Lung cancer metabolomics: a pooled analysis in the Cancer Prevention Studies.

BACKGROUND: A better understanding of lung cancer etiology and the development of screening biomarkers have important implications for lung cancer prevention. METHODS: We included 623 matched case-control pairs from the Cancer Prevention Study (CPS) cohorts. Pre-diagnosis blood samples were collected between 1998 and 2001 in the CPS-II Nutrition cohort and 2006 and 2013 in the CPS-3 cohort and were sent for metabolomics profiling simultaneously. Cancer-free controls at the time of case diagnosis were 1:1 matched to cases on date of birth, blood draw date, sex, and race/ethnicity. Odds ratios (ORs) and 95% confidence intervals (CIs) were estimated using conditional logistic regression, controlling for confounders. The Benjamini-Hochberg method was used to correct for multiple comparisons. RESULTS: Sphingomyelin (d18:0/22:0) (OR: 1.32; 95% CI: 1.15, 1.53, FDR = 0.15) and taurodeoxycholic acid 3-sulfate (OR: 1.33; 95% CI: 1.14, 1.55, FDR = 0.15) were positively associated with lung cancer risk. Participants diagnosed within 3 years of blood draw had a 55% and 48% higher risk of lung cancer per standard deviation increase in natural log-transformed sphingomyelin (d18:0/22:0) and taurodeoxycholic acid 3-sulfate level, while 26% and 28% higher risk for those diagnosed beyond 3 years, compared to matched controls. Lipid and amino acid metabolism accounted for 47% to 80% of lung cancer-associated metabolites at P < 0.05 across all participants and subgroups. Notably, ever-smokers exhibited a higher proportion of lung cancer-associated metabolites (P < 0.05) in xenobiotic- and lipid-associated pathways, whereas never-smokers showed a more pronounced involvement of amino acid- and lipid-associated metabolic pathways. CONCLUSIONS: This is the largest prospective study examining untargeted metabolic profiles regarding lung cancer risk. Sphingomyelin (d18:0/22:0), a sphingolipid, and taurodeoxycholic acid 3-sulfate, a bile salt, may be risk factors and potential screening biomarkers for lung cancer. Lipid and amino acid metabolism may contribute significantly to lung cancer etiology which varied by smoking status.

Former smoking associated with epigenetic modifications in human granulosa cells among women undergoing assisted reproduction.

Smoking exposure during adulthood can disrupt oocyte development in women, contributing to infertility and possibly adverse birth outcomes. Some of these effects may be reflected in epigenome profiles in granulosa cells (GCs) in human follicular fluid. We compared the epigenetic modifications throughout the genome in GCs from women who were former (N = 15) versus never smokers (N = 44) undergoing assisted reproductive technologies (ART). This study included 59 women undergoing ART. Smoking history including time since quitting was determined by questionnaire. GCs were collected during oocyte retrieval and DNA methylation (DNAm) levels were profiled using the Infinium MethylationEPIC BeadChip. We performed an epigenome-wide association study with robust linear models, regressing DNAm level at individual loci on smoking status, adjusting for age, ovarian stimulation protocol, and three surrogate variables. We performed differentially methylated regions (DMRs) analysis and over-representation analysis of the identified CpGs and corresponding gene set. 81 CpGs were differentially methylated among former smokers compared to never smokers (FDR < 0.05). We identified 2 significant DMRs (KCNQ1 and RHBDD2). The former smoking-associated genes were enriched in oxytocin signaling, adrenergic signaling in cardiomyocytes, platelet activation, axon guidance, and chemokine signaling pathway. These epigenetic variations have been associated with inflammatory responses, reproductive outcomes, cancer development, neurodevelopmental disorder, and cardiometabolic health. Secondarily, we examined the relationships between time since quitting and DNAm at significant CpGs. We observed three CpGs in negative associations with the length of quitting smoking (p < 0.05), which were cg04254052 (KCNIP1), cg22875371 (OGDHL), and cg27289628 (LOC148145), while one in positive association, which was cg13487862 (PLXNB1). As a pilot study, we demonstrated epigenetic modifications associated with former smoking in GCs. The study is informative to potential biological pathways underlying the documented association between smoking and female infertility and biomarker discovery for smoking-associated reproductive outcomes.

A State-of-the-Science Review on High-Resolution Metabolomics Application in Air Pollution Health Research: Current Progress, Analytical Challenges, and Recommendations for Future Direction.

BACKGROUND: Understanding the mechanistic basis of air pollution toxicity is dependent on accurately characterizing both exposure and biological responses. Untargeted metabolomics, an analysis of small-molecule metabolic phenotypes, may offer improved estimation of exposures and corresponding health responses to complex environmental mixtures such as air pollution. The field remains nascent, however, with questions concerning the coherence and generalizability of findings across studies, study designs and analytical platforms. OBJECTIVES: We aimed to review the state of air pollution research from studies using untargeted high-resolution metabolomics (HRM), highlight the areas of concordance and dissimilarity in methodological approaches and reported findings, and discuss a path forward for future use of this analytical platform in air pollution research. METHODS: We conducted a state-of-the-science review to a) summarize recent research of air pollution studies using untargeted metabolomics and b) identify gaps in the peer-reviewed literature and opportunities for addressing these gaps in future designs. We screened articles published within Pubmed and Web of Science between 1 January 2005 and 31 March 2022. Two reviewers independently screened 2,065 abstracts, with discrepancies resolved by a third reviewer. RESULTS: We identified 47 articles that applied untargeted metabolomics on serum, plasma, whole blood, urine, saliva, or other biospecimens to investigate the impact of air pollution exposures on the human metabolome. Eight hundred sixteen unique features confirmed with level-1 or -2 evidence were reported to be associated with at least one or more air pollutants. Hypoxanthine, histidine, serine, aspartate, and glutamate were among the 35 metabolites consistently exhibiting associations with multiple air pollutants in at least 5 independent studies. Oxidative stress and inflammation-related pathways-including glycerophospholipid metabolism, pyrimidine metabolism, methionine and cysteine metabolism, tyrosine metabolism, and tryptophan metabolism-were the most commonly perturbed pathways reported in >70% of studies. More than 80% of the reported features were not chemically annotated, limiting the interpretability and generalizability of the findings. CONCLUSIONS: Numerous investigations have demonstrated the feasibility of using untargeted metabolomics as a platform linking exposure to internal dose and biological response. Our review of the 47 existing untargeted HRM-air pollution studies points to an underlying coherence and consistency across a range of sample analytical quantitation methods, extraction algorithms, and statistical modeling approaches. Future directions should focus on validation of these findings via hypothesis-driven protocols and technical advances in metabolic annotation and quantification. https://doi.org/10.1289/EHP11851.

Metapone: a Bioconductor package for joint pathway testing for untargeted metabolomics data.

MOTIVATION: Testing for pathway enrichment is an important aspect in the analysis of untargeted metabolomics data. Due to the unique characteristics of untargeted metabolomics data, some key issues have not been fully addressed in existing pathway testing algorithms: (i) matching uncertainty between data features and metabolites; (ii) lacking of method to analyze positive mode and negative mode liquid chromatography-mass spectrometry (LC/MS) data simultaneously on the same set of subjects; (iii) the incompleteness of pathways in individual software packages. RESULTS: We developed an innovative R/Bioconductor package: metabolic pathway testing with positive and negative mode data (metapone), which can perform two novel statistical tests that take matching uncertainty into consideration-(i) a weighted gene set enrichment analysis-type test and (ii) a permutation-based weighted hypergeometric test. The package is capable of combining positive- and negative-ion mode results in a single testing scheme. For comprehensiveness, the built-in pathways were manually curated from three sources: Kyoto Encyclopedia of Genes and Genomes, Mummichog and The Small Molecule Pathway Database. AVAILABILITY AND IMPLEMENTATION: The package is available at https://bioconductor.org/packages/devel/bioc/html/metapone.html. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Length of PM2.5 exposure and alterations in the serum metabolome among women undergoing infertility treatment.

BACKGROUND: Both acute and chronic exposure to fine particulate matter (PM2.5) have been linked to negative health outcomes. Studies have used metabolomics to describe the biological pathways linking PM2.5 with disease but have focused on a single exposure window. We compared alterations in the serum metabolome following various short- and long-term PM2.5 exposures. METHODS: Participants were women undergoing in vitro fertilization at a New England fertility clinic (n = 200). Women provided their residential address and provided a blood sample during controlled ovarian stimulation. PM2.5 exposure was estimated in the 1, 2, and 3 days, 2 weeks, and 3 months prior to blood collection using a validated spatiotemporal model. We utilized liquid chromatography with high-resolution mass spectrometry. We used generalized linear models to test for associations between metabolomic features and PM2.5 exposures after adjusting for potential confounders. Significant features (P < 0.005) were used for pathway analysis and metabolite identification. RESULTS: We identified 17 pathways related to amino acid, lipid, energy, and nutrient metabolism that were solely associated with acute PM2.5 exposure. Fifteen pathways, mostly, pro-inflammatory, anti-inflammatory, amino acid, and energy metabolism, were solely associated with long-term PM2.5 exposure. Seven pathways were associated with the majority of exposure windows and were mostly related to anti-inflammatory and lipid metabolism. Among the significant features, we confirmed seven metabolites with level-1 evidence. CONCLUSIONS: We identified serum metabolites and metabolic pathways uniquely associated with acute versus chronic PM2.5 exposure. These different biologic pathways may help explain differences in disease states when investigating different lengths of PM2.5 exposure.

The Oxidative Potential of Fine Particulate Matter and Biological Perturbations in Human Plasma and Saliva Metabolome.

Particulate oxidative potential may comprise a key health-relevant parameter of particulate matter (PM) toxicity. To identify biological perturbations associated with particulate oxidative potential and examine the underlying molecular mechanisms, we recruited 54 participants from two dormitories near and far from a congested highway in Atlanta, GA. Fine particulate matter oxidative potential ("FPMOP") levels at the dormitories were measured using dithiothreitol assay. Plasma and saliva samples were collected from participants four times for longitudinal high-resolution metabolic profiling. We conducted metabolome-wide association studies to identify metabolic signals with FPMOP. Leukotriene metabolism and galactose metabolism were top pathways associated with ≥5 FPMOP-related indicators in plasma, while vitamin E metabolism and leukotriene metabolism were found associated with most FPMOP indicators in saliva. We observed different patterns of perturbed pathways significantly associated with water-soluble and -insoluble FPMOPs, respectively. We confirmed five metabolites directly associated with FPMOP, including hypoxanthine, histidine, pyruvate, lactate/glyceraldehyde, and azelaic acid, which were implications of perturbations in acute inflammation, nucleic acid damage and repair, and energy perturbation. The unique metabolic signals were specific to FPMOP, but not PM mass, providing initial indication that FPMOP might constitute a more sensitive, health-relevant measure for elucidating etiologies related to PM2.5 exposures.

High-resolution metabolomics of exposure to tobacco smoke during pregnancy and adverse birth outcomes in the Atlanta African American maternal-child cohort.

Exposure to tobacco smoke during pregnancy has been associated with a series of adverse reproductive outcomes; however, the underlying molecular mechanisms are not well-established. We conducted an untargeted metabolome-wide association study to identify the metabolic perturbations and molecular mechanisms underlying the association between cotinine, a widely used biomarker of tobacco exposure, and adverse birth outcomes. We collected early and late pregnancy urine samples for cotinine measurement and serum samples for high-resolution metabolomics (HRM) profiling from 105 pregnant women from the Atlanta African American Maternal-Child cohort (2014-2016). Maternal metabolome perturbations mediating prenatal tobacco smoke exposure and adverse birth outcomes were assessed by an untargeted HRM workflow using generalized linear models, followed by pathway enrichment analysis and chemical annotation, with a meet-in-the-middle approach. The median maternal urinary cotinine concentrations were 5.93 µg/g creatinine and 3.69 µg/g creatinine in early and late pregnancy, respectively. In total, 16,481 and 13,043 metabolic features were identified in serum samples at each visit from positive and negative electrospray ionization modes, respectively. Twelve metabolic pathways were found to be associated with both cotinine concentrations and adverse birth outcomes during early and late pregnancy, including tryptophan, histidine, urea cycle, arginine, and proline metabolism. We confirmed 47 metabolites associated with cotinine levels, preterm birth, and shorter gestational age, including glutamate, serine, choline, and taurine, which are closely involved in endogenous inflammation, vascular reactivity, and lipid peroxidation processes. The metabolic perturbations associated with cotinine levels were related to inflammation, oxidative stress, placental vascularization, and insulin action, which could contribute to shorter gestations. The findings will support the further understanding of potential internal responses in association with tobacco smoke exposures, especially among African American women who are disproportionately exposed to high tobacco smoke and experience higher rates of adverse birth outcomes.

Periconception air pollution, metabolomic biomarkers, and fertility among women undergoing assisted reproduction.

BACKGROUND: Air pollution exposure has been linked with diminished fertility. Identifying the metabolic changes induced by periconception air pollution exposure among women could enhance our understanding of the potential biological pathways underlying air pollution's reproductive toxicity. OBJECTIVE: To identify serum metabolites associated with periconception air pollution exposure and evaluate the extent to which these metabolites mediate the association between air pollution and live birth. METHODS: We included 200 women undergoing a fresh assisted reproductive technology (ART) cycle at Massachusetts General Hospital Fertility Center (2005-2015). A serum sample was collected during stimulation, and untargeted metabolic profiling was conducted using liquid chromatography with ultra-high-resolution mass spectrometry. Exposure to nitrogen dioxide (NO2), ozone (O3), fine particulate matter <2.5 µm (PM2.5), and black carbon (BC) was estimated using validated spatiotemporal models. Multivariable linear regression models were used to evaluate the associations between the air pollutants, live birth, and metabolic feature intensities. A meet in the middle approach was used to identify overlapping features and metabolic pathways. RESULTS: From the C18 and HILIC chromatography columns, 10,803 and 12,968 metabolic features were extracted. There were 190 metabolic features and 18 pathways that were significantly associated with both air pollution and live birth (P < 0.05) across chromatography columns. Eight features were confirmed metabolites implicated in amino acid and nutrient metabolism with downstream effects on oxidative stress and inflammation. Six confirmed metabolites fell into two intuitive clusters - "antioxidants" and "oxidants"- which could potentially mediate some of the association between air pollution and lower odds of live birth. Tryptophan and vitamin B3 metabolism were common pathways linking air pollution exposure to decreased probability of live birth. CONCLUSION: Higher periconception air pollution exposure was associated with metabolites and biologic pathways involved in inflammation and oxidative stress that may mediate the observed associations with lower probability of live birth following ART.