Clomifene and Assisted Reproductive Technology in Humans Are Associated with Sex-Specific Offspring Epigenetic Alterations in Imprinted Control Regions.

Children conceived with assisted reproductive technology (ART) have an increased risk of adverse outcomes, including congenital malformations and imprinted gene disorders. In a retrospective North Carolina-based-birth-cohort, we examined the effect of ovulation drugs and ART on CpG methylation in differentially methylated CpGs in known imprint control regions (ICRs). Nine ICRs containing 48 CpGs were assessed for methylation status by pyrosequencing in mixed leukocytes from cord blood. After restricting to non-smoking, college-educated participants who agreed to follow-up, ART-exposed (n = 27), clomifene-only-exposed (n = 22), and non-exposed (n = 516) groups were defined. Associations of clomifene and ART with ICR CpG methylation were assessed with linear regression and stratifying by offspring sex. In males, ART was associated with hypomethylation of the PEG3 ICR [ß(95% CI) = -1.46 (-2.81, -0.12)] and hypermethylation of the MEG3 ICR [3.71 (0.01, 7.40)]; clomifene-only was associated with hypomethylation of the NNAT ICR [-5.25 (-10.12, -0.38)]. In female offspring, ART was associated with hypomethylation of the IGF2 ICR [-3.67 (-6.79, -0.55)]. Aberrant methylation of these ICRs has been associated with cardiovascular disease and metabolic and behavioral outcomes in children. The results suggest that the increased risk of adverse outcomes in offspring conceived through ART may be due in part to altered methylation of ICRs. Larger studies utilizing epigenome-wide interrogation are warranted.

Low-Dose Silver Nanoparticle Surface Chemistry and Temporal Effects on Gene Expression in Human Liver Cells.

Silver nanoparticles (AgNPs) are widely incorporated into consumer and biomedical products for their antimicrobial and plasmonic properties with limited risk assessment of low-dose cumulative exposure in humans. To evaluate cellular responses to low-dose AgNP exposures across time, human liver cells (HepG2) are exposed to AgNPs with three different surface charges (1.2 µg mL-1 ) and complete gene expression is monitored across a 24 h period. Time and AgNP surface chemistry mediate gene expression. In addition, since cells are fed, time has marked effects on gene expression that should be considered. Surface chemistry of AgNPs alters gene transcription in a time-dependent manner, with the most dramatic effects in cationic AgNPs. Universal to all surface coatings, AgNP-treated cells responded by inactivating proliferation and enabling cell cycle checkpoints. Further analysis of these universal features of AgNP cellular response, as well as more detailed analysis of specific AgNP treatments, time points, or specific genes, is facilitated with an accompanying application. Taken together, these results provide a foundation for understanding hepatic response to low-dose AgNPs for future risk assessment.

Application of Ion Mobility Spectrometry-Mass Spectrometry for Compositional Characterization and Fingerprinting of a Library of Diverse Crude Oil Samples.

Exposure characterization of crude oils, especially in time-sensitive circumstances such as spills and disasters, is a well-known analytical chemistry challenge. Gas chromatography-mass spectrometry is commonly used for "fingerprinting" and origin tracing in oil spills; however, this method is both time-consuming and lacks the resolving power to separate co-eluting compounds. Recent advances in methodologies to analyze petroleum substances using high-resolution analytical techniques have demonstrated both improved resolving power and higher throughput. One such method, ion mobility spectrometry-mass spectrometry (IMS-MS), is especially promising because it is both rapid and high-throughput, with the ability to discern among highly homologous hydrocarbon molecules. Previous applications of IMS-MS to crude oil analyses included a limited number of samples and did not provide detailed characterization of chemical constituents. We analyzed a diverse library of 195 crude oil samples using IMS-MS and applied a computational workflow to assign molecular formulas to individual features. The oils were from 12 groups based on geographical and geological origins: non-US (1 group), US onshore (3), and US Gulf of Mexico offshore (8). We hypothesized that information acquired through IMS-MS data would provide a more confident grouping and yield additional fingerprint information. Chemical composition data from IMS-MS was used for unsupervised hierarchical clustering, as well as machine learning-based supervised analysis to predict geographic and source rock categories for each sample; the latter also yielded several novel prospective biomarkers for fingerprinting of crude oils. We found that IMS-MS data have complementary advantages for fingerprinting and characterization of diverse crude oils and that proposed polycyclic aromatic hydrocarbon biomarkers can be used for rapid exposure characterization. Environ Toxicol Chem 2023;42:2336-2349. © 2023 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Data Processing Workflow to Identify Structurally Related Compounds in Petroleum Substances Using Ion Mobility Spectrometry-Mass Spectrometry.

Ion mobility spectrometry coupled with mass spectrometry (IMS-MS) is a post-ionization separation technique that can be used for rapid multidimensional analyses of complex samples. IMS-MS offers untargeted analysis, including ion-specific conformational data derived as collisional cross section (CCS) values. Here, we combine nitrogen gas drift tube CCS (DTCCSN2) and Kendrick mass defect (KMD) analyses based on CH2 and H functional units to enable compositional analyses of petroleum substances. First, polycyclic aromatic compound standards were analyzed by IMS-MS to demonstrate how CCS assists the identification of isomeric species in homologous series. Next, we used case studies of a gasoline standard previously characterized for paraffin, isoparaffin, aromatic, naphthene, and olefinic (PIANO) compounds, and a crude oil sample to demonstrate the application of the KMD analyses and CCS filtering. Finally, we propose a workflow that enables confident molecular formula assignment to the IMS-MS-derived features in petroleum samples. Collectively, this work demonstrates how rapid untargeted IMS-MS analysis and the proposed data processing workflow can be used to provide confident compositional characterization of hydrocarbon-containing substances.

Associations between maternal obesity, gestational cytokine levels and child obesity in the NEST cohort.

BACKGROUND: Although maternal systemic inflammation is hypothesized to link maternal pre-pregnancy obesity to offspring metabolic dysfunction, patient empirical data are limited. OBJECTIVES: In this study, we hypothesized that pre-pregnancy obesity alters systemic chemo/cytokines concentrations in pregnancy, and this alteration contributes to obesity in children. METHODS: In a multi-ethnic cohort of 361 mother-child pairs, we measured prenatal concentrations of plasma TNF-α, IL-6, IL-8, IL-1ß, IL-4, IFN-γ, IL-12 p70 subunit, and IL-17A using a multiplex ELISA and examined associations of pre-pregnancy obesity on maternal chemo/cytokine levels, and associations of these cytokine levels with offspring body mass index z score (BMI-z) at age 2-6 years using linear regression. RESULTS: After adjusting for maternal smoking, ethnicity, age, and education, pre-pregnancy obesity was associated with increased concentrations of TNF-α (P = .026) and IFN-γ (P = .06). While we found no evidence for associations between TNF-α concentrations and offspring BMI-z, increased IFN-γ concentrations were associated with decreased BMI-z (P = .0002), primarily in Whites (P = .0011). In addition, increased maternal IL-17A concentrations were associated with increased BMI-z in offspring (P = .0005) with stronger associations in African Americans (P = .0042) than Whites (P = .24). CONCLUSIONS: Data from this study are consistent with maternal obesity-related inflammation during pregnancy, increasing the risk of childhood obesity in an ethnic-specific manner.