Molecular Gatekeeper Discovery: Workflow for Linking Multiple Exposure Biomarkers to Metabolomics

Per- and poly-fluoroalkyl substances (PFAS) accelerate biological aging mediated by increased C-reactive protein

Unhealthy biological aging is related to higher incidence of varied age-related diseases, even higher all-cause mortality. Previous small sample size study suggested that Per- and poly-fluoroalkyl substances (PFAS) was associated with biological aging, but the evidence of exposure-response relationships, potential effect modifiers, and potential mediators were not investigated. Therefore, we conducted a cross-sectional analysis of national study including 14, 865 adults in the US from 8 survey cycles of NHANES from 2003 to 2018, to investigate the associations of PFAS compounds in body serum, including perfluorooctanoic acid (PFOA), perfluorooctane sulfonic acid (PFOS), perfluorononanoic acid (PFNA), and perfluorohexane sulfonic acid (PFHxS), with biological aging. Generalized linear models showed that higher human exposure to PFAS was associated with accelerated biological aging. Importantly, human exposure to PFOA, PFOS, PFNA, and PFHxS with detected level (above 0.10 ng/mL) was associated with an average of 3.3 year (95 %CI: 2.7, 3.9, P < 0.001), 14.9 year (95 %CI: 7.2, 22.7, P < 0.001), 10.9 years (95 %CI: 3.9, 17.7, P < 0.001), and 8.8 years (95 %CI: 4.8, 12.9, P < 0.001) of biological aging acceleration. Cubic spline models indicated exposure-response relationships where there was no safe threshold of PFAS level regarding harms to human healthy aging. The weighted sum regression model found the significant associations of PFAS compound mixture with biological aging acceleration, and PFOA was the dominant contributor among 4 PFAS compounds. Mediation analysis suggested that C-reactive protein, one of the inflammation biomarkers, might play as mediator in PFAS-induced accelerated biological aging, but not Triglyceride-glucose index. In summary, our study suggests that the effects of PFAS on biological aging acceleration should be of concern and more action plans to address their negative impact on human health should be launched.

Volatile organic compound exposure in relation to lung cancer: Insights into mechanisms of action through metabolomics

Volatile organic compounds (VOCs) have proven to be hazardous to the human respiratory system. However, the underlying biological mechanisms remain poorly understood. Therefore, targeted determination of eleven VOC metabolites (mVOCs) along with the nontargeted metabolomic analysis was performed on urine samples collected from lung cancer patients and healthy individuals. Nine mVOCs mainly derived from aldehydes, alkenes, amides, and aromatics were detected in > 90 % of the urine samples, suggesting that the participants were ubiquitously exposed to these typical VOCs. A molecular gatekeeper discovery workflow was employed to link the exposure biomarkers with correlated clusters of endogenous metabolites. As a result, multiple metabolic pathways, including amino acid metabolism, steroid hormone biosynthesis and metabolism, and fatty acid β-oxidation were connected with VOC exposure. Furthermore, 16 of 73 molecular gatekeepers were associated with lung cancer and pointed to a few disrupted metabolic pathways related to hydroxysteroids and acylcarnitine. The shift in molecular profiles was validated in rat model post VOC administration. Thereinto, the up-regulation of enzymes involved in acylcarnitine synthesis and transport in rat lung tissues highlighted that the mitochondrial dysfunction may be a potential carcinogenic mechanism. Our findings provide new insights into the mechanisms underlying lung cancer induced by VOC exposure.

Rich nutrition decreases the concentration of metals in Chaeturichthys stigmatias

Metals play a vital role in living organisms, serving as cofactors for enzymes, structural components of proteins, and participants in signaling pathways. However, the relationship between metal content and nutrient levels in organisms has not been thoroughly elucidated, which is the major barrier to regulate metal levels in organisms. In this study, we investigated the association between muscle metal concentration and external nutritional conditions, as well as intrinsic nutrient requirements in Chaeturichthys stigmatias. The results demonstrated a negative correlation between muscle metal levels and body mass index (BMI). Furthermore, our investigation unveiled a negative correlation between metal levels and zooplankter abundance, as well as a positive correlation with the abundance of underlying phytoplankton and chlorophyll. Moreover, metal levels gradually increased during the development of gonads, particularly in female individuals. As the gonads matured and ovulated, metal levels gradually decreased. The same trends were observed in Mouse erythroleukemia cells (MEL) when different concentrations of FBS were added. Collectively, these findings highlight the inherent connection between metal levels and nutrition, and offer potential guidance for regulating metal homeostasis in organisms, as well as reducing the exposure of organisms to toxic heavy metals in the environment. SYNOPSIS: With an increase in the level of external nutrients and a decrease in intrinsic nutrient requirements, the level of metals in the organism gradually decreases.

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.

Hunting Metabolic Biomarkers for Exposure to Per- and Polyfluoroalkyl Substances: A Review

Per- and polyfluoroalkyl substances (PFAS) represent a class of persistent synthetic chemicals extensively utilized across industrial and consumer sectors, raising substantial environmental and human health concerns. Epidemiological investigations have robustly linked PFAS exposure to a spectrum of adverse health outcomes. Altered metabolites stand as promising biomarkers, offering insights into the identification of specific environmental pollutants and their deleterious impacts on human health. However, elucidating metabolic alterations attributable to PFAS exposure and their ensuing health effects has remained challenging. In light of this, this review aims to elucidate potential biomarkers of PFAS exposure by presenting a comprehensive overview of recent metabolomics-based studies exploring PFAS toxicity. Details of PFAS types, sources, and human exposure patterns are provided. Furthermore, insights into PFAS-induced liver toxicity, reproductive and developmental toxicity, cardiovascular toxicity, glucose homeostasis disruption, kidney toxicity, and carcinogenesis are synthesized. Additionally, a thorough examination of studies utilizing metabolomics to delineate PFAS exposure and toxicity biomarkers across blood, liver, and urine specimens is presented. This review endeavors to advance our understanding of PFAS biomarkers regarding exposure and associated toxicological effects.

Active Molecular Network Discovery Links Lifestyle Variables to Breast Cancer in the Long Island Breast Cancer Study Project

A healthy lifestyle has been associated with decreased risk of developing breast cancer. Using untargeted metabolomics profiling, which provides unbiased information regarding lifestyle choices such as diet and exercise, we aim to identify the molecular mechanisms connecting lifestyle and breast cancer through network analysis. A total of 100 postmenopausal women, 50 with breast cancer and 50 cancer-free controls, were selected from the Long Island Breast Cancer Study Project (LIBCSP). We measured untargeted plasma metabolomics using liquid chromatography-high-resolution mass spectrometry (LC-HRMS). Using the "enet" package, we retained highly correlated metabolites representing active molecular network (AMN) clusters for analysis. LASSO was used to examine associations between cancer status and AMN metabolites and covariates such as BMI, age, and reproductive factors. LASSO was then repeated to examine associations between AMN metabolites and 10 lifestyle-related variables including smoking, physical activity, alcohol consumption, meat consumption, fruit and vegetable consumption, and supplemental vitamin use. Results were displayed as a network to uncover biological pathways linking lifestyle factors to breast cancer status. After filtering, 851 "active" metabolites out of 1797 metabolomics were retained in 197 correlation AMN clusters. Using LASSO, breast cancer status was associated with 71 "active" metabolites. Several of these metabolites were associated with lifestyle variables including meat consumption, alcohol consumption, and supplemental β-carotene, B12, and folate use. Those metabolites could potentially serve as molecular-level biological intermediaries connecting healthy lifestyle factors to breast cancer, even though direct associations between breast cancer and the investigated lifestyles at the phenotype level are not evident. In particular, DiHODE, a metabolite linked with inflammation, was associated with breast cancer status and connected to β-carotene supplement usage through an AMN. We found several plasma metabolites associated with lifestyle factors and breast cancer status. Future studies investigating the mechanistic role of inflammation in linking supplement usage to breast cancer status are warranted.

Comparison of maternal venous blood metabolomics collected as dried blood spots, dried blood microsamplers, and plasma for integrative environmental health research

Use of capillary blood devices for exposome research can deepen our understanding of the intricate relationship between environment and health, and open up new avenues for preventive and personalized medicine, particularly for vulnerable populations. While the potential of these whole blood devices to accurately measure chemicals and metabolites has been demonstrated, how untargeted metabolomics data from these samplers can be integrated with previous and ongoing environmental health studies that have used conventional blood collection approaches is not yet clear. Therefore, we performed a comprehensive comparison between relative-quantitative metabolite profiles measured in venous blood collected with dried whole blood microsamplers (DBM), dried whole blood spots (DBS), and plasma from 54 mothers in an ethnically diverse population. We determined that a majority of the 309 chemicals and metabolites showed similar median intensity rank, moderate correlation, and moderate agreement between participant-quantiled intraclass correlation coefficients (ICCs) for pair-wise comparisons among the three biomatrices. In particular, whole blood sample types, DBM and DBS, were in highest agreement across metabolite comparison metrics, followed by metabolites measured in DBM and plasma, and then metabolites measured in DBS and plasma. We provide descriptive characteristics and measurement summaries as a reference database. This includes unique metabolites that were particularly concordant or discordant in pairwise comparisons. Our results demonstrate that the range of metabolites from untargeted metabolomics data collected with DBM, DBS, and plasma provides biologically relevant information for use in independent exposome investigations. However, before meta-analysis with combined datasets are performed, robust statistical approaches that integrate untargeted metabolomics data collected on different blood matrices need to be developed.

Effects of storage temperature and time on metabolite profiles measured in dried blood spots, dried blood microsamplers, and plasma

The practical advantages of capillary whole blood collection over venipuncture plasma collection for human exposome research are well known. However, before epidemiologists, clinicians, and public health researchers employ these microvolume sample collections, a rigorous evaluation of pre-analytical storage conditions is needed to develop protocols that maximize sample stability and reliability over time. Therefore, we performed a controlled experiment of dried whole blood collected on 10 μL Mitra microsamplers (DBM), 5-mm punches of whole blood from a dried blood spot (DBS), and 10 μL of plasma, and evaluated the effects of storage conditions at 4 °C, -20 °C, or -80 °C for up to 6 months on the resulting metabolite profiles measured with untargeted liquid chromatography-high resolution mass spectrometry (LC-HRMS). At -80 °C storage conditions, metabolite profiles from DBS, DBM, and plasma showed similar stability. While DBS and DBM metabolite profiles remained similarly stable at -20 °C storage, plasma profiles showed decreased stability at -20 °C compared to -80 °C storage. At refrigerated temperatures (4 °C), metabolite profiles collected on DBM were more stable than plasma or DBS, particularly for lipid classes. These results inform robust capillary blood sample storage protocols for DBM and DBS at potentially warmer temperatures than -80 °C, which may facilitate blood collections for populations outside of a clinical setting.

Metabolic and Microbial Profiling of Soil Microbial Community under Per- and Polyfluoroalkyl Substance (PFAS) Stress

Per- and polyfluoroalkyl substances (PFAS) represent significant stress to organisms and are known to disrupt microbial community structure and function. Nevertheless, a detailed knowledge of the soil microbial community responding to PFAS stress at the metabolism level is required. Here we integrated UPLC-HRMS-based metabolomics data with 16S rRNA and ITS amplicon data across soil samples collected adjacent to a fluoropolymer production facility to directly identify the biochemical intermediates in microbial metabolic pathways and the interactions with microbial community structure under PFAS stress. A strong correlation between metabolite and microbial diversity was observed, which demonstrated significant variations in soil metabolite profiles and microbial community structures along with the sampling locations relative to the facility. Certain key metabolites were identified in the metabolite-PFAS co-occurrence network, functioning on microbial metabolisms including lipid metabolism, amino acid metabolism, and secondary metabolite biosynthesis. These results provide novel insights into the impacts of PFAS contamination on soil metabolomes and microbiomes. We suggest that soil metabolomics is an informative and useful tool that could be applied to reinforce the chemical evidence on the disruption of microbial ecological traits.

Per- and polyfluoroalkyl substances (PFAS) exposure and thyroid cancer risk

BACKGROUND

Although per- and polyfluoroalkyl substances (PFAS) exposure is a potential contributor to the increasing thyroid cancer trend, limited studies have investigated the association between PFAS exposure and thyroid cancer in human populations. We therefore investigated associations between plasma PFAS levels and thyroid cancer diagnosis using a nested case-control study of patients with thyroid cancer with plasma samples collected at/before cancer diagnosis.

METHODS

88 patients with thyroid cancer using diagnosis codes and 88 healthy (non-cancer) controls pair-matched on sex, age (±5 years), race/ethnicity, body mass index, smoking status, and year of sample collection were identified in the BioMe population (a medical record-linked biobank at the Icahn School of Medicine at Mount Sinai in New York); 74 patients had papillary thyroid cancer. Eight plasma PFAS were measured using untargeted analysis with liquid chromatography-high resolution mass spectrometry and suspect screening. Associations between individual PFAS levels and thyroid cancer were evaluated using unconditional logistic regression models to estimate adjusted odds ratios (ORadj) and 95% confidence intervals (CI).

FINDINGS

There was a 56% increased rate of thyroid cancer diagnosis per doubling of linear perfluorooctanesulfonic acid (n-PFOS) intensity (ORadj, 1.56, 95% CI: 1.17-2.15, P = 0.004); results were similar when including patients with papillary thyroid cancer only (ORadj, 1.56, 95% CI: 1.13-2.21, P = 0.009). This positive association remained in subset analysis investigating exposure timing including 31 thyroid cancer cases diagnosed ≥1 year after plasma sample collection (ORadj, 2.67, 95% CI: 1.59-4.88, P < 0.001).

INTERPRETATION

This study reports associations between exposure to PFAS and increased rate of (papillary) thyroid cancer. Thyroid cancer risk from PFAS exposure is a global concern given the prevalence of PFAS exposure. Individual PFAS studied here are a small proportion of the total number of PFAS supporting additional large-scale prospective studies investigating thyroid cancer risk associated with exposure to PFAS chemicals.

FUNDING

National Institutes of Health grants and The Andrea and Charles Bronfman Philanthropies.

PFAS Exposures and the Human Metabolome: A Systematic Review of Epidemiological Studies

Purpose of Review

There is a growing interest in understanding the health effects of exposure to per- and polyfluoroalkyl substances (PFAS) through the study of the human metabolome. In this systematic review, we aimed to identify consistent findings between PFAS and metabolomic signatures. We conducted a search matching specific keywords that was independently reviewed by two authors on two databases (EMBASE and PubMed) from their inception through July 19, 2022 following PRISMA guidelines.

Recent Findings

We identified a total of 28 eligible observational studies that evaluated the associations between 31 different PFAS exposures and metabolomics in humans. The most common exposure evaluated was legacy long-chain PFAS. Population sample sizes ranged from 40 to 1,105 participants at different stages across the lifespan. A total of 19 studies used a non-targeted metabolomics approach, 7 used targeted approaches, and 2 included both. The majority of studies were cross-sectional (n = 25), including four with prospective analyses of PFAS measured prior to metabolomics.

Summary

Most frequently reported associations across studies were observed between PFAS and amino acids, fatty acids, glycerophospholipids, glycerolipids, phosphosphingolipids, bile acids, ceramides, purines, and acylcarnitines. Corresponding metabolic pathways were also altered, including lipid, amino acid, carbohydrate, nucleotide, energy metabolism, glycan biosynthesis and metabolism, and metabolism of cofactors and vitamins. We found consistent evidence across studies indicating PFAS-induced alterations in lipid and amino acid metabolites, which may be involved in energy and cell membrane disruption.

Salivary Metabolomic Signatures and Body Mass Index in Italian Adolescents: A Pilot Study

Context

Obesity surveillance is scarce in adolescents, and little is known on whether salivary metabolomics data, emerging minimally invasive biomarkers, can characterize metabolic patterns associated with overweight or obesity in adolescents.

Objective

This pilot study aims to identify the salivary molecular signatures associated with body mass index (BMI) in Italian adolescents.

Methods

Saliva samples and BMI were collected in a subset of n = 74 young adolescents enrolled in the Public Health Impact of Metal Exposure study (2007-2014). A total of 217 untargeted metabolites were identified using liquid chromatography-high resolution mass spectrometry. Robust linear regression was used to cross-sectionally determine associations between metabolomic signatures and sex-specific BMI-for-age z-scores (z-BMI).

Results

Nearly 35% of the adolescents (median age: 12 years; 51% females) were either obese or overweight. A higher z-BMI was observed in males compared to females (P = .02). One nucleoside (deoxyadenosine) and 2 lipids (18:0-18:2 phosphatidylcholine and dipalmitoyl-phosphoethanolamine) were negatively related to z-BMI (P < .05), whereas 2 benzenoids (3-hydroxyanthranilic acid and a phthalate metabolite) were positively associated with z-BMI (P < .05). In males, several metabolites including deoxyadenosine, as well as deoxycarnitine, hyodeoxycholic acid, N-methylglutamic acid, bisphenol P, and trigonelline were downregulated, while 3 metabolites (3-hydroxyanthranilic acid, theobromine/theophylline/paraxanthine, and alanine) were upregulated in relation to z-BMI (P < .05). In females, deoxyadenosine and dipalmitoyl-phosphoethanolamine were negatively associated with z-BMI while deoxycarnitine and a phthalate metabolite were positively associated (P < .05). A single energy-related pathway was enriched in the identified associations in females (carnitine synthesis, P = .04).

Conclusion

Salivary metabolites involved in nucleotide, lipid, and energy metabolism were primarily altered in relation to BMI in adolescents.

AI/ML-driven advances in untargeted metabolomics and exposomics for biomedical applications

Metabolomics describes a high-throughput approach for measuring a repertoire of metabolites and small molecules in biological samples. One utility of untargeted metabolomics, unbiased global analysis of the metabolome, is to detect key metabolites as contributors to, or readouts of, human health and disease. In this perspective, we discuss how artificial intelligence (AI) and machine learning (ML) have promoted major advances in untargeted metabolomics workflows and facilitated pivotal findings in the areas of disease screening and diagnosis. We contextualize applications of AI and ML to the emerging field of high-resolution mass spectrometry (HRMS) exposomics, which unbiasedly detects endogenous metabolites and exogenous chemicals in human tissue to characterize exposure linked with disease outcomes. We discuss the state of the science and suggest potential opportunities for using AI and ML to improve data quality, rigor, detection, and chemical identification in untargeted metabolomics and exposomics studies.