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The genetic architecture of pain intensity in a sample of 598,339 U.S. veterans

Chronic pain is a common problem, with more than one-fifth of adult Americans reporting pain daily or on most days. It adversely affects quality of life and imposes substantial personal and economic costs. Efforts to treat chronic pain using opioids played a central role in precipitating the opioid...

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Autores principales: Toikumo, Sylvanus, Vickers-Smith, Rachel, Jinwala, Zeal, Xu, Heng, Saini, Divya, Hartwell, Emily, Venegas, Mirko P., Sullivan, Kyle A., Xu, Ke, Jacobson, Daniel A., Gelernter, Joel, Rentsch, Christopher T., Stahl, Eli, Cheatle, Martin, Zhou, Hang, Waxman, Stephen G., Justice, Amy C., Kember, Rachel L., Kranzler, Henry R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cold Spring Harbor Laboratory 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10055465/
https://www.ncbi.nlm.nih.gov/pubmed/36993749
http://dx.doi.org/10.1101/2023.03.09.23286958
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author Toikumo, Sylvanus
Vickers-Smith, Rachel
Jinwala, Zeal
Xu, Heng
Saini, Divya
Hartwell, Emily
Venegas, Mirko P.
Sullivan, Kyle A.
Xu, Ke
Jacobson, Daniel A.
Gelernter, Joel
Rentsch, Christopher T.
Stahl, Eli
Cheatle, Martin
Zhou, Hang
Waxman, Stephen G.
Justice, Amy C.
Kember, Rachel L.
Kranzler, Henry R.
author_facet Toikumo, Sylvanus
Vickers-Smith, Rachel
Jinwala, Zeal
Xu, Heng
Saini, Divya
Hartwell, Emily
Venegas, Mirko P.
Sullivan, Kyle A.
Xu, Ke
Jacobson, Daniel A.
Gelernter, Joel
Rentsch, Christopher T.
Stahl, Eli
Cheatle, Martin
Zhou, Hang
Waxman, Stephen G.
Justice, Amy C.
Kember, Rachel L.
Kranzler, Henry R.
author_sort Toikumo, Sylvanus
collection PubMed
description Chronic pain is a common problem, with more than one-fifth of adult Americans reporting pain daily or on most days. It adversely affects quality of life and imposes substantial personal and economic costs. Efforts to treat chronic pain using opioids played a central role in precipitating the opioid crisis. Despite an estimated heritability of 25-50%, the genetic architecture of chronic pain is not well characterized, in part because studies have largely been limited to samples of European ancestry. To help address this knowledge gap, we conducted a cross-ancestry meta-analysis of pain intensity in 598,339 participants in the Million Veteran Program, which identified 125 independent genetic loci, 82 of which are novel. Pain intensity was genetically correlated with other pain phenotypes, level of substance use and substance use disorders, other psychiatric traits, education level, and cognitive traits. Integration of the GWAS findings with functional genomics data shows enrichment for putatively causal genes (n = 142) and proteins (n = 14) expressed in brain tissues, specifically in GABAergic neurons. Drug repurposing analysis identified anticonvulsants, beta-blockers, and calcium-channel blockers, among other drug groups, as having potential analgesic effects. Our results provide insights into key molecular contributors to the experience of pain and highlight attractive drug targets.
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spelling pubmed-100554652023-03-30 The genetic architecture of pain intensity in a sample of 598,339 U.S. veterans Toikumo, Sylvanus Vickers-Smith, Rachel Jinwala, Zeal Xu, Heng Saini, Divya Hartwell, Emily Venegas, Mirko P. Sullivan, Kyle A. Xu, Ke Jacobson, Daniel A. Gelernter, Joel Rentsch, Christopher T. Stahl, Eli Cheatle, Martin Zhou, Hang Waxman, Stephen G. Justice, Amy C. Kember, Rachel L. Kranzler, Henry R. medRxiv Article Chronic pain is a common problem, with more than one-fifth of adult Americans reporting pain daily or on most days. It adversely affects quality of life and imposes substantial personal and economic costs. Efforts to treat chronic pain using opioids played a central role in precipitating the opioid crisis. Despite an estimated heritability of 25-50%, the genetic architecture of chronic pain is not well characterized, in part because studies have largely been limited to samples of European ancestry. To help address this knowledge gap, we conducted a cross-ancestry meta-analysis of pain intensity in 598,339 participants in the Million Veteran Program, which identified 125 independent genetic loci, 82 of which are novel. Pain intensity was genetically correlated with other pain phenotypes, level of substance use and substance use disorders, other psychiatric traits, education level, and cognitive traits. Integration of the GWAS findings with functional genomics data shows enrichment for putatively causal genes (n = 142) and proteins (n = 14) expressed in brain tissues, specifically in GABAergic neurons. Drug repurposing analysis identified anticonvulsants, beta-blockers, and calcium-channel blockers, among other drug groups, as having potential analgesic effects. Our results provide insights into key molecular contributors to the experience of pain and highlight attractive drug targets. Cold Spring Harbor Laboratory 2023-03-13 /pmc/articles/PMC10055465/ /pubmed/36993749 http://dx.doi.org/10.1101/2023.03.09.23286958 Text en https://creativecommons.org/licenses/by-nc-nd/4.0/This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (https://creativecommons.org/licenses/by-nc-nd/4.0/) , which allows reusers to copy and distribute the material in any medium or format in unadapted form only, for noncommercial purposes only, and only so long as attribution is given to the creator.
spellingShingle Article
Toikumo, Sylvanus
Vickers-Smith, Rachel
Jinwala, Zeal
Xu, Heng
Saini, Divya
Hartwell, Emily
Venegas, Mirko P.
Sullivan, Kyle A.
Xu, Ke
Jacobson, Daniel A.
Gelernter, Joel
Rentsch, Christopher T.
Stahl, Eli
Cheatle, Martin
Zhou, Hang
Waxman, Stephen G.
Justice, Amy C.
Kember, Rachel L.
Kranzler, Henry R.
The genetic architecture of pain intensity in a sample of 598,339 U.S. veterans
title The genetic architecture of pain intensity in a sample of 598,339 U.S. veterans
title_full The genetic architecture of pain intensity in a sample of 598,339 U.S. veterans
title_fullStr The genetic architecture of pain intensity in a sample of 598,339 U.S. veterans
title_full_unstemmed The genetic architecture of pain intensity in a sample of 598,339 U.S. veterans
title_short The genetic architecture of pain intensity in a sample of 598,339 U.S. veterans
title_sort genetic architecture of pain intensity in a sample of 598,339 u.s. veterans
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10055465/
https://www.ncbi.nlm.nih.gov/pubmed/36993749
http://dx.doi.org/10.1101/2023.03.09.23286958
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