Using mixture and exposome methods to assess the associations and interactions of chemical biomarkers with semen parameters - Maximilien Génard-Walton; Charline Warembourg; Paige L. Williams; Irene Souter; Jennifer B. Ford; Jorge E. Chavarro; Russ Hauser; Lidia Mínguez-Alarcón (Environment International)
Background: Although epidemiologic studies have found associations between several chemical biomarkers and semen parameters, only a few studies have evaluated their combined effects and interactions. Methods: We included 420 men aged 18–55 years who participated in the Environment and Reproductive Health (EARTH) study between 2005 and 2019 at the Massachusetts General Hospital Fertility Center. Four mixture/exposome models, including exposome-wide association studies (ExWAS), Deletion/Substitution/Addition algorithm (DSA), Bayesian Kernel Machine Regression (BKMR), and the non-linear interaction model (NLinteraction), were used to evaluate associations between 24 chemical biomarkers (urinary bisphenol A, four parabens, triclosan, 17 phthalate metabolites, and hair mercury [Hg]) and semen parameters (sperm count, concentration, morphology, motility, and semen volume). Results: Overall, Hg was positively, and triclosan was negatively significantly associated with all semen outcomes except semen volume across multiple models. In BKMR, when increasing the mixture from the 10th to 90th percentile, the chemical mixture was negatively associated with percent normal sperm morphology (−1.42 %, 95 % Credibility Interval [CRI] −12.36; 9.52), motility (−0.10 %, 95 % CRI −1.78; 1.58), and volume (−0.26 mL, 95 % CRI −0.79; 0.28), and positively associated with sperm count (0.21 mill, 95 % CRI −0.23; 0.65) and concentration (0.33 mill/mL, 95 % CRI −0.14; 0.80). We detected one interaction between urinary triclosan and butylparaben in relation to normal sperm morphology using NLinteraction. Conclusion: Among 24 biomarkers tested, Hg and triclosan showed consistent associations with semen parameters while other biomarkers were less consistent depending on the model used. Similar research studies should be encouraged to use multiple models to incorporate interaction assessment and assess the robustness of results.