Applying an evolutionary mismatch framework to understand disease susceptibility

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Abstract

Noncommunicable diseases (NCDs) are on the rise worldwide. Obesity, cardiovascular disease and type 2 diabetes are among a long list of "lifestyle"diseases that were rare throughout human history but are now common. The evolutionary mismatch hypothesis posits that humans evolved in environments that radically differ from those we currently experience; consequently, traits that were once advantageous may now be "mismatched"and disease causing. At the genetic level, this hypothesis predicts that loci with a history of selection will exhibit "genotype by environment"(GxE) interactions, with different health effects in "ancestral"versus "modern"environments. To identify such loci, we advocate for combining genomic tools with partnerships with subsistence-level groups experiencing rapid lifestyle change. In these populations, comparisons of individuals falling on opposite extremes of the "matched"to "mismatched"spectrum are uniquely possible. More broadly, the work we propose will inform our understanding of environmental and genetic risk factors for NCDs across diverse ancestries and cultures. Copyright:

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Lea, A. J., Clark, A. G., Dahl, A. W., Devinsky, O., Garcia, A. R., Golden, C. D., … Ayroles, J. F. (2023). Applying an evolutionary mismatch framework to understand disease susceptibility. PLoS Biology, 21(9 September). https://doi.org/10.1371/journal.pbio.3002311

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