ArticleChemical research in toxicology2017
Benchmark Dose Modeling Estimates of the Concentrations of Inorganic Arsenic That Induce Changes to the Neonatal Transcriptome, Proteome, and Epigenome in a Pregnancy Cohort.
Article in Chemical research in toxicology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers, 1 of them a synthesis that pooled it.
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Who cites it
31 citing papers in PubMed, 1 synthesis or guideline pooled it, 51 citations in OpenAlex.
- 'Omics in environmental epidemiological studies of chemical exposures: A systematic evidence map.Environment international · 2022Pooled it
- Environmental Toxicants in the Hispanic Community Epigenetically Contributing to Preeclampsia.Cardiovascular toxicology · 2025Review
- Placental DNA methylation key topics: sex- and cell-type specificity, mediation, multi-omics, and biomarker discovery.Epigenomics · 2025Review
- Progress in toxicogenomics to protect human health.Nature reviews. Genetics · 2025Review
- Article
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- Investigation of Peroxisome Proliferator-Activated Receptor Genes as Requirements for Visual Startle Response Hyperactivity in Larval Zebrafish Exposed to Structurally Similar Per- and Polyfluoroalkyl Substances (PFAS).Environmental health perspectives · 2024Article
- Early microRNA responses in rodent liver mediated by furan exposure establish dose thresholds for later adverse outcomes.Toxicology letters · 2023Article
- Metal mixtures modeling identifies birth weight-associated gene networks in the placentas of children born extremely preterm.Chemosphere · 2023Article
- Toenail arsenic species and metallome profiles associated with breast, cervical, prostate, and skin cancer prevalence in the Atlantic Partnership for Tomorrow's Health cohort.Frontiers in public health · 2023Article
- Computational Approach to Link Chemicals in Anthropogenic Smoke Particulate Matter with Toxicity.Chemical research in toxicology · 2022Article
- Wildfire Variable Toxicity: Identifying Biomass Smoke Exposure Groupings through Transcriptomic Similarity Scoring.Environmental science & technology · 2022Article
- Integrative exposomic, transcriptomic, epigenomic analyses of human placental samples links understudied chemicals to preeclampsia.Environment international · 2022Article
- The placenta epigenome-brain axis: placental epigenomic and transcriptomic responses that preprogram cognitive impairment.Epigenomics · 2022Article
- Development of the InTelligence And Machine LEarning (TAME) Toolkit for Introductory Data Science, Chemical-Biological Analyses, Predictive Modeling, and Database Mining for Environmental Health Research.Frontiers in toxicology · 2022Article
- Comparing the Predictivity of Human Placental Gene, microRNA, and CpG Methylation Signatures in Relation to Perinatal Outcomes.Toxicological sciences : an official journal of the Society of Toxicology · 2021Article
- Development of the genomic inflammatory index (GII) to assess key maternal antecedents associated with placental inflammation.Placenta · 2021Article
- Mixtures modeling identifies chemical inducers versus repressors of toxicity associated with wildfire smoke.The Science of the total environment · 2021Article
- Linking Coregulated Gene Modules with Polycyclic Aromatic Hydrocarbon-Related Cancer Risk in the 3D Human Bronchial Epithelium.Chemical research in toxicology · 2021Article
- Mid-pregnancy maternal blood nitric oxide-related gene and miRNA expression are associated with preterm birth.Epigenomics · 2021Article
Corrections and comments
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Authors and funding
6 authors at 3 institutions in 1 country.
Funding
Abstract
Prenatal inorganic arsenic (iAs) exposure influences the expression of critical genes and proteins associated with adverse outcomes in newborns, in part through epigenetic mediators. The doses at which these genomic and epigenomic changes occur have yet to be evaluated in the context of dose-response modeling. The goal of the present study was to estimate iAs doses that correspond to changes in transcriptomic, proteomic, epigenomic, and integrated multi-omic signatures in human cord blood through benchmark dose (BMD) modeling. Genome-wide DNA methylation, microRNA expression, mRNA expression, and protein expression levels in cord blood were modeled against total urinary arsenic (U-tAs) levels from pregnant women exposed to varying levels of iAs. Dose-response relationships were modeled in BMDExpress, and BMDs representing 10% response levels were estimated. Overall, DNA methylation changes were estimated to occur at lower exposure concentrations in comparison to other molecular endpoints. Multi-omic module eigengenes were derived through weighted gene co-expression network analysis, representing co-modulated signatures across transcriptomic, proteomic, and epigenomic profiles. One module eigengene was associated with decreased gestational age occurring alongside increased iAs exposure. Genes/proteins within this module eigengene showed enrichment for organismal development, including potassium voltage-gated channel subfamily Q member 1 (KCNQ1), an imprinted gene showing differential methylation and expression in response to iAs. Modeling of this prioritized multi-omic module eigengene resulted in a BMD(BMDL) of 58(45) μg/L U-tAs, which was estimated to correspond to drinking water arsenic concentrations of 51(40) μg/L. Results are in line with epidemiological evidence supporting effects of prenatal iAs occurring at levels <100 μg As/L urine. Together, findings present a variety of BMD measures to estimate doses at which prenatal iAs exposure influences neonatal outcome-relevant transcriptomic, proteomic, and epigenomic profiles.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.