Association of Prenatal Exposure to Endocrine-Disrupting Chemicals With Liver Injury in Children

Midya, Vishal; Colicino, Elena; Conti, David V.; Berhane, Kiros; Garcia, Erika; Stratakis, Nikos; Andrušaitytė, Sandra; Basagaña, Xavier; Casas, Maribel; Fossati, Serena; Haug, Line Småstuen; Heude, Barbara; Maitre, Léa; McEachan, Rosemary; Papadopoulou, Eleni; Roumeliotaki, Theano; Philippat, Claire; Thomsen, Cathrine; Urquiza, José; Vafeiadi, Marina; Varo, Nerea; Vos, Miriam B.; Wright, John; McConnell, Rob; Vrijheid, Martine; Chatzi, Lida; Valvi, Damaskini

doi:10.1001/jamanetworkopen.2022.20176

Cited by 51 publications

(32 citation statements)

References 66 publications

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“…Epidemiological studies have suggested that urinary phthalate metabolite concentrations are associated with elevated markers of liver injury, such as serum ALT AST, gamma-glutamyl transferase (GGT) and alkaline phosphatase (ALP), indicating the potential toxic effect of phthalate exposure on the liver. ( Yu et al, 2021 ; Midya et al, 2022 ). Animal experiments have also reported that DEHP exacerbates nonalcoholic fatty liver in rats.…”

Section: Discussionmentioning

confidence: 99%

“…Humans, even pregnant women and children are widely exposed to DEHP in everyday life via ingestion of food, inhalation, skin contact, and medical devices. Growing epidemiological evidence has highlighted the association between phthalate exposure and a higher risk for liver injury ( Yu et al, 2021 ; Midya et al, 2022 ). As an endocrine disrupting chemical (EDC), DEHP is reported to be toxic to rodent liver, leading to lipid metabolism disorder, liver injury and nonalcoholic fatty liver disease ( Chen et al, 2016 ; Zhao et al, 2020 ; Liu et al, 2021 ).…”

Section: Introductionmentioning

confidence: 99%

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Di-(2-ethylhexyl) phthalate exposure induces liver injury by promoting ferroptosis via downregulation of GPX4 in pregnant mice

Zhang

Zhen

Cheng

et al. 2022

Front. Cell Dev. Biol.

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As one kind of endocrine disrupting chemical, di-(2-ethylhexyl) phthalate (DEHP) has been reported to cause liver dysfunction in epidemiological and experimental studies. Abnormal liver function in pregnancy is associated with adverse maternal and perinatal outcomes. Few studies have investigated the potential effect of gestational DEHP exposure on the liver in pregnant mice, and the underlying mechanisms remain unclear. In the present study, pregnant ICR mice were exposed to doses (0, 500, 1,000 mg/kg/day) of DEHP in the presence or absence of 5 mg/kg/day ferrostatin-1 (Fer-1, ferroptosis inhibitor) by oral gavage from gestation day 4 to day 18. HepG2 cells were exposed to different doses of monoethylhexyl phthalate (MEHP, a major metabolite of DEHP) in vitro. Hepatic function and pathologic changes were observed. Oxidative stress, iron metabolism, and ferroptosis-related indicators and genes were evaluated both in vivo and in vitro. The results showed that gestational DEHP exposure induced disordered liver function and hepatocyte morphology changes in pregnant mice, along with increased malondialdehyde (MDA) and Fe2+ content and decreased glutathione (GSH) levels. The expression levels of the selected ferroptosis-related genes Slc7a11, Gpx4, and Nfr2 were significantly decreased, and Ptgs2 and Lpcat3 were significantly increased. Notably, Fer-1 attenuated DEHP-induced liver injury and ferroptosis. Furthermore, MEHP exhibited a synergistic effect with RSL3 (a GPX4 inhibitor) in promoting ferroptosis in vitro. Taken together, the results demonstrated that DEHP induced liver injury and ferroptosis in pregnant mice, probably by inhibiting the GPX4 pathway through lipid peroxidation and iron accumulation.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Di-(2-ethylhexyl) phthalate exposure induces liver injury by promoting ferroptosis via downregulation of GPX4 in pregnant mice

Zhang

Zhen

Cheng

et al. 2022

Front. Cell Dev. Biol.

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“…Of those participants aged 70 years or older, 71.7% had high PCB levels compared to only 2.2% of those aged under 30 years. A study of 1,108 mother–child pairs from six countries by Midya ( 72 ) discovered that prenatal exposure to PCBs is a potential risk factor for pediatric NAFLD, and were further associated with increased CK-18 levels (a novel marker of hepatocyte apoptosis and NAFLD). Notably, researchers have identified potential therapeutic targets for improving PCB-induced NAFLD, including the anti-fibrotic compound recombinant FGF21, which reduced the overexpression of hepatic lipocalin-2 (LCN2), a group of transporters of small lipophilic molecules that are upregulated in several liver diseases, and attenuated NAFLD ( 62 , 77 ).…”

Section: Relationship Between Nafld and Edcsmentioning

confidence: 99%

Endocrine disrupting chemicals: A promoter of non-alcoholic fatty liver disease

Chen

Wang

Cui

et al. 2023

Front. Public Health

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Non-alcoholic fatty liver disease (NAFLD) is the most prevalent liver disorder. With the improvement in human living standards, the prevalence of NAFLD has been increasing in recent years. Endocrine-disrupting chemicals (EDCs) are a class of exogenous chemicals that simulate the effects of hormones in the body. There has been growing evidence regarding the potential effects of EDCs on liver health, especially in NAFLD. This paper aims to summarize the major EDCs that contribute to the growing burden of NAFLD and to raise public awareness regarding the hazards posed by EDCs with the objective of reducing the incidence of NAFLD.

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“…First, inspired by the correlation patterns of endocrine-disrupting chemicals from (Midya et al (2022a)),…”

Section: Simulation Setupmentioning

confidence: 99%

Detecting Shape-based Interactions among Environmental Chemicals using an Ensemble of Exposure-Mixture Regression and Interpretable Machine Learning Tools

Midya

Gennings

2023

Preprint

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There is growing interest in discovering interactions between multiple environmental chemicals associated with increased adverse health effects. However, most existing approaches (1) either use a projection or product of multiple chemical exposures, which are difficult to interpret, and (2) can not simultaneously handle multi-ordered interactions. Therefore, we develop and validate a method to discover shape-based interactions that mimic usual toxicological interactions. We developed the "Multi-ordered explanatory interaction" (Moxie) algorithm by merging the efficacy of Extreme Gradient Boosting with the inferential power of Weighted Quantile Sum regression to extract synergistic interactions associated with the outcome/odds of disease in an adverse direction. We evaluated the algorithm's performance through simulations and compared it with the currently available gold standard, the signed-iterative random forest algorithm. We used the 2017–18 US-NHANES dataset (n=447 adults) to evaluate interactions among nine per-and poly-fluoroalkyl substances and five metals measured in whole-blood in association with serum low-density lipoprotein cholesterol. In simulations, the Moxie algorithm was highly specific and sensitive and had very low false discovery rates in detecting true synergistic interactions of 2nd, 3rd, and 4th order through moderate (n=250) to large (n=1000) sample sizes. In NHANES data, we found a two-order synergistic interaction between cadmium and lead detected in people with whole-blood cadmium concentrations and lead above 0.605 ug/dL and 1.485 ug/dL, respectively. Our findings demonstrate a novel validated approach in environmental epidemiology for detecting shape-based toxicologically mimicking interactions by integrating exposure-mixture regression and machine learning methods.

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Association of Prenatal Exposure to Endocrine-Disrupting Chemicals With Liver Injury in Children

Cited by 51 publications

References 66 publications

Di-(2-ethylhexyl) phthalate exposure induces liver injury by promoting ferroptosis via downregulation of GPX4 in pregnant mice

Di-(2-ethylhexyl) phthalate exposure induces liver injury by promoting ferroptosis via downregulation of GPX4 in pregnant mice

Endocrine disrupting chemicals: A promoter of non-alcoholic fatty liver disease

Detecting Shape-based Interactions among Environmental Chemicals using an Ensemble of Exposure-Mixture Regression and Interpretable Machine Learning Tools

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