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Environmental Factor

Environmental Factor

Your Online Source for NIEHS News

April 2018

New research approaches target gene-environment interactions

A special issue of the journal Mammalian Genome looks to genetics for reasons why people respond differently to environmental stressors.

Kim McAllister McAllister oversees grants for gene-environment interaction studies, statistical and bioinformatics methods, as well as genetics, DNA repair, and animal models of disease. (Photo courtesy of Steve McCaw)

A special issue of the journal Mammalian Genome highlights research on why individuals vary in their responses to environmental stressors. The papers explore mechanisms involved in how genetics and the environment combine to influence disease outcomes.

Published in February, the issue includes articles by NIEHS researchers and trainees, scientists at the National Toxicology Program (NTP), which is housed at NIEHS, as well as grantees and other academic researchers.

Why individuals respond differently

“Differences in genetic susceptibility to environmental exposures may affect which individuals get particular diseases, and thus has important implications,” said Kimberly McAllister, Ph.D., a health scientist administrator in the Genes, Environment, and Health Branch at NIEHS. McAllister is a guest editor of the special issue.

“Research on the impact of interindividual variability for human disease outcomes will help to identify which people in a population might be the most susceptible to certain environmental exposures,” she said. It also gives scientists a more comprehensive view of all relevant factors.

Steve Kleeberger Kleeberger leads the Environmental Genetics Group and is especially interested in how genetic factors influence susceptibility to and the course of complex lung diseases. (Photo courtesy of Steve McCaw)

Fellow guest editor Steven Kleeberger, Ph.D., a lead researcher in the NIEHS Immunity, Inflammation, and Disease Lab, emphasized that by identifying which genes contribute to that differing susceptibility, researchers may uncover better means of preventing or treating diseases.

Studying gene-environment interactions should lead to novel strategies to prevent and treat environmentally driven diseases, according to McAllister and the other authors of the issue’s introductory article. “The application of these studies to environmental health decisions and risk assessment will need to be major next steps,” said McAllister.

Key data for decision makers

Those who assess risks from chemicals need to identify susceptible populations and characterize their potential adverse responses. Traditional approaches are not well-suited to achieving this goal, so authors of the special issue papers highlighted newer alternatives.

Ivan Rusyn Rusyn’s lab develops innovative experimental methods and computational tools to enable analysis of data across multiple dimensions to uncover links between exposures and adverse health effects. (Photo courtesy of TAMU)

“This special issue takes a look at the current state of experimental models and at potential barriers to using new data in decision-making,” said Ivan Rusyn, M.D., Ph.D., a professor of Veterinary Medicine and Biomedical Sciences at Texas A&M University (TAMU) and an NIEHS grantee. Rusyn co-edited the special issue and co-wrote its introductory article.

Along with McAllister, Kleeberger, and Rusyn, Karen Svenson, Ph.D., senior scientific program manager at the Jackson Laboratory, also served as a guest editor and author of the introduction.

“Population-based studies aiming to understand the relationship between interindividual variation and environmental stressors are now being conducted in humans, rodents, and other model organisms,” the authors pointed out.

Incorporating genetic diversity

Rusyn co-authored a paper in the issue that highlighted obstacles involved in characterizing interindividual variability. Data on varied responses cannot be obtained from studies that use homogeneous, inbred experimental animal populations. Moreover, studies using human cell-based assays typically do not focus on differences among individuals.

According to Rusyn, mammalian models that are genetically diverse are necessary for characterizing human variability and informing environmental decision-making. In addition, more sophisticated computational and statistical models are required to analyze population-based toxicity data. However, the extra time, cost, and complexity involved in taking these steps and translating the results into public health policy pose major hurdles.

“Regulators and decision makers need education in how to use the data from the population-based models,” Rusyn said. “Also, the researchers need to make sure their study designs are suitable for decision-making, and that they take the time to connect the outcomes and hypotheses to real-life challenges in regulatory applications.”

Rusyn I, Kleeberger SR, McAllister KA, French JE, Svenson KL. 2018. Introduction to mammalian genome special issue: the combined role of genetics and environment relevant to human disease outcomes. Mamm Genome 29(1-2):1–4.

Chiu WA, Rusyn I. 2018. Advancing chemical risk assessment decision-making with population variability data: challenges and opportunities. Mamm Genome 29(1-2):182–189.

(Janelle Weaver, Ph.D., is a contract writer for the Office of Communications and Public Liaison.)

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