A nested case-control study of untargeted plasma metabolomics and lung cancer among never-smoking women within the prospective Shanghai Women's Health Study.

The etiology of lung cancer in never-smokers remains elusive, despite 15% of lung cancer cases in men and 53% in women worldwide being unrelated to smoking. Here, we aimed to enhance our understanding of lung cancer pathogenesis among never-smokers using untargeted metabolomics. This nested case-control study included 395 never-smoking women who developed lung cancer and 395 matched never-smoking cancer-free women from the prospective Shanghai Women's Health Study with 15,353 metabolic features quantified in pre-diagnostic plasma using liquid chromatography high-resolution mass spectrometry. Recognizing that metabolites often correlate and seldom act independently in biological processes, we utilized a weighted correlation network analysis to agnostically construct 28 network modules of correlated metabolites. Using conditional logistic regression models, we assessed the associations for both metabolic network modules and individual metabolic features with lung cancer, accounting for multiple testing using a false discovery rate (FDR) < 0.20. We identified a network module of 121 features inversely associated with all lung cancer (p = .001, FDR = 0.028) and lung adenocarcinoma (p = .002, FDR = 0.056), where lyso-glycerophospholipids played a key role driving these associations. Another module of 440 features was inversely associated with lung adenocarcinoma (p = .014, FDR = 0.196). Individual metabolites within these network modules were enriched in biological pathways linked to oxidative stress, and energy metabolism. These pathways have been implicated in previous metabolomics studies involving populations exposed to known lung cancer risk factors such as traffic-related air pollution and polycyclic aromatic hydrocarbons. Our results suggest that untargeted plasma metabolomics could provide novel insights into the etiology and risk factors of lung cancer among never-smokers.

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.

Environmental pollutant risk factors for worse COVID-19 related clinical outcomes in predominately hispanic and latino populations.

BACKGROUND: Per- and poly-fluorinated compounds (PFAS) and heavy metals constitute two classes of environmental exposures with known immunotoxicant effects. In this pilot study, we aimed to evaluate the impact of exposure to heavy metals and PFAS on COVID-19 severity. We hypothesized that elevated plasma-PFAS concentrations and urinary heavy metal concentrations would be associated with increased odds of ICU admission in COVID-19 hospitalized individuals. METHODS: Using the University of Southern California Clinical Translational Sciences Institute (SC-CTSI) biorepository of hospitalized COVID-19 patients, urinary concentrations of 15 heavy metals and urinary creatinine were measured in n = 101 patients and plasma concentrations of 13 PFAS were measured in n = 126 patients. COVID-19 severity was determined based on whether a patient was admitted to the ICU during hospitalization. Associations of metals and PFAS with ICU admission were assessed using logistic regression models, controlling for age, sex, ethnicity, smoking status, and for metals, urinary dilution. RESULTS: The average age of patients was 55 ± 14.2 years. Among SC-CTSI participants with urinary measurement of heavy metals and blood measures of PFAS, 54.5% (n = 61) and 54.8% (n = 80) were admitted to the ICU, respectively. For heavy metals, we observed higher levels of Cd, Cr, and Cu in ICU patients. The strongest associations were with Cadmium (Cd). After accounting for covariates, each 1 SD increase in Cd resulted in a 2.00 (95% CI: 1.10-3.60; p = 0.03) times higher odds of admission to the ICU. When including only Hispanic or Latino participants, the effect estimates between cadmium and ICU admission remained similar. Results for PFAS were less consistent, with perfluorodecanesulfonic acid (PFDS) exhibiting a positive but non-significant association with ICU admission (Odds ratio, 95% CI: 1.50, 0.97-2.20) and perfluorodecanoic acid (PFDA) exhibiting a negative association with ICU admission (0.53, 0.31-0.88). CONCLUSIONS: This study supports the hypothesis that environmental exposures may impact COVID-19 severity.

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.

Exposure to per- and polyfluoroalkyl substances and alterations in plasma microRNA profiles in children.

BACKGROUND: Per- and polyfluoroalkyl substances (PFAS) are synthetic chemicals that persist in the environment and can accumulate in humans, leading to adverse health effects. MicroRNAs (miRNAs) are emerging biomarkers that can advance the understanding of the mechanisms of PFAS effects on human health. However, little is known about the associations between PFAS exposures and miRNA alterations in humans. OBJECTIVE: To investigate associations between PFAS concentrations and miRNA levels in children. METHODS: Data from two distinct cohorts were utilized: 176 participants (average age 16.6 years; 75.6% female) from the Teen-Longitudinal Assessment of Bariatric Surgery (Teen-LABS) cohort in the United States, and 64 participants (average age 6.5 years, 39.1% female) from the Rhea study, a mother-child cohort in Greece. PFAS concentrations and miRNA levels were assessed in plasma samples from both studies. Associations between individual PFAS and plasma miRNA levels were examined after adjusting for covariates. Additionally, the cumulative effects of PFAS mixtures were evaluated using an exposure burden score. Ingenuity Pathways Analysis was employed to identify potential disease functions of PFAS-associated miRNAs. RESULTS: Plasma PFAS concentrations were associated with alterations in 476 miRNAs in the Teen-LABs study and 13 miRNAs in the Rhea study (FDR p < 0.1). Specifically, plasma PFAS concentrations were consistently associated with decreased levels of miR-148b-3p and miR-29a-3p in both cohorts. Pathway analysis indicated that PFAS-related miRNAs were linked to numerous chronic disease pathways, including cardiovascular diseases, inflammatory conditions, and carcinogenesis. CONCLUSION: Through miRNA screenings in two independent cohorts, this study identified both known and novel miRNAs associated with PFAS exposure in children. Pathway analysis revealed the involvement of these miRNAs in several cancer and inflammation-related pathways. Further studies are warranted to enhance our understanding of the relationships between PFAS exposure and disease risks, with miRNA emerging as potential biomarkers and/or mediators in these complex pathways.

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.

BIOMARKERS OF MATERNAL SMOKING AND THE RISK OF RETINOBLASTOMA IN OFFSPRING.

PURPOSE: Previous studies examining the risk of retinoblastoma with maternal smoking were inconclusive, likely due in part to the reliance on self-reported maternal smoking. This study uses biomarkers of tobacco smoking in neonatal dried blood spots to investigate associations between maternal smoking and retinoblastoma in offspring. METHODS: The authors randomly selected 498 retinoblastoma cases and 895 control subjects born between 1983 and 2011 from a population-based case-control study in California. Maternal pregnancy-related smoking was measured using the following three metrics: provider or self-reported smoking during pregnancy, cotinine, and hydroxycotinine in neonatal blood. The authors used multivariable logistic regression to estimate the effects of maternal tobacco smoking on retinoblastoma. RESULTS: Using all metrics (biomarkers or self-report), maternal smoking late in pregnancy or early postpartum was related to retinoblastoma (all types; odds ratio = 1.44, 95% confidence interval: 1.00-2.09). Relying on cotinine or hydroxycotinine to ascertain smoking, maternal smoking was related to unilateral retinoblastoma (odds ratio = 1.66, 95% confidence interval: 1.08-2.57). CONCLUSION: The results indicate that maternal smoking during pregnancy may be a risk factor for retinoblastoma, particularly among unilateral cases.

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.

Chain alignment of collagen I deciphered using computationally designed heterotrimers.

The most abundant member of the collagen protein family, collagen I (also known as type I collagen; COL1), is composed of one unique (chain B) and two similar (chain A) polypeptides that self-assemble with one amino acid offset into a heterotrimeric triple helix. Given the offset, chain B can occupy either the leading (BAA), middle (ABA) or trailing (AAB) position of the triple helix, yielding three isomeric biomacromolecules with different protein recognition properties. Despite five decades of intensive research, there is no consensus on the position of chain B in COL1. Here, three triple-helical heterotrimers that each contain a putative von Willebrand factor (VWF) and discoidin domain receptor (DDR) recognition sequence from COL1 were designed with chain B permutated in all three positions. AAB demonstrated a strong preference for both VWF and DDR, and also induced higher levels of cellular DDR phosphorylation. Thus, we resolve this long-standing mystery and show that COL1 adopts an AAB register.