Explore the Dosimetric Relationship between the Intake of Chemical Contaminants and Their Occurrence in Blood and Urine

Methodology for Biological Sample Collection, Processing, and Storage in the Newcastle 1000 Pregnancy Cohort: Protocol for a Longitudinal, Prospective Population-Based Study in Australia

BACKGROUND

Research in the developmental origins of health and disease provides compelling evidence that adverse events during the first 1000 days of life from conception can impact life course health. Despite many decades of research, we still lack a complete understanding of the mechanisms underlying some of these associations. The Newcastle 1000 Study (NEW1000) is a comprehensive, prospective population-based pregnancy cohort study based in Newcastle, New South Wales, Australia, that will recruit pregnant women and their partners at 11-14 weeks' gestation, with assessments at 20, 28, and 36 weeks; birth; 6 weeks; and 6 months, in order to provide detailed data about the first 1000 days of life to investigate the developmental origins of noncommunicable diseases.

OBJECTIVE

The study aims to provide a longitudinal multisystem approach to phenotyping, supported by robust clinical data and collection of biological samples in NEW1000.

METHODS

This manuscript describes in detail the large variety of samples collected in the study and the method of collection, storage, and utility of the samples in the biobank, with a particular focus on incorporation of the samples into emerging and novel large-scale "-omics" platforms, including the genome, microbiome, epigenome, transcriptome, fragmentome, metabolome, proteome, exposome, and cell-free DNA and RNA. Specifically, this manuscript details the methods used to collect, process, and store biological samples, including maternal, paternal, and fetal blood, microbiome (stool, skin, vaginal, oral), urine, saliva, hair, toenail, placenta, colostrum, and breastmilk.

RESULTS

Recruitment for the study began in March 2021. As of July 2024, 1040 women and 684 partners were enrolled, with 922 infants born. The NEW1000 biobank contains 24,357 plasma aliquots from ethylenediaminetetraacetic acid (EDTA) tubes, 5284 buffy coat aliquots, 4000 plasma aliquots from lithium heparin tubes, 15,884 blood serum aliquots, 2977 PAX RNA tubes, 26,595 urine sample aliquots, 2280 fecal swabs, 17,687 microbiome swabs, 2356 saliva sample aliquots, 1195 breastmilk sample aliquots, 4007 placental tissue aliquots, 2680 hair samples, and 2193 nail samples.

CONCLUSIONS

NEW1000 will generate a multigenerational, deeply phenotyped cohort with a comprehensive biobank of samples relevant to a large variety of analyses, including multiple -omics platforms.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/63562.

Are We Justified in Modeling Human Exposure to Chlorinated Paraffin Mixtures Using the Average Properties of Congeners and Homologues?

Concern over human exposure to chlorinated paraffin (CP) mixtures keeps increasing. The absence of a comprehensive understanding of how human exposure varies with the physicochemical properties of CP constituents has hindered the ability to determine at what level of aggregation exposure to CPs should be assessed. We answer this question by comparing exposure predicted with either a "complex" method that utilizes isomer-specific properties or "simplified" methods that rely on median properties of congener, homologue, or short-/medium-/long-chain CP groups. Our results demonstrate the wide range of physicochemical properties across CP mixtures and their dependence on molecular structures. Assuming unit emissions in the environment, these variances translate into an extensive disparity in whole-body concentrations predicted for different isomers, spanning ∼11 orders of magnitude. CPs with 13-19 carbons and 6-10 chlorines exhibit the highest human exposure potential, primarily owing to moderate to high hydrophobicity and slow environmental degradation and biotransformation. Far-field exposure is dominant for most CP constituents. Our study underscores that using average properties of congener, homologue, or S/M/LCCP groups yields results that are consistent with those derived from isomer-based modeling, thus offering an efficient and practical framework for future risk assessments and human exposure studies of CPs and other complex chemical mixtures.

Human biomonitoring and toxicokinetics as key building blocks for next generation risk assessment

Human health risk assessment is historically built upon animal testing, often following Organisation for Economic Co-operation and Development (OECD) test guidelines and exposure assessments. Using combinations of human relevant in vitro models, chemical analysis and computational (in silico) approaches bring advantages compared to animal studies. These include a greater focus on the human species and on molecular mechanisms and kinetics, identification of Adverse Outcome Pathways and downstream Key Events as well as the possibility of addressing susceptible populations and additional endpoints. Much of the advancement and progress made in the Next Generation Risk Assessment (NGRA) have been primarily focused on new approach methodologies (NAMs) and physiologically based kinetic (PBK) modelling without incorporating human biomonitoring (HBM). The integration of toxicokinetics (TK) and PBK modelling is an essential component of NGRA. PBK models are essential for describing in quantitative terms the TK processes with a focus on the effective dose at the expected target site. Furthermore, the need for PBK models is amplified by the increasing scientific and regulatory interest in aggregate and cumulative exposure as well as interactions of chemicals in mixtures. Since incorporating HBM data strengthens approaches and reduces uncertainties in risk assessment, here we elaborate on the integrated use of TK, PBK modelling and HBM in chemical risk assessment highlighting opportunities as well as challenges and limitations. Examples are provided where HBM and TK/PBK modelling can be used in both exposure assessment and hazard characterization shifting from external exposure and animal dose/response assays to animal-free, internal exposure-based NGRA.

Prioritizing molecular formulae identified by non-target analysis through high-throughput modelling: application to identify compounds with high human accumulation potential from house dust

Because it is typically not possible to pursue compound identification efforts for all chemical features detected during non-target analysis (NTA), the need for prioritization arises. Here we propose a strategy that ranks chemical features detected in environmental samples based on a model-derived metric that quantifies a feature's attribute that makes it desirable to elucidate its structure, e.g., a high potential for bioaccumulation in humans or wildlife. The procedure involves the identification of isomers that could plausibly represent the molecular formulae assigned to NTA-detected chemical features. For each isomer, the prioritization metric is calculated using properties predicted with high-throughput methods. After the molecular formulae are ranked based on the average values of the prioritization metric calculated for all isomers assigned to a formula, the highest ranked molecular formulae are prioritized for structure elucidation. We applied this workflow to features identified in house dust, using the ratio of chemical intake through dust ingestion to chemical concentration in blood (dose-to-concentration ratio, DCR) as the prioritization metric. Collections of isomers for the molecular formulae were assembled from the PubChem database and DCR was estimated using partitioning and biotransformation properties predicted for each isomer using quantitative structure property relationships. The ten top-ranked molecular formulae with notably lower average DCR-values represented mostly compounds already known to be indoor pollutants of concern, such as two polybrominated diphenyl ethers, bis(2-ethylhexyl) tetrabromophthalate, tetrabromobisphenol A, tris(1,3-dichloroisopropyl)phosphate and the azo dye disperse blue 373.