Toby J. Athersuch

The Human Early-Life Exposome (HELIX): Project Rationale and Design

Background: Developmental periods in early life may be particularly vulnerable to impacts of environmental exposures. Human research on this topic has generally focused on single exposure–health effect relationships. The “exposome” concept encompasses the totality of exposures from conception onward, complementing the genome. Objectives: The Human Early-Life Exposome (HELIX) project is a new collaborative research project that aims to implement novel exposure assessment and biomarker methods to characterize early-life exposure to multiple environmental factors and associate these with omics biomarkers and child health outcomes, thus characterizing the “early-life exposome.” Here we describe the general design of the project. Methods: In six existing birth cohort studies in Europe, HELIX will estimate prenatal and postnatal exposure to a broad range of chemical and physical exposures. Exposure models will be developed for the full cohorts totaling 32,000 mother–child pairs, and biomarkers will be measured in a subset of 1,200 mother–child pairs. Nested repeat-sampling panel studies (n = 150) will collect data on biomarker variability, use smartphones to assess mobility and physical activity, and perform personal exposure monitoring. Omics techniques will determine molecular profiles (metabolome, proteome, transcriptome, epigenome) associated with exposures. Statistical methods for multiple exposures will provide exposure–response estimates for fetal and child growth, obesity, neurodevelopment, and respiratory outcomes. A health impact assessment exercise will evaluate risks and benefits of combined exposures. Conclusions: HELIX is one of the first attempts to describe the early-life exposome of European populations and unravel its relation to omics markers and health in childhood. As proof of concept, it will form an important first step toward the life-course exposome. Citation: Vrijheid M, Slama R, Robinson O, Chatzi L, Coen M, van den Hazel P, Thomsen C, Wright J, Athersuch TJ, Avellana N, Basagaña X, Brochot C, Bucchini L, Bustamante M, Carracedo A, Casas M, Estivill X, Fairley L, van Gent D, Gonzalez JR, Granum B, Gražulevičienė R, Gutzkow KB, Julvez J, Keun HC, Kogevinas M, McEachan RR, Meltzer HM, Sabidó E, Schwarze PE, Siroux V, Sunyer J, Want EJ, Zeman F, Nieuwenhuijsen MJ. 2014. The Human Early-Life Exposome (HELIX): project rationale and design. Environ Health Perspect 122:535–544; http://dx.doi.org/10.1289/ehp.1307204

Performance in omics analyses of blood samples in long-term storage : opportunities for the exploitation of existing biobanks in environmental health research

Background: The suitability for omic analysis of biosamples collected in previous decades and currently stored in biobanks is unknown. Objectives: We evaluated the influence of handling and storage conditions of blood-derived biosamples on transcriptomic, epigenomic (CpG methylation), plasma metabolomic [UPLC-ToFMS (ultra performance liquid chromatography–time-of-flight mass spectrometry)], and wide-target proteomic profiles. Methods: We collected fresh blood samples without RNA preservative in heparin, EDTA, or citrate and held them at room temperature for ≤ 24 hr before fractionating them into buffy coat, erythrocytes, and plasma and freezing the fractions at –80oC or in liquid nitrogen. We developed methodology for isolating RNA from the buffy coats and conducted omic analyses. Finally, we analyzed analogous samples from the EPIC-Italy and Northern Sweden Health and Disease Study biobanks. Results: Microarray-quality RNA could be isolated from buffy coats (including most biobank samples) that had been frozen within 8 hr of blood collection by thawing the samples in RNA preservative. Different anticoagulants influenced the metabolomic, proteomic, and to a lesser extent transcriptomic profiles. Transcriptomic profiles were most affected by the delay (as little as 2 hr) before blood fractionation, whereas storage temperature had minimal impact. Effects on metabolomic and proteomic profiles were noted in samples processed ≥ 8 hr after collection, but no effects were due to storage temperature. None of the variables examined significantly influenced the epigenomic profiles. No systematic influence of time-in-storage was observed in samples stored over a period of 13–17 years. Conclusions: Most samples currently stored in biobanks are amenable to meaningful omics analysis, provided that they satisfy collection and storage criteria defined in this study.

Meeting-in-the-middle using metabolic profiling – a strategy for the identification of intermediate biomarkers in cohort studies

Background: Predictive disease risk biomarkers that can be linked to exposure have proved difficult to identify in case-control studies. Methods: Parallel statistical analysis of the correlation between 1H NMR profiles from plasma samples collected before disease onset (EPIC cohort), versus exposure to dietary compounds, and follow-up disease endpoints (colon and breast cancer) was performed. Results: Metabonomic signatures associated with colon cancer and dietary fiber intake (a protective factor according to epidemiological studies) were identified. Conclusion: This implementation of the novel “meet-in-the-middle” analytical strategy indicates how case-control studies nested in prospectively collected cohorts may reveal intermediate biomarkers linking exposure and disease.

Consensus-phenotype integration of transcriptomic and metabolomic data implies a role for metabolism in the chemosensitivity of tumour cells

Using transcriptomic and metabolomic measurements from the NCI60 cell line panel, together with a novel approach to integration of molecular profile data, we show that the biochemical pathways associated with tumour cell chemosensitivity to platinum-based drugs are highly coincident, i.e. they describe a consensus phenotype. Direct integration of metabolome and transcriptome data at the point of pathway analysis improved the detection of consensus pathways by 76%, and revealed associations between platinum sensitivity and several metabolic pathways that were not visible from transcriptome analysis alone. These pathways included the TCA cycle and pyruvate metabolism, lipoprotein uptake and nucleotide synthesis by both salvage and de novo pathways. Extending the approach across a wide panel of chemotherapeutics, we confirmed the specificity of the metabolic pathway associations to platinum sensitivity. We conclude that metabolic phenotyping could play a role in predicting response to platinum chemotherapy and that consensus-phenotype integration of molecular profiling data is a powerful and versatile tool for both biomarker discovery and for exploring the complex relationships between biological pathways and drug response.

The carcinoGENOMICS project: Critical selection of model compounds for the development of omics-based in vitro carcinogenicity screening assays

Recent changes in the European legislation of chemical-related substances have forced the scientific community to speed up the search for alternative methods that could partly or fully replace animal experimentation. The Sixth Framework Program project carcinoGENOMICS was specifically raised to develop omics-based in vitro screens for testing the carcinogenic potential of chemical compounds in a pan-European context. This paper provides an in-depth analysis of the complexity of choosing suitable reference compounds used for creating and fine-tuning the in vitro carcinogenicity assays. First, a number of solid criteria for the selection of the model compounds are defined. Secondly, the strategy followed, including resources consulted, is described and the selected compounds are briefly illustrated. Finally, limitations and problems encountered during the selection procedure are discussed. Since selecting an appropriate set of chemicals is a frequent impediment in the early stages of similar research projects, the information provided in this paper might be extremely valuable.

Advancing the application of omics-based biomarkers in environmental epidemiology

The use of omics represents a shift in approach for environmental epidemiology and exposure science. In this article, the aspects of the use of omics that will require further development in the near future are discussed, including (a) the underlying causal interpretation and models; (b) the “meet‐in‐the‐middle” concept, with examples; (c) the role of “calibration” of measurements; and (d) the role of life‐course epidemiology and the related development of adequate biostatistical models. Environ. Mol. Mutagen. 54:461‐467, 2013.

Delineation of the Key Aspects in the Regulation of Epithelial Monolayer Formation

ABSTRACT The formation, maintenance, and repair of epithelial barriers are of critical importance for whole-body homeostasis. However, the molecular events involved in epithelial tissue maturation are not fully established. To this end, we investigated the molecular processes involved in renal epithelial proximal-tubule monolayer maturation utilizing transcriptomic, metabolomic, and functional parameters. We uncovered profound dynamic alterations in transcriptional regulation, energy metabolism, and nutrient utilization over the maturation process. Proliferating cells exhibited high glycolytic rates and high transcript levels for fatty acid synthesis genes (FASN), whereas matured cells had low glycolytic rates, increased oxidative capacity, and preferentially expressed genes for beta oxidation. There were dynamic alterations in the expression and localization of several adherens (CDH1, -4, and -16) and tight junction (TJP3 and CLDN2 and -10) proteins. Genes involved in differentiated proximal-tubule function, cilium biogenesis (BBS1), and transport (ATP1A1 and ATP1B1) exhibited increased expression during epithelial maturation. Using TransAM transcription factor activity assays, we could demonstrate that p53 and FOXO1 were highly active in matured cells, whereas HIF1A and c-MYC were highly active in proliferating cells. The data presented here will be invaluable in the further delineation of the complex dynamic cellular processes involved in epithelial cell regulation.

Urinary metabolic profiles in early pregnancy are associated with preterm birth and fetal growth restriction in the Rhea mother-child cohort study.

BackgroundPreterm birth (PB) and fetal growth restriction (FGR) convey the highest risk of perinatal mortality and morbidity, as well as increasing the chance of developing chronic disease in later life. Identifying early in pregnancy the unfavourable maternal conditions that can predict poor birth outcomes could help their prevention and management. Here we used an exploratory metabolic profiling approach (metabolomics) to investigate the association between birth outcomes and metabolites in maternal urine collected early in pregnancy as part of the prospective mother–child cohort Rhea study. Metabolomic techniques can simultaneously capture information about genotype and its interaction with the accumulated exposures experienced by an individual from their diet, environment, physical activity or disease (the exposome). As metabolic syndrome has previously been shown to be associated with PB in this cohort, we sought to gain further insight into PB-linked metabolic phenotypes and to define new predictive biomarkers.MethodsOur study was a case–control study nested within the Rhea cohort. Major metabolites (n = 34) in maternal urine samples collected at the end of the first trimester (n = 438) were measured using proton nuclear magnetic resonance spectroscopy. In addition to PB, we used FGR in weight and small for gestational age as study endpoints.ResultsWe observed significant associations between FGR and decreased urinary acetate (interquartile odds ratio (IOR) = 0.18 CI 0.04 to 0.60), formate (IOR = 0.24 CI 0.07 to 0.71), tyrosine (IOR = 0.27 CI 0.08 to 0.81) and trimethylamine (IOR = 0.14 CI 0.04 to 0.40) adjusting for maternal education, maternal age, parity, and smoking during pregnancy. These metabolites were inversely correlated with blood insulin. Women with clinically induced PB (IPB) had a significant increase in a glycoprotein N-acetyl resonance (IOR = 5.84 CI 1.44 to 39.50). This resonance was positively correlated with body mass index, and stratified analysis confirmed that N-acetyl glycoprotein and IPB were significantly associated in overweight and obese women only. Spontaneous PB cases were associated with elevated urinary lysine (IOR = 2.79 CI 1.20 to 6.98) and lower formate levels (IOR = 0.42 CI 0.19 to 0.94).ConclusionsUrinary metabolites measured at the end of the first trimester are associated with increased risk of negative birth outcomes, and provide novel information about the possible mechanisms leading to adverse pregnancies in the Rhea cohort. This study emphasizes the potential of metabolic profiling of urine as a means to identify novel non-invasive biomarkers of PB and FGR risk.

Heteronuclear 19F−1H Statistical Total Correlation Spectroscopy as a Tool in Drug Metabolism: Study of Flucloxacillin Biotransformation

We present a novel application of the heteronuclear statistical total correlation spectroscopy (HET-STOCSY) approach utilizing statistical correlation between one-dimensional 19F/1H NMR spectroscopic data sets collected in parallel to study drug metabolism. Parallel one-dimensional (1D) 800 MHz 1H and 753 MHz 19F{1H} spectra (n = 21) were obtained on urine samples collected from volunteers (n = 6) at various intervals up to 24 h after oral dosing with 500 mg of flucloxacillin. A variety of statistical relationships between and within the spectroscopic datasets were explored without significant loss of the typically high 1D spectral resolution, generating 1H-1H STOCSY plots, and novel 19F-1H HET-STOCSY, 19F-19F STOCSY, and 19F-edited 1H-1H STOCSY (X-STOCSY) spectroscopic maps, with a resolution of approximately 0.8 Hz/pt for both nuclei. The efficient statistical editing provided by these methods readily allowed the collection of drug metabolic data and assisted structure elucidation. This approach is of general applicability for studying the metabolism of other fluorine-containing drugs, including important anticancer agents such as 5-fluorouracil and flutamide, and is extendable to any drug metabolism study where there is a spin-active X-nucleus (e.g., 13C, 15N, 31P) label present.

Robust Algorithms for Automated Chemical Shift Calibration of 1D 1H NMR Spectra of Blood Serum

In biofluid NMR spectroscopy, the frequency of each resonance is typically calibrated by addition of a reference compound such as 3-(trimethylsilyl)-propionic acid- d 4 (TSP) to the sample. However biofluids such as serum cannot be referenced to TSP, due to shifts resonance caused by binding to macromolecules in solution. In order to overcome this limitation we have developed algorithms, based on analysis of derivative spectra, to locate and calibrate (1)H NMR spectra to the alpha-glucose anomeric doublet. We successfully used these algorithms to calibrate 77 serum (1)H NMR spectra and demonstrate the greater reproducibility of the calculated chemical-shift corrections ( r = 0.97) than those generated by manual alignment ( r = 0.8-0.88). Hence we show that these algorithms provide robust and reproducible methods of calibrating (1)H NMR of serum, plasma, or any biofluid in which glucose is abundant. Precise automated calibration of complex biofluid NMR spectra is an important tool in large-scale metabonomic or metabolomic studies, where hundreds or even thousands of spectra may be analyzed in high-resolution by pattern recognition analysis.