Background: The chemical exposome includes exposure to numerous environmental and endogenous molecules, many of which have been linked to reproductive outcomes due to their endocrine-disrupting properties. As several breast cancer risk factors, including age and parity, are related to reproduction, it is imperative to investigate the interplay between such factors and the chemical exposome prior to conducting large scale exposome-based breast cancer studies.

Objective: This pilot study aimed to provide an overview of the chemical exposome in plasma samples from healthy women and identify associations between environmental exposures and three risk factors for breast cancer: age, parity, and age at menarche.

Material and methods: Plasma samples (n = 161), were selected based on reproductive history from 100 women participating in the Northern Sweden Health and Disease Study, between 1987 and 2006. Samples were analyzed by liquid chromatography high-resolution mass spectrometry (LC-HRMS) for 77 priority target analytes including contaminants and hormones, with simultaneous untargeted profiling of the chemical exposome and metabolome. Linear mixed effects models were applied to test associations between risk factors and chemical levels.

Results: Fifty-five target analytes were detected in at least one individual and over 94,000 untargeted features were detected across all samples. Among untargeted features, 430 could be annotated and were broadly classified as environmental (246), endogenous (167) or ambiguous (17). Applying mixed effect models to features detected in at least 70% of the samples (16,778), we found seven targeted analytes (including caffeine and various per- and poly-fluoroalkyl substances) and 38 untargeted features, positively associated with age. The directionality of these associations reversed for parity, decreasing with increasing births. Seven separate targeted analytes were associated with age at menarche.

Significance: This study demonstrates how a comprehensive chemical exposome approach can be used to inform future research prioritization regarding associations between known and unknown substances, reproduction, and breast cancer risk.

Cetaceans face numerous anthropogenic chemical stressors in global oceans, yet there is a lack of studies that simultaneously assess their cumulative exposure to both legacy and emerging contaminants and their combined effects. To evaluate the susceptibility of fin whale (Balaenoptera physalus) to chemical pollution, this study employed for the first time a multidiagnostic molecular approach that integrates chemical exposomics and gene expression analysis in live-sampled skin and blubber biopsies from two distinct populations: the endangered Mediterranean subpopulation (Italy) and the vulnerable population from the Sea of Cortez (Mexico). Both marine regions are biodiversity hotspots characterized by different anthropogenic impacts, making them ideal for the assessment of heterogeneous contaminants exposure and their effects. Results revealed distinct exposure profiles in the two populations, with Mediterranean fin whales exhibiting higher concentrations of legacy pollutants such as polychlorinated biphenyls (PCBs), as well as plasticizers, perfluoroalkyl substances (PFAS), while both populations showed traces of pharmaceuticals and lifestyle-related chemicals (e.g., paracetamol, diclofenac, nicotine, UV filters) and other substances not previously reported in whales. Supported by 32 network correlations with gene expression relevant to transcriptional regulation, endocrine disruption, lipid homeostasis, and inflammation, our findings suggest that complex anthropogenic chemical exposures may compromise the health and reproductive viability of the endangered Mediterranean fin whales, affirming their importance as a global sentinel species, which reflects marine ecosystem integrity within the “One Health” framework.

For comprehensive chemical exposomics in blood, analytical workflows are evolving through advances in sample preparation and instrumental methods. We hypothesized that gas chromatography-high-resolution mass spectrometry (GC-HRMS) workflows could be enhanced by minimizing lipid coextractives, thereby enabling larger injection volumes and lower matrix interference for improved target sensitivity and nontarget molecular discovery. A simple protocol was developed for small plasma volumes (100-200 μL) by using isohexane (H) to extract supernatants of acetonitrile-plasma (A-P). The HA-P method was quantitative for a wide range of hydrophobic multiclass target analytes (i.e., log Kow > 3.0), and the extracts were free of major lipids, thereby enabling robust large-volume injections (LVIs; 25 μL) in long sequences (60-70 h, 70-80 injections) to a GC-Orbitrap HRMS. Without lipid removal, LVI was counterproductive because method sensitivity suffered from the abundant matrix signal, resulting in low ion injection times to the Orbitrap. The median method quantification limit was 0.09 ng/mL (range 0.005-4.83 ng/mL), and good accuracy was shown for a certified reference serum. Applying the method to plasma from a Swedish cohort (n = 32; 100 μL), 51 of 103 target analytes were detected. Simultaneous nontarget analysis resulted in 112 structural annotations (12.8% annotation rate), and Level 1 identification was achieved for 7 of 8 substances in follow-up confirmations. The HA-P method is potentially scalable for application in cohort studies and is also compatible with many liquid-chromatography-based exposomics workflows.

Offshore oil platforms discharge enormous volumes of produced water that contain mixtures of petrochemicals and production chemicals. It is crucial to avoid the discharge of particularly those chemicals that are persistent in the marine environment. This study aims to (1) develop a biodegradation testing approach for discharged chemicals by native marine microorganism, (2) determine how dilution affects biodegradation, and (3) determine biodegradation kinetics for many discharged chemicals at low and noninhibitory concentrations. Produced water from an offshore oil platform was diluted in the ratio of 1:20, 1:60, and 1:200 in seawater from the same location and incubated for 60 days at 10 °C. Automated solid-phase microextraction GC-MS was used as a sensitive analytical technique, and chemical-specific primary degradation was determined based on peak area ratios between biotic test systems and abiotic controls. Biodegradation was inhibited at lower dilutions, consistent with ecotoxicity tests. Biodegradation kinetics were determined at the highest dilution for 139 chemicals (43 tentatively identified), and 6 chemicals were found persistent (half-life >60 days). Nontargeted analysis by liquid chromatography-high-resolution MS was demonstrated as a proof-of-principle for a comprehensive assessment. Biodegradation testing of chemicals in discharges provides the possibility to assess hundreds of chemicals at once and find the persistent ones.

Dissolved organic matter (DOM) in aquatic systems is a highly heterogeneous mixture of water-soluble organic compounds, acting as a major carbon reservoir driving biogeochemical cycles. Understanding DOM molecular composition is thus of vital interest for the health assessment of aquatic ecosystems, yet its characterization poses challenges due to its complex and dynamic chemical profile. Here, we performed a comprehensive chemical analysis of DOM from highly urbanized river and seawater sources and compared it to drinking water. Extensive analyses by nontargeted direct infusion (DI) and liquid chromatography (LC) high-resolution mass spectrometry (HRMS) through Orbitrap were integrated with novel computational workflows to allow molecular- and structural-level characterization of DOM. Across all water samples, over 7000 molecular formulas were calculated using both methods (∼4200 in DI and ∼3600 in LC). While the DI approach was limited to molecular formula calculation, the downstream data processing of MS2 spectral information combining library matching and in silico predictions enabled a comprehensive structural-level characterization of 16% of the molecular space detected by LC-HRMS across all water samples. Both analytical methods proved complementary, covering a broad chemical space that includes more highly polar compounds with DI and more less polar ones with LC. The innovative integration of diverse analytical techniques and computational workflow introduces a robust and largely available framework in the field, providing a widely applicable approach that significantly contributes to understanding the complex molecular composition of DOM.

In the modern “omics” era, measurement of the human exposome is a critical missing link between genetic drivers and disease outcomes. High-resolution mass spectrometry (HRMS), routinely used in proteomics and metabolomics, has emerged as a leading technology to broadly profile chemical exposure agents and related biomolecules for accurate mass measurement, high sensitivity, rapid data acquisition, and increased resolution of chemical space. Non-targeted approaches are increasingly accessible, supporting a shift from conventional hypothesis-driven, quantitation-centric targeted analyses toward data-driven, hypothesis-generating chemical exposome-wide profiling. However, HRMS-based exposomics encounters unique challenges. New analytical and computational infrastructures are needed to expand the analysis coverage through streamlined, scalable, and harmonized workflows and data pipelines that permit longitudinal chemical exposome tracking, retrospective validation, and multi-omics integration for meaningful health-oriented inferences. In this article, we survey the literature on state-of-the-art HRMS-based technologies, review current analytical workflows and informatic pipelines, and provide an up-to-date reference on exposomic approaches for chemists, toxicologists, epidemiologists, care providers, and stakeholders in health sciences and medicine. We propose efforts to benchmark fit-for-purpose platforms for expanding coverage of chemical space, including gas/liquid chromatography-HRMS (GC-HRMS and LC-HRMS), and discuss opportunities, challenges, and strategies to advance the burgeoning field of the exposome.

Chemical exposomes can now be comprehensively measured in human blood, but knowledge of their variability and longitudinal stability is required for robust application in cohort studies. Here, we applied high-resolution chemical exposomics to plasma of 46 adults, each sampled 6 times over 2 years in a multiomic cohort, resulting in 276 individual exposomes. In addition to quantitative analysis of 83 priority target analytes, we discovered and semiquantified substances that have rarely or never been reported in humans, including personal care products, pesticide transformation products, and polymer additives. Hierarchical cluster analysis for 519 confidently annotated substances revealed unique and distinctive coexposures, including clustered pesticides, poly(ethylene glycols), chlorinated phenols, or natural substances from tea and coffee; interactive heatmaps were publicly deposited to support open exploration of the complex (meta)data. Intraclass correlation coefficients (ICC) for all annotated substances demonstrated the relatively low stability of the exposome compared to that of proteome, microbiome, and endogenous small molecules. Implications are that the chemical exposome must be measured more frequently than other omics in longitudinal studies and four longitudinal exposure types are defined that can be considered in study design. In this small cohort, mixed-effect models nevertheless revealed significant associations between testosterone and perfluoroalkyl substances, demonstrating great potential for longitudinal exposomics in precision health research.

Nontarget mass spectrometry has great potential to reveal patterns of water contamination globally through community science, but few studies are conducted in low-income countries, nor with open-source workflows, and few datasets are FAIR (Findable, Accessible, Interoperable, Reusable). Water was collected from urban and rural rivers around Dhaka, Bangladesh, and analyzed by liquid chromatography high-resolution mass spectrometry in four ionization modes (electrospray ionization +/-, atmospheric pressure chemical ionization +/-) with data -independent MS2 acquisition. The acquisition strategy was complementary: 19,427 and 7365 features were unique to ESI and APCI, respectively. The complexity of water pollution was revealed by >26,000 unique molecular features resolved by MS-DIAL, among which >20,000 correlated with urban sources in Dhaka. A major wastewater treatment plant was not a dominant pollution source, consistent with major contributions from uncontrolled urban drainage, a result that encourages development of further wastewater infrastructures. Matching of deconvoluted MS2 spectra to public libraries resulted in 62 confident annotations (i.e., Level 1-2a) and allowed semiquantification of 42 analytes including pharmaceuticals, pesticides, and personal care products. In silico structure prediction for the top 100 unknown molecular features associated with an urban source allowed 15 additional chemicals of anthropogenic origin to be annotated (i.e., Level 3). The authentic MS2 spectra were uploaded to MassBank Europe, mass spectral data were openly shared on the MassIVE repository, a tool (i.e., MASST) that could be used for community science environmental surveillance was demonstrated, and current limitations were discussed.

Chemical exposomics in human plasma wasenhanced by an optimizedphospholipid removal step that increased targeted method sensitivitywhile also revealing >13,000 new molecular features by LC-HRMSnon-targetedacquisition. The challenge of chemical exposomics in human plasmais the 1000-foldconcentration gap between endogenous substances and environmentalpollutants. Phospholipids are the major endogenous small moleculesin plasma, thus we validated a chemical exposomics protocol with anoptimized phospholipid-removal step prior to targeted and non-targetedliquid chromatography high-resolution mass spectrometry. Increasedinjection volume with negligible matrix effect permitted sensitivemulticlass targeted analysis of 77 priority analytes; median MLOQ= 0.05 ng/mL for 200 & mu;L plasma.In non-targeted acquisition, mean total signal intensities of non-phospholipidswere enhanced 6-fold in positive (max 28-fold) and 4-fold in negativemode (max 58-fold) compared to a control method without phospholipidremoval. Moreover, 109 and 28% more non-phospholipid molecular featureswere detected by exposomics in positive and negative mode, respectively,allowing new substances to be annotated that were non-detectable withoutphospholipid removal. In individual adult plasma (100 & mu;L, n = 34), 28 analytes were detected and quantified among10 chemical classes, and quantitation of per- and polyfluoroalkylsubstances (PFAS) was externally validated by independent targetedanalysis. Retrospective discovery and semi-quantification of PFAS-precursorswas demonstrated, and widespread fenuron exposure is reported in plasmafor the first time. The new exposomics method is complementary tometabolomics protocols, relies on open science resources, and canbe scaled to support large studies of the exposome.

The airborne chemical exposome is a dynamic complex mixture of gases and particles, and despite clear links to chronic disease and premature death, its molecular composition and variability remains largely uncharacterized. To overcome this, we aimed to pair nontarget analysis by high-resolution mass spectrometry (HRMS) with an inexpensive and stable passive sampling media for airborne gases and particles. To this end, we synthesized silicone (polydimethylsiloxane; PDMS) foam disks resulting in a low cost (0.02$/disk) and ultraclean material suitable for analysis by gas or liquid chromatography (GC/LC)HRMS. When tested for indoor passive sampling over 1-3 months, alongside a PDMS sheet, PDMS foam accumulated many nonpolar gas phase environmental contaminants (e.g., polychlorinated biphenyls), and a surprisingly complex mixture of larger polar substances (e.g., oxygen, nitrogen and sulfur-containing) that were absent from the PDMS sheet, suggesting sampling of the particulate phase. The airborne molecular discovery potential was further demonstrated using an open-science LC-HRMS workflow integrating molecular networks and in silico structural predictions tailored on PubChemLite for Exposomics, which revealed series of known and unknown substances, including aromatic nitrophenols and sulfonyls. Future studies may benefit from implementing PDMS foam as wearable or stationary passive samplers to support advances in understanding exposure and contaminant sources in the indoor, outdoor, and personal airborne exposomes.