Analytical Complexity in Detection of Gene Variant-by-Environment Exposure Interactions in High-Throughput Genomic
1Department of Biomedical Informatics, Harvard Medical School, 10 Shattuck St., Boston, MA, 02215, USA. chirag_patel@hms.harvard.edu.
Abstract:
It seems intuitive that disease risk is influenced by the interaction between inherited genetic variants and environmental exposure factors; however, we have few documented interactions between variants and exposures. Advances in technology may enable the simultaneous measurement (i.e., on the same individuals in an epidemiological study) of millions of genome variants with thousands of environmental "exposome" factors, significantly increasing the number of possible factor pairs available for testing for the presence of interactions. The burden of analytic complexity, or sheer number of genetic and exposure factors measured, poses a considerable challenge for discovery of interactions in population-scale data. Advances in analytic approaches, large sample sizes, less conservative methods to mitigate multiple testing, and strong biological priors will be required to prune the search space to find reproducible and robust gene-by-environment interactions in observational data.
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