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Applying an evolutionary mismatch framework to understand disease susceptibility
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 th...
Autores principales: | , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10513379/ https://www.ncbi.nlm.nih.gov/pubmed/37695771 http://dx.doi.org/10.1371/journal.pbio.3002311 |
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author | Lea, Amanda J. Clark, Andrew G. Dahl, Andrew W. Devinsky, Orrin Garcia, Angela R. Golden, Christopher D. Kamau, Joseph Kraft, Thomas S. Lim, Yvonne A. L. Martins, Dino J. Mogoi, Donald Pajukanta, Päivi Perry, George H. Pontzer, Herman Trumble, Benjamin C. Urlacher, Samuel S. Venkataraman, Vivek V. Wallace, Ian J. Gurven, Michael Lieberman, Daniel E. Ayroles, Julien F. |
author_facet | Lea, Amanda J. Clark, Andrew G. Dahl, Andrew W. Devinsky, Orrin Garcia, Angela R. Golden, Christopher D. Kamau, Joseph Kraft, Thomas S. Lim, Yvonne A. L. Martins, Dino J. Mogoi, Donald Pajukanta, Päivi Perry, George H. Pontzer, Herman Trumble, Benjamin C. Urlacher, Samuel S. Venkataraman, Vivek V. Wallace, Ian J. Gurven, Michael Lieberman, Daniel E. Ayroles, Julien F. |
author_sort | Lea, Amanda J. |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-10513379 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-105133792023-09-22 Applying an evolutionary mismatch framework to understand disease susceptibility Lea, Amanda J. Clark, Andrew G. Dahl, Andrew W. Devinsky, Orrin Garcia, Angela R. Golden, Christopher D. Kamau, Joseph Kraft, Thomas S. Lim, Yvonne A. L. Martins, Dino J. Mogoi, Donald Pajukanta, Päivi Perry, George H. Pontzer, Herman Trumble, Benjamin C. Urlacher, Samuel S. Venkataraman, Vivek V. Wallace, Ian J. Gurven, Michael Lieberman, Daniel E. Ayroles, Julien F. PLoS Biol Essay 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. Public Library of Science 2023-09-11 /pmc/articles/PMC10513379/ /pubmed/37695771 http://dx.doi.org/10.1371/journal.pbio.3002311 Text en © 2023 Lea et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Essay Lea, Amanda J. Clark, Andrew G. Dahl, Andrew W. Devinsky, Orrin Garcia, Angela R. Golden, Christopher D. Kamau, Joseph Kraft, Thomas S. Lim, Yvonne A. L. Martins, Dino J. Mogoi, Donald Pajukanta, Päivi Perry, George H. Pontzer, Herman Trumble, Benjamin C. Urlacher, Samuel S. Venkataraman, Vivek V. Wallace, Ian J. Gurven, Michael Lieberman, Daniel E. Ayroles, Julien F. Applying an evolutionary mismatch framework to understand disease susceptibility |
title | Applying an evolutionary mismatch framework to understand disease susceptibility |
title_full | Applying an evolutionary mismatch framework to understand disease susceptibility |
title_fullStr | Applying an evolutionary mismatch framework to understand disease susceptibility |
title_full_unstemmed | Applying an evolutionary mismatch framework to understand disease susceptibility |
title_short | Applying an evolutionary mismatch framework to understand disease susceptibility |
title_sort | applying an evolutionary mismatch framework to understand disease susceptibility |
topic | Essay |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10513379/ https://www.ncbi.nlm.nih.gov/pubmed/37695771 http://dx.doi.org/10.1371/journal.pbio.3002311 |
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