证实的子宫内膜异位症的女性。使用高分辨率 MS 分析血清样品中大约 30 种多氯联苯 (PCB)、有机氯农药和全氟烷基物质 (PFAS)。使用串联 MS 和 Biocrates MxP® Quant 500 试剂盒，通过靶向代谢组学鉴定了大约 600 种血清代谢物和脂质。使用基于 ELISA 的 4-PLEX 分析仪分析了一组 4 种促炎细胞因子。统计分析包括一系列变量选择方法、单一化学关联的多变量逻辑回归、贝叶斯核机器回归 (BKMR) 以识别 POPs 的混合效应，以及用于识别高风险集群之间共享生物标志物特征的多块方法。反式壬草胺优势比（95% 置信区间）3.38 (2.06–5.98), p < 0.0001 和 PCB 114 OR (95% CI) 1.83 (1.17–2.93), p = 0.009。BKMR 方法显示混合物具有积极累积效应的趋势，但反式壬草胺在混合物中表现出显着的关联并与其他 PCB 相互作用，从而在最高浓度下增强了效果。最后，将各种数据块关联起来的多块分析揭示了一组潜在的子宫内膜异位症风险较高的女性，其反式浓度较高。- 壬草胺、多氯联苯 114 和多氯联苯中的二恶英类毒性等效物，以及炎症特征增加（即白细胞介素 8 和单核细胞趋化蛋白 1 升高）。它还强调了以胆汁酸稳态和脂肪酶活性失调为特征的特定代谢模式。需要更大样本量的进一步研究来证实这些发现并深入了解持久性有机污染物与子宫内膜异位症之间的潜在机制。