Ecotoxicology and Environmental Safety (Nov 2024)

Associations between phenols, parabens, and phthalates and depressive symptoms: The role of inflammatory markers and bioinformatic insights

  • Luli Wu,
  • Junrou Zhang,
  • Ye Xin,
  • Junxiang Ma,
  • Tian Chen,
  • Jisheng Nie,
  • Piye Niu

Journal volume & issue
Vol. 286
p. 117191

Abstract

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Phenols, parabens, and phthalates are commonly found in consumer products, yet there is limited research on their individual and combined effects on depressive symptoms, particularly regarding the role of inflammation in these associations. This study aimed to evaluate these effects and explore potential molecular mechanisms, with a focus on inflammation as a mediator. We conducted a cross-sectional analysis involving 2766 adult participants from the National Health and Nutrition Examination Survey (NHANES) 2013–2016. Urine samples were analyzed for 15 chemicals, including 3 phenols, 2 parabens, and 10 phthalates. Depressive symptoms were assessed using the Patient Health Questionnaire-9 (PHQ-9). Statistical analyses included linear regression, restricted cubic splines, Bayesian Kernel Machine Regression and quantile g-computation models to investigate the relationships between chemical exposures and depressive symptoms. Additionally, mediation analysis was employed to explore the potential role of inflammation (immune cells, CRP, NLR) in these associations. The underlying molecular mechanisms were analyzed using bioinformatic approaches. Notably, BPA, MECPP, MEHHP, MiBP and MBP were found to be positively associated with depressive symptoms among females. Besides, BPA was the most significant positive contributor to the effect in the context of the chemical mixture, while the overall mixture effect was relatively weak. Furthermore, WBC were found to mediate a marginal portion (4 %) of the potential effects of MBP on depressive symptoms. The 15 genes identified are primarily involved in neurotransmission, mood regulation, and stress response. Further research is needed to elucidate the mechanisms underlying the observed associations.

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