Dataset Information

Community Approaches for Integrating Environmental Exposures into Human Models of Disease.

ABSTRACT:

Background

A critical challenge in genomic medicine is identifying the genetic and environmental risk factors for disease. Currently, the available data links a majority of known coding human genes to phenotypes, but the environmental component of human disease is extremely underrepresented in these linked data sets. Without environmental exposure information, our ability to realize precision health is limited, even with the promise of modern genomics. Achieving integration of gene, phenotype, and environment will require extensive translation of data into a standard, computable form and the extension of the existing gene/phenotype data model. The data standards and models needed to achieve this integration do not currently exist.

Objectives

Our objective is to foster development of community-driven data-reporting standards and a computational model that will facilitate the inclusion of exposure data in computational analysis of human disease. To this end, we present a preliminary semantic data model and use cases and competency questions for further community-driven model development and refinement.

Discussion

There is a real desire by the exposure science, epidemiology, and toxicology communities to use informatics approaches to improve their research workflow, gain new insights, and increase data reuse. Critical to success is the development of a community-driven data model for describing environmental exposures and linking them to existing models of human disease. https://doi.org/10.1289/EHP7215.

SUBMITTER: Thessen AE

PROVIDER: S-EPMC7769179 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature

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Publications

Community Approaches for Integrating Environmental Exposures into Human Models of Disease.

Thessen Anne E AE Grondin Cynthia J CJ Kulkarni Resham D RD Brander Susanne S Truong Lisa L Vasilevsky Nicole A NA Callahan Tiffany J TJ Chan Lauren E LE Westra Brian B Willis Mary M Rothenberg Sarah E SE Jarabek Annie M AM Burgoon Lyle L Korrick Susan A SA Haendel Melissa A MA

Environmental health perspectives 20201228 12

<h4>Background</h4>A critical challenge in genomic medicine is identifying the genetic and environmental risk factors for disease. Currently, the available data links a majority of known coding human genes to phenotypes, but the environmental component of human disease is extremely underrepresented in these linked data sets. Without environmental exposure information, our ability to realize precision health is limited, even with the promise of modern genomics. Achieving integration of gene, phen ...[more]

PMID: 33369481

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Project description:Blood pressure is a leading risk factor for cardiovascular disease, influenced by chemical and non-chemical stressors. Exposure reduction strategies can potentially improve public health, but there are analytical challenges in developing quantitative models of health benefits, including the need for detailed multi-stressor exposure models, corresponding health evidence, and methods to simulate changes in exposure and resultant health benefits. These challenges are pronounced in low-income urban communities, where residents are often simultaneously exposed to numerous chemical and non-chemical stressors. For New Bedford (Massachusetts, USA), a low-income community near a Superfund site, we simulated geographically-resolved individual data, and applied previously published structural equation models developed from National Health and Nutrition Examination Survey (NHANES) data. These models simultaneously predict exposures to multiple chemicals (e.g., lead (Pb), cadmium (Cd), and polychlorinated biphenyls (PCBs)) and non-chemical factors (e.g., socioeconomic status), and determine their combined effects on blood pressure. We then modeled counterfactual scenarios reducing exposures and estimated the resulting changes in blood pressure distribution in the community. Results indicated small shifts in mean blood pressure and percentage of normotensive individuals with a reduction of Pb and/or PCB exposure. For example, a reduction in PCB to the lowest 10th percentile exposure in the NHANES resulted in a 2.4 mm Hg shift in systolic blood pressure (SBP), corresponding with 3% fewer individuals with SBP in the Stage 2 hypertension category [SBP ≥140]. Our model also emphasized the importance of the multi-stressor framework by simulating benefits of reductions in smoking rates, given positive associations with Pb and Cd but inverse associations with body mass index and blood pressure. This research demonstrates the ability to jointly consider chemical and non-chemical exposures and their impact on cardiovascular health, using approaches generalizable to other cumulative risk assessment applications.

Dataset Information

Community Approaches for Integrating Environmental Exposures into Human Models of Disease.

Background

Objectives

Discussion

Publications

Community Approaches for Integrating Environmental Exposures into Human Models of Disease.

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