Am J Epidemiol

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.CC999999/Intramural CDC HHS/United States2017-08-15T00:00:00Z27519539PMC502532

Application of the urban exposome framework using drinking water and quality of life indicators: a proof-of-concept study in Limassol, Cyprus

Background Cities face rapid changes leading to increasing inequalities and emerging public health issues that require cost-effective interventions. The urban exposome concept refers to the continuous monitoring of urban environmental and health indicators using the city and smaller intra-city areas as measurement units in an interdisciplinary approach that combines qualitative and quantitative methods from social sciences, to epidemiology and exposure assessment. Methods In this proof of concept study, drinking water and quality of life indicators were described as part of the development of the urban exposome of Limassol (Cyprus) and were combined with agnostic environment-wide association analysis. This study was conducted as a two-part project with a qualitative part assessing the perceptions of city stakeholders, and quantitative part using a cross-sectional study design (an urban population study). We mapped the water quality parameters and participants’ opinions on city life (i.e., neighborhood life, health care, and green space access) using quarters (small administrative areas) as the reference unit of the city. In an exploratory, agnostic, environment-wide association study analysis, we used all variables (questionnaire responses and water quality metrics) to describe correlations between them. Results Overall, urban drinking-water quality using conventional indicators of chemical (disinfection byproducts-trihalomethanes (THM)) and microbial (coliforms, E. coli, and Enterococci) quality did not raise particular concerns. The general health and chronic health status of the urban participants were significantly (false discovery rate corrected p-value < 0.1) associated with different health conditions such as hypertension and asthma, as well as having financial issues in access to dental care. Additionally, correlations between THM exposures and participant behavioral characteristics (e.g., household cleaning, drinking water habits) were documented. Conclusion This proof-of-concept study showed the potential of using integrative approaches to develop urban exposomic profiles and identifying within-city differences in environmental and health indicators. The characterization of the urban exposome of Limassol will be expanded via the inclusion of biomonitoring tools and untargeted metabolomics

Assessing the Exposome with External Measures: Commentary on the State of the Science and Research Recommendations

The exposome comprises all environmental exposures that a person experiences from conception throughout the life course. Here we review the state of the science for assessing external exposures within the exposome. This article reviews (a) categories of exposures that can be assessed externally, (b) the current state of the science in external exposure assessment, (c) current tools available for external exposure assessment, and (d) priority research needs. We describe major scientific and technological advances that inform external assessment of the exposome, including geographic information systems; remote sensing; global positioning system and geolocation technologies; portable and personal sensing, including smartphone-based sensors and assessments; and self-reported questionnaire assessments, which increasingly rely on Internet-based platforms. We also discuss priority research needs related to methodological and technological improvement, data analysis and interpretation, data sharing, and other practical considerations, including improved assessment of exposure variability as well as exposure in multiple, critical life stages

Assessing health risks from multiple environmental stressors: Moving from G×E to I×E.

Research on disease causation often attempts to isolate the effects of individual factors, including individual genes or environmental factors. This reductionist approach has generated many discoveries, but misses important interactive and cumulative effects that may help explain the broad range of variability in disease occurrence observed across studies and individuals. A disease rarely results from a single factor, and instead results from a broader combination of factors, characterized here as intrinsic (I) and extrinsic (E) factors. Intrinsic vulnerability or resilience emanates from a variety of both fixed and shifting biological factors including genetic traits, while extrinsic factors comprise all biologically-relevant external stressors encountered across the lifespan. The I×E concept incorporates the multi-factorial and dynamic nature of health and disease and provides a unified, conceptual basis for integrating results from multiple areas of research, including genomics, G×E, developmental origins of health and disease, and the exposome. We describe the utility of the I×E concept to better understand and characterize the cumulative impact of multiple extrinsic and intrinsic factors on individual and population health. New research methods increasingly facilitate the measurement of multifactorial and interactive effects in epidemiological and toxicological studies. Tiered or indicator-based approaches can guide the selection of potentially relevant I and E factors for study and quantification, and exposomics methods may eventually produce results that can be used to generate a response function over the life course. Quantitative data on I×E interactive effects should generate a better understanding of the variability in human response to environmental factors. The proposed I×E concept highlights the role for broader study design in order to identify extrinsic and intrinsic factors amenable to interventions at the individual and population levels in order to enhance resilience, reduce vulnerability and improve health

The Impact of Built and Social Environment on Physical Activity among Older Adults

Physical activity, defined as bodily movement produced by skeletal muscles that results in energy expenditure, has many known mental and physical health benefits for older adults. However, as of 2008, only 22.6% of older adults in the United States reported meeting recommended physical activity guidelines. This dissertation examines the role of the built and social environment on physical activity among older adults, with particular focus on physical disorder, or the visual indications of neighborhood deterioration. All empirical analyses use data from the New York City Neighborhood and Mental Health in the Elderly Study (NYCNAMES-II), a three-wave longitudinal study of about 3,500 older adults living in New York City. We first systematically review the existing literature concerning physical disorder as an influence on physical activity among adults of all ages. We find that most prior studies of disorder and activity have been cross-sectional and that disorder has not consistently been associated with less activity across all studies. However, we also find indications that older adults’ activity levels may be more negatively impacted by disorder than younger adults’ activity levels. Next, we use a longitudinal analysis to estimate the association between neighborhood disorder and total physical activity among the NYCNAMES-II cohort. In multivariable mixed regression models accounting for individual and neighborhood factors, for missing data, and for loss to follow-up, we find that each standard deviation increase in neighborhood disorder was associated with an estimated 3.0 units (95% CI: 1.9, 4.2) lower PASE score at baseline, or the equivalent of about 10 minutes of walking per day. There was no significant interaction between physical disorder and changes in PASE score over two years of follow-up. We next apply a latent transition analysis to identify patterns of types of physical activity the same cohort, identifying seven latent classes of activity. Of these seven classes, three pairs of classes were roughly equivalent except for participation in exercise. About three quarters of subjects remained within each latent class between waves; most transitions that did occur were between classes defined by exercise to the parallel class without exercise or vice-versa. More neighborhood disorder was modestly associated with moving out of a sports and recreation class (Relative Risk = 1.27, 95% CI = 1.00, 1.61 between waves 1 and 2, Relative Risk = 1.28, 95% CI = 0.85, 1.93 between waves 2 and 3). Finally, we develop the Neighborhood Environment-Wide Association Study (NE-WAS), an agnostic approach to systematically explore the plethora of neighborhood measures available to modern researchers equipped with geographic information systems (GIS) software. We find that only neighborhood socioeconomic status and disorder measures were associated with total activity and gardening, whereas a broader range of measures was associated with walking. Substantively, we conclude that more physical disorder was associated with less physical activity, potentially due to decreases in sports and recreation among those living amidst physical disorder, though latent transition analysis estimates were too imprecise to rule out chance. Future longitudinal research on physical disorder as an influence on physical activity would benefit from longer periods of follow-up in which more subjects moved between neighborhoods. Methodologically, the NE-WAS approach appears to be a promising way to systematize neighborhood research as the scale of available spatially located administrative data continues to grow. Future NE-WASes might profitably focus on comparing the spatial scale of neighborhood measures

Gene-environment and gene-gene interactions in myopia

Motivated by the release of the UK Biobank data and the lack of documented gene-environment (GxE) and gene-gene (GxG) interactions in myopia, I sought to apply various statistical tools to provide a quantitative assessment of the interplay between environmental and genetic risk factors shaping refractive error. The comparison between the two different risk measurement scales with which GxE interactions can be identified suggested that the additive risk scale can lead to a more informative perspective about refractive error aetiology. The evaluation of two indirect methods for detecting genetic variants affecting refractive error via interaction effects suggested the enrichment of GxG and GxE among the variants that display marginal SNP effects. For genetic variants already known from prior GWAS studies to influence refractive error, genetic effect sizes were highly non-uniform; individuals from the tails of the refractive error distribution (i.e. high myopes and hyperopes) displayed much larger effects compared to individuals in the middle of the distribution (i.e. emmetropes). Prediction of refractive error using GxE interactions indicated that although some of the variance of refractive error could be explained by a risk score constructed using interaction effects, the contribution of GxE was already accounted for by a risk score constructed using marginal SNP effects only. Although a handful of candidate genes were identified using multifactor dimensionality reduction technique, none displayed compelling evidence of involvement in a GxG interaction. There was, however, suggestive evidence that the candidate genes constitute a genetic interaction network which is regulated by hub gene ZMAT4. In summary, the analyses reported in this thesis provide further support for the challenging nature of definitively identifying loci involved in GxE and GxG interactions. The thesis provides several guidelines that future studies could take into account to obtain more insightful results regarding the extent of interactions in refractive error