Exposome: time for transformative research

Exploring the impact of solar radiation on skin microbiome to develop improved photoprotection strategies

The skin microbiome undergoes constant exposure to solar radiation (SR), with its effects on health well-documented. However, understanding SR's influence on host-associated skin commensals remains nascent. This review surveys existing knowledge on SR's impact on the skin microbiome and proposes innovative sun protection methods that safeguard both skin integrity and microbiome balance. A team of skin photodamage specialists conducted a comprehensive review of 122 articles sourced from PubMed and Research Gateway. Key terms included skin microbiome, photoprotection, photodamage, skin cancer, ultraviolet radiation, solar radiation, skin commensals, skin protection, and pre/probiotics. Experts offered insights into novel sun protection products designed not only to shield the skin but also to mitigate SR's effects on the skin microbiome. Existing literature on SR's influence on the skin microbiome is limited. SR exposure can alter microbiome composition, potentially leading to dysbiosis, compromised skin barrier function, and immune system activation. Current sun protection methods generally overlook microbiome considerations. Tailored sun protection products that prioritize both skin and microbiome health may offer enhanced defense against SR-induced skin conditions. By safeguarding both skin and microbiota, these specialized products could mitigate dysbiosis risks associated with SR exposure, bolstering skin defense mechanisms and reducing the likelihood of SR-mediated skin issues.

The built environment and cardiovascular disease: an umbrella review and meta-meta-analysis

AIMS

To provide a comprehensive overview of the current evidence on objectively measured neighbourhood built environment exposures in relation to cardiovascular disease (CVD) events in adults.

METHODS AND RESULTS

We searched seven databases for systematic reviews on associations between objectively measured long-term built environmental exposures, covering at least one domain (i.e. outdoor air pollution, food environment, physical activity environment like greenspace and walkability, urbanization, light pollution, residential noise, and ambient temperature), and CVD events in adults. Two authors extracted summary data and assessed the risk of bias independently. Robustness of evidence was rated based on statistical heterogeneity, small-study effect, and excess significance bias. Meta-meta-analyses were conducted to combine the meta-analysis results from reviews with comparable exposure and outcome within each domain. From the 3304 initial hits, 51 systematic reviews were included, covering 5 domains and including 179 pooled estimates. There was strong evidence of the associations between increased air pollutants (especially PM2.5 exposure) and increased residential noise with greater risk of CVD. Highly suggestive evidence was found for an association between increased ambient temperature and greater risk of CVD. Systematic reviews on physical activity environment, food environment, light pollution, and urbanization in relation to CVD were scarce or lacking.

CONCLUSION

Air pollutants, increased noise levels, temperature, and greenspace were associated with CVD outcomes. Standardizing design and exposure assessments may foster the synthesis of evidence. Other crucial research gaps concern the lack of prospective study designs and lack of evidence from low-to-middle-income countries (LMICs).

REGISTRATION

PROSPERO: CRD42021246580.

Inflammatory Bowel Diseases Before and After 1990

BACKGROUND AND AIMS

Inflammatory bowel disease (IBD) is caused by interaction of genetic and environmental risk factors. We evaluated potential determinants of the post-1990 increased incidence in North America.

METHODS

Using fitted generalized linear models, we assessed clinical features, smoking and genetic risk scores (GRS) for Crohn's disease (CD) and ulcerative colitis (UC) in the National Institutes of Diabetes, Digestion and Kidney Diseases IBD Genetics Consortium database, before and post 1990.

RESULTS

Among 2744 patients (55% CD, 42.2% UC), smoking status and GRS were the main determinants of diagnosis age. After 1990, smoking at diagnosis declined significantly in both UC and CD (34.1% vs 20.8%, P < .001, and 14.7% vs 8.7%, P = .06, respectively). In UC, ex-smoking increased (9% vs 15%, P < .001), and nonsmoking rates remained unchanged, whereas in CD, ex-smoking remained unchanged. CD-GRS and IBD-GRS were significantly associated with young diagnosis age, Jewish ethnicity, IBD family history, and surgery. CD-GRS showed a borderline significant decrease (P = .058) in multivariate analysis post 1990 but only when excluding surgery in the model; surgery significantly decreased post 1990 in both CD and UC. CD-GRS inversely correlated with smoking at diagnosis (P < .001) suggesting that, in the presence of smoking, CD may only require a low genetic risk to develop.

CONCLUSION

Significantly increase in ex-smoking correlates with UC incidence post 1990. Conversely, smoking risk decreased significantly post 1990 despite rising CD incidence. CD-GRS likewise trended to decrease post 1990 only when not accounting for a significant decrease in CD surgery. We therefore deduce that unaccounted risk factors (eg, dietary, obesity, antibiotic use, improved hygiene, etc.) or greater detection or presence of mild CD may underlie post-1990 increased CD incidence.

Defining the Exposome Using Popular Education and Concept Mapping With Communities in Atlanta, Georgia

Introduction

The exposome concept provides a framework to better incorporate the environment into the study of health and disease and has been defined by academics to encompass all lifetime exposures including toxicants, diet, and lifestyle choices. However, initial applications of the exposome concept have been less apt at measuring social determinants of health, focusing primarily on conventional environmental exposures and lifestyle choices that do not reflect the complex lived experience of many communities. To bring community voice into the exposome concept, the HERCULES Exposome Research Center and its Stakeholder Advisory Board co-developed the Exposome Roadshow. We present and discuss the resulting community-exposome definition to inform and improve exposome research.

Materials and Methods

Four communities from distinct areas across metro-Atlanta participated in separate 2-day Exposome Roadshow workshops with concept mapping. Aligned with a popular education approach in which community knowledge is used to work collectively for change, concept mapping provided a systematic method to collect and visualize community members' knowledge and create a shared understanding to take action. Community members brainstormed, sorted, and rated their responses to the prompt: "What in your environment is affecting your and your community's health?" Responses were analyzed and visually depicted by concept maps consisting of separate but interrelated clusters of ideas. Community members discussed and validated the maps, selecting a final map illustrating their community's exposome.

Results

A total of 118 community members completed concept mapping. On average communities identified 7 clusters to define their exposome. The resulting concept maps offer a community definition of the exposome. Five major themes arose across all four communities: conventional environmental concerns, built environment, social relationships, crime and safety, and individual health and behaviors.

Discussion

The resulting community-exposome definition demonstrates the importance of expanding the scope of exposures beyond traditional environmental influences to include the lived experience of individuals and communities. While newer exposome definitions align more closely with this community definition, traditional exposome methods do not routinely include these factors. To truly capture the totality of lifetime exposures and improve human health, researchers should incorporate community perspectives into exposome research.

Measuring Clinical, Biological, and Behavioral Variables to Elucidate Trajectories of Patient (Reported) Outcomes: The PROFILES Registry

To take cancer survivorship research to the next level, it's important to gain insight in trajectories of changing patient (reported) outcomes and impaired recovery after cancer. This is needed as the number of survivors is increasing and a large proportion is confronted with changing health after treatment. Mechanistic research can facilitate the development of personalized risk-stratified follow-up care and tailored interventions to promote healthy cancer survivorship. We describe how these trajectories can be studied by taking the recently extended Dutch population-based PROFILES (Patient Reported Outcomes Following Initial treatment and Long term Evaluation of Survivorship) registry as an example. PROFILES combines longitudinal assessment of patient-reported outcomes with novel, ambulatory and objective measures (e.g., activity trackers; blood draws; hair samples; online food diaries; online cognitive tests; weighing scales; online symptoms assessment), and cancer registry and pharmacy databases. Furthermore, we discuss methods to optimize the use of a multidomain data collection like return of individual results to participants which may not only improve patient empowerment but also long-term cohort retention. Also, advanced statistical methods are needed to handle high-dimensional longitudinal data (with missing values) and provide insight into trajectories of changing patient (reported) outcomes after cancer. Our coded data can be used by academic researchers around the world. Registries like PROFILES, that go beyond boundaries of disciplines and institutions, will contribute to better predictions of who will experience changes and why. This is needed to prevent and mitigate long-term and late effects of cancer (treatment) and to identify new interventions to promote health.

Joint modeling of time-varying HIV exposure and infection for estimation of per-act efficacy in HIV prevention trials

Objectives

Using the MTN-020/ASPIRE HIV prevention trial as a motivating example, our objective is to construct a joint model for the HIV exposure process through vaginal intercourse and the time to HIV infection in a population of sexually active women. By modeling participants' HIV infection in terms of exposures, rather than time exposed, our aim is to obtain a valid estimate of the per-act efficacy of a preventive intervention.

Methods

Within the context of HIV prevention trials, in which the frequency of sex acts is self-reported periodically by the participants, we model the exposure process of the trial participants with a non-homogeneous Poisson process. This approach allows for variability in the rate of sexual contacts between participants as well as variability in the rate of sexual contacts over time. The time to HIV infection for each participant is modeled as the time to the exposure that results in HIV infection, based on the modeled sexual contact rate. We propose an empirical Bayes approach for estimation.

Results

We report the results of a simulation study where we evaluate the performance of our proposed approachandcompareittothetraditionalapproachofestimatingtheoverallreductioninHIVincidenceusing a Proportional Hazards Cox model. The proposed approach is also illustrated with data from the MTN-020/ASPIRE trial.

Conclusions

The proposed joint modeling, along with the proposed empirical Bayes estimation approach, can provide valid estimation of the per-exposure efficacy of a preventive intervention.

Associations between the built environment and obesity: an umbrella review

BACKGROUND

In the past two decades, the built environment emerged as a conceptually important determinant of obesity. As a result, an abundance of studies aiming to link environmental characteristics to weight-related outcomes have been published, and multiple reviews have attempted to summarise these studies under different scopes and domains. We set out to summarise the accumulated evidence across domains by conducting a review of systematic reviews on associations between any aspect of the built environment and overweight or obesity.

METHODS

Seven databases were searched for eligible publications from the year 2000 onwards. We included systematic literature reviews, meta-analyses and pooled analyses of observational studies in the form of cross-sectional, case-control, longitudinal cohort, ecological, descriptive, intervention studies and natural experiments. We assessed risk of bias and summarised results structured by built environmental themes such as food environment, physical activity environment, urban-rural disparity, socioeconomic status and air pollution.

RESULTS

From 1850 initial hits, 32 systematic reviews were included, most of which reported equivocal evidence for associations. For food- and physical activity environments, associations were generally very small or absent, although some characteristics within these domains were consistently associated with weight status such as fast-food exposure, urbanisation, land use mix and urban sprawl. Risks of bias were predominantly high.

CONCLUSIONS

Thus far, while most studies have not been able to confirm the assumed influence of built environments on weight, there is evidence for some obesogenic environmental characteristics. Registration: This umbrella review was registered on PROSPERO under ID CRD42019135857.

Use of an Exposome Approach to Understand the Effects of Exposures From the Natural, Built, and Social Environments on Cardio-Vascular Disease Onset, Progression, and Outcomes

Obesity, diabetes, and hypertension have increased by epidemic proportions in recent years among African Americans in comparison to Whites resulting in significant adverse cardiovascular disease (CVD) disparities. Today, African Americans are 30% more likely to die of heart disease than Whites and twice as likely to have a stroke. The causes of these disparities are not yet well-understood. Improved methods for identifying underlying risk factors is a critical first step toward reducing Black:White CVD disparities. This article will focus on environmental exposures in the external environment and how they can lead to changes at the cellular, molecular, and organ level to increase the personal risk for CVD and lead to population level CVD racial disparities. The external environment is defined in three broad domains: natural (air, water, land), built (places you live, work, and play) and social (social, demographic, economic, and political). We will describe how environmental exposures in the natural, built, and social environments "get under the skin" to affect gene expression though epigenetic, pan-omics, and related mechanisms that lead to increased risk for adverse CVD health outcomes and population level disparities. We also will examine the important role of metabolomics, proteomics, transcriptomics, genomics, and epigenomics in understanding how exposures in the natural, built, and social environments lead to CVD disparities with implications for clinical, public health, and policy interventions. In this review, we apply an exposome approach to Black:White CVD racial disparities. The exposome is a measure of all the exposures of an individual across the life course and the relationship of those exposures to health effects. The exposome represents the totality of exogenous (external) and endogenous (internal) exposures from conception onwards, simultaneously distinguishing, characterizing, and quantifying etiologic, mediating, moderating, and co-occurring risk and protective factors and their relationship to disease. Specifically, it assesses the biological mechanisms and underlying pathways through which chemical and non-chemical environmental exposures are associated with CVD onset, progression and outcomes. The exposome is a promising approach for understanding the complex relationships among environment, behavior, biology, genetics, and disease phenotypes that underlie population level, Black: White CVD disparities.

Predicting mortality from 57 economic, behavioral, social, and psychological factors

In our prospective study using nationally representative data from 13,611 adults in the US Health and Retirement Study, we used traditional and machine-learning statistical approaches to reveal the most important factors across the behavioral and social sciences that predict mortality in older adults. In the study, we found that top predictors of mortality spanned all investigated domains, opening up opportunities for future hypothesis generation in observational and clinical studies and the identification of potential new targets for screening and policy.

Behavioral and social scientists have identified many nonbiological predictors of mortality. An important limitation of much of this research, however, is that risk factors are not studied in comparison with one another or from across different fields of research. It therefore remains unclear which factors should be prioritized for interventions and policy to reduce mortality risk. In the current investigation, we compare 57 factors within a multidisciplinary framework. These include (i) adverse socioeconomic and psychosocial experiences during childhood and (ii) socioeconomic conditions, (iii) health behaviors, (iv) social connections, (v) psychological characteristics, and (vi) adverse experiences during adulthood. The current prospective cohort investigation with 13,611 adults from 52 to 104 y of age (mean age 69.3 y) from the nationally representative Health and Retirement Study used weighted traditional (i.e., multivariate Cox regressions) and machine-learning (i.e., lasso, random forest analysis) statistical approaches to identify the leading predictors of mortality over 6 y of follow-up time. We demonstrate that, in addition to the well-established behavioral risk factors of smoking, alcohol abuse, and lack of physical activity, economic (e.g., recent financial difficulties, unemployment history), social (e.g., childhood adversity, divorce history), and psychological (e.g., negative affectivity) factors were also among the strongest predictors of mortality among older American adults. The strength of these predictors should be used to guide future transdisciplinary investigations and intervention studies across the fields of epidemiology, psychology, sociology, economics, and medicine to understand how changes in these factors alter individual mortality risk.

Analyzing Metabolomics Data for Environmental Health and Exposome Research

The exposome is the cumulative measure of environmental influences and associated biological responses across the life span, with critical relevance for understanding how exposures can impact human health. Metabolomics analysis of biological samples offers unique advantages for examining the exposome. Simultaneous analysis of external exposures, biological responses, and host susceptibility at a systems level can help establish links between external exposures and health outcomes. As metabolomics technologies continue to evolve for the study of the exposome, metabolomics ultimately will help provide valuable insights for exposure risk assessment, and disease prevention and management. Here, we discuss recent advances in metabolomics, and describe data processing protocols that can enable analysis of the exposome. This chapter focuses on using liquid chromatography-mass spectrometry (LC-MS)-based untargeted metabolomics for analysis of the exposome, including (1) preprocessing of untargeted metabolomics data, (2) identification of exposure chemicals and their metabolites, and (3) methods to establish associations between exposures and diseases.

An overview of the current progress, challenges, and prospects of human biomonitoring and exposome studies

Human Biomonitoring (HB), the process for determining whether and to what extent chemical substances penetrated our bodies, serves as a useful tool to quantify human exposure to pollutants. In cases of nutrition and physiologic status, HB plays a critical role in the identification of excess or deficiency of essential nutrients. In pollutant HB studies, levels of substances measured in body fluids (blood, urine, and breast milk) or tissues (hair, nails or teeth) aid in the identification of potential health risks or associated adverse effects. However, even as a widespread practice in several countries, most HB studies reflect exposure to a single compound or mixtures which are measured at a single time point in lifecycle. On the other hand, throughout an individual's lifespan, the contact with different physical, chemical, and social stressors occurs at varying intensities, differing times and durations. Further, the interaction between stressors and body receptors leads to dynamic responses of the entire biological system including proteome, metabolome, transcriptome, and adductome. Bearing this in mind, a relatively new vision in exposure science, defined as the exposome, is postulated to expand the traditional practice of measuring a single exposure to one or few chemicals at one-time point to an approach that addresses measures of exposure to multiple stressors throughout the lifespan. With the exposome concept, the science of exposure advances to an Environment-Wide Association Perspective, which might exhibit a stronger relationship with good health or disease conditions for an individual (phenotype). Thus, this critical review focused on the current progress of HB and exposome investigations, anticipating some challenges, strategies, and future needs to be taken into account for designing future surveys.

High-Dimensional Confounding Adjustment Using Continuous Spike and Slab Priors

In observational studies, estimation of a causal effect of a treatment on an outcome relies on proper adjustment for confounding. If the number of the potential confounders (p) is larger than the number of observations (n), then direct control for all potential confounders is infeasible. Existing approaches for dimension reduction and penalization are generally aimed at predicting the outcome, and are less suited for estimation of causal effects. Under standard penalization approaches (e.g. Lasso), if a variable Xj is strongly associated with the treatment T but weakly with the outcome Y, the coefficient βj will be shrunk towards zero thus leading to confounding bias. Under the assumption of a linear model for the outcome and sparsity, we propose continuous spike and slab priors on the regression coefficients βj corresponding to the potential confounders Xj . Specifically, we introduce a prior distribution that does not heavily shrink to zero the coefficients (βj s) of the Xj s that are strongly associated with T but weakly associated with Y. We compare our proposed approach to several state of the art methods proposed in the literature. Our proposed approach has the following features: 1) it reduces confounding bias in high dimensional settings; 2) it shrinks towards zero coefficients of instrumental variables; and 3) it achieves good coverages even in small sample sizes. We apply our approach to the National Health and Nutrition Examination Survey (NHANES) data to estimate the causal effects of persistent pesticide exposure on triglyceride levels.

A cosmetic treatment based on the secretion of Cryptomphalus aspersa 40% improves the clinical results after the use of nonablative fractional laser in skin aging

Introduction

The main purpose of this study was to evaluate whether the application of a cosmetic treatment based on the secretion of Cryptomphalus aspersa (SCA) enhances the clinical results, tolerance, and skin regeneration after nonablative laser treatment in patients with moderate photoaging.

Methods

Randomized, double‐blind, split‐face trial in 20 patients with moderate aging. Two sessions with fractional nonablative laser were performed, and the cosmetic treatments (SCA 40% on one hemiface and vehicle on the other) were applied immediately after laser session and daily during the study (28 days). Tewameter, Cutometer, Visioscan, VisioFace, photography, dermoscopy, and clinical evaluation were assessed. Side effects were also evaluated.

Results

A significant decrease in the density of microcolumns (25%, 71%, 32%, and 61% less density, respectively, at T3 P = 0.008, T7 P = 0.002, T22 P < 0.001, and T24 P < 0.001) was observed on the side treated with SCA compared to the vehicle‐treated side. Cutaneous elasticity, area of wrinkles, and hydration on the SCA‐treated side also showed a significant improvement compared to the vehicle‐treated side. Both the researcher and patients observed a significant improvement on the side treated with SCA compared to the vehicle‐treated side. Significantly fewer side effects (erythema, burning, and dryness) were also detected.

Conclusion

A cosmetic product with SCA 40% applied immediately after laser and for a period thereafter enhances and accelerates repair of damage produced by the laser and significantly reduces related adverse effects. In addition, SCA treatment could improve clinical results. In conclusion, we suggest that SCA enhances the effectiveness of laser in the treatment of cutaneous aging.

Quantitative characterization of the urine and serum metabolomes of children is essential for 'omics' studies

Understanding the long-term health impacts of the early-life exposome requires the characterization and assimilation of multi 'omics' data to ultimately link molecular changes to exposures. In this way, markers associated with negative health outcomes, such as increased disease risk, can be ascertained. However, determining the extent and direction of metabolic perturbations relies on comparisons to existing metabolomic reference profiles. While such resources are increasingly available for adult populations, analogous tools for children are decidedly lacking. Lau et al. have compiled robust, translatable quantitative metabolomics data on urine and serum samples for European children across six study locations. Metabolites were associated with body mass index, diet and demographics, and correlated within and between biofluids. As a result, a novel association between urinary 4-deoxyerythronic acid and body mass index was uncovered. This work serves as a crucial reference for future studies in exposomics, and - more broadly - represents a significant step forward for metabolomics by creating the foundation for a comprehensive reference metabolome for children.Please see related article: https://bmcmedicine.biomedcentral.com/articles/10.1186/s12916-018-1190-8.

Towards environmental health equity in health impact assessment: innovations and opportunities

OBJECTIVES

As global environmental change drives inequitable health outcomes, novel health equity assessment methodologies are increasingly required. We review literatures on equity-focused HIA to clarify how equity is informing HIA practice, and to surface innovations for assessing health equity in relation to a range of exposures across geographic and temporal scales.

METHODS

A narrative review of the health equity and HIA literatures analysed English articles published between 2003 and 2017 across PubMed, PubMed Central, Biomed Central and Ovid Medline. Title and abstract reviews of 849 search results yielded 89 articles receiving full text review.

RESULTS

Considerations of equity in HIA increased over the last 5 years, but equity continues to be conflated with health disparities rather than their root causes (i.e. inequities). Lessons from six literatures to inform future HIA practice are described: HIA for healthy cities, climate change vulnerability assessment, cumulative health risk assessment, intersectionality-based policy analysis, corporate health impact assessment and global health impact assessment.

CONCLUSIONS

Academic reporting on incorporating equity in HIA practice has been limited. Nonetheless, significant methodological advancements are being made to examine the health equity implications of multiple environmental exposures.

Model-averaged confounder adjustment for estimating multivariate exposure effects with linear regression

In environmental and nutritional epidemiology and in many other fields, there is increasing interest in estimating the effect of simultaneous exposure to several agents (e.g., multiple nutrients, pesticides, or air pollutants) on a health outcome. We consider estimating the effect of a multivariate exposure that includes several continuous agents and their interactions-on an outcome, when the true confounding variables are an unknown subset of a potentially large (relative to sample size) set of measured covariates. Our approach is rooted in the ideas of Bayesian model averaging: the exposure effect is estimated as a weighted average of the estimated exposure effects obtained under several linear regression models that include different sets of the potential confounders. We introduce a data-driven prior that assigns to the likely confounders a higher probability of being included into the regression model. We show that our approach can also be formulated as a penalized likelihood formulation with an interpretable tuning parameter. Through a simulation study, we demonstrate that the proposed approach identifies parsimonious models that are fully adjusted for observed confounding and estimates the multivariate exposure effect with smaller mean squared error compared to several alternatives. We apply the method to an Environmental Wide Association Study using National Heath and Nutrition Examination Survey to estimate the effect of mixtures of nutrients and pesticides on lipid levels.

A multivariate approach to investigate the combined biological effects of multiple exposures

Epidemiological studies provide evidence that environmental exposures may affect health through complex mixtures. Formal investigation of the effect of exposure mixtures is usually achieved by modelling interactions, which relies on strong assumptions relating to the identity and the number of the exposures involved in such interactions, and on the order and parametric form of these interactions. These hypotheses become difficult to formulate and justify in an exposome context, where influential exposures are numerous and heterogeneous. To capture both the complexity of the exposome and its possibly pleiotropic effects, models handling multivariate predictors and responses, such as partial least squares (PLS) algorithms, can prove useful. As an illustrative example, we applied PLS models to data from a study investigating the inflammatory response (blood concentration of 13 immune markers) to the exposure to four disinfection by-products (one brominated and three chlorinated compounds), while swimming in a pool. To accommodate the multiple observations per participant (n=60; before and after the swim), we adopted a multilevel extension of PLS algorithms, including sparse PLS models shrinking loadings coefficients of unimportant predictors (exposures) and/or responses (protein levels). Despite the strong correlation among co-occurring exposures, our approach identified a subset of exposures (n=3/4) affecting the exhaled levels of 8 (out of 13) immune markers. PLS algorithms can easily scale to high-dimensional exposures and responses, and prove useful for exposome research to identify sparse sets of exposures jointly affecting a set of (selected) biological markers. Our descriptive work may guide these extensions for higher dimensional data.

Is in utero exposure to maternal socioeconomic disadvantage related to offspring ovarian reserve in adulthood?

BACKGROUND

Because the ovarian follicle pool is established in utero, adverse exposures during this period may be especially impactful on the size and health of the initial follicle endowment, potentially shaping trajectories of ovarian follicle loss and the eventual onset of menopause. Building on a robust literature linking socioeconomic status (SES) and menopausal timing, the current study examined adverse prenatal exposures related to maternal SES, hypothesizing that greater maternal socioeconomic disadvantage would be associated with lower ovarian reserve in the adult offspring.

METHODS

In a healthy, community-based sub-sample (n = 350) of reproductive age participants in the OVA Study (2006-2011), prenatal maternal SES was examined in relation to two biomarkers of ovarian reserve, antimullerian hormone (AMH) and antral follicle count (AFC). Prenatal maternal SES was assessed indirectly using maternal addresses abstracted from participant birth certificates, geocoded, and linked to US Census-derived variables, including neighborhood-level characteristics: education (% of individuals with a HS diploma); poverty (% of families below the poverty line); unemployment (% of individuals > 16 years who are unemployed); and income (median family income).

RESULTS

In separate covariate-adjusted linear regression models (following the backward elimination of main effects with P > .10), greater maternal neighborhood education was related to higher ovarian reserve as marked by higher levels of offspring AMH (beta = .142, P < .001) and AFC (beta = .092, P < .10) with models accounting for 19.6% and 21.5% of the variance in AMH and AFC, respectively. In addition, greater maternal neighborhood poverty was related to lower ovarian reserve as marked by lower offspring AMH (beta = -.144, P < .01), with the model accounting for 19.5% of the variance in AMH.

CONCLUSIONS

Maternal socioeconomic disadvantage measured indirectly at the neighborhood level was associated with lower ovarian reserve among the adult offspring, independently of offspring SES and other potential confounding factors. This suggests SES-related adversity exposures may have a detrimental impact on the size or health of the initial follicle endowment, leading to accelerated follicle loss over time.

The Exposome Research Paradigm: an Opportunity to Understand the Environmental Basis for Human Health and Disease

PURPOSE OF REVIEW

This paper presents an overview of the exposome research paradigm with particular application to understanding human reproduction and development and its implications for health across a lifespan.

RECENT FINDINGS

The exposome research paradigm has generated considerable discussion about its feasibility and utility for delineating the impact of environmental exposures on human health. Early initiatives are underway, including smaller proof-of-principle studies and larger concerted efforts. Despite the notable challenges underlying the exposome paradigm, analytic techniques are being developed to handle its untargeted approach and correlated and multi-level or hierarchical data structures such initiatives generate, while considering multiple comparisons. The relatively short intervals for critical and sensitive windows of human reproduction and development seem well suited for exposome research and may revolutionize our understanding of later onset diseases. Early initiatives suggest that the exposome paradigm is feasible, but its utility remains to be established with applications to population human health research.

The influence of exposome on acne

BACKGROUND

Acne vulgaris is one of the main reasons for dermatological consultations. Severity and response to treatment may be impacted by various external factors or exposome.

AIM

To assess the impact of environmental factors on acne and to provide a comprehensive overview of the acne exposome.

METHODS

Two consensus meetings of five European dermatologists and a comprehensive literature search on exposome factors triggering acne served as a basis for this review.

RESULTS

Acne exposome was defined as the sum of all environmental factors influencing the occurrence, duration and severity of acne. Exposome factors impact on the response and the frequency of relapse to treatments by interacting with the skin barrier, sebaceous gland, innate immunity and cutaneous microbiota. They may be classified into the following six main categories: nutrition, psychological and lifestyle factors, occupational factors including cosmetics, as well as pollutants, medication and climatic factors. Moreover, practical considerations for the dermatologist's clinical practice are proposed.

CONCLUSION

Exposome factors including nutrition, medication, occupational factors, pollutants, climatic factors, and psychosocial and lifestyle factors may impact on the course and severity of acne and on treatment efficacy. Identifying and reducing the impact of exposome is important for an adequate acne disease management.

The Relationship Between Hospital Construction and High-Risk Infant Auditory Function at NICU Discharge: A Retrospective Descriptive Cohort Study

PURPOSE

To describe the difference in auditory function at neonatal intensive care unit (NICU) discharge between high-risk infant cases exposed to hospital construction during NICU stay and those not exposed.

BACKGROUND

Noise produced by routine NICU caregiving exceeds recommended intensity. As California hospitals undergo construction to meet seismic safety regulations, vulnerable neonates are potentially exposed to even higher levels of noise. Ramifications are unknown.

METHODS

Retrospective data-based descriptive cohort design was used to compare high-risk infant auditory function at NICU discharge between hospital construction exposed and unexposed groups.

SAMPLE SIZE

N = 540 infant cases (243 construction exposed and 297 unexposed controls).

INCLUSION CRITERIA

Infant cases born and discharged from the study site NICU in the year 2010 (unexposed) and year 2015 (exposed) and received a newborn hearing screening by automated auditory brainstem evoked response (ABER) prior to discharge with results reported. Infant cases excluded: hearing screen results by ABER unavailable, potentially confounding characteristics (congenital infection, major anomalies including cleft lip and/or palate), and transferred into or out of the study site.

INSTRUMENTATION

ABER.

ANALYSIS

descriptive statistics (SPSS Version 24.0), hypothesis testing, correlation, and logistic regression.

RESULTS

The difference in auditory function at NICU discharge between high-risk infant cases exposed to hospital construction noise and those unexposed was statistically insignificant, χ² = 1.666, df = 4, p = .1968, 95% confidence interval [-0.635, 2.570].

CONCLUSIONS

More research is needed to better understand whether hospital construction exposure during NICU admission negatively affects high-risk infant auditory function. Findings may catalyze theory development, future research, and child health policy.

Research standardization tools: pregnancy measures in the PhenX Toolkit

Only through concerted and well-executed research endeavors can we gain the requisite knowledge to advance pregnancy care and have a positive impact on maternal and newborn health. Yet the heterogeneity inherent in individual studies limits our ability to compare and synthesize study results, thus impeding the capacity to draw meaningful conclusions that can be trusted to inform clinical care. The PhenX Toolkit (http://www.phenxtoolkit.org), supported since 2007 by the National Institutes of Health, is a web-based catalog of standardized protocols for measuring phenotypes and exposures relevant for clinical research. In 2016, a working group of pregnancy experts recommended 15 measures for the PhenX Toolkit that are highly relevant to pregnancy research. The working group followed the established PhenX consensus process to recommend protocols that are broadly validated, well established, nonproprietary, and have a relatively low burden for investigators and participants. The working group considered input from the pregnancy experts and the broader research community and included measures addressing the mode of conception, gestational age, fetal growth assessment, prenatal care, the mode of delivery, gestational diabetes, behavioral and mental health, and environmental exposure biomarkers. These pregnancy measures complement the existing measures for other established domains in the PhenX Toolkit, including reproductive health, anthropometrics, demographic characteristics, and alcohol, tobacco, and other substances. The preceding domains influence a woman's health during pregnancy. For each measure, the PhenX Toolkit includes data dictionaries and data collection worksheets that facilitate incorporation of the protocol into new or existing studies. The measures within the pregnancy domain offer a valuable resource to investigators and clinicians and are well poised to facilitate collaborative pregnancy research with the goal to improve patient care. To achieve this aim, investigators whose work includes the perinatal population are encouraged to utilize the PhenX Toolkit in the design and implementation of their studies, thus potentially reducing heterogeneity in data measures across studies. Such an effort will enhance the overall impact of individual studies, increasing the ability to draw more meaningful conclusions that can then be translated into clinical practice.

Informatics and Data Analytics to Support Exposome-Based Discovery for Public Health

The complexity of the human exposome-the totality of environmental exposures encountered from birth to death-motivates systematic, high-throughput approaches to discover new environmental determinants of disease. In this review, we describe the state of science in analyzing the human exposome and provide recommendations for the public health community to consider in dealing with analytic challenges of exposome-based biomedical research. We describe extant and novel analytic methods needed to associate the exposome with critical health outcomes and contextualize the data-centered challenges by drawing parallels to other research endeavors such as human genomics research. We discuss efforts for training scientists who can bridge public health, genomics, and biomedicine in informatics and statistics. If an exposome data ecosystem is brought to fruition, it will likely play a role as central as genomic science has had in molding the current and new generations of biomedical researchers, computational scientists, and public health research programs.

Global open data management in metabolomics

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The metabolome allows accessing the external influences under which an organism exists and develops in a dynamic way.

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Recent years have seen the establishment of a global network for metabolomics data exchange.

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Global metabolomics data exchange is leading to an exponential growth of publically available metabolomics data for re-analysis.

Chemical Biology employs chemical synthesis, analytical chemistry and other tools to study biological systems. Recent advances in both molecular biology such as next generation sequencing (NGS) have led to unprecedented insights towards the evolution of organisms’ biochemical repertoires. Because of the specific data sharing culture in Genomics, genomes from all kingdoms of life become readily available for further analysis by other researchers. While the genome expresses the potential of an organism to adapt to external influences, the Metabolome presents a molecular phenotype that allows us to asses the external influences under which an organism exists and develops in a dynamic way. Steady advancements in instrumentation towards high-throughput and highresolution methods have led to a revival of analytical chemistry methods for the measurement and analysis of the metabolome of organisms. This steady growth of metabolomics as a field is leading to a similar accumulation of big data across laboratories worldwide as can be observed in all of the other omics areas. This calls for the development of methods and technologies for handling and dealing with such large datasets, for efficiently distributing them and for enabling re-analysis. Here we describe the recently emerging ecosystem of global open-access databases and data exchange efforts between them, as well as the foundations and obstacles that enable or prevent the data sharing and reanalysis of this data.

The skin aging exposome

The term "exposome" describes the totality of exposures to which an individual is subjected from conception to death. It includes both external and internal factors as well as the human body's response to these factors. Current exposome research aims to understand the effects all factors have on specific organs, yet today, the exposome of human skin has not received major attention and a corresponding definition is lacking. This review was compiled with the collaboration of European scientists, specialized in either environmental medicine or skin biology. A comprehensive review of the existing literature was performed using PubMed. The search was restricted to exposome factors and skin aging. Key review papers and all relevant, epidemiological, in vitro, ex vivo and clinical studies were analyzed to determine the key elements of the exposome influencing skin aging. Here we propose a definition of the skin aging exposome. It is based on a summary of the existing scientific evidence for the role of exposome factors in skin aging. We also identify future research needs which concern knowledge about the interaction of distinct exposomal factors with each other and the resulting net effects on skin aging and suggest some protective measures.

Influencing Genomic Change and Cancer Disparities through Neighborhood Chronic Toxic Stress Exposure: A Research Framework

Black Americans have disproportionately higher incidence and mortality rates for many cancers. These disparities may be related to genomic changes that occur from exposure to chronic toxic stress and may result from conditions associated with living in racially segregated neighborhoods with high rates of concentrated poverty. The purpose of this article is to present a nursing research framework for developing and testing neighborhood-level interventions that have the potential to mitigate exposure to neighborhood-associated chronic toxic stress, improve individual-level genomic sequelae and cancer outcomes, and reduce cancer health disparities of Black Americans. Public health nursing researchers should collaborate with local officials to determine ways to reduce neighborhood-level stress. Intermediate outcomes can be measured using genomic or other stress biomarkers, and long-term outcomes can be measured by evaluating population-level cancer incidence and mortality.

Microarray based gene expression analysis of Sus Scrofa duodenum exposed to zearalenone: significance to human health

Background

Zearalenone (ZEA) is a secondary metabolite produced by Fusarium species. ZEA was proved to exert a wide range of unwanted side effects, but its mechanism of action, particularly at duodenum levels, remains unclear. In our study based on the microarray technology we assessed the alteration of gene expression pattern Sus scrofa duodenum which has been previously exposed to ZEA. Gene expression data was validated by qRT-PCR and ELISA. The gene expression data were further extrapolated the results to their human orthologues and analyzed the data in the context of human health using IPA (Ingenuity Pathways Analysis).

Results

Using Agilent microarray technology, we found that gene expression pattern was significantly affected by ZEA exposure, considering a 2-fold expression difference as a cut-off level and a p-value < 0.05. In total, we found 1576 upregulated and 2446 downregulated transcripts. About 1084 genes (764 downregulated and 751 overexpressed) were extrapolated to their human orthologues. IPA analysis showed various altered key cellular and molecular pathways. As expected, we observed a significant alteration of immune response related genes, MAPK (mitogen activate protein kinases) pathways or Toll-Like Receptors (TLRs). What captured our attention was the modulation of pathways related to the activation of early carcinogenesis.

Conclusions

Our data demonstrate that ZEA has a complex effect at duodenum level. ZEA is able to activate not only the immune response related genes, but also those relate to colorectal carcinogenesis. The effects can be more dramatic when connected with the exposure to other environmental toxic agents or co-occurrence with different microorganisms.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-016-2984-8) contains supplementary material, which is available to authorized users.

Use of the "Exposome" in the Practice of Epidemiology: A Primer on -Omic Technologies

The exposome has been defined as the totality of exposures individuals experience over the course of their lives and how those exposures affect health. Three domains of the exposome have been identified: internal, specific external, and general external. Internal factors are those that are unique to the individual, and specific external factors include occupational exposures and lifestyle factors. The general external domain includes sociodemographic factors such as educational level and financial status. Eliciting information on the exposome is daunting and not feasible at present; the undertaking may never be fully realized. A variety of tools have been identified to measure the exposome. Biomarker measurements will be one of the major tools in exposomic studies. However, exposure data can also be obtained from other sources such as sensors, geographic information systems, and conventional tools such as survey instruments. Proof-of-concept studies are being conducted that show the promise of exposomic investigation and the integration of different kinds of data. The inherent value of exposomic data in epidemiologic studies is that they can provide greater understanding of the relationships among a broad range of chemical and other risk factors and health conditions and ultimately lead to more effective and efficient disease prevention and control.

Analytical Complexity in Detection of Gene Variant-by-Environment Exposure Interactions in High-Throughput Genomic and Exposomic Research

It seems intuitive that disease risk is influenced by the interaction between inherited genetic variants and environmental exposure factors; however, we have few documented interactions between variants and exposures. Advances in technology may enable the simultaneous measurement (i.e., on the same individuals in an epidemiological study) of millions of genome variants with thousands of environmental "exposome" factors, significantly increasing the number of possible factor pairs available for testing for the presence of interactions. The burden of analytic complexity, or sheer number of genetic and exposure factors measured, poses a considerable challenge for discovery of interactions in population-scale data. Advances in analytic approaches, large sample sizes, less conservative methods to mitigate multiple testing, and strong biological priors will be required to prune the search space to find reproducible and robust gene-by-environment interactions in observational data.

Sequencing the exposome: A call to action

The exposome is a complement to the genome that includes non-genetic causes of disease. Multiple definitions are available, with salient points being global inclusion of exposures and behaviors, and cumulative integration of associated biologic responses. As such, the concept is both refreshingly simple and dauntingly complex. This article reviews high-resolution metabolomics (HRM) as an affordable approach to routinely analyze samples for a broad spectrum of environmental chemicals and biologic responses. HRM has been successfully used in multiple exposome research paradigms and is suitable to implement in a prototype universal exposure surveillance system. Development of such a structure for systematic monitoring of environmental exposures is an important step toward sequencing the exposome because it builds upon successes of exposure science, naturally connects external exposure to body burden and partitions the exposome into workable components. Practical results would be repositories of quantitative data on chemicals according to geography and biology. This would support new opportunities for environmental health analysis and predictive modeling. Complementary approaches to hasten development of exposome theory and associated biologic response networks could include experimental studies with model systems, analysis of archival samples from longitudinal studies with outcome data and study of relatively short-lived animals, such as household pets (dogs and cats) and non-human primates (common marmoset). International investment and cooperation to sequence the human exposome will advance scientific knowledge and also provide an important foundation to control adverse environmental exposures to sustain healthy living spaces and improve prediction and management of disease.

The Epidemiology and Genetics of Uterine Leiomyoma

Uterine leiomyomas (fibroids) are the most common benign neoplasms in premenopausal women, which confer significant morbidity during the reproductive years and represent a significant public health issue. The incidence of fibroids has been associated with African-American race, early onset of menarche, early parity, and environmental/dietary exposures. These sex steroid-responsive uterine tumors are characterized by de novo transformation of the myometrium into fibroids via excessive formation of the extracellular matrix (ECM). Cytogenic anomalies, mutations in mediator complex subunit 12 (MED 12), and aberrant DNA methylation/demethylation have been observed, but have not been reported as direct mediators of fibroid development. Recent advances in epigenetics have implied a functional role of G protein-coupled receptor 10 (GPR10) overexpression and irregular microRNA expression in the pathobiology of fibroids that require future investigation. Herein, the impact of epidemiologic and genetic factors on the incidence and development of fibroids is reviewed.

Only one health, and so many omics

The development of new approaches based on wide profiling methods in studying biological and medical systems is bringing large amounts of data on a daily basis. The causes of complex diseases have been directed to the genome examination bringing formidable knowledge. We can study genome, but also proteome, exome, transcriptome, epigenome, metabolome, and newcomers too such as microbiome, connectome and exposome. The title of this editorial is paraphrasing the famous saying of Victor Schlichter from Buenos Aires children hospital in Argentina who said "How unfair! Only one health, and so many diseases". Today there is indeed a whole lot of omics. We think that we are lucky to have all the omics possible, but we also wanted to stress the importance of future holistic approach in integrating the knowledge omics has rewarded us.

Exposome in IBD: recent insights in environmental factors that influence the onset and course of IBD

It is generally agreed that environmental factors trigger the onset and cause flares of inflammatory bowel disease. Although we have learned much about genetic susceptibility factors of inflammatory bowel disease in recent years, our knowledge on these environmental factors is limited. The sum of all environmental factors a human is exposed to during lifetime has been termed the exposome. The challenge of investigating the exposome is discussed in this overview. The environmental exposure of a subject causes changes in the intestinal microbiota and subsequently changes the epigenetic imprinting of the mucosa and the associated immune system. Some relevant environmental factors have been investigated in recent years in inflammatory bowel disease and other (auto)inflammatory disease. These factors can be categorized in air pollution, diet, drugs, stress, infections, water pollution, food additives, and lifestyle. Examples from those categories and their potential pathophysiological mechanism are discussed.

Toward a road map for global -omics: a primer on -omic technologies

As highlighted in a recent editorial in the Journal (Am J Epidemiol. 2014;180(2):127-128), the research area of "-omics" includes genomics, proteomics, metabolomics, and nascent fields of scientific inquiry such as epigenomics and exposomics. These fields can be collectively referred to as "global -omics." Increasing efforts have been made over the past 2 decades to identify and modify environmental risk factors among persons who are susceptible to disease because of their genotype and to integrate genetic information and other biological variables with information about individual-level risk factors and group-level or societal factors related to the broader residential, behavioral, or cultural context. In genome-wide association studies, only a small proportion of heritability is explained by genetic variants identified to date, which has prompted researchers in bioinformatics and biostatistics to take into account nonlinear relationships due to gene-environment or gene-gene interactions. The exposome, which is dynamic and variable, consists of all of the internal and external exposures an individual incurs over a lifetime. Both the epigenome and exposome change with age. The prenatal and perinatal periods are thought to be important times for epigenetic marking. Once the human epigenome has been fully mapped, identification of the effects of all deleterious environmental exposures according to duration of exposure and time period will be a complex undertaking, requiring collaborative epidemiologic studies.

The public health exposome: a population-based, exposure science approach to health disparities research

The lack of progress in reducing health disparities suggests that new approaches are needed if we are to achieve meaningful, equitable, and lasting reductions. Current scientific paradigms do not adequately capture the complexity of the relationships between environment, personal health and population level disparities. The public health exposome is presented as a universal exposure tracking framework for integrating complex relationships between exogenous and endogenous exposures across the lifespan from conception to death. It uses a social-ecological framework that builds on the exposome paradigm for conceptualizing how exogenous exposures "get under the skin". The public health exposome approach has led our team to develop a taxonomy and bioinformatics infrastructure to integrate health outcomes data with thousands of sources of exogenous exposure, organized in four broad domains: natural, built, social, and policy environments. With the input of a transdisciplinary team, we have borrowed and applied the methods, tools and terms from various disciplines to measure the effects of environmental exposures on personal and population health outcomes and disparities, many of which may not manifest until many years later. As is customary with a paradigm shift, this approach has far reaching implications for research methods and design, analytics, community engagement strategies, and research training.

Using personal sensors to assess the exposome and acute health effects

Introduction: The exposome encompasses the totality of human environmental exposures. Recent developments in sensor technology have made it possible to better measure personal exposure to environmental pollutants and other factors. We aimed to discuss and demonstrate the recent developments in personal sensors to measure multiple exposures and possible acute health responses, and discuss the main challenges ahead. Methods: We searched for a range of sensors to measure air pollution, noise, temperature, UV, physical activity, location, blood pressure, heart rate and lung function and to obtain information on green space and emotional status/mood and put it on a person. Results and Conclusions: We discussed the recent developments and main challenges for personal sensors to measure multiple exposures. We found and put together a personal sensor set that measures a comprehensive set of personal exposures continuously over 24 h to assess part of the current exposome and acute health responses. We obtained data for a whole range of exposures and some acute health responses, but many challenges remain to apply the methodology for extended time periods and larger populations including improving the ease of wear, e.g., through miniaturization and extending battery life, and the reduction of costs. However, the technology is moving fast and opportunities will come closer for further wide spread use to assess, at least part of the exposome.

Environmental risk score as a new tool to examine multi-pollutants in epidemiologic research: an example from the NHANES study using serum lipid levels

Objective

A growing body of evidence suggests that environmental pollutants, such as heavy metals, persistent organic pollutants and plasticizers play an important role in the development of chronic diseases. Most epidemiologic studies have examined environmental pollutants individually, but in real life, we are exposed to multi-pollutants and pollution mixtures, not single pollutants. Although multi-pollutant approaches have been recognized recently, challenges exist such as how to estimate the risk of adverse health responses from multi-pollutants. We propose an “Environmental Risk Score (ERS)” as a new simple tool to examine the risk of exposure to multi-pollutants in epidemiologic research.

Methods and Results

We examined 134 environmental pollutants in relation to serum lipids (total cholesterol, high-density lipoprotein cholesterol (HDL), low-density lipoprotein cholesterol (LDL) and triglycerides) using data from the National Health and Nutrition Examination Survey between 1999 and 2006. Using a two-stage approach, stage-1 for discovery (n = 10818) and stage-2 for validation (n = 4615), we identified 13 associated pollutants for total cholesterol, 9 for HDL, 5 for LDL and 27 for triglycerides with adjustment for sociodemographic factors, body mass index and serum nutrient levels. Using the regression coefficients (weights) from joint analyses of the combined data and exposure concentrations, ERS were computed as a weighted sum of the pollutant levels. We computed ERS for multiple lipid outcomes examined individually (single-phenotype approach) or together (multi-phenotype approach). Although the contributions of ERS to overall risk predictions for lipid outcomes were modest, we found relatively stronger associations between ERS and lipid outcomes than with individual pollutants. The magnitudes of the observed associations for ERS were comparable to or stronger than those for socio-demographic factors or BMI.

Conclusions

This study suggests ERS is a promising tool for characterizing disease risk from multi-pollutant exposures. This new approach supports the need for moving from a single-pollutant to a multi-pollutant framework.

Investigation of maternal environmental exposures in association with self-reported preterm birth

Identification of maternal environmental factors influencing preterm birth risks is important to understand the reasons for the increase in prematurity since 1990. Here, we utilized a health survey, the US National Health and Nutrition Examination Survey (NHANES) to search for personal environmental factors associated with preterm birth. 201 urine and blood markers of environmental factors, such as allergens, pollutants, and nutrients were assayed in mothers (range of N: 49-724) who answered questions about any children born preterm (delivery <37 weeks). We screened each of the 201 factors for association with any child born preterm adjusting by age, race/ethnicity, education, and household income. We attempted to verify the top finding, urinary bisphenol A, in an independent study of pregnant women attending Lucile Packard Children's Hospital. We conclude that the association between maternal urinary levels of bisphenol A and preterm birth should be evaluated in a larger epidemiological investigation.

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.

Personality, behavior and environmental features associated with OXTR genetic variants in British mothers

BACKGROUND

It is assumed that the oxytocin receptor gene (OXTR) is associated with factors that are related to features of reproduction as well as the currently emerging fields of mood and emotional response.

METHODS

We analysed data from over 8000 mothers who participated in the Avon Longitudinal Study of Parents and Children (ALSPAC). We determined reproductive, emotional and personality differences related to the two SNPs rs53576 and rs2254298 of the oxytocin receptor gene to determine whether there was evidence in this population for: (i) associations with emotional and personality differences, and (ii) behavioural or environmental links with these SNPs using a hypothesis free approach with over 1000 types of exposure.

RESULTS

Our analyses of 7723 women showed that there were no differences in 11 mood, social or relationship characteristics associated with the rs2254298, and just one with rs53576 (with emotional loneliness)--one statistically significant out of 22 tests is no more than would be expected by chance. There were no interactions with childhood abuse. Using a hypothesis-free approach we found few indicators of environmental or behavioural differences associated with rs2254298, but there was an excess of associations with eating habits with rs53576. The findings included an association with dieting to lose weight, and habits typical of bulimia for the women with GG. The nutrition of the women also showed negative associations of the GG genotype with 13 nutrients, including vitamins D, B12 and retinol, and intake of calcium, potassium and iodine.

CONCLUSIONS

We conclude that this large database of pregnant women was unable to provide confirmation of the types of personality associated with these two OXTR SNPs, but we have shown some evidence of eating differences in those with GG on rs53576. Confirmation of our hypothesis free associations using other data sets is important.

A biobehavioral perspective on telomere length and the exposome

A major objective of biobehavioral research is defining the mechanisms that underlie linkages among behavior, biology, health, and disease. The genomic revolution has demonstrated the importance of studying the role of the environment in (epi)genetic mechanisms. The idea that interactions between environment and genetics influence health outcomes is a central concept of the exposome, a measure of environmental exposures throughout a lifetime. Research suggests that telomere length (TL) and biologic factors involved in telomere stability may provide an understanding of the effects of gene-environment interaction on disease risk. Telomeres, thus, have become important biomarkers for aging as well as for stress-related disease. However, incorporating telomeres into biobehavioral research requires consideration of several aspects of the exposome. Internal and external modifiable and nonmodifiable exposures have the potential to influence TL. Future research utilizing the concept of the exposome will provide meaningful findings related to exposure sources as well as dosage and duration across the life span that influence telomere biology and disease occurrence. Such findings can be translated into clinical practice and may provide a basis for personalized disease prevention and treatment approaches.

Proceedings from the Third National Institutes of Health International Congress on Advances in Uterine Leiomyoma Research: comprehensive review, conference summary and future recommendations

BACKGROUND Uterine fibroids are the most common gynecologic tumors in women of reproductive age yet the etiology and pathogenesis of these lesions remain poorly understood. Age, African ancestry, nulliparity and obesity have been identified as predisposing factors for uterine fibroids. Symptomatic tumors can cause excessive uterine bleeding, bladder dysfunction and pelvic pain, as well as associated reproductive disorders such as infertility, miscarriage and other adverse pregnancy outcomes. Currently, there are limited noninvasive therapies for fibroids and no early intervention or prevention strategies are readily available. This review summarizes the advances in basic, applied and translational uterine fibroid research, in addition to current and proposed approaches to clinical management as presented at the 'Advances in Uterine Leiomyoma Research: 3rd NIH International Congress'. Congress recommendations and a review of the fibroid literature are also reported. METHODS This review is a report of meeting proceedings, the resulting recommendations and a literature review of the subject. RESULTS The research data presented highlights the complexity of uterine fibroids and the convergence of ethnicity, race, genetics, epigenetics and environmental factors, including lifestyle and possible socioeconomic parameters on disease manifestation. The data presented suggest it is likely that the majority of women with uterine fibroids will have normal pregnancy outcomes; however, additional research is warranted. As an alternative to surgery, an effective long-term medical treatment for uterine fibroids should reduce heavy uterine bleeding and fibroid/uterine volume without excessive side effects. This goal has not been achieved and current treatments reduce symptoms only temporarily; however, a multi-disciplined approach to understanding the molecular origins and pathogenesis of uterine fibroids, as presented in this report, makes our quest for identifying novel targets for noninvasive, possibly nonsystemic and effective long-term treatment very promising. CONCLUSIONS The Congress facilitated the exchange of scientific information among members of the uterine leiomyoma research and health-care communities. While advances in research have deepened our knowledge of the pathobiology of fibroids, their etiology still remains incompletely understood. Further needs exist for determination of risk factors and initiation of preventive measures for fibroids, in addition to continued development of new medical and minimally invasive options for treatment.

Exposome informatics: considerations for the design of future biomedical research information systems

The environment's contribution to health has been conceptualized as the exposome. Biomedical research interest in environmental exposures as a determinant of physiopathological processes is rising as such data increasingly become available. The panoply of miniaturized sensing devices now accessible and affordable for individuals to use to monitor a widening range of parameters opens up a new world of research data. Biomedical informatics (BMI) must provide a coherent framework for dealing with multi-scale population data including the phenome, the genome, the exposome, and their interconnections. The combination of these more continuous, comprehensive, and personalized data sources requires new research and development approaches to data management, analysis, and visualization. This article analyzes the implications of a new paradigm for the discipline of BMI, one that recognizes genome, phenome, and exposome data and their intricate interactions as the basis for biomedical research now and for clinical care in the near future.

Effect-directed analysis to explore the polar bear exposome: identification of thyroid hormone disrupting compounds in plasma

Compounds with transthyretin (TTR)-binding potency in the blood plasma of polar bear cubs were identified with effect-directed analysis (EDA). This approach contributes to the understanding of the thyroid disrupting exposome of polar bears. The selection of these samples for in-depth EDA was based on the difference between the observed TTR-binding potency on the one hand and the calculated potency (based on known concentrations of TTR-binding compounds and their relative potencies) on the other. A library-based identification was applied to the liquid chromatography-time-of-flight-mass spectrometry (LC-ToF-MS) data by screening for matches between compound lists and the LC-ToF-MS data regarding accurate mass and isotope pattern. Then, isotope cluster analysis (ICA) was applied to the LC-ToF-MS data allowing specific screening for halogen isotope patterns. The presence of linear and branched nonylphenol (NP) was observed for the first time in polar bears. Furthermore, the presence of one di- and two monohydroxylated octachlorinated biphenyls (octaCBs) was revealed in the extracts. Linear and branched NP, 4'-OH-CB201 and 4,4'-OH-CB202 could be successfully confirmed with respect to their retention time in the analytical system. In addition, branched NP, mono- and dihydroxylated-octaCBs showed TTR-binding potencies and could explain another 32 ± 2% of the total measured activities in the extracts.