4.7 Article

Adipose to serum ratio and mixtures of persistent organic pollutants in relation to endometriosis: Findings from the ENDO Study

Journal

ENVIRONMENTAL RESEARCH
Volume 195, Issue -, Pages -

Publisher

ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.envres.2021.110732

Keywords

Endometriosis; Endocrine disrupting chemicals; Mixtures; Omental adipose; Organochlorine pesticide; Polychlorinated biphenyl; Polybrominated diphenyl ether

Funding

  1. Endometriosis Foundation of America
  2. NIEHS [R01-ES031079]
  3. Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), National Institutes of Health [NO1-DK-6-3428, NO1-DK-6-3427, 10001406-02]

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The study found that lipophilic endocrine disrupting chemicals are associated with incident endometriosis. Adipose-to-serum ratio of estrogenic PCBs and OCPs in adipose tissue may increase the risk of endometriosis. Bayesian models indicate differences in associations between adipose and ASR for these chemicals and endometriosis.
Background: Endometriosis is an estrogen-dependent disease. Endocrine disrupting chemicals (EDCs) and their mixtures may play an etiologic role. Objectives: We evaluated an adipose-to-serum ratio (ASR) of lipophilic EDCs and their mixtures associated with incident endometriosis. Methods: We quantified 13 polychlorinated biphenyl (PCB) congeners, 6 polybrominated diphenyl ether (PBDE) congeners, and 11 organochlorine pesticides (OCPs) in serum and omental fat among women from the ENDO Study (2007-2009) aged 18-44 years diagnosed with (n=190) or without (n=283) surgically-visualized incident endometriosis. Odds ratios (OR) and 95% confidence intervals (CI) between ASR and endometriosis were estimated using logistic regression models adjusted for age (years), body mass index (kg/m(2)), serum cotinine (ng/Yml), and breastfeeding conditional on parity. Bayesian hierarchical models (BHM) compared estimated associations for adipose and ASR to serum. Bayesian kernel machine regression (BKMR) estimated change in latent health and 95% posterior intervals (PI) between chemical mixtures and endometriosis. Results: Select ASR for estrogenic PCBs and OCPs were associated with an increased odds of an endometriosis diagnosis, but not for anti-estrogenic PCBs or PBDEs. Across all chemicals, BHMs generated ORs that were on average 14% (95% PI: 6%, 22%) higher for adipose and 20% (95% PI: 12%, 29%) higher for ASR in comparison to serum. ORs from BHMs were greater for estrogenic PCBs and OCPs, with no differences for PBDEs. BKMR models comparing the 75th to 25th percentile were moderately associated with endometriosis for estrogenic PCBs [adipose 0.27 (95% PI: 0.18, 0.72) and ASR 0.37 (95% PI: 0.06, 0.80)] and OCPs [adipose 0.17 (95% PI: 0.21, 0.56) and ASR 0.26 (95% PI: 0.05, 0.57)], but not for antiestrogenic PCBs and PBDEs. Discussion: ASR added little insight beyond adipose for lipophilic chemicals. BKMR results supported associations between ASR and adipose estrogenic PCB and OCP mixtures and incident endometriosis. These findings underscore the importance of choice of biospecimen and considering mixtures when assessing exposure-disease relationships.

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