Recent developments in technologies have offered opportunities to measure the exposome with unprecedented accuracy and scale. However, because most investigations have targeted only a few exposures ...at a time, it is hypothesized that the majority of the environmental determinants of chronic diseases remain unknown.
We describe a functional exposome concept and explain how it can leverage existing bioassays and high-resolution mass spectrometry for exploratory study. We discuss how such an approach can address well-known barriers to interpret exposures and present a vision of next-generation exposomics.
The exposome is vast. Instead of trying to capture all exposures, we can reduce the complexity by measuring the functional exposome-the totality of the biologically active exposures relevant to disease development-through coupling biochemical receptor-binding assays with affinity purification-mass spectrometry. We claim the idea of capturing exposures with functional biomolecules opens new opportunities to solve critical problems in exposomics, including low-dose detection, unknown annotations, and complex mixtures of exposures. Although novel, biology-based measurement can make use of the existing data processing and bioinformatics pipelines. The functional exposome concept also complements conventional targeted and untargeted approaches for understanding exposure-disease relationships.
Although measurement technology has advanced, critical technological, analytical, and inferential barriers impede the detection of many environmental exposures relevant to chronic-disease etiology. Through biology-driven exposomics, it is possible to simultaneously scale up discovery of these causal environmental factors. https://doi.org/10.1289/EHP8327.
Evidence of bisphenols' obesogenic effects on humans is mixed and inconsistent. We aimed to explore the presence of bisphenol A (BPA), bisphenol F (BPF) and chlorinated BPA (ClBPA), collectively ...called the bisphenols, in different brain regions and their association with obesity using post-mortem hypothalamic and white matter brain material from twelve pairs of obese (body mass index (BMI) >30 kg/m
) and normal-weight individuals (BMI <25 kg/m
). Mean ratios of hypothalamus:white matter for BPA, BPF and ClBPA were 1.5, 0.92, 0.95, respectively, suggesting no preferential accumulation of the bisphenols in the grey matter (hypothalamic) or white matter-enriched brain areas. We observed differences in hypothalamic concentrations among the bisphenols, with highest median level detected for ClBPA (median: 2.4 ng/g), followed by BPF (2.2 ng/g) and BPA (1.2 ng/g); similar ranking was observed for the white matter samples (median for: ClBPA-2.5 ng/g, BPF-2.3 ng/g, and BPA-1.0 ng/g). Furthermore, all bisphenol concentrations, except for white-matter BPF were associated with obesity (p < 0.05). This is the first study reporting the presence of bisphenols in two distinct regions of the human brain. Bisphenols accumulation in the white matter-enriched brain tissue could signify that they are able to cross the blood-brain barrier.
Non-persistent endocrine disrupting chemicals (npEDCs) can affect multiple organs and systems in the body. Whether npEDCs can accumulate in the human brain is largely unknown. The major aim of this ...pilot study was to examine the presence of environmental phenols and parabens in two distinct brain regions: the hypothalamus and white-matter tissue. In addition, a potential association between these npEDCs concentrations and obesity was investigated. Post-mortem brain material was obtained from 24 individuals, made up of 12 obese and 12 normal-weight subjects (defined as body mass index (BMI) > 30 and BMI < 25 kg/m², respectively). Nine phenols and seven parabens were measured by isotope dilution TurboFlow-LC-MS/MS. In the hypothalamus, seven suspect npEDCs (bisphenol A, triclosan, triclocarban and methyl-, ethyl-, n-propyl-, and benzyl paraben) were detected, while five npEDCs (bisphenol A, benzophenone-3, triclocarban, methyl-, and n-propyl paraben) were found in the white-matter brain tissue. We observed higher levels of methylparaben (MeP) in the hypothalamic tissue of obese subjects as compared to controls (
0.008). Our findings indicate that some suspected npEDCs are able to cross the blood-brain barrier. Whether the presence of npEDCs can adversely affect brain function and to which extent the detected concentrations are physiologically relevant needs to be further investigated.
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•Unique genome-wide association study of multiple EDCs in 24-hour urine.•Four independent SNPs associated with EDCs through multi-trait GWAS analysis.•SNPs in CYP450 and SLC genes ...associated with MECPP and MEHHP.•CYP2C9 and SLC17A1 likely play causal roles in phthalate metabolism and excretion.
Ubiquitous exposure to environmental endocrine disrupting chemicals (EDCs) instigates a major public health problem, but much remains unknown on the inter-individual differences in metabolism and excretion of EDCs. To examine this we performed a two-stage genome-wide association study (GWAS) for 24-hour urinary excretions of four parabens, two bisphenols, and nine phthalate metabolites. Results showed five genome-wide significant (p-value < 5x10-8) and replicated single nucleotide polymorphisms (SNPs) representing four independent signals that associated with mono-(2-ethyl-5-carboxypentyl) phthalate (MECPP) and mono-(2-ethyl-5-hydroxyhexyl) phthalate (MEHHP). Three of the four signals were located on chromosome 10 in a locus harboring the cytochrome P450 (CYP) genes CYP2C9, CYP2C58P, and CYP2C19 (rs117529685, pMECPP = 5.38x10-25; rs117033379, pMECPP = 1.96x10-19; rs4918798, pMECPP = 4.01x10-71; rs7895726, pMEHHP = 1.37x10-15, r2 with rs4918798 = 0.93). The other signal was on chromosome 6 close to the solute carrier (SLC) genes SLC17A1, SLC17A3, SLC17A4, and SCGN (rs1359232, pMECPP = 7.6x10-16). These four SNPs explained a substantial part (8.3 % - 9.2 %) of the variance in MECPP in the replication cohort. Bioinformatics analyses supported a likely causal role of CYP2C9 and SLC17A1 in metabolism and excretion of MECPP and MEHHP. Our results provide biological insights into mechanisms of phthalate metabolism and excretion with a likely causal role for CYP2C9 and SLC17A1.
•Unique study of association of multiple EDCs with genome-wide DNA methylation.•EDC excretions in 24-hour urine were associated with 20 DNA methylation markers.•EDC-associated CpGs were associated ...with glucose, HbA1c, lipids and blood pressure.•EDC-associated CpGs may be functional markers for assessing metabolic alterations.
Exposure to environmental endocrine disrupting chemicals (EDCs) may play an important role in the epidemic of metabolic diseases. Epigenetic alterations may functionally link EDCs with gene expression and metabolic traits.
We aimed to evaluate metabolic-related effects of the exposure to endocrine disruptors including five parabens, three bisphenols, and 13 metabolites of nine phthalates as measured in 24-hour urine on epigenome-wide DNA methylation.
A blood-based epigenome-wide association study was performed in 622 participants from the Lifelines DEEP cohort using Illumina Infinium HumanMethylation450 methylation data and EDC excretions in 24-hour urine. Out of the 21 EDCs, 13 compounds were detected in >75% of the samples and, together with bisphenol F, were included in these analyses. Furthermore, we explored the putative function of identified methylation markers and their correlations with metabolic traits.
We found 20 differentially methylated cytosine-phosphate-guanines (CpGs) associated with 10 EDCs at suggestive p-value < 1 × 10−6, of which four, associated with MEHP and MEHHP, were genome-wide significant (Bonferroni-corrected p-value < 1.19 × 10−7). Nine out of 20 CpGs were significantly associated with at least one of the tested metabolic traits, such as fasting glucose, glycated hemoglobin, blood lipids, and/or blood pressure. 18 out of 20 EDC-associated CpGs were annotated to genes functionally related to metabolic syndrome, hypertension, obesity, type 2 diabetes, insulin resistance and glycemic traits.
The identified DNA methylation markers for exposure to the most common EDCs provide suggestive mechanism underlying the contributions of EDCs to metabolic health. Follow-up studies are needed to unravel the causality of EDC-induced methylation changes in metabolic alterations.
Aims/hypothesis
We aimed to assess and contextualise 134 potential risk variables for the development of type 2 diabetes and to determine their applicability in risk prediction.
Methods
A total of ...96,534 people without baseline diabetes (372,007 person-years) from the Dutch Lifelines cohort were included. We used a risk variable-wide association study (RV-WAS) design to independently screen and replicate risk variables for 5-year incidence of type 2 diabetes. For identified variables, we contextualised HRs, calculated correlations and assessed their robustness and unique contribution in different clinical contexts using bootstrapped and cross-validated lasso regression models. We evaluated the change in risk, or ‘HR trajectory’, when sequentially assigning variables to a model.
Results
We identified 63 risk variables, with novel associations for quality-of-life indicators and non-cardiovascular medications (i.e., proton-pump inhibitors, anti-asthmatics). For continuous variables, the increase of 1 SD of HbA
1c
, i.e., 3.39 mmol/mol (0.31%), was equivalent in risk to an increase of 0.53 mmol/l of glucose, 19.8 cm of waist circumference, 8.34 kg/m
2
of BMI, 0.67 mmol/l of HDL-cholesterol, and 0.14 mmol/l of uric acid. Other variables required an increase of >3 SD, which is not physiologically realistic or a rare occurrence in the population. Though moderately correlated, the inclusion of four variables satiated prediction models. Invasive variables, except for glucose and HbA
1c
, contributed little compared with non-invasive variables. Glucose, HbA
1c
and family history of diabetes explained a unique part of disease risk. Adding risk variables to a satiated model can impact the HRs of variables already in the model.
Conclusions
Many variables show weak or inconsistent associations with the development of type 2 diabetes, and only a handful can reliably explain disease risk. Newly discovered risk variables will yield little over established factors, and existing prediction models can be simplified. A systematic, data-driven approach to identify risk variables for the prediction of type 2 diabetes is necessary for the practice of precision medicine.
Graphical abstract
The importance of microbial communities (MCs) cannot be overstated. MCs underpin the biogeochemical cycles of the earth's soil, oceans and the atmosphere, and perform ecosystem functions that impact ...plants, animals and humans. Yet our ability to predict and manage the function of these highly complex, dynamically changing communities is limited. Building predictive models that link MC composition to function is a key emerging challenge in microbial ecology. Here, we argue that addressing this challenge requires close coordination of experimental data collection and method development with mathematical model building. We discuss specific examples where model-experiment integration has already resulted in important insights into MC function and structure. We also highlight key research questions that still demand better integration of experiments and models. We argue that such integration is needed to achieve significant progress in our understanding of MC dynamics and function, and we make specific practical suggestions as to how this could be achieved.
The link between exposure to endocrine disrupting chemicals (EDCs) and the rapid increase in prevalence of obesity has recently been suggested. However, the magnitude and health impact of EDC ...exposure in at-risk populations remain largely unclear. In this study, we investigated the effect of a dietary intervention driven reduction in adipose tissue on the magnitude of urinary EDC exposure and mobilization, and whether higher EDC exposure leads to impaired weight loss in obese individuals. In this post-hoc analysis of the Lifestyle, OverWeight, Energy Restriction (LOWER) study from the Netherlands, 218 subjects were included. Five parabens, three bisphenols and thirteen metabolites of eight phthalates were measured in 24-h urine using LC-MS/MS, before and after three-months of a calory-restricted weight reduction intervention program. Associations between adiposity-related traits and EDCs were tested using multivariable linear regression and linear mixed effects models. A multiple testing correction based on the false discovery rate (FDR) was applied. After the 3-month intervention, urinary paraben and bisphenol excretions remained similar. Excretions of mono-butyl phthalates and most high-molecular-weight phthalates decreased, whereas mono-ethyl phthalate increased (all FDR<0.05). A reduction in adipose tissue was not associated with higher urinary EDC excretions. Higher baseline EDC excretions were associated with higher post-intervention body-mass index (methyl-, propylparaben), waist circumference (propylparaben, mono-n-butyl phthalate, mono-benzyl phthalate), and body fat percentage (mono-ethyl phthalate, mono-benzyl phthalate). Associations between parabens and body-mass index, and mono-benzyl phthalate and waist circumference and body fat percentage remained after multiple testing correction (all FDR<0.05). In a study of obese participants, we observed a reduction in most phthalates after a weight reduction intervention. A reduction in adipose tissue may not lead to mobilization and successively to higher urinary EDC excretions. Higher baseline paraben and phthalate exposures were associated with reduced weight loss, suggesting obesogenic properties.
•A 3-month dietary intervention decreased exposure to some non-persistent Endocrine Disrupting Chemicals (EDCs) but increased exposure to others.•A decrease in adipose tissue was not associated with an increase in EDC excretions via the release of stored EDCs.•Higher baseline excretions of EDCs were associated with an impaired loss of adipose tissue during the intervention.
Endocrine disrupting chemicals (EDCs) include non-persistent exogenous substances such as parabens, bisphenols and phthalates which have been associated with a range of metabolic disorders and ...disease. It is unclear if exposure remains consistent over time. We investigated change in indicators of EDC exposure between 2009 and 2016 and assessed its consistency between and within individuals over a median follow-up time of 47 months in a sample of Dutch individuals. Of 500 Dutch individuals, two 24 h urine samples were analysed for 5 parabens, 3 bisphenols and 13 metabolites of in total 8 different phthalates. We calculated per-year differences using meta-analysis and assessed temporal correlations between and within individuals using Spearman correlation coefficients, intra-class correlation coefficients (ICC) and kappa-statistics. We found a secular decrease in concentrations of methyl, ethyl, propyl and n-butyl paraben, bisphenol A, and metabolites of di-ethyl phthalate (DEP), di-butyl phthalate (DBP), di-(2-ethyl-hexyl) phthalate (DEHP), and butylbenzyl phthalate (DBzP) which varied from 8 to 96% (ethyl paraben, propyl paraben) between 2009 and 2016. Within-person temporal correlations were highest for parabens (ICC: 0.34 to 0.40) and poorest for bisphenols (ICC: 0.15 to 0.23). For phthalate metabolites, correlations decreased most between time periods (ICC < 48 months: 0.22 to 0.39; ≥48 months: 0.05 to 0.32). When categorizing EDC concentrations, 33–54% of individuals remained in the lowest or highest category and temporal correlations were similar to continuous measurements. Exposure to most EDCs decreased between 2009 and 2016 in a sample of individuals with impaired fasting glucose from the Dutch population. Temporal consistency was generally poor. The inconsistency in disease associations may be influenced by individual-level or temporal variation exhibited by EDCs. Our findings call for the need for repeated measurements of EDCs in observational studies before and during at-risk temporal windows for the disease.
•Exposure to phenols and phthalates decreased between 2009 and 2016 in the Netherlands.•Some decreases coincided with the introduction of European legislation.•Temporal consistency of EDCs over 7 years was generally poor.•Categorization of EDCs did not improve consistency and should be avoided.•We call for the need for repeated measurements in disease association investigations.
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