Implications of estrogen receptor alpha (ERa) with the intersection of organophosphate flame retardants and diet-induced obesity in adult mice.
Gwyndolin M VailSabrina N WalleyAli YasrebiAngela MaengThomas J DegroatKristie M CondeTroy A RoepkePublished in: Journal of toxicology and environmental health. Part A (2022)
Previously, organophosphate flame retardants (OPFRs) were found to produce intersecting disruptions of energy homeostasis using an adult mouse model of diet-induced obesity. Using the same mixture consisting of 1 mg/kg/day of each triphenyl phosphate, tricresyl phosphate, and tris(1,3-dichloro-2-propyl)phosphate, the current study aimed to identify the role of estrogen receptor alpha (ERα) in OPFR-induced disruption, utilizing ERα knockout (ERαKO) mice fed either a low-fat diet (LFD) or high-fat diet (HFD). Body weight and composition, food intake patterns, glucose and insulin tolerance, circulating peptide hormones, and expression of hypothalamic genes associated with energy homeostasis were measured. When fed HFD, no marked direct effects of OPFR were observed in mice lacking ERα, suggesting a role for ERα in generating previously reported wildtype (WT) findings. Male ERαKO mice fed LFD experienced decreased feeding efficiency and altered insulin tolerance, whereas their female counterparts displayed less fat mass and circulating ghrelin when exposed to OPFRs. These effects were not noted in the previous WT study, indicating that loss of ERα may sensitize animals fed LFD to alternate pathways of endocrine disruption by OFPRs. Collectively, these data demonstrate both direct and indirect actions of OPFRs on ERα-mediated pathways governing energy homeostasis and support a growing body of evidence urging concern for risk of human exposure.
Keyphrases
- estrogen receptor
- high fat diet
- high fat diet induced
- insulin resistance
- type diabetes
- adipose tissue
- endoplasmic reticulum
- mouse model
- body weight
- weight loss
- metabolic syndrome
- endothelial cells
- body mass index
- poor prognosis
- physical activity
- blood pressure
- high glucose
- young adults
- big data
- machine learning
- oxidative stress
- artificial intelligence
- data analysis
- diabetic rats