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OICR-led study shows that environmental exposures such as air pollution are more determinant of respiratory health than inherited genetics

Researchers from the Ontario Institute for Cancer Research (OICR), with colleagues at other institutions in Canada and the UK, have found strong evidence that environmental exposures, including air pollution, affect gene expressions associated with respiratory diseases much more than genetic ancestry.

The study, published as an open-access paper in Nature Communications, analyzed more than 1.6 million data points from biological specimens, health questionnaires and environmental datasets, making this study one of the largest ever to examine the relationship between gene expression and environmental stimuli.

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Differentially expressed genes are associated with local ambient air pollution. Coinertia (CoIA) analysis between gene expression (columns) and fine-scale environmental variables (rows). (CoIA is a multivariate method for coupling two tables.) CoIA analyses were performed on genes that were significantly differentially expressed among regions and the regulators of those genes (RDEG).

CoIAs were computed between differentially expressed genes profiles and fine-scale environmental data. The researchers performed two sets (Group 1 and Group 2, each composed of a random draw of half the cohort) of CoIAs: each set included 10,000× resampling of 200 individuals (without replacement, from Group 1 or Group 2), and the CoIAs were performed between environment and gene expression for each of the 10,000 iterations.

The heatmap represents, for each Group 1 or Group 2, the median of each environment–gene associations from the cross-tabulated values distribution.

Associations from Group 1 and Group 2 largely cluster together, indicating a strong signal of the association between fine-scale air pollution levels and gene expression. A permutation test (n = 10,000 steps) indicates the that the correlations between the matrices are significant (p = 0.00089 and p = 9.9 × 10−5 for Group 1 and 2 respectively). Favé et al. Click to enlarge.

These findings represent a groundbreaking use of big data to uncover the environmental factors that are behind diseases and inform strategies for prevention, an approach that would apply to a number of diseases, including cancer.

Genetic, health and disease data of participants from Montreal, Québec City and Saguenay were linked with environmental information such as air pollution, walkability and access to food to see how these factors impact gene expression.

Participants were enrolled in the Québec arm (CARTaGENE) of the Canadian Partnership for Tomorrow Project (CPTP), which supports research into environmental, lifestyle and genetic factors related to the development and progression of cancer and chronic diseases. More than 300,000 Canadians—1% of the population—have enrolled in CPTP since its launch in 2008.

The study used deep characterization of gene expression signatures from participants and linked that data with environmental information.

We were surprised to find that we were able to stratify genetic ancestry within Québec, identifying individuals whose descendants were from Montreal versus Saguenay for example. This helped us to show how most gene expression is not derived by ancestry, and that environmental exposures associated with living in a particular city or region are more impactful on gene expression associated with disease traits than heritable variation.

—Dr. Philip Awadalla, senior author

One of the main findings of the study was that exposure to higher levels of particulate matter and nitrous dioxide in the Saguenay area affected the expression of genes associated with oxygen pathways and respiratory function. This resulted in higher rates of respiratory ailments such as asthma and chronic obstructive pulmonary disease (COPD). The study also revealed that there are genetic variants that control how a person’s gene expression responds when exposed to environmental stimuli.

Our findings illustrate that the impact of the geographic region of residence on the blood transcriptome overrides that of ancestry. Moreover, ambient air pollution exposures are likely contributing to this regional effect in Quebec and may explain the differences in some clinical traits among regions such as asthma prevalence. Fortunately, in Québec, and in many parts of the developed world, air quality has improved since the 1980s.

However, there has been a sharp increase in anthropogenic pollution levels in many parts of Asia caused by the rapid industrialization and increased use of fossil fuel energies. In the context of global climate change, air pollution and hazardous air quality events are predicted to become more frequent and cause additional morbidity and mortality. More broadly, our work shows how environmental exposures modulate gene expression directly, can act upon the penetrance of genetic variants, and can affect clinically relevant phenotypes in humans.

—Favé et al.

Awadalla is Director and Sr. Principal Investigator, Computational Biology, OICR, the Executive Scientific Director of the Ontario Health Study (Ontario’s CPTP cohort), Director of the Genome Canada, Canadian Data Integration Centre and Professor, Department of Molecular Genetics, Faculty of Medicine, University of Toronto.

Controlled access to cohort data and biological samples is available to researchers through the CPTP Data Portal and CARTaGENE.

The Ontario Institute for Cancer Research (OICR) is a collaborative, not-for-profit research institute focused on accelerating the translation of new cancer research discoveries to patients around the world while maximizing the economic benefit of this research for the people of Ontario. Funding for OICR is provided by the Government of Ontario.

Resources

  • Marie-Julie Favé, Fabien C. Lamaze, David Soave, Alan Hodgkinson, Héloïse Gauvin, Vanessa Bruat, Jean-Christophe Grenier, Elias Gbeha, Kimberly Skead, Audrey Smargiassi, Markey Johnson, Youssef Idaghdour & Philip Awadalla (2018) “Gene-by-environment interactions in urban populations modulate risk phenotypes” Nature Communications volume 9, Article number: 827 doi: 10.1038/s41467-018-03202-2

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