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Applying an evolutionary mismatch framework to understand disease susceptibility.

Publication ,  Journal Article
Lea, AJ; Clark, AG; Dahl, AW; Devinsky, O; Garcia, AR; Golden, CD; Kamau, J; Kraft, TS; Lim, YAL; Martins, DJ; Mogoi, D; Pajukanta, P ...
Published in: PLoS biology
September 2023

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 in partnership 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.

Duke Scholars

Published In

PLoS biology

DOI

EISSN

1545-7885

ISSN

1544-9173

Publication Date

September 2023

Volume

21

Issue

9

Start / End Page

e3002311

Related Subject Headings

  • Humans
  • Genomics
  • Disease Susceptibility
  • Diabetes Mellitus, Type 2
  • Developmental Biology
  • Cardiovascular Diseases
  • Biological Evolution
  • 32 Biomedical and clinical sciences
  • 31 Biological sciences
  • 30 Agricultural, veterinary and food sciences
 

Citation

APA
Chicago
ICMJE
MLA
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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), e3002311. https://doi.org/10.1371/journal.pbio.3002311
Lea, Amanda J., Andrew G. Clark, Andrew W. Dahl, Orrin Devinsky, Angela R. Garcia, Christopher D. Golden, Joseph Kamau, et al. “Applying an evolutionary mismatch framework to understand disease susceptibility.PLoS Biology 21, no. 9 (September 2023): e3002311. https://doi.org/10.1371/journal.pbio.3002311.
Lea AJ, Clark AG, Dahl AW, Devinsky O, Garcia AR, Golden CD, et al. Applying an evolutionary mismatch framework to understand disease susceptibility. PLoS biology. 2023 Sep;21(9):e3002311.
Lea, Amanda J., et al. “Applying an evolutionary mismatch framework to understand disease susceptibility.PLoS Biology, vol. 21, no. 9, Sept. 2023, p. e3002311. Epmc, doi:10.1371/journal.pbio.3002311.
Lea AJ, Clark AG, Dahl AW, Devinsky O, Garcia AR, Golden CD, Kamau J, Kraft TS, Lim YAL, Martins DJ, Mogoi D, Pajukanta P, Perry GH, Pontzer H, Trumble BC, Urlacher SS, Venkataraman VV, Wallace IJ, Gurven M, Lieberman DE, Ayroles JF. Applying an evolutionary mismatch framework to understand disease susceptibility. PLoS biology. 2023 Sep;21(9):e3002311.
Journal cover image

Published In

PLoS biology

DOI

EISSN

1545-7885

ISSN

1544-9173

Publication Date

September 2023

Volume

21

Issue

9

Start / End Page

e3002311

Related Subject Headings

  • Humans
  • Genomics
  • Disease Susceptibility
  • Diabetes Mellitus, Type 2
  • Developmental Biology
  • Cardiovascular Diseases
  • Biological Evolution
  • 32 Biomedical and clinical sciences
  • 31 Biological sciences
  • 30 Agricultural, veterinary and food sciences