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Multi-trait genome-wide association analyses leveraging alcohol use disorder findings identify novel loci for smoking behaviors in the Million Veteran Program

Smoking behaviors and alcohol use disorder (AUD), both moderately heritable traits, commonly co-occur in the general population. Single-trait genome-wide association studies (GWAS) have identified multiple loci for smoking and AUD. However, GWASs that have aimed to identify loci contributing to co-o...

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Autores principales: Cheng, Youshu, Dao, Cecilia, Zhou, Hang, Li, Boyang, Kember, Rachel L., Toikumo, Sylvanus, Zhao, Hongyu, Gelernter, Joel, Kranzler, Henry R., Justice, Amy C., Xu, Ke
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10162964/
https://www.ncbi.nlm.nih.gov/pubmed/37147289
http://dx.doi.org/10.1038/s41398-023-02409-2
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author Cheng, Youshu
Dao, Cecilia
Zhou, Hang
Li, Boyang
Kember, Rachel L.
Toikumo, Sylvanus
Zhao, Hongyu
Gelernter, Joel
Kranzler, Henry R.
Justice, Amy C.
Xu, Ke
author_facet Cheng, Youshu
Dao, Cecilia
Zhou, Hang
Li, Boyang
Kember, Rachel L.
Toikumo, Sylvanus
Zhao, Hongyu
Gelernter, Joel
Kranzler, Henry R.
Justice, Amy C.
Xu, Ke
author_sort Cheng, Youshu
collection PubMed
description Smoking behaviors and alcohol use disorder (AUD), both moderately heritable traits, commonly co-occur in the general population. Single-trait genome-wide association studies (GWAS) have identified multiple loci for smoking and AUD. However, GWASs that have aimed to identify loci contributing to co-occurring smoking and AUD have used small samples and thus have not been highly informative. Applying multi-trait analysis of GWASs (MTAG), we conducted a joint GWAS of smoking and AUD with data from the Million Veteran Program (N = 318,694). By leveraging GWAS summary statistics for AUD, MTAG identified 21 genome-wide significant (GWS) loci associated with smoking initiation and 17 loci associated with smoking cessation compared to 16 and 8 loci, respectively, identified by single-trait GWAS. The novel loci for smoking behaviors identified by MTAG included those previously associated with psychiatric or substance use traits. Colocalization analysis identified 10 loci shared by AUD and smoking status traits, all of which achieved GWS in MTAG, including variants on SIX3, NCAM1, and near DRD2. Functional annotation of the MTAG variants highlighted biologically important regions on ZBTB20, DRD2, PPP6C, and GCKR that contribute to smoking behaviors. In contrast, MTAG of smoking behaviors and alcohol consumption (AC) did not enhance discovery compared with single-trait GWAS for smoking behaviors. We conclude that using MTAG to augment the power of GWAS enables the identification of novel genetic variants for commonly co-occuring phenotypes, providing new insights into their pleiotropic effects on smoking behavior and AUD.
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spelling pubmed-101629642023-05-07 Multi-trait genome-wide association analyses leveraging alcohol use disorder findings identify novel loci for smoking behaviors in the Million Veteran Program Cheng, Youshu Dao, Cecilia Zhou, Hang Li, Boyang Kember, Rachel L. Toikumo, Sylvanus Zhao, Hongyu Gelernter, Joel Kranzler, Henry R. Justice, Amy C. Xu, Ke Transl Psychiatry Article Smoking behaviors and alcohol use disorder (AUD), both moderately heritable traits, commonly co-occur in the general population. Single-trait genome-wide association studies (GWAS) have identified multiple loci for smoking and AUD. However, GWASs that have aimed to identify loci contributing to co-occurring smoking and AUD have used small samples and thus have not been highly informative. Applying multi-trait analysis of GWASs (MTAG), we conducted a joint GWAS of smoking and AUD with data from the Million Veteran Program (N = 318,694). By leveraging GWAS summary statistics for AUD, MTAG identified 21 genome-wide significant (GWS) loci associated with smoking initiation and 17 loci associated with smoking cessation compared to 16 and 8 loci, respectively, identified by single-trait GWAS. The novel loci for smoking behaviors identified by MTAG included those previously associated with psychiatric or substance use traits. Colocalization analysis identified 10 loci shared by AUD and smoking status traits, all of which achieved GWS in MTAG, including variants on SIX3, NCAM1, and near DRD2. Functional annotation of the MTAG variants highlighted biologically important regions on ZBTB20, DRD2, PPP6C, and GCKR that contribute to smoking behaviors. In contrast, MTAG of smoking behaviors and alcohol consumption (AC) did not enhance discovery compared with single-trait GWAS for smoking behaviors. We conclude that using MTAG to augment the power of GWAS enables the identification of novel genetic variants for commonly co-occuring phenotypes, providing new insights into their pleiotropic effects on smoking behavior and AUD. Nature Publishing Group UK 2023-05-05 /pmc/articles/PMC10162964/ /pubmed/37147289 http://dx.doi.org/10.1038/s41398-023-02409-2 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Cheng, Youshu
Dao, Cecilia
Zhou, Hang
Li, Boyang
Kember, Rachel L.
Toikumo, Sylvanus
Zhao, Hongyu
Gelernter, Joel
Kranzler, Henry R.
Justice, Amy C.
Xu, Ke
Multi-trait genome-wide association analyses leveraging alcohol use disorder findings identify novel loci for smoking behaviors in the Million Veteran Program
title Multi-trait genome-wide association analyses leveraging alcohol use disorder findings identify novel loci for smoking behaviors in the Million Veteran Program
title_full Multi-trait genome-wide association analyses leveraging alcohol use disorder findings identify novel loci for smoking behaviors in the Million Veteran Program
title_fullStr Multi-trait genome-wide association analyses leveraging alcohol use disorder findings identify novel loci for smoking behaviors in the Million Veteran Program
title_full_unstemmed Multi-trait genome-wide association analyses leveraging alcohol use disorder findings identify novel loci for smoking behaviors in the Million Veteran Program
title_short Multi-trait genome-wide association analyses leveraging alcohol use disorder findings identify novel loci for smoking behaviors in the Million Veteran Program
title_sort multi-trait genome-wide association analyses leveraging alcohol use disorder findings identify novel loci for smoking behaviors in the million veteran program
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10162964/
https://www.ncbi.nlm.nih.gov/pubmed/37147289
http://dx.doi.org/10.1038/s41398-023-02409-2
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