Integrating -Omics Approaches into Human Population-Based Studies of Prenatal and Early-Life Exposures

Methylomic, Proteomic, and Metabolomic Correlates of Traffic-Related Air Pollution in the Context of Cardiorespiratory Health: A Systematic Review, Pathway Analysis, and Network Analysis

A growing body of literature has attempted to characterize how traffic-related air pollution (TRAP) affects molecular and subclinical biological processes in ways that could lead to cardiorespiratory disease. To provide a streamlined synthesis of what is known about the multiple mechanisms through which TRAP could lead to cardiorespiratory pathology, we conducted a systematic review of the epidemiological literature relating TRAP exposure to methylomic, proteomic, and metabolomic biomarkers in adult populations. Using the 139 papers that met our inclusion criteria, we identified the omic biomarkers significantly associated with short- or long-term TRAP and used these biomarkers to conduct pathway and network analyses. We considered the evidence for TRAP-related associations with biological pathways involving lipid metabolism, cellular energy production, amino acid metabolism, inflammation and immunity, coagulation, endothelial function, and oxidative stress. Our analysis suggests that an integrated multi-omics approach may provide critical new insights into the ways TRAP could lead to adverse clinical outcomes. We advocate for efforts to build a more unified approach for characterizing the dynamic and complex biological processes linking TRAP exposure and subclinical and clinical disease and highlight contemporary challenges and opportunities associated with such efforts.

Prenatal exposures to endocrine disrupting chemicals: The role of multi-omics in understanding toxicity

Endocrine disrupting chemicals (EDCs) are a diverse group of toxicants detected in populations globally. Prenatal EDC exposures impact birth and childhood outcomes. EDCs work through persistent changes at the molecular, cellular, and organ level. Molecular and biochemical signals or 'omics' can be measured at various functional levels - including the epigenome, transcriptome, proteome, metabolome, and the microbiome. In this narrative review, we introduce each omics and give examples of associations with prenatal EDC exposures. There is substantial research on epigenomic modifications in offspring exposed to EDCs during gestation, and a growing number of studies evaluating the transcriptome, proteome, metabolome, or microbiome in response to these exposures. Multi-omics, integrating data across omics layers, may improve understanding of disrupted function pathways related to early life exposures. We highlight several data integration methods to consider in multi-omics studies. Information from multi-omics can improve understanding of the biological processes and mechanisms underlying prenatal EDC toxicity.

Methylomic, proteomic, and metabolomic correlates of traffic-related air pollution: A systematic review, pathway analysis, and network analysis relating traffic-related air pollution to subclinical and clinical cardiorespiratory outcomes

A growing body of literature has attempted to characterize how traffic-related air pollution (TRAP) affects molecular and subclinical biological processes in ways that could lead to cardiorespiratory disease. To provide a streamlined synthesis of what is known about the multiple mechanisms through which TRAP could lead cardiorespiratory pathology, we conducted a systematic review of the epidemiological literature relating TRAP exposure to methylomic, proteomic, and metabolomic biomarkers in adult populations. Using the 139 papers that met our inclusion criteria, we identified the omic biomarkers significantly associated with short- or long-term TRAP and used these biomarkers to conduct pathway and network analyses. We considered the evidence for TRAP-related associations with biological pathways involving lipid metabolism, cellular energy production, amino acid metabolism, inflammation and immunity, coagulation, endothelial function, and oxidative stress. Our analysis suggests that an integrated multi-omics approach may provide critical new insights into the ways TRAP could lead to adverse clinical outcomes. We advocate for efforts to build a more unified approach for characterizing the dynamic and complex biological processes linking TRAP exposure and subclinical and clinical disease, and highlight contemporary challenges and opportunities associated with such efforts.

Integrating -omics approaches into population-based studies of endocrine disrupting chemicals: A scoping review

Health effects of endocrine disrupting chemicals (EDCs) are challenging to detect in the general population. Omics technologies become increasingly common to identify early biological changes before the apparition of clinical symptoms, to explore toxic mechanisms and to increase biological plausibility of epidemiological associations. This scoping review systematically summarises the application of omics in epidemiological studies assessing EDCs-associated biological effects to identify potential gaps and priorities for future research. Ninety-eight human studies (2004-2021) were identified through database searches (PubMed, Scopus) and citation chaining and focused on phthalates (34 studies), phenols (19) and PFASs (17), while PAHs (12) and recently-used pesticides (3) were less studied. The sample sizes ranged from 10 to 12,476 (median = 159), involving non-pregnant adults (38), pregnant women (11), children/adolescents (15) or both latter populations studied together (23). Several studies included occupational workers (10) and/or highly exposed groups (11) focusing on PAHs, PFASs and pesticides, while studies on phenols and phthalates were performed in the general population only. Analysed omics layers included metabolic profiles (30, including 14 targeted analyses), miRNA (13), gene expression (11), DNA methylation (8), microbiome (5) and proteins (3). Twenty-one studies implemented targeted multi-assays focusing on clinical routine blood lipid traits, oxidative stress or hormones. Overall, DNA methylation and gene expression associations with EDCs did not overlap across studies, while some EDC-associated metabolite groups, such as carnitines, nucleotides and amino acids in untargeted metabolomic studies, and oxidative stress markers in targeted studies, were consistent across studies. Studies had common limitations such as small sample sizes, cross-sectional designs and single sampling for exposure biomonitoring. In conclusion, there is a growing body of evidence evaluating the early biological responses to exposure to EDCs. This review points to a need for larger longitudinal studies, wider coverage of exposures and biomarkers, replication studies and standardisation of research methods and reporting.

Associations of prenatal exposure to NO2 and near roadway residence with placental gene expression

INTRODUCTION

Traffic-related air pollution (TRAP), a common exposure, potentially impacts pregnancy through altered placental function. We investigated associations between prenatal TRAP exposure and placental gene expression.

METHODS

Whole transcriptome sequencing was performed on placental samples from CANDLE (Memphis, TN) (n = 776) and GAPPS (Seattle and Yakima, WA) (n = 205), cohorts of the ECHO-PATHWAYS Consortium. Residential NO₂ exposures were computed via spatiotemporal models for full-pregnancy, each trimester, and the first/last months of pregnancy. Individual cohort-specific, covariate-adjusted linear models were fit for 10,855 genes and respective exposures (NO₂ or roadway proximity [≤150 m]). Infant-sex/exposure interactions on placental gene expression were tested with interaction terms in separate models. Significance was based on false discovery rate (FDR<0.10).

RESULTS

In GAPPS, final-month NO₂ exposure was positively associated with MAP1LC3C expression (FDR p-value = 0.094). Infant-sex interacted with second-trimester NO₂ on STRIP2 expression (FDR interaction p-value = 0.011, inverse and positive associations among male and female infants, respectively) and roadway proximity on CEBPA expression (FDR interaction p-value = 0.045, inverse among females). In CANDLE, infant-sex interacted with first-trimester and full-pregnancy NO₂ on RASSF7 expression (FDR interaction p-values = 0.067 and 0.013, respectively, positive among male infants and inverse among female infants).

DISCUSSION

Overall, pregnancy NO₂ exposure and placental gene expression associations were primarily null, with exception of final month NO₂ exposure and placental MAP1LC3C association. We found several interactions of infant sex and TRAP exposures on placental expression of STRIP2, CEBPA, and RASSF7. These highlighted genes suggest influence of TRAP on placental cell proliferation, autophagy, and growth, though additional replication and functional studies are required for validation.

Mono(2-ethylhexyl) phthalate induces transcriptomic changes in placental cells based on concentration, fetal sex, and trophoblast cell type

Phthalates are ubiquitous plasticizer chemicals found in consumer products. Exposure to phthalates during pregnancy has been associated with adverse pregnancy and birth outcomes and differences in placental gene expression in human studies. The objective of this research was to evaluate global changes in placental gene expression via RNA sequencing in two placental cell models following exposure to the phthalate metabolite mono(2-ethylhexyl) phthalate (MEHP). HTR-8/SVneo and primary syncytiotrophoblast cells were exposed to three concentrations (1, 90, 180 µM) of MEHP for 24 h with DMSO (0.1%) as a vehicle control. mRNA and lncRNAs were quantified using paired-end RNA sequencing, followed by identification of differentially expressed genes (DEGs), significant KEGG pathways, and enriched transcription factors (TFs). MEHP caused gene expression changes across all concentrations for HTR-8/SVneo and primary syncytiotrophoblast cells. Sex-stratified analysis of primary cells identified different patterns of sensitivity in response to MEHP dose by sex, with male placentas being more responsive to MEHP exposure. Pathway analysis identified 11 KEGG pathways significantly associated with at least one concentration in both cell types. Four ligand-inducible nuclear hormone TFs (PPARG, PPARD, ESR1, AR) were enriched in at least three treatment groups. Overall, we demonstrated that MEHP differentially affects placental gene expression based on concentration, fetal sex, and trophoblast cell type. This study confirms prior studies, as enrichment of nuclear hormone receptor TFs were concordant with previously published mechanisms of phthalate disruption, and generates new hypotheses, as we identified many pathways and genes not previously linked to phthalate exposure.

Placental transcriptomic signatures of prenatal exposure to Hydroxy-Polycyclic aromatic hydrocarbons

BACKGROUND

Polycyclic aromatic hydrocarbons (PAHs) are ubiquitous pollutants originating from petrogenic and pyrogenic sources. PAH compounds can cross the placenta, and prenatal PAH exposure is linked to adverse infant and childhood health outcomes.

OBJECTIVE

In this first human transcriptomic assessment of PAHs in the placenta, we examined associations between prenatal PAH exposure and placental gene expression to gain insight into mechanisms by which PAHs may disrupt placental function.

METHODS

The ECHO PATHWAYS Consortium quantified prenatal PAH exposure and the placental transcriptome from 629 pregnant participants enrolled in the CANDLE study. Concentrations of 12 monohydroxy-PAH (OH-PAH) metabolites were measured in mid-pregnancy urine using high performance liquid chromatography tandem mass spectrometry. Placental transcriptomic data were obtained using paired-end RNA sequencing. Linear models were fitted to estimate covariate-adjusted associations between maternal urinary OH-PAHs and placental gene expression. We performed sex-stratified analyses to evaluate whether associations varied by fetal sex. Selected PAH/gene expression analyses were validated by treating HTR-8/SVneo cells with phenanthrene, and quantifying expression via qPCR.

RESULTS

Urinary concentrations of 6 OH-PAHs were associated with placental expression of 8 genes. Three biological pathways were associated with 4 OH-PAHs. Placental expression of SGF29 and TRIP13 as well as the vitamin digestion and absorption pathway were positively associated with multiple metabolites. HTR-8/SVneo cells treated with phenanthrene also exhibited 23 % increased TRIP13 expression compared to vehicle controls (p = 0.04). Fetal sex may modify the relationship between prenatal OH-PAHs and placental gene expression, as more associations were identified in females than males (45 vs 28 associations).

DISCUSSION

Our study highlights novel genes whose placental expression may be disrupted by OH-PAHs. Increased expression of DNA damage repair gene TRIP13 may represent a response to double-stranded DNA breaks. Increased expression of genes involved in vitamin digestion and metabolism may reflect dietary exposures or represent a compensatory mechanism to combat damage related to OH-PAH toxicity. Further work is needed to study the role of these genes in placental function and their links to perinatal outcomes and lifelong health.

Metal mixtures modeling identifies birth weight-associated gene networks in the placentas of children born extremely preterm

Prenatal exposure to toxic metals is linked to numerous adverse birth and later-in-life outcomes. These outcomes are tied to disrupted biological processes in fetal-derived tissues including the placenta and umbilical cord yet the precise pathways are understudied in these target tissues. We set out to examine the relationship between metal concentrations in umbilical cord and altered gene expression networks in placental tissue. These novel relationships were investigated in a subset of the Extremely Low Gestational Age Newborn (ELGAN) cohort (n = 226). Prenatal exposure to 11 metals/metalloids was measured using inductively coupled plasma tandem-mass spectrometry (ICP-MS/MS) in cord tissue, ensuring passage through the placental barrier. RNA-sequencing was used to quantify >37,000 mRNA transcripts. Differentially expressed genes (DEGs) were identified with respect to each metal. Weighted gene co-expression analysis identified gene networks modulated by metals. Two innovative mixtures modeling techniques, namely principal components analysis and quantile-based g-computation, were employed to identify genes/gene networks associated with multi-metal exposure. Individually, lead was associated with the strongest genomic response of 191 DEGs. Joint lead and cadmium exposure was related to 657 DEGs, including DNA Methyl Transferase 1 (DNMT1). These genes were enriched for the Eukaryotic Initiation Factor 2 (EIF2) pathway. Four gene networks, each containing genes within a Nuclear Factor kappa-light-chain-enhancer of Activated B Cells (NF-kB)-mediated network, were significantly increased in average expression level in relation to increases in all metal concentrations. All four of these metal mixture-associated gene networks were negatively correlated with important predictors of neonatal health including birth weight, placenta weight, and fetal growth. Bringing together novel methodologies from epidemiological mixtures analyses and toxicogenomics, applied to a unique cohort of extremely preterm children, the present study highlighted critical genes and pathways in the placenta dysregulated by prenatal metal mixtures. These represent potential mechanisms underlying the developmental origins of metal-induced disease.

Multi-omics signatures of the human early life exposome

Environmental exposures during early life play a critical role in life-course health, yet the molecular phenotypes underlying environmental effects on health are poorly understood. In the Human Early Life Exposome (HELIX) project, a multi-centre cohort of 1301 mother-child pairs, we associate individual exposomes consisting of >100 chemical, outdoor, social and lifestyle exposures assessed in pregnancy and childhood, with multi-omics profiles (methylome, transcriptome, proteins and metabolites) in childhood. We identify 1170 associations, 249 in pregnancy and 921 in childhood, which reveal potential biological responses and sources of exposure. Pregnancy exposures, including maternal smoking, cadmium and molybdenum, are predominantly associated with child DNA methylation changes. In contrast, childhood exposures are associated with features across all omics layers, most frequently the serum metabolome, revealing signatures for diet, toxic chemical compounds, essential trace elements, and weather conditions, among others. Our comprehensive and unique resource of all associations ( https://helixomics.isglobal.org/ ) will serve to guide future investigation into the biological imprints of the early life exposome.

Climate change, human health, and the exposome: Utilizing OMIC technologies to navigate an era of uncertainty

Climate change is an anthropogenic phenomenon that is alarming scientists and non-scientists alike. The emission of greenhouse gases is causing the temperature of the earth to rise and this increase is accompanied by a multitude of climate change-induced environmental exposures with potential health impacts. Tracking human exposure has been a major research interest of scientists worldwide. This has led to the development of exposome studies that examine internal and external individual exposures over their lifetime and correlate them to health. The monitoring of health has also benefited from significant technological advances in the field of "omics" technologies that analyze physiological changes on the nucleic acid, protein, and metabolism levels, among others. In this review, we discuss various climate change-induced environmental exposures and their potential health implications. We also highlight the potential integration of the technological advancements in the fields of exposome tracking, climate monitoring, and omics technologies shedding light on important questions that need to be answered.

'Omics in environmental epidemiological studies of chemical exposures: A systematic evidence map

BACKGROUND

Systematic evidence maps are increasingly used to develop chemical risk assessments. These maps can provide an overview of available studies and relevant study information to be used for various research objectives and applications. Environmental epidemiological studies that examine the impact of chemical exposures on various 'omic profiles in human populations provide relevant mechanistic information and can be used for benchmark dose modeling to derive potential human health reference values.

OBJECTIVES

To create a systematic evidence map of environmental epidemiological studies examining environmental contaminant exposures with 'omics in order to characterize the extent of available studies for future research needs.

METHODS

Systematic review methods were used to search and screen the literature and included the use of machine learning methods to facilitate screening studies. The Populations, Exposures, Comparators and Outcomes (PECO) criteria were developed to identify and screen relevant studies. Studies that met the PECO criteria after full-text review were summarized with information such as study population, study design, sample size, exposure measurement, and 'omics analysis.

RESULTS

Over 10,000 studies were identified from scientific databases. Screening processes were used to identify 84 studies considered PECO-relevant after full-text review. Various contaminants (e.g. phthalate, benzene, arsenic, etc.) were investigated in epidemiological studies that used one or more of the four 'omics of interest: epigenomics, transcriptomics, proteomics, and metabolomics . The epidemiological study designs that were used to explore single or integrated 'omic research questions with contaminant exposures were cohort studies, controlled trials, cross-sectional, and case-control studies. An interactive web-based systematic evidence map was created to display more study-related information.

CONCLUSIONS

This systematic evidence map is a novel tool to visually characterize the available environmental epidemiological studies investigating contaminants and biological effects using 'omics technology and serves as a resource for investigators and allows for a range of applications in chemical research and risk assessment needs.

The Placental Epigenome as a Molecular Link Between Prenatal Exposures and Fetal Health Outcomes Through the DOHaD Hypothesis

Purpose of Review

The developmental origins of health and disease (DOHaD) hypothesis posits that the perinatal environment can impact fetal and later life health. The placenta is uniquely situated to assess prenatal exposures in the context of DOHaD because it is an essential ephemeral fetal organ that manages the transport of oxygen, nutrients, waste, and endocrine signals between the mother and fetus. The purpose of this review is to summarize recent studies that evaluated the DOHaD hypothesis in human placentas using epigenomics, including DNA methylation and transcriptomic studies of mRNA, lncRNA, and microRNAs.

Recent Findings

Between 2016 and 2021, 28 articles evaluated associations between prenatal exposures and placental epigenomics across broad exposure categories including maternal smoking, psychosocial stressors, chemicals, air pollution, and metals. Sixteen of these studies connected exposures to health outcome such as birth weight, fetal growth, or infant neurobehavior through mediation analysis, identification of shared associations between exposure and outcome, or network analysis. These aspects of infant and childhood health serve as a foundation for future studies that aim to use placental epigenetics to understand relationships between the prenatal environment and perinatal complications (such as preterm birth or fetal growth restriction) or later life childhood health.

Summary

Placental DNA methylation and RNA expression have been linked to numerous prenatal exposures, such as PM2.5 air pollution, metals, and maternal smoking, as well as infant and childhood health outcomes, including fetal growth and birth weight. Placental epigenomics provides a unique opportunity to expand the DOHaD premise, particularly if research applies novel methodologies such as multi-omics analysis, sequencing of non-coding RNAs, mixtures analysis, and assessment of health outcomes beyond early childhood.

A Comprehensive Assessment of Associations between Prenatal Phthalate Exposure and the Placental Transcriptomic Landscape

BACKGROUND

Phthalates are commonly used endocrine-disrupting chemicals that are ubiquitous in the general population. Prenatal phthalate exposure may alter placental physiology and fetal development, leading to adverse perinatal and childhood health outcomes.

OBJECTIVE

We examined associations between prenatal phthalate exposure in the second and third trimesters and the placental transcriptome at birth, including genes and long noncoding RNAs (lncRNAs), to gain insight into potential mechanisms of action during fetal development.

METHODS

The ECHO PATHWAYs consortium quantified 21 urinary phthalate metabolites from 760 women enrolled in the CANDLE study (Shelby County, TN) using high-performance liquid chromatography-tandem mass spectrometry. Placental transcriptomic data were obtained using paired-end RNA sequencing. Linear models were fitted to estimate separate associations between maternal urinary phthalate metabolite concentration during the second and third trimester and placental gene expression at birth, adjusted for confounding variables. Genes were considered differentially expressed at a Benjamini-Hochberg false discovery rate (FDR) p<0.05. Associations between phthalate metabolites and biological pathways were identified using self-contained gene set testing and considered significantly altered with an FDR-adjusted p<0.2.

RESULTS

We observed significant associations between second-trimester phthalate metabolites mono (carboxyisooctyl) phthalate (MCIOP), mono-2-ethyl-5-carboxypentyl phthalate, and mono-2-ethyl-5-oxohexyl phthalate and 18 genes in total, including four lncRNAs. Specifically, placental expression of NEAT1 was associated with multiple phthalate metabolites. Third-trimester MCIOP and mono-isobutyl phthalate concentrations were significantly associated with placental expression of 18 genes and two genes, respectively. Expression of genes within 27 biological pathways was associated with mono-methyl phthalate, MCIOP, and monoethyl phthalate concentrations.

DISCUSSION

To our knowledge, this is the first genome-wide assessment of the relationship between the placental transcriptome at birth and prenatal phthalate exposure in a large and diverse birth cohort. We identified numerous genes and lncRNAs associated with prenatal phthalate exposure. These associations mirror findings from other epidemiological and in vitro analyses and may provide insight into biological pathways affected in utero by phthalate exposure. https://doi.org/10.1289/EHP8973.

Variability of multi-omics profiles in a population-based child cohort

BACKGROUND

Multiple omics technologies are increasingly applied to detect early, subtle molecular responses to environmental stressors for future disease risk prevention. However, there is an urgent need for further evaluation of stability and variability of omics profiles in healthy individuals, especially during childhood.

METHODS

We aimed to estimate intra-, inter-individual and cohort variability of multi-omics profiles (blood DNA methylation, gene expression, miRNA, proteins and serum and urine metabolites) measured 6 months apart in 156 healthy children from five European countries. We further performed a multi-omics network analysis to establish clusters of co-varying omics features and assessed the contribution of key variables (including biological traits and sample collection parameters) to omics variability.

RESULTS

All omics displayed a large range of intra- and inter-individual variability depending on each omics feature, although all presented a highest median intra-individual variability. DNA methylation was the most stable profile (median 37.6% inter-individual variability) while gene expression was the least stable (6.6%). Among the least stable features, we identified 1% cross-omics co-variation between CpGs and metabolites (e.g. glucose and CpGs related to obesity and type 2 diabetes). Explanatory variables, including age and body mass index (BMI), explained up to 9% of serum metabolite variability.

CONCLUSIONS

Methylation and targeted serum metabolomics are the most reliable omics to implement in single time-point measurements in large cross-sectional studies. In the case of metabolomics, sample collection and individual traits (e.g. BMI) are important parameters to control for improved comparability, at the study design or analysis stage. This study will be valuable for the design and interpretation of epidemiological studies that aim to link omics signatures to disease, environmental exposures, or both.

Endocrine disrupting chemicals (EDCs) and placental function: Impact on fetal brain development

Pregnancy is a critical time of vulnerability for the development of the fetal brain. Exposure to environmental pollutants at any point in pregnancy can negatively impact many aspects of fetal development, especially the organization and differentiation of the brain. The placenta performs a variety of functions that can help protect the fetus and sustain brain development. However, disruption of any of these functions can have negative impacts on both the pregnancy outcome and fetal neurodevelopment. This review presents current understanding of how environmental exposures, specifically to endocrine disrupting chemicals (EDCs), interfere with placental function and, in turn, neurodevelopment. Some of the key differences in placental development between animal models are presented, as well as how placental functions such as serving as a xenobiotic barrier and exchange organ, immune interface, regulator of growth and fetal oxygenation, and a neuroendocrine organ, could be vulnerable to environmental exposure. This review illustrates the importance of the placenta as a modulator of fetal brain development and suggests critical unexplored areas and possible vulnerabilities to environmental exposure.

Exacerbation of cardiovascular ageing by diabetes mellitus and its associations with acyl-carnitines

Objective: To demonstrate differences in cardiovascular structure and function between diabetic and non-diabetic older adults. To investigate associations between acyl-carnitines and cardiovascular function as indexed by imaging measurements.

Methods: A community-based cohort of older adults without cardiovascular disease underwent current cardiovascular imaging and metabolomics acyl-carnitines profiling based on current and archived sera obtained fifteen years prior to examination.

Results: A total of 933 participants (women 56%, n=521) with a mean age 63±13 years were studied. Old diabetics compared to old non-diabetics had lower myocardial relaxation (0.8±0.2 vs 0.9±0.3, p=0.0039); lower left atrial conduit strain (12±4.3 vs 14±4.1, p=0.045), lower left atrial conduit strain rate (-1.2±0.4 vs -1.3±0.5, p=0.042) and lower ratio of left atrial conduit strain to left atrial booster strain (0.5±0.2 vs 0.7±0.3, p=0.0029). Higher levels of archived short chain acyl-carnitine were associated with present-day impairments in myocardial relaxation (C5:1; OR 1.03, p=0.011), worse left atrial conduit strain function (C5:1; OR 1.03, p=0.037). Increases in hydroxylated acyl-carnitines were associated with worse left atrial conduit strain [(C4-OH; OR 1.05, p=0.0017), (C16:2-OH; OR 1.18, p=0.037)]. Current, archived and changes in long chain acyl-carnitines were associated with cardiovascular functions [(C16; OR 1.02, p=0.002), (C20:3; OR 1.01, p=0.014), (C14:3; OR 1.12, p=0.033), (C18:1; OR 1.01, p=0.018), (C18:2; OR 1.01, p=0.028), (C20:4; OR 1.10, p=0.038)] (all p<0.05).

Conclusion: Older diabetic adults had significant impairments in left ventricular myocardial relaxation and left atrial strain, compared to older non-diabetic adults. Short chain and long chain, di-carboxyl and hydroxylated acyl-carnitines were associated with these cardiovascular functional differences.

A Structured Approach to Evaluating Life-Course Hypotheses: Moving Beyond Analyses of Exposed Versus Unexposed in the -Omics Context

The structured life-course modeling approach (SLCMA) is a theory-driven analytical method that empirically compares multiple prespecified life-course hypotheses characterizing time-dependent exposure-outcome relationships to determine which theory best fits the observed data. In this study, we performed simulations and empirical analyses to evaluate the performance of the SLCMA when applied to genomewide DNA methylation (DNAm). Using simulations (n = 700), we compared 5 statistical inference tests used with SLCMA, assessing the familywise error rate, statistical power, and confidence interval coverage to determine whether inference based on these tests was valid in the presence of substantial multiple testing and small effects-2 hallmark challenges of inference from -omics data. In the empirical analyses (n = 703), we evaluated the time-dependent relationship between childhood abuse and genomewide DNAm. In simulations, selective inference and the max-|t|-test performed best: Both controlled the familywise error rate and yielded moderate statistical power. Empirical analyses using SLCMA revealed time-dependent effects of childhood abuse on DNAm. Our findings show that SLCMA, applied and interpreted appropriately, can be used in high-throughput settings to examine time-dependent effects underlying exposure-outcome relationships over the life course. We provide recommendations for applying the SLCMA in -omics settings and encourage researchers to move beyond analyses of exposed versus unexposed individuals.

Proteomics in systems toxicology

Proteins are the ultimate product of gene expression. As they hinge between gene transcription and phenotype, they offer a more realistic perspective of toxicopathic effects, responses and even susceptibility to insult than targeting genes and mRNAs while dodging some inter-individual variability that hinders measuring downstream endpoints like metabolites or enzyme activity. Toxicologists have long focused on proteins as biomarkers but the advent of proteomics shifted risk assessment from narrow single-endpoint analyses to whole-proteome screening, enabling deriving protein-centric adverse outcome pathways (AOPs), which are pivotal for the derivation of Systems Biology informally named Systems Toxicology. Especially if coupled pathology, the identification of molecular initiating events (MIEs) and AOPs allow predictive modeling of toxicological pathways, which now stands as the frontier for the next generation of toxicologists. Advances in mass spectrometry, bioinformatics, protein databases and top-down proteomics create new opportunities for mechanistic and effects-oriented research in all fields, from ecotoxicology to pharmacotoxicology.

Metabolomics and cardiovascular imaging: a combined approach for cardiovascular ageing

The purpose of this review is to explore how metabolomics can help uncover new biomarkers and mechanisms for cardiovascular ageing. Cardiovascular ageing refers to cardiovascular structural and functional alterations that occur with chronological ageing and that can lead to the development of cardiovascular disease. These alterations, which were previously only detectable on tissue histology or corroborated on blood samples, are now detectable with modern imaging techniques. Despite the emergence of powerful new imaging tools, clinical investigation into cardiovascular ageing is challenging because ageing is a life course phenomenon involving known and unknown risk factors that play out in a dynamic fashion. Metabolomic profiling measures large numbers of metabolites with diverse chemical properties. Metabolomics has the potential to capture changes in biochemistry brought about by pathophysiologic processes as well as by normal ageing. When combined with non-invasive cardiovascular imaging tools, metabolomics can be used to understand pathological consequences of cardiovascular ageing. This review will summarize previous metabolomics and imaging studies in cardiovascular ageing. These methods may be a clinically relevant and novel approach to identify mechanisms of cardiovascular ageing and formulate or personalize treatment strategies.

Metabolomics data complemented drug use information in epidemiological databases: pilot study of potential kidney donors

OBJECTIVE

The objective of this study was to investigate whether clinical metabolomics, which is increasingly applied in population-based and epidemiological studies, can be used to provide analytical evidence of exposures, and whether such information can be useful to strengthen and/or complement corresponding clinical database entries, taking drug use as an example.

STUDY DESIGN AND SETTING

Liquid chromatography-mass spectrometry (LC-MS) metabolomics analyses were performed on urine from 100 randomly-selected control subjects (50% females) from the TransplantLines Food and Nutrition Biobank and Cohort Study (NCT identifier 'NCT02811835'), and drugs were identified through spectral library searching and targeted signal extraction.

RESULTS

In 83 subjects for whom drug use information was available, 22 expected and 26 unexpected prescription-only drugs were identified, while 28 expected prescription-only drugs remained undetected. In addition, 7 prescription-only drugs were found in 17 subjects for whom drug use information was unavailable, and 58 over-the-counter drugs were identified in all 100 subjects.

CONCLUSION

Molecular evidence for many drugs could be retrieved from LC-MS metabolomics data, which could be useful to complement and strengthen epidemiological databases given that considerable discrepancies were found between analytically-identified drugs and drugs listed in the available clinical database.

Exposomal research in the context of birth cohorts: What have they taught us?

OBJECTIVE

To review birth cohorts with an exposomal approach and their key outcomes and challenges. Exposome encompasses all human environmental exposures from conception onward. The impact of environmental exposures is greatest in critical stages of life, including fetal and early childhood. Birth cohorts provide a good study setting to assess exposome in the sensitive periods of life. Here, we review birth cohorts with an exposomal approach and their key outcomes and challenges.

DATA SOURCES

MEDLINE was searched for birth cohorts that have used an exposomal approach.

STUDY SELECTIONS

Relevant studies in English language were selected and reviewed.

RESULTS

The outcomes of birth cohorts with an exposomal approach improve our understanding of the association between environmental exposures and childhood diseases. For example, results from The Canadian Healthy Infant Longitudinal Development Study suggest an association between first trimester exposure to traffic-related air pollution and increased risk of allergic sensitization at 12 months of age (P = .6). In a smaller Canadian birth cohort study, it was found that regular use of air fresheners (adjusted P = .04) and presence of mold in the residence (adjusted P < .001) were associated with early childhood wheezing and cough. The application of emerging molecular omics technologies and new analytical tools has facilitated the comprehensive assessment of exposome in birth cohorts.

CONCLUSION

Birth cohort studies with an exposomal approach improve our understanding of the origin of childhood diseases by examining a complex network of environmental exposures during pregnancy and years beyond birth. International collaboration is required to develop large birth cohorts for better and more extensive assessment of exposome with standardized protocols and new statistical frameworks.

Clinical expression of endocrine disruptors in children

PURPOSE OF REVIEW

Health status is the result of complex interaction between individual factors, general environmental factors and specific factors as nutrition or the presence of chemicals. Aim of this review is to point out the more recent knowledge covering the role of the endocrine disrupting chemical (EDC) on pediatric population wellbeing.

RECENT FINDINGS

Prenatal, postnatal life and puberty are the three main temporal windows of susceptibility when EDCs may act. The mechanism is independent from dose or duration of exposition, sex, age or combination of chemicals and may also be transgenerational, affecting both growth and pubertal timing. A window of susceptibility for breast cancer has been detected. Thyroid gland is influenced by environmental chemicals, both in utero and during childhood. Alteration in Thyrotropin stimulating hormone (TSH) levels and neurodevelopmental impairment have been demonstrate. It has been detected a pro-obesogenic action of specific chemicals, impairing also glucose homeostasis during childhood.

SUMMARY

With a multidisciplinary approach and the use of big data platforms, an attempt has to be made to verify biological variations related to a disease, and how much the risk is influenced by the presence of the endocrine disruptors. This may help the future generation to better interpret uncommunicable diseases.

Using phenome-wide association studies to examine the effect of environmental exposures on human health

The field of environmental epidemiology has been using "-omics" technologies, including the exposome, metabolome, and methylome, to understand the potential effects and biological pathways of a number of environmental pollutants. However, the majority of studies have focused on a single disease or phenotype, and have not systematically considered patterns of multimorbidity and whether environmental pollutants have pleiotropic effects. These questions could be addressed by examining the relation between environmental exposures and the phenome - the patterns and profiles of human health that individuals experience from birth to death. By conducting Phenome Wide Association Studies (PheWAS), we can generate new hypotheses about new or poorly understood exposures, identify novel associations for established toxicants, and better understand biological pathways affected by environmental pollutants. In this article, we provide a conceptual framework for conducting PheWAS in environmental epidemiology and summarize some of the advantages and challenges to using the PheWAS to study environmental pollutant exposures. Ultimately, by adding the PheWAS to our "-omics" toolbox, we could substantially improve our understanding of the potential health effects of environmental pollutants.