Metabolomic Effects of Folic Acid Supplementation in Adults: Evidence from the FACT Trial.

BACKGROUND: Folic acid (FA) is the oxidized form of folate found in supplements and FA-fortified foods. Most FA is reduced by dihydrofolate reductase to 5-methyltetrahydrofolate (5mTHF); the latter is the form of folate naturally found in foods. Ingestion of FA increases the plasma levels of both 5mTHF and unmetabolized FA (UMFA). Limited information is available on the downstream metabolic effects of FA supplementation, including potential effects associated with UMFA. OBJECTIVE: We aimed to assess the metabolic effects of FA-supplementation, and the associations of plasma 5mTHF and UMFA with the metabolome in FA-naïve Bangladeshi adults. METHODS: Sixty participants were selected from the Folic Acid and Creatine Trial; half received 800 µg FA/day for 12 weeks and half placebo. Plasma metabolome profiles were measured by high-resolution mass spectrometry, including 170 identified metabolites and 26,541 metabolic features. Penalized regression methods were used to assess the associations of targeted metabolites with FA-supplementation, plasma 5mTHF, and plasma UMFA. Pathway analyses were conducted using Mummichog. RESULTS: In penalized models of identified metabolites, FA-supplementation was associated with higher choline. Changes in 5mTHF concentrations were positively associated with metabolites involved in amino acid metabolism (5-hydroxyindoleacetic acid, acetylmethionine, creatinine, guanidinoacetate, hydroxyproline/n-acetylalanine) and 2 fatty acids (docosahexaenoic acid and linoleic acid). Changes in 5mTHF concentrations were negatively associated with acetylglutamate, acetyllysine, carnitine, propionyl carnitine, cinnamic acid, homogentisate, arachidonic acid, and nicotine. UMFA concentrations were associated with lower levels of arachidonic acid. Together, metabolites selected across all models were related to lipids, aromatic amino acid metabolism, and the urea cycle. Analyses of nontargeted metabolic features identified additional pathways associated with FA supplementation. CONCLUSION: In addition to the recapitulation of several expected metabolic changes associated with 5mTHF, we observed additional metabolites/pathways associated with FA-supplementation and UMFA. Further studies are needed to confirm these associations and assess their potential implications for human health. TRIAL REGISTRATION NUMBER: This trial was registered at https://clinicaltrials.gov as NCT01050556.

A prediction model for classifying maternal pregnancy smoking using California state birth certificate information.

BACKGROUND: Systematically recorded smoking data are not always available in vital statistics records, and even when available it can underestimate true smoking rates. OBJECTIVE: To develop a prediction model for maternal tobacco smoking in late pregnancy based on birth certificate information using a combination of self- or provider-reported smoking and biomarkers (smoking metabolites) in neonatal blood spots as the alloyed gold standard. METHODS: We designed a case-control study where childhood cancer cases were identified from the California Cancer Registry and controls were from the California birth rolls between 1983 and 2011 who were cancer-free by the age of six. In this analysis, we included 894 control participants and performed high-resolution metabolomics analyses in their neonatal dried blood spots, where we extracted cotinine [mass-to-charge ratio (m/z) = 177.1023] and hydroxycotinine (m/z = 193.0973). Potential predictors of smoking were selected from California birth certificates. Logistic regression with stepwise backward selection was used to build a prediction model. Model performance was evaluated in a training sample, a bootstrapped sample, and an external validation sample. RESULTS: Out of seven predictor variables entered into the logistic model, five were selected by the stepwise procedure: maternal race/ethnicity, maternal education, child's birth year, parity, and child's birth weight. We calculated an overall discrimination accuracy of 0.72 and an area under the receiver operating characteristic curve (AUC) of 0.81 (95% confidence interval [CI] 0.77, 0.84) in the training set. Similar accuracies were achieved in the internal (AUC 0.81, 95% CI 0.77, 0.84) and external (AUC 0.69, 95% CI 0.64, 0.74) validation sets. CONCLUSIONS: This easy-to-apply model may benefit future birth registry-based studies when there is missing maternal smoking information; however, some smoking status misclassification remains a concern when only variables from the birth certificate are used to predict maternal smoking.

Dioxin(-like)-Related Biological Effects through Integrated Chemical-wide and Metabolome-wide Analyses.

Dioxin(-like) exposures are linked to adverse health effects, including cancer. However, metabolic alterations induced by these chemicals remain largely unknown. Beyond known dioxin(-like) compounds, we leveraged a chemical-wide approach to assess chlorinated co-exposures and parent compound products [termed dioxin(-like)-related compounds] among 137 occupational workers. Endogenous metabolites were profiled by untargeted metabolomics, namely, reversed-phase chromatography with negative electrospray ionization (C18-negative) and hydrophilic interaction liquid chromatography with positive electrospray ionization (HILIC-positive). We performed a metabolome-wide association study to select dioxin(-like) associated metabolic features using a 20% false discovery rate threshold. Metabolic features were then characterized by pathway enrichment analyses. There are no significant features associated with polychlorinated dibenzo-p-dioxins (PCDDs), a subgroup of known dioxin(-like) compounds. However, 3,110 C18-negative and 2,894 HILIC-positive features were associated with at least one of the PCDD-related compounds. Abundant metabolic changes were also observed for polychlorinated dibenzofuran-related and polychlorinated biphenyl-related compounds. These metabolic features were primarily enriched in pathways of amino acids, lipid and fatty acids, carbohydrates, cofactors, and nucleotides. Our study highlights the potential of chemical-wide analysis for comprehensive exposure assessment beyond targeted chemicals. Coupled with advanced endogenous metabolomics, this approach allows for an in-depth exploration of metabolic alterations induced by environmental chemicals.

High-Resolution Mass Spectrometry for Human Exposomics: Expanding Chemical Space Coverage.

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.

Associations between metals and metabolomic profiles related to diabetes among adults in a rural region.

INTRODUCTION: Exposure to metals is associated with increased risk of type 2 diabetes (T2D). Potential mechanisms for metals-T2D associations involve biological processes including oxidative stress and disruption of insulin-regulated glucose uptake. In this study, we assessed whether associations between metal exposure and metabolite profiles relate to biological pathways linked to T2D. MATERIALS AND METHODS: We used data from 29 adults rural Colorado residents enrolled in the San Luis Valley Diabetes Study. Urinary concentrations of arsenic, cadmium, cobalt, lead, manganese, and tungsten were measured. Metabolic effects were evaluated using untargeted metabolic profiling, which included 61,851 metabolite signals detected in serum. We evaluated cross-sectional associations between metals and metabolites present in at least 50% of samples. Primary analyses adjusted urinary heavy metal concentrations for creatinine. Metabolite outcomes associated with each metal exposure were evaluated using pathway enrichment to investigate potential mechanisms underlying the relationship between metals and T2D. RESULTS: Participants had a mean age of 58.5 years (standard deviation = 9.2), 48.3% were female, 48.3% identified as Hispanic/Latino, 13.8% were current smokers, and 65.5% had T2D. Of the detected metabolites, 455 were associated with at least one metal, including 42 associated with arsenic, 22 with cadmium, 10 with cobalt, 313 with lead, 66 with manganese, and two with tungsten. The metabolic features were linked to 24 pathways including linoleate metabolism, butanoate metabolism, and arginine and proline metabolism. Several of these pathways have been previously associated with T2D, and our results were similar when including only participants with T2D. CONCLUSIONS: Our results support the hypothesis that metals exposure may be associated with biological processes related to T2D, including amino acid, co-enzyme, and sugar and fatty acid metabolism. Insight into biological pathways could influence interventions to prevent adverse health outcomes due to metal exposure.

Neonatal per- and polyfluoroalkyl substance exposure in relation to retinoblastoma.

BACKGROUND: Neonatal per- and polyfluoroalkyl substance (PFAS) exposure can disrupt hormonal homeostasis and induce neuro- and immunotoxicity in children. In this exploratory study, we investigated associations between PFAS levels in neonatal dried blood spots and retinoblastoma risk. MATERIALS AND METHODS: This study included 501 retinoblastoma cases born from 1983 to 2011 and 899 controls frequency-matched by birth year (20:1 matching ratio), born to 755 US-born and 366 Mexico-born mothers in California. Perfluorooctanesulfonic acid (PFOS), perflurooctanoic acid (PFOA), and perfluorononanoic acid (PFNA) feature intensities were identified from neonatal blood spots from California newborn Genetic Disease Screening Program. Using logistic regression, we assessed whether an interquartile range (IQR) increase of PFAS levels or having above-mean levels of PFAS in blood affects retinoblastoma risk overall or its subtypes (i.e., unilateral, bilateral). We assessed children of US-born and Mexico-born mothers, separately. RESULTS AND DISCUSSION: Among all children, above-mean PFOS levels at birth increased the odds of retinoblastoma overall by 29% (95% Confidence Interval (CI): 1.00, 1.67) and unilateral retinoblastoma by 42% (95% CI: 1.03, 1.97). For children of Mexico-born mothers, we estimated the highest odds of retinoblastoma overall (adjusted odds ratio (aOR): 1.67; 95% CI: 1.06, 2.66) and bilateral retinoblastoma (aOR: 2.06; 95% CI: 1.12, 3.92) with above-mean PFOS levels. Among children of US-born mothers, higher PFOS levels increased the odds of unilateral retinoblastoma by 15% (95% CI: 0.99, 1.35) for each IQR increase and by 71% among children with above-mean PFOS levels (95% CI: 1.04, 2.90). In addition, for children of US-born mothers, PFOA increased the odds of retinoblastoma overall (aOR: 1.41; 95% CI: 1.00, 2.02 for above-mean levels, aOR: 1.06; 95% CI: 0.98, 1.16 per IQR increase). PFNA was not associated with retinoblastoma risk. CONCLUSIONS: Our results suggested that PFOS and PFOA might contribute to retinoblastoma risk in children born in California.

Per- and polyfluoroalkyl substances, polychlorinated biphenyls, organochlorine pesticides, and polybrominated diphenyl ethers and dysregulation of MicroRNA expression in humans and animals-A systematic review.

BACKGROUND: Persistent organic pollutants (POPs) are chemicals characterized by their environmental persistence. Evidence suggests that exposure to POPs, which is ubiquitous, is associated with microRNA (miRNA) dysregulation. miRNA are key regulators in many physiological processes. It is thus of public health concern to understand the relationships between POPs and miRNA as related to health outcomes. OBJECTIVES: This systematic review evaluated the relationship between widely recognized, intentionally manufactured, POPs, including per- and polyfluoroalkyl substances (PFAS), polychlorinated biphenyls (PCBs), polybrominated diphenyl ethers (PBDEs), and organochlorine pesticides (dichlorodiphenyltrichloroethane [DDT], dichlorodiphenyldichloroethylene [DDE], hexachlorobenzene [HCB]), with miRNA expression in both human and animal studies. METHODS: We used PubMed and Embase to systematically search the literature up to September 29th, 2023. Search results for human and animal studies were included if they incorporated at least one POP of interest in relation to at least one miRNA. Data were synthesized to determine the direction and significance of associations between POPs and miRNA. We utilized ingenuity pathway analysis to review disease pathways for miRNA that were associated with POPs. RESULTS: Our search identified 38 eligible studies: 9 in humans and 29 in model organisms. PFAS were associated with decreased expression of miR-19, miR-193b, and miR-92b, as well as increased expression of miR-128, miR-199a-3p, and miR-26b across species. PCBs were associated with increased expression of miR-15a, miR-1537, miR-21, miR-22-3p, miR-223, miR-30b, and miR-34a, as well as decreased expression of miR-130a and let-7b in both humans and animals. Pathway analysis for POP-associated miRNA identified pathways related to carcinogenesis. DISCUSSION: This is the first systematic review of the association of POPs with miRNA in humans and model organisms. Large-scale prospective human studies are warranted to examine the role of miRNA as mediators between POPs and health outcomes.

Exposure to perfluoroalkyl substances and longitudinal changes in bone mineral density in adolescents and young adults: A multi-cohort study.

BACKGROUND: Per- and polyfluoroalkyl substances (PFAS) may impair bone development in adolescence, which impacts life-long bone health. No previous studies have examined prospective associations of individual PFAS and their mixture with bone mineral density (BMD) changes in Hispanic young persons, a population at high risk of osteoporosis in adulthood. OBJECTIVES: To examine associations of individual PFAS and PFAS mixtures with longitudinal changes in BMD in an adolescent Hispanic cohort and examine generalizability of findings in a mixed-ethnicity young adult cohort (58.4% Hispanic). METHODS: Overweight/obese adolescents from the Study of Latino Adolescents at Risk of Type 2 Diabetes (SOLAR; n = 304; mean follow-up = 1.4 years) and young adults from the Southern California Children's Health Study (CHS; n = 137; mean follow-up = 4.1 years) were included in this study. Plasma PFAS were measured at baseline and dual x-ray absorptiometry scans were performed at baseline and follow-up to measure BMD. We estimated longitudinal associations between BMD and five PFAS via separate covariate-adjusted linear mixed effects models, and between BMD and the PFAS mixture via quantile g-computation. RESULTS: In SOLAR adolescents, baseline plasma perfluorooctanesulfonic acid (PFOS) was associated with longitudinal changes in BMD. Each doubling of PFOS was associated with an average -0.003 g/cm2 difference in change in trunk BMD per year over follow-up (95% CI: -0.005, -0.0002). Associations with PFOS persisted in CHS young adults, where each doubling of plasma PFOS was associated with an average -0.032 g/cm2 difference in total BMD at baseline (95% CI -0.062, -0.003), though longitudinal associations were non-significant. We did not find associations of other PFAS with BMD; associations of the PFAS mixture with BMD outcomes were primarily negative though non-significant. DISCUSSION: PFOS exposure was associated with lower BMD in adolescence and young adulthood, important periods for bone development, which may have implications on future bone health and risk of osteoporosis in adulthood.

Metabolite Stability in Archived Neonatal Dried Blood Spots Used for Epidemiologic Research.

Epidemiologic studies of low-frequency exposures or outcomes using metabolomics analyses of neonatal dried blood spots (DBS) often require assembly of samples with substantial differences in duration of storage. Independent assessment of stability of metabolites in archived DBS will enable improved design and interpretation of epidemiologic research utilizing DBS. Neonatal DBS routinely collected and stored as part of the California Genetic Disease Screening Program between 1983 and 2011 were used. The study population included 899 children without cancer before age 6 years, born in California. High-resolution metabolomics with liquid-chromatography mass spectrometry was performed, and the relative ion intensities of common metabolites and selected xenobiotic metabolites of nicotine (cotinine and hydroxycotinine) were evaluated. In total, we detected 26,235 mass spectral features across 2 separate chromatography methods (C18 hydrophobic reversed-phase chromatography and hydrophilic-interaction liquid chromatography). For most of the 39 metabolites related to nutrition and health status, we found no statistically significant annual trends across the years of storage. Nicotine metabolites were captured in the DBS with relatively stable intensities. This study supports the usefulness of DBS stored long-term for epidemiologic studies of the metabolome. -Omics-based information gained from DBS may also provide a valuable tool for assessing prenatal environmental exposures in child health research.

Lipopolysaccharide-binding protein and future Parkinson's disease risk: a European prospective cohort.

INTRODUCTION: Lipopolysaccharide (LPS) is the outer membrane component of Gram-negative bacteria. LPS-binding protein (LBP) is an acute-phase reactant that mediates immune responses triggered by LPS and has been used as a blood marker for LPS. LBP has recently been indicated to be associated with Parkinson's disease (PD) in small-scale retrospective case-control studies. We aimed to investigate the association between LBP blood levels with PD risk in a nested case-control study within a large European prospective cohort. METHODS: A total of 352 incident PD cases (55% males) were identified and one control per case was selected, matched by age at recruitment, sex and study center. LBP levels in plasma collected at recruitment, which was on average 7.8 years before diagnosis of the cases, were analyzed by enzyme linked immunosorbent assay. Odds ratios (ORs) were estimated for one unit increase of the natural log of LBP levels and PD incidence by conditional logistic regression. RESULTS: Plasma LBP levels were higher in prospective PD cases compared to controls (median (interquartile range) 26.9 (18.1-41.0) vs. 24.7 (16.6-38.4) µg/ml). The OR for PD incidence per one unit increase of log LBP was elevated (1.46, 95% CI 0.98-2.19). This association was more pronounced among women (OR 2.68, 95% CI 1.40-5.13) and overweight/obese subjects (OR 1.54, 95% CI 1.09-2.18). CONCLUSION: The findings suggest that higher plasma LBP levels may be associated with an increased risk of PD and may thus pinpoint to a potential role of endotoxemia in the pathogenesis of PD, particularly in women and overweight/obese individuals.

Comprehensive characterization of putative genetic influences on plasma metabolome in a pediatric cohort.

BACKGROUND: The human exposome is composed of diverse metabolites and small chemical compounds originated from endogenous and exogenous sources, respectively. Genetic and environmental factors influence metabolite levels, while the extent of genetic contributions across metabolic pathways is not yet known. Untargeted profiling of human metabolome using high-resolution mass spectrometry (HRMS) combined with genome-wide genotyping allows comprehensive identification of genetically influenced metabolites. As such previous studies of adults discovered and replicated genotype-metabotype associations. However, these associations have not been characterized in children. RESULTS: We conducted the largest genome by metabolome-wide association study to date of children (N = 441) using 619,688 common genetic variants and 14,342 features measured by HRMS. Narrow-sense heritability (h2) estimates of plasma metabolite concentrations using genomic relatedness matrix restricted maximum likelihood (GREML) method showed a bimodal distribution with high h2 (> 0.8) for 15.9% of features and low h2 (< 0.2) for most of features (62.0%). The features with high h2 were enriched for amino acid and nucleic acid metabolism, while carbohydrate and lipid concentrations showed low h2. For each feature, a metabolite quantitative trait loci (mQTL) analysis was performed to identify genetic variants that were potentially associated with plasma levels. Fifty-four associations among 29 features and 43 genetic variants were identified at a genome-wide significance threshold p < 3.5 × 10-12 (= 5 × 10-8/14,342 features). Previously reported associations such as UGT1A1 and bilirubin; PYROXD2 and methyl lysine; and ACADS and butyrylcarnitine were successfully replicated in our pediatric cohort. We found potential candidates for novel associations including CSMD1 and a monostearyl alcohol triglyceride (m/z 781.7483, retention time (RT) 89.3 s); CALN1 and Tridecanol (m/z 283.2741, RT 27.6). A gene-level enrichment analysis using MAGMA revealed highly interconnected modules for dADP biosynthesis, sterol synthesis, and long-chain fatty acid transport in the gene-feature network. CONCLUSION: Comprehensive profiling of plasma metabolome across age groups combined with genome-wide genotyping revealed a wide range of genetic influence on diverse chemical species and metabolic pathways. The developmental trajectory of a biological system is shaped by gene-environment interaction especially in early life. Therefore, continuous efforts on generating metabolomics data in diverse human tissue types across age groups are required to understand gene-environment interaction toward healthy aging trajectories.

Associations of a Prenatal Serum Per- and Polyfluoroalkyl Substance Mixture with the Cord Serum Metabolome in the HOME Study.

Per- and polyfluoroalkyl substances (PFAS) are ubiquitous and persistent chemicals associated with multiple adverse health outcomes; however, the biological pathways affected by these chemicals are unknown. To address this knowledge gap, we used data from 264 mother-infant dyads in the Health Outcomes and Measures of the Environment (HOME) Study and employed quantile-based g-computation to estimate covariate-adjusted associations between a prenatal (∼16 weeks' gestation) serum PFAS mixture [perfluorooctanesulfonic acid (PFOS), perfluorooctanoic acid (PFOA), perfluorohexanesulfonic acid (PFHxS), and perfluorononanoic acid (PFNA)] and 14,402 features measured in cord serum. The PFAS mixture was associated with four features: PFOS, PFHxS, a putatively identified metabolite (3-monoiodo-l-thyronine 4-O-sulfate), and an unidentified feature (590.0020 m/z and 441.4 s retention time; false discovery rate <0.20). Using pathway enrichment analysis coupled with quantile-based g-computation, the PFAS mixture was associated with 49 metabolic pathways, most notably amino acid, carbohydrate, lipid and cofactor and vitamin metabolism, as well as glycan biosynthesis and metabolism (P(Gamma) <0.05). Future studies should assess if these pathways mediate associations of prenatal PFAS exposure with infant or child health outcomes, such as birthweight or vaccine response.

Paired Liver:Plasma PFAS Concentration Ratios from Adolescents in the Teen-LABS Study and Derivation of Empirical and Mass Balance Models to Predict and Explain Liver PFAS Accumulation.

Animal studies have pointed at the liver as a hotspot for per- and polyfluoroalkyl substances (PFAS) accumulation and toxicity; however, these findings have not been replicated in human populations. We measured concentrations of seven PFAS in matched liver and plasma samples collected at the time of bariatric surgery from 64 adolescents in the Teen-Longitudinal Assessment of Bariatric Surgery (Teen-LABS) study. Liver:plasma concentration ratios were perfectly explained (r2 > 0.99) in a multilinear regression (MLR) model based on toxicokinetic (TK) descriptors consisting of binding to tissue constituents and membrane permeabilities. Of the seven matched plasma and liver PFAS concentrations compared in this study, the liver:plasma concentration ratio of perfluoroheptanoic acid (PFHpA) was considerably higher than the liver:plasma concentration ratio of other PFAS congeners. Comparing the MLR model with an equilibrium mass balance model (MBM) suggested that complex kinetic transport processes are driving the unexpectedly high liver:plasma concentration ratio of PFHpA. Intratissue MBM modeling pointed to membrane lipids as the tissue constituents that drive the liver accumulation of long-chain, hydrophobic PFAS, whereas albumin binding of hydrophobic PFAS dominated PFAS distribution in plasma. The liver:plasma concentration data set, empirical MLR model, and mechanistic MBM modeling allow the prediction of liver from plasma concentrations measured in human cohort studies. Our study demonstrates that combining biomonitoring data with mechanistic modeling can identify underlying mechanisms of internal distribution and specific target organ toxicity of PFAS in humans.

The Exposome: Molecules to Populations.

Derived from the term exposure, the exposome is an omic-scale characterization of the nongenetic drivers of health and disease. With the genome, it defines the phenome of an individual. The measurement of complex environmental factors that exert pressure on our health has not kept pace with genomics and historically has not provided a similar level of resolution. Emerging technologies make it possible to obtain detailed information on drugs, toxicants, pollutants, nutrients, and physical and psychological stressors on an omic scale. These forces can also be assessed at systems and network levels, providing a framework for advances in pharmacology and toxicology. The exposome paradigm can improve the analysis of drug interactions and detection of adverse effects of drugs and toxicants and provide data on biological responses to exposures. The comprehensive model can provide data at the individual level for precision medicine, group level for clinical trials, and population level for public health.

Metabolomics for exposure assessment and toxicity effects of occupational pollutants: current status and future perspectives.

INTRODUCTION: Work-related exposures to harmful agents or factors are associated with an increase in incidence of occupational diseases. These exposures often represent a complex mixture of different stressors, challenging the ability to delineate the mechanisms and risk factors underlying exposure-disease relationships. The use of omics measurement approaches that enable characterization of biological marker patterns provide internal indicators of molecular alterations, which could be used to identify bioeffects following exposure to a toxicant. Metabolomics is the comprehensive analysis of small molecule present in biological samples, and allows identification of potential modes of action and altered pathways by systematic measurement of metabolites. OBJECTIVES: The aim of this study is to review the application of metabolomics studies for use in occupational health, with a focus on applying metabolomics for exposure monitoring and its relationship to occupational diseases. METHODS: PubMed, Web of Science, Embase and Scopus electronic databases were systematically searched for relevant studies published up to 2021. RESULTS: Most of reviewed studies included worker populations exposed to heavy metals such as As, Cd, Pb, Cr, Ni, Mn and organic compounds such as tetrachlorodibenzo-p-dioxin, trichloroethylene, polyfluoroalkyl, acrylamide, polyvinyl chloride. Occupational exposures were associated with changes in metabolites and pathways, and provided novel insight into the relationship between exposure and disease outcomes. The reviewed studies demonstrate that metabolomics provides a powerful ability to identify metabolic phenotypes and bioeffect of occupational exposures. CONCLUSION: Continued application to worker populations has the potential to enable characterization of thousands of chemical signals in biological samples, which could lead to discovery of new biomarkers of exposure for chemicals, identify possible toxicological mechanisms, and improved understanding of biological effects increasing disease risk associated with occupational exposure.

Child serum metabolome and traffic-related air pollution exposure in pregnancy.

BACKGROUND: Maternal exposure to traffic-related air pollution during pregnancy has been shown to increase the risk of adverse birth outcomes and childhood disorders. High-resolution metabolomics (HRM) has previously been employed to identify metabolic responses to traffic-related air pollution in adults, including pregnant women. Thus far, no studies have examined metabolic effects of air pollution exposure in utero on neonates. METHODS: We retrieved stored neonatal blood spots for 241 children born in California between 1998 and 2007. These children were randomly selected from all California birth rolls to serve as birth-year matched controls for children with retinoblastoma identified from the California cancer registry for a case control study of childhood cancer. We estimated prenatal traffic-related air pollution exposure (particulate matter less than 2.5 µm (PM2.5)) during the third-trimester using the California Line Source Dispersion Model, version 4 (CALINE4) based on residential addresses recorded at birth. We employed untargeted HRM to obtain metabolic profiles, and metabolites associated with air pollution exposure were identified using partial least squares (PLS) regression and linear regressions. Biological effects were characterized using pathway enrichment analyses adjusting for potential confounders including maternal age, race/ethnicity, and education. RESULTS: In total we extracted 4038 and 4957 metabolite features from neonatal blood spots in hydrophilic interaction (HILIC) chromatography (positive ion mode) and C18 reverse phase columns (negative ion mode), respectively. After controlling for confounding factors, partial least square regression (Variable Importance in Projection (VIP) ≥ 2) selected 402 HILIC positive and 182 C18 negative features as statistically significantly associated with increasing third trimester PM2.5 exposure. Using pathway enrichment analysis, we identified metabolites in oxidative stress and inflammation pathways as being altered, primarily involving lipid metabolism. CONCLUSION: The metabolite features and pathways associated with air pollution exposure in neonates suggest that maternal exposure during late pregnancy contributes to oxidative stress and inflammation in newborn children.

Plasma concentrations of lipophilic persistent organic pollutants and glucose homeostasis in youth populations.

BACKGROUND: Exposure to lipophilic persistent organic pollutants (POPs) is ubiquitous. POPs are metabolic disrupting chemicals and are potentially diabetogenic. METHODS: Using a multi-cohort study including overweight adolescents from the Study of Latino Adolescents at Risk (SOLAR, N = 301, 2001-2012) and young adults from the Southern California Children's Health Study (CHS, N = 135, 2014-2018), we examined associations of POPs and risk factors for type 2 diabetes. SOLAR participants underwent annual visits for a median of 2.2 years and CHS participants performed a single visit, during which a 2-h oral glucose tolerance test was performed. Linear mixed models were used to examine associations between plasma concentrations of POPs [4,4'-dichlorodiphenyldichloroethylene (4,4'-DDE), hexachlorobenzene (HCB), PCBs-153, 138, 118, 180 and PBDEs-154, 153, 100, 85, 47] and changes in glucose homeostasis across age and pubertal stage. RESULTS: In SOLAR, exposure to HCB, PCB-118, and PBDE-153 was associated with dysregulated glucose metabolism. For example, each two-fold increase in HCB was associated with approximately 2 mg/dL higher glucose concentrations at 30 min (p = 0.001), 45 min (p = 0.0006), and 60 min (p = 0.03) post glucose challenge. Compared to individuals with low levels of PCB-118, individuals with high levels exhibited a 4.7 mg/dL (p = 0.02) higher glucose concentration at 15 min and a 3.6 mg/dL (p = 0.01) higher glucose concentration at 30 min. The effects observed with exposure to organochlorine compounds were independent of pubertal stages. PBDE-153 was associated with the development of dysregulated glucose metabolism beginning in late puberty. At Tanner stage 4, exposure to PBDE-153 was associated with a 12.7 mg/dL higher 60-min glucose concentration (p = 0.009) and a 16.1 mg*dl-1*hr-1 higher glucose AUC (p = 0.01). These associations persisted at Tanner 5. In CHS, PBDE-153 and total PBDE were associated with similar increases in glucose concentrations. CONCLUSION: Our results suggest that childhood exposure to lipophilic POPs is associated with dysregulated glucose metabolism.

Metabolome-wide association study of occupational exposure to benzene.

Benzene is a recognized hematotoxin and leukemogen; however, its mechanism of action in humans remain unclear. To provide insight into the processes underlying benzene hematotoxicity, we performed high-resolution metabolomic profiling of plasma collected from a cross-sectional study of 33 healthy workers exposed to benzene (median 8-h time-weighted average exposure; 20 ppma), and 25 unexposed controls in Shanghai, China. Metabolic features associated with benzene were identified using a metabolome-wide association study (MWAS) that tested for the relationship between feature intensity and benzene exposure. MWAS identified 478 mass spectral features associated with benzene exposure at false discovery rate < 20%. Comparison to a list of 13 known benzene metabolites and metabolites predicted using a multi-component biotransformation algorithm showed five metabolites were detected, which included the known metabolites phenol and benzene diolepoxide. Metabolic pathway enrichment identified 41 pathways associated with benzene exposure, with altered pathways including carnitine shuttle, fatty acid metabolism, sulfur amino acid metabolism, glycolysis, gluconeogenesis and branched chain amino acid metabolism. These results suggest disruption to fatty acid uptake, energy metabolism and increased oxidative stress, and point towards pathways related to mitochondrial dysfunction, which has previously been linked to benzene exposure in animal models and human studies. Taken together, these results suggest benzene exposure is associated with disruption of mitochondrial pathways, and provide promising, systems biology biomarkers for risk assessment of benzene-induced hematotoxicity in humans.

High-Resolution Metabolomic Assessment of Pesticide Exposure in Central Valley, California.

Pesticides are widely used in the agricultural Central Valley region of California. Historically, this has included organophosphates (OPs), organochlorines (OCs), and pyrethroids (PYRs). This study aimed to identify perturbations of the serum metabolome in response to each class of pesticide and mutual associations between groups of metabolites and multiple pesticides. We conducted high-resolution metabolomic profiling of serum samples from 176 older adults living in the California Central Valley using liquid chromatography with high-resolution mass spectrometry. We estimated chronic pesticide exposure (from 1974 to year of blood draw) to OPs, OCs, and PYRs from ambient sources at homes and workplaces with a geographic information system (GIS)-based model. Based on partial least-squares regression and pathway enrichment analysis, we identified metabolites and metabolic pathways associated with one or multiple pesticide classes, including mitochondrial energy metabolism, fatty acid and lipid metabolism, and amino acid metabolism. Utilizing an integrative network approach, we found that the fatty acid ß-oxidation pathway is a common pathway shared across all three pesticide classes. The disruptions of the serum metabolome suggested that chronic pesticide exposure might result in oxidative stress, inflammatory reactions, and mitochondrial dysfunction, all of which have been previously implicated in a wide variety of diseases. Overall, our findings provided a comprehensive view of the molecular mechanisms of chronic pesticide toxicity, and, for the first time, our approach informs exposome research by moving from macrolevel population exposures to microlevel biologic responses.

Metabolomics analysis of maternal serum exposed to high air pollution during pregnancy and risk of autism spectrum disorder in offspring.

BACKGROUND: Previously, numerous epidemiologic studies reported an association between autism spectrum disorder (ASD) and exposure to air pollution during pregnancy. However, there have been no metabolomics studies investigating the impact of pregnancy pollution exposure to ASD risk in offspring. OBJECTIVES: To identify differences in maternal metabolism that may reflect a biological response to exposure to high air pollution in pregnancies of offspring who later did or did not develop ASD. METHODS: We obtained stored mid-pregnancy serum from 214 mothers who lived in California's Central Valley and experienced the highest levels of air pollution during early pregnancy. We estimated each woman's average traffic-related air pollution exposure (carbon monoxide, nitric oxides, and particulate matter <2.5 µm) during the first trimester using the California Line Source Dispersion Model, version 4 (CALINE4). By utilizing liquid chromatography-high resolution mass spectrometry, we identified the metabolic profiles of maternal serum for 116 mothers with offspring who later developed ASD and 98 control mothers. Partial least squares discriminant analysis (PLS-DA) was employed to select metabolic features associated with air pollution exposure or autism risk in offspring. We also conducted extensive pathway enrichment analysis to elucidate potential ASD-related changes in the metabolome of pregnant women. RESULTS: We extracted 4022 and 4945 metabolic features from maternal serum samples in hydrophilic interaction (HILIC) chromatography (positive ion mode) and C18 (negative ion mode) columns, respectively. After controlling for potential confounders, we identified 167 and 222 discriminative features (HILIC and C18, respectively). Pathway enrichment analysis to discriminate metabolic features associated with ASD risk indicated various metabolic pathway perturbations linked to the tricarboxylic acid (TCA) cycle and mitochondrial function, including carnitine shuttle, amino acid metabolism, bile acid metabolism, and vitamin A metabolism. CONCLUSION: Using high resolution metabolomics, we identified several metabolic pathways disturbed in mothers with ASD offspring among women experiencing high exposure to traffic-related air pollution during pregnancy that were associated with mitochondrial dysfunction. These findings provide us with a better understanding of metabolic disturbances involved in the development of ASD under adverse environmental conditions.