Environmental Exposome and Atrial Fibrillation: Emerging Evidence and Future Directions.

There has been increased awareness of the linkage between environmental exposures and cardiovascular health and disease. Atrial fibrillation is the most common sustained cardiac arrhythmia, affecting millions of people worldwide and contributing to substantial morbidity and mortality. Although numerous studies have explored the role of genetic and lifestyle factors in the development and progression of atrial fibrillation, the potential impact of environmental determinants on this prevalent condition has received comparatively less attention. This review aims to provide a comprehensive overview of the current evidence on environmental determinants of atrial fibrillation, encompassing factors such as air pollution, temperature, humidity, and other meteorologic conditions, noise pollution, greenspace, and the social environment. We discuss the existing evidence from epidemiological and mechanistic studies, critically evaluating the strengths and limitations of these investigations and the potential underlying biological mechanisms through which environmental exposures may affect atrial fibrillation risk. Furthermore, we address the potential implications of these findings for public health and clinical practice and identify knowledge gaps and future research directions in this emerging field.

Geospatial Science for the Environmental Epidemiology of Cancer in the Exposome Era.

Geospatial science is the science of location or place that harnesses geospatial tools, such as geographic information systems (GIS), to understand the features of the environment according to their locations. Geospatial science has been transformative for cancer epidemiologic studies through enabling large-scale environmental exposure assessments. As the research paradigm for the exposome, or the totality of environmental exposures across the life course, continues to evolve, geospatial science will serve a critical role in determining optimal practices for how to measure the environment as part of the external exposome. The objectives of this article are to provide a summary of key concepts, present a conceptual framework that illustrates how geospatial science is applied to environmental epidemiology in practice and through the lens of the exposome, and discuss the following opportunities for advancing geospatial science in cancer epidemiologic research: enhancing spatial and temporal resolutions and extents for geospatial data; geospatial methodologies to measure climate change factors; approaches facilitating the use of patient addresses in epidemiologic studies; combining internal exposome data and geospatial exposure models of the external exposome to provide insights into biological pathways for environment-disease relationships; and incorporation of geospatial data into personalized cancer screening policies and clinical decision making.

An exposome atlas of serum reveals the risk of chronic diseases in the Chinese population.

Although adverse environmental exposures are considered a major cause of chronic diseases, current studies provide limited information on real-world chemical exposures and related risks. For this study, we collected serum samples from 5696 healthy people and patients, including those with 12 chronic diseases, in China and completed serum biomonitoring including 267 chemicals via gas and liquid chromatography-tandem mass spectrometry. Seventy-four highly frequently detected exposures were used for exposure characterization and risk analysis. The results show that region is the most critical factor influencing human exposure levels, followed by age. Organochlorine pesticides and perfluoroalkyl substances are associated with multiple chronic diseases, and some of them exceed safe ranges. Multi-exposure models reveal significant risk effects of exposure on hyperlipidemia, metabolic syndrome and hyperuricemia. Overall, this study provides a comprehensive human serum exposome atlas and disease risk information, which can guide subsequent in-depth cause-and-effect studies between environmental exposures and human health.

Medication use and risk of amyotrophic lateral sclerosis: using machine learning for an exposome-wide screen of a large clinical database.

BACKGROUND: Accumulating evidence suggests that non-genetic factors have important etiologic roles in amyotrophic lateral sclerosis (ALS), yet identification of specific culprit factors has been challenging. Many medications target biological pathways implicated in ALS pathogenesis, and screening large pharmacologic datasets for signals could greatly accelerate the identification of risk-modulating pharmacologic factors for ALS. METHOD: We conducted a high-dimensional screening of patients' history of medication use and ALS risk using an advanced machine learning approach based on gradient-boosted decision trees coupled with Bayesian model optimization and repeated data sampling. Clinical and medication dispensing data were obtained from a large Israeli health fund for 501 ALS cases and 4,998 matched controls using a lag period of 3 or 5 years prior to ALS diagnosis for ascertaining medication exposure. RESULTS: Of over 1,000 different medication classes, we identified 8 classes that were consistently associated with increased ALS risk across independently trained models, where most are indicated for control of symptoms implicated in ALS. Some suggestive protective effects were also observed, notably for vitamin E. DISCUSSION: Our results indicate that use of certain medications well before the typically recognized prodromal period was associated with ALS risk. This could result because these medications increase ALS risk or could indicate that ALS symptoms can manifest well before suggested prodromal periods. The results also provide further evidence that vitamin E may be a protective factor for ALS. Targeted studies should be performed to elucidate the possible pathophysiological mechanisms while providing insights for therapeutics design.

Nature-versus-nurture considered harmful: Actionability as an alternative tool for understanding the exposome from an ethical perspective.

Exposome research is put forward as a major tool for solving the nature-versus-nurture debate because the exposome is said to represent "the nature of nurture." Against this influential idea, we argue that the adoption of the nature-versus-nurture debate into the exposome research program is a mistake that needs to be undone to allow for a proper bioethical assessment of exposome research. We first argue that this adoption is originally based on an equivocation between the traditional nature-versus-nurture debate and a debate about disease prediction/etiology. Second, due to this mistake, exposome research is pushed to adopt a limited conception of agential control that is harmful to one's thinking about the good that exposome research can do for human health and wellbeing. To fully excise the nature-versus-nurture debate from exposome research, we argue that exposome researchers and bioethicists need to think about the exposome afresh from the perspective of actionability. We define the concept of actionability and related concepts and show how these can be used to analyze the ethical aspects of the exposome. In particular, we focus on refuting the popular "gun analogy" in exposome research, returning results to study participants and risk-taking in the context of a well-lived life.

Hair-Derived Exposome Exploration of Cardiometabolic Health: Piloting a Bayesian Multitrait Variable Selection Approach.

Cardiometabolic health is complex and characterized by an ensemble of correlated and/or co-occurring conditions including obesity, dyslipidemia, hypertension, and diabetes mellitus. It is affected by social, lifestyle, and environmental factors, which in-turn exhibit complex correlation patterns. To account for the complexity of (i) exposure profiles and (ii) health outcomes, we propose to use a multitrait Bayesian variable selection approach and identify a sparse set of exposures jointly explanatory of the complex cardiometabolic health status. Using data from a subset (N = 941 participants) of the nutrition, environment, and cardiovascular health (NESCAV) study, we evaluated the link between measurements of the cumulative exposure to (N = 33) pollutants derived from hair and cardiometabolic health as proxied by up to nine measured traits. Our multitrait analysis showed increased statistical power, compared to single-trait analyses, to detect subtle contributions of exposures to a set of clinical phenotypes, while providing parsimonious results with improved interpretability. We identified six exposures that were jointly explanatory of cardiometabolic health as modeled by six complementary traits, of which, we identified strong associations between hexachlorobenzene and trifluralin exposure and adverse cardiometabolic health, including traits of obesity, dyslipidemia, and hypertension. This supports the use of this type of approach for the joint modeling, in an exposome context, of correlated exposures in relation to complex and multifaceted outcomes.

Association between Ambient Volatile Organic Compounds Exposome and Emergency Hospital Admissions for Cardiovascular Disease.

The limited research on volatile organic compounds (VOCs) has not taken into account the interactions between constituents. We used the weighted quantile sum (WQS) model and generalized linear model (GLM) to quantify the joint effects of ambient VOCs exposome and identify the substances that play key roles. For a 0 day lag, a quartile increase of WQS index for n-alkanes, iso/anti-alkanes, aromatic, halogenated aromatic hydrocarbons, halogenated saturated chain hydrocarbons, and halogenated unsaturated chain hydrocarbons were associated with 1.09% (95% CI: 0.13, 2.06%), 0.98% (95% CI: 0.22, 1.74%), 0.92% (95% CI: 0.14, 1.69%), 1.03% (95% CI: 0.14, 1.93%), 1.69% (95% CI: 0.48, 2.91%), and 1.85% (95% CI: 0.93, 2.79%) increase in cardiovascular disease (CVD) emergency hospital admissions, respectively. Independent effects of key substances on CVD-related emergency hospital admissions were also reported. In particular, an interquartile range increase in 1,1,1-trichloroethane, methylene chloride, styrene, and methylcyclohexane is associated with a greater risk of CVD-associated emergency hospital admissions [3.30% (95% CI: 1.93, 4.69%), 3.84% (95% CI: 1.21, 6.53%), 5.62% (95% CI: 1.35, 10.06%), 8.68% (95% CI: 3.74, 13.86%), respectively]. We found that even if ambient VOCs are present at a considerably low concentration, they can cause cardiovascular damage. This should prompt governments to establish and improve concentration standards for VOCs and their sources. At the same time, policies should be introduced to limit VOCs emission to protect public health.

Longitudinal Mapping of Personal Biotic and Abiotic Exposomes and Transcriptome in Underwater Confined Space Using Wearable Passive Samplers.

Silicone-based passive samplers, commonly paired with gas chromatography-mass spectrometry (GC-MS) analysis, are increasingly utilized for personal exposure assessments. However, its compatibility with the biotic exposome remains underexplored. In this study, we introduce the wearable silicone-based AirPie passive sampler, coupled with nontargeted liquid chromatography with high-resolution tandem mass spectrometry (LC-HRMS/MS), GC-HRMS, and metagenomic shotgun sequencing methods, offering a comprehensive view of personalized airborne biotic and abiotic exposomes. We applied the AirPie samplers to 19 participants in a unique deep underwater confined environment, annotating 4,390 chemical and 2,955 microbial exposures, integrated with corresponding transcriptomic data. We observed significant shifts in environmental exposure and gene expression upon entering this unique environment. We noted increased exposure to pollutants, such as benzenoids, polycyclic aromatic hydrocarbons (PAHs), opportunistic pathogens, and associated antibiotic-resistance genes (ARGs). Transcriptomic analyses revealed the activation of neurodegenerative disease-related pathways, mostly related to chemical exposure, and the repression of immune-related pathways, linked to both biological and chemical exposures. In summary, we provided a comprehensive, longitudinal exposome map of the unique environment and underscored the intricate linkages between external exposures and human health. We believe that the AirPie sampler and associated analytical methods will have broad applications in exposome and precision medicine.

Associations of environmental factors with neurodegeneration: An exposome-wide Mendelian randomization investigation.

Neurodegenerative diseases (NDDs) remain a global health challenge. Previous studies have reported potential links between environmental factors and NDDs, however, findings remain controversial across studies and elusive to be interpreted as evidence of robust causal associations. In this study, we comprehensively explored the causal associations of the common environmental factors with major NDDs including Alzheimer's disease (AD), Parkinson's disease (PD), amyotrophic lateral sclerosis (ALS), and multiple sclerosis (MS), based on updated large-scale genome-wide association study data through two-sample Mendelian randomization (MR) approach. Our results indicated that, overall, 28 significant sets of exposure-outcome causal association evidence were detected, 12 of which were previously underestimated and newly identified, including average weekly beer plus cider intake, strenuous sports or other exercises, diastolic blood pressure, and body fat percentage with AD, alcohol intake frequency with PD, apolipoprotein B, systolic blood pressure, and forced expiratory volume in 1 s (FEV1) with ALS, and alcohol intake frequency, hip circumference, forced vital capacity, and FEV1 with MS. Moreover, the causal effects of several environmental factors on NDDs were found to overlap. From a triangulation perspective, our investigation provided insights into understanding the associations of environmental factors with NDDs, providing causality-oriented evidence to establish the risk profile of NDDs.

Modeling the impact of urban and hospital eco-exposomes on antibiotic-resistance dynamics in wastewaters.

The emergence and selection of antibiotic resistance is a major public health problem worldwide. The presence of antibiotic-resistant bacteria (ARBs) in natural and anthropogenic environments threatens the sustainability of efforts to reduce resistance in human and animal populations. Here, we use mathematical modeling of the selective effect of antibiotics and contaminants on the dynamics of bacterial resistance in water to analyze longitudinal spatio-temporal data collected in hospital and urban wastewater between 2012 and 2015. Samples were collected monthly during the study period at four different sites in Haute-Savoie, France: hospital and urban wastewater, before and after water treatment plants. Three different categories of exposure variables were collected simultaneously: 1) heavy metals, 2) antibiotics and 3) surfactants for a total of 13 drugs/molecules; in parallel to the normalized abundance of 88 individual genes and mobile genetic elements, mostly conferring resistance to antibiotics. A simple hypothesis-driven model describing weekly antibiotic resistance gene (ARG) dynamics was proposed to fit the available data, assuming that normalized gene abundance is proportional to antibiotic resistant bacteria (ARB) populations in water. The detected compounds were found to influence the dynamics of 17 genes found at multiple sites. While mercury and vancomycin were associated with increased ARG and affected the dynamics of 10 and 12 identified genes respectively, surfactants antagonistically affected the dynamics of three genes. The models proposed here make it possible to analyze the relationship between the persistence of resistance genes in the aquatic environment and specific compounds associated with human activities from longitudinal data. Our analysis of French data over 2012-2015 identified mercury and vancomycin as co-selectors for some ARGs.

[Risk analysis of serum chemical residues for metabolic associated fatty liver disease based on exposome-lipidome wide association study].

Metabolic associated fatty liver disease (MAFLD) is a common liver disease with a prevalence of up to 25%; it not only adversely affects human health but also aggravates the economic burden of society. An increasing number of studies have suggested that the occurrence of chronic noncommunicable diseases is affected by both environmental exposures and genetic factors. Research has also shown that environmental pollution may increase the risk of MAFLD and promote its occurrence and development. However, the relationship between these concepts, as well as the underlying exposure effects and mechanism, remains incompletely understood. Lipidomics, a branch of metabolomics that studies lipid disorders, can help researchers investigate abnormal lipid metabolites in various disease states. Lipidome-exposome wide association studies are a promising paradigm for investigating the health effects of cumulative environmental exposures on biological responses, and could provide new ideas for determining the associations between metabolic and lipid changes and disease risk caused by chemical-pollutant exposure. Hence, in this study, targeted exposomics and nontargeted lipidomics studies based on ultra-high performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) and ultra-high performance liquid chromatography-high resolution mass spectrometry (UHPLC-HRMS) were used to characterize exogenous chemical pollutants and endogenous lipid metabolites in the sera of patients with MAFLD and healthy subjects. The results demonstrated that fipronil sulfone, malathion dicarboxylic acid, and monocyclohexyl phthalate may be positively associated with the disease risk of patients diagnosed as simple fatty liver disease (hereafter referred to as MAFLD(0)). Moreover, fipronil sulfone, acesulfame potassium, perfluorooctanoic acid (PFOA), perfluorononanoic acid (PFNA), perfluoroundecanoic acid (PFUnDA), 4-hydroxybenzophenone, and 3,5-di-tert-butyl-4-hydroxybenzoic acid (DBPOB) may be positively associated with the disease risk of patients diagnosed as fatty liver complicated by single or multiple metabolic disorders. Association analysis was carried out to explore the lipid metabolites induced by chemical residues. Triglyceride (TG) and diglyceride (DG) were significantly increased in MAFLD and MAFLD(0). The numbers of carbons of significantly changed DGs and TGs were mainly in the ranges of 32-40 and 35-60, respectively, and both were mainly characterized by changes in polyunsaturated lipids. Most of the lipid-effect markers were positively correlated with chemical residues and associated with increased disease risk. Our research provides a scientific basis for studies on the association and mechanism between serum chemical-pollutant residues and disease outcomes.

Blood and urine multi-omics analysis of the impact of e-vaping, smoking, and cessation: from exposome to molecular responses.

Cigarette smoking is a major preventable cause of morbidity and mortality. While quitting smoking is the best option, switching from cigarettes to non-combustible alternatives (NCAs) such as e-vapor products is a viable harm reduction approach for smokers who would otherwise continue to smoke. A key challenge for the clinical assessment of NCAs is that self-reported product use can be unreliable, compromising the proper evaluation of their risk reduction potential. In this cross-sectional study of 205 healthy volunteers, we combined comprehensive exposure characterization with in-depth multi-omics profiling to compare effects across four study groups: cigarette smokers (CS), e-vapor users (EV), former smokers (FS), and never smokers (NS). Multi-omics analyses included metabolomics, transcriptomics, DNA methylomics, proteomics, and lipidomics. Comparison of the molecular effects between CS and NS recapitulated several previous observations, such as increased inflammatory markers in CS. Generally, FS and EV demonstrated intermediate molecular effects between the NS and CS groups. Stratification of the FS and EV by combustion exposure markers suggested that this position on the spectrum between CS and NS was partially driven by non-compliance/dual use. Overall, this study highlights the importance of in-depth exposure characterization before biological effect characterization for any NCA assessment study.

[Application of multiomics mass spectrometry in the research of chemical exposome].

Environmental factors, such as environmental pollutants, behaviors, and lifestyles, are the leading causes of chronic noncommunicable diseases. Estimates indicate that approximately 50% of all deaths worldwide can be attributed to environmental factors. The exposome is defined as the totality of human environmental (i.e., all nongenetic) exposures from conception, including general external exposure (e.g., climate, education, and urban environment), specific external exposure (e.g., pollution, physical activity, and diet), and internal exposure (e.g., metabolic factors, oxidative stress, inflammation, and protein modification). As a new paradigm, this concept aims to comprehensively understand the link between human health and environmental factors. Therefore, a comprehensive measurement of the exposome, including accurate and reliable measurements of exposure to the external environment and a wide range of biological responses to the internal environment, is of great significance. The measurement of the general external exposome depends on advances in environmental sensors, personal-sensing technologies, and geographical information systems. The determination of exogenous chemicals to which individuals are exposed and endogenous chemicals that are produced or modified by external stressors relies on improvements in methodology and the development of instrumental approaches, including colorimetric, chromatographic, spectral, and mass-spectrometric methods. This article reviews the research strategies for chemical exposomes and summarizes existing exposome-measurement methods, focusing on mass spectrometry (MS)-based methods. The top-down and bottom-up approaches are commonly used in exposome studies. The bottom-up approach focuses on the identification of chemicals in the external environment (e.g., soil, water, diet, and air), whereas the top-down approach focuses on the evaluation of endogenous chemicals and biological processes in biological samples (e.g., blood, urine, and serum). Low- and high-resolution MS (LRMS and HRMS, respectively) have become the most popular methods for the direct measurement of exogenous and endogenous chemicals owing to their superior sensitivity, specificity, and dynamic range. LRMS has been widely applied in the targeted analysis of expected chemicals, whereas HRMS is a promising technique for the suspect and unknown screening of unexpected chemicals. The development of MS-based multiomics, including proteomics, metabolomics, epigenomics, and spatial omics, provides new opportunities to understand the effects of environmental exposure on human health. Metabolomics involves the sum of all low-molecular-weight metabolites in a living system. Nontargeted metabolomics can measure both endogenous and exogenous chemicals, which would directly link exposure to biological effects, internal dose, and disease pathobiology, whereas proteomics could play an important role in predicting potential adverse health outcomes and uncovering molecular mechanisms. MS imaging (MSI) is an emerging technique that provides unlabeled in-depth measurements of endogenous and exogenous molecules directly from tissue and cell sections without changing their spatial information. MSI-based spatial omics, which has been widely applied in biomarker discovery for clinical diagnosis, as well as drug and pollutant monitoring, is expected to become an effective method for exposome measurement. Integrating these response measurements from metabolomics, proteomics, spatial omics, and epigenomics will enable the generation of new hypotheses to discover the etiology of diseases caused by chemical exposure. Finally, we highlight the major challenges in achieving chemical exposome measurements.

Costs of molecular adaptation to the chemical exposome: a focus on xenobiotic metabolism pathways.

Organisms adapt to their environment through different pathways. In vertebrates, xenobiotics are detected, metabolized and eliminated through the inducible xenobiotic-metabolizing pathways (XMP) which can also generate reactive toxic intermediates. In this review, we will discuss the impacts of the chemical exposome complexity on the balance between detoxication and side effects. There is a large discrepancy between the limited number of proteins involved in these pathways (few dozens) and the diversity and complexity of the chemical exposome (tens of thousands of chemicals). Several XMP proteins have a low specificity which allows them to bind and/or metabolize a large number of chemicals. This leads to undesired consequences, such as cross-inhibition, inefficient metabolism, release of toxic intermediates, etc. Furthermore, several XMP proteins have endogenous functions that may be disrupted upon exposure to exogenous chemicals. The gut microbiome produces a very large number of metabolites that enter the body and are part of the chemical exposome. It can metabolize xenobiotics and either eliminate them or lead to toxic derivatives. The complex interactions between chemicals of different origins will be illustrated by the diverse roles of the aryl hydrocarbon receptor which binds and transduces the signals of a large number of xenobiotics, microbiome metabolites, dietary chemicals and endogenous compounds. This article is part of the theme issue 'Endocrine responses to environmental variation: conceptual approaches and recent developments'.

Role of the Exposome in Neurodegenerative Disease: Recent Insights and Future Directions.

Neurodegenerative diseases are increasing in prevalence and place a significant burden on society. The causes are multifactorial and complex, and increasing evidence suggests a dynamic interplay between genes and the environment, emphasizing the importance of identifying and understanding the role of lifelong exposures, known as the exposome, on the nervous system. This review provides an overview of recent advances toward defining neurodegenerative disease exposomes, focusing on Parkinson's disease, amyotrophic lateral sclerosis, and Alzheimer's disease. We present the current state of the field based on emerging data, elaborate on key themes and potential mechanisms, and conclude with limitations and future directions. ANN NEUROL 2024;95:635-652.

A plausibility database summarizing the level of evidence regarding the hazards induced by the exposome on children health.

Childhood diseases correspond to major public health issues. A large number of studies using different approaches provide evidence regarding effects of environmental exposures, encompassed in the exposome, on children's health. We aimed to summarize the overall level of evidence (LoE) from all streams of evidence regarding exposome effects on child health. For 88 selected chemical and urban factors, we retrieved the conclusions of agency reports or literature reviews published between 2015 and 2021 regarding effects on child health, including cardiovascular, metabolic, neurodevelopmental, respiratory and other health outcomes. Adapted versions of PRISMA flowchart and AMSTAR-2 tool were used to select and assess the quality of the systematic reviews retrieved from PubMed and SCOPUS databases. For each factor-outcome pair, conclusions in three streams of evidence (epidemiological, toxicological and mechanistic, the latter corresponding to in vitro and in silico approaches) were translated into stream-specific LoEs and then combined into an overall LoE ranging from "very unlikely" to "very likely". The 88 environmental factors were implied in 611 factor-outcome pairs. Forty-four pairs (7%), corresponding to 16 factors, had a very likely overall LoE (≥80%); 127 pairs (21%), corresponding to 49 factors, had a likely or more overall LoE (≥60%). For 81 pairs (13%), no evidence was available in agency reports or published reviews, while for 275 pairs (45%), corresponding to 68 factors, the overall LoE was very unlikely (<20%). Exposure factors with the greatest number of associated health outcomes with a high overall LoE were HCB, PCBs, temperature (8 outcomes), PFOA (7 outcomes), PFOS, cotinine (6 outcomes), arsenic, lead (5 outcomes), bisphenols A and S, PFNA and PM2.5 (4 outcomes), DDT, DDE and DDD, PFHxA, PFDA, green space, UV radiation (3 outcomes). We developed an approach to extract and summarize the existing evidence about effects of environmental factors on health. The plausibility database built for children's health can be used to identify research gaps, conduct quantitative risk assessment studies. It could be expanded to consider a larger fraction of the exposome and other age groups and should be updated on a regular basis.

Exposome in ischaemic heart disease: beyond traditional risk factors.

Ischaemic heart disease represents the leading cause of morbidity and mortality, typically induced by the detrimental effects of risk factors on the cardiovascular system. Although preventive interventions tackling conventional risk factors have helped to reduce the incidence of ischaemic heart disease, it remains a major cause of death worldwide. Thus, attention is now shifting to non-traditional risk factors in the built, natural, and social environments that collectively contribute substantially to the disease burden and perpetuate residual risk. Of importance, these complex factors interact non-linearly and in unpredictable ways to often enhance the detrimental effects attributable to a single or collection of these factors. For this reason, a new paradigm called the 'exposome' has recently been introduced by epidemiologists in order to define the totality of exposure to these new risk factors. The purpose of this review is to outline how these emerging risk factors may interact and contribute to the occurrence of ischaemic heart disease, with a particular attention on the impact of long-term exposure to different environmental pollutants, socioeconomic and psychological factors, along with infectious diseases such as influenza and COVID-19. Moreover, potential mitigation strategies for both individuals and communities will be discussed.

Linking Toxicology and Human Health Through the Exposome.

Current analytical technology and continuing maturation of -omics methodology have enabled detailed assessment of human exposure via the exposome. Topics exploring the connection between etiology of disease and toxicology were presented at the 2023 Fall American Chemical Society meeting.

Development and evaluation of a comprehensive workflow for suspect screening of exposome-related xenobiotics and phase II metabolites in diverse human biofluids.

Suspect and non-target screening (SNTS) methods are being promoted in order to decode the human exposome since a wide chemical space can be analysed in a diversity of human biofluids. However, SNTS approaches in the exposomics field are infra-studied in comparison to environmental or food monitoring studies. In this work, a comprehensive suspect screening workflow was developed to annotate exposome-related xenobiotics and phase II metabolites in diverse human biofluids. Precisely, human urine, breast milk, saliva and ovarian follicular fluid were employed as samples and analysed by means of ultra-high performance liquid chromatography coupled with high resolution tandem mass spectrometry (UHPLC-HRMS/MS). To automate the workflow, the "peak rating" parameter implemented in Compound Discoverer 3.3.2 was optimized to avoid time-consuming manual revision of chromatographic peaks. In addition, the presence of endogenous molecules that might interfere with the annotation of xenobiotics was carefully studied as the employment of inclusion and exclusion suspect lists. To evaluate the workflow, limits of identification (LOIs) and type I and II errors (i.e., false positives and negatives, respectively) were calculated in both standard solutions and spiked biofluids using 161 xenobiotics and 22 metabolites. For 80.3 % of the suspects, LOIs below 15 ng/mL were achieved. In terms of type I errors, only two cases were identified in standards and spiked samples. Regarding type II errors, the 7.7 % errors accounted in standards increased to 17.4 % in real samples. Lastly, the use of an inclusion list for endogens was favoured since it avoided 18.7 % of potential type I errors, while the exclusion list caused 7.2 % of type II errors despite making the annotation workflow less time-consuming.