Precision environmental health (PEH) is focused on understanding the basis of interindividual differences in disease susceptibility, progression, and severity, in a way that takes account of environmental exposures throughout life. PEH aims to provide the tools and understanding needed to better understand how environmental exposures affect individual health and disease susceptibility to ensure more equitable health status for all. A PEH approach requires integrating genome/epigenome profiles, measuring exposures at critical stages of life using the exposomics framework, public health, and incorporating powerful data science tools to create connections and understanding across many different types of data. Next generation PEH research occurs at the intersection of genomics, genomic modifications that do not change genomic sequences (epigenomics), and environmental exposures and is informed by other “-omics” data. The goal of PEH is to better understand individual environmental risk and susceptibility to help create and deliver personalized interventions for promoting health and for the prevention and treatment of disease.
Translational Goal
Advance PEH science to obtain a level of knowledge that will permit individuals and health care providers to better understand, manage, and communicate environmental risks, in both general and clinical settings, based on individual susceptibilities.
Priority Approaches
- Focus on understanding factors and markers of risk, resilience, and susceptibility at the individual level.
- Develop methods of measuring multiple exposures at the individual level so that exposures over time and from different sources can be better understood.
- Incorporate multiple “-omics” approaches for individual measurements from different tissues and at different timepoints across diverse populations of individuals.
- Conduct human studies using community-engaged research approaches, when possible, to identify and understand the factors or markers of risk, resilience, and susceptibility at the individual level.
- Develop human biology-based testing methods that provide insights into specific biological processes or disease states and represent population diversity to inform individual risk and susceptibility.
- Develop innovative approaches in data science, analytics, and artificial intelligence/machine learning (AI/ML),and improve computational methods for integration of complex data sets.
- Establish partnerships for sharing and integrating exposomics and genomics into environmental health studies to generate more holistic results.
- Advance research on communicating exposure and disease risk using the framework of precision prevention.
