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Adipose tissue eQTL meta-analysis reveals the contribution of allelic heterogeneity to gene expression regulation and cardiometabolic traits

Complete characterization of the genetic effects on gene expression is needed to elucidate tissue biology and the etiology of complex traits. Here, we analyzed 2,344 subcutaneous adipose tissue samples and identified 34K conditionally distinct expression quantitative trait locus (eQTL) signals in 18...

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Autores principales: Brotman, Sarah M., El-Sayed Moustafa, Julia S., Guan, Li, Broadaway, K. Alaine, Wang, Dongmeng, Jackson, Anne U., Welch, Ryan, Currin, Kevin W., Tomlinson, Max, Vadlamudi, Swarooparani, Stringham, Heather M., Roberts, Amy L., Lakka, Timo A., Oravilahti, Anniina, Silva, Lilian Fernandes, Narisu, Narisu, Erdos, Michael R., Yan, Tingfen, Bonnycastle, Lori L., Raulerson, Chelsea K., Raza, Yasrab, Yan, Xinyu, Parker, Stephen C.J., Kuusisto, Johanna, Pajukanta, Päivi, Tuomilehto, Jaakko, Collins, Francis S., Boehnke, Michael, Love, Michael I., Koistinen, Heikki A., Laakso, Markku, Mohlke, Karen L., Small, Kerrin S., Scott, Laura J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cold Spring Harbor Laboratory 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10634839/
https://www.ncbi.nlm.nih.gov/pubmed/37961277
http://dx.doi.org/10.1101/2023.10.26.563798
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author Brotman, Sarah M.
El-Sayed Moustafa, Julia S.
Guan, Li
Broadaway, K. Alaine
Wang, Dongmeng
Jackson, Anne U.
Welch, Ryan
Currin, Kevin W.
Tomlinson, Max
Vadlamudi, Swarooparani
Stringham, Heather M.
Roberts, Amy L.
Lakka, Timo A.
Oravilahti, Anniina
Silva, Lilian Fernandes
Narisu, Narisu
Erdos, Michael R.
Yan, Tingfen
Bonnycastle, Lori L.
Raulerson, Chelsea K.
Raza, Yasrab
Yan, Xinyu
Parker, Stephen C.J.
Kuusisto, Johanna
Pajukanta, Päivi
Tuomilehto, Jaakko
Collins, Francis S.
Boehnke, Michael
Love, Michael I.
Koistinen, Heikki A.
Laakso, Markku
Mohlke, Karen L.
Small, Kerrin S.
Scott, Laura J.
author_facet Brotman, Sarah M.
El-Sayed Moustafa, Julia S.
Guan, Li
Broadaway, K. Alaine
Wang, Dongmeng
Jackson, Anne U.
Welch, Ryan
Currin, Kevin W.
Tomlinson, Max
Vadlamudi, Swarooparani
Stringham, Heather M.
Roberts, Amy L.
Lakka, Timo A.
Oravilahti, Anniina
Silva, Lilian Fernandes
Narisu, Narisu
Erdos, Michael R.
Yan, Tingfen
Bonnycastle, Lori L.
Raulerson, Chelsea K.
Raza, Yasrab
Yan, Xinyu
Parker, Stephen C.J.
Kuusisto, Johanna
Pajukanta, Päivi
Tuomilehto, Jaakko
Collins, Francis S.
Boehnke, Michael
Love, Michael I.
Koistinen, Heikki A.
Laakso, Markku
Mohlke, Karen L.
Small, Kerrin S.
Scott, Laura J.
author_sort Brotman, Sarah M.
collection PubMed
description Complete characterization of the genetic effects on gene expression is needed to elucidate tissue biology and the etiology of complex traits. Here, we analyzed 2,344 subcutaneous adipose tissue samples and identified 34K conditionally distinct expression quantitative trait locus (eQTL) signals in 18K genes. Over half of eQTL genes exhibited at least two eQTL signals. Compared to primary signals, non-primary signals had lower effect sizes, lower minor allele frequencies, and less promoter enrichment; they corresponded to genes with higher heritability and higher tolerance for loss of function. Colocalization of eQTL with conditionally distinct genome-wide association study signals for 28 cardiometabolic traits identified 3,605 eQTL signals for 1,861 genes. Inclusion of non-primary eQTL signals increased colocalized signals by 46%. Among 30 genes with ≥2 pairs of colocalized signals, 21 showed a mediating gene dosage effect on the trait. Thus, expanded eQTL identification reveals more mechanisms underlying complex traits and improves understanding of the complexity of gene expression regulation.
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spelling pubmed-106348392023-11-13 Adipose tissue eQTL meta-analysis reveals the contribution of allelic heterogeneity to gene expression regulation and cardiometabolic traits Brotman, Sarah M. El-Sayed Moustafa, Julia S. Guan, Li Broadaway, K. Alaine Wang, Dongmeng Jackson, Anne U. Welch, Ryan Currin, Kevin W. Tomlinson, Max Vadlamudi, Swarooparani Stringham, Heather M. Roberts, Amy L. Lakka, Timo A. Oravilahti, Anniina Silva, Lilian Fernandes Narisu, Narisu Erdos, Michael R. Yan, Tingfen Bonnycastle, Lori L. Raulerson, Chelsea K. Raza, Yasrab Yan, Xinyu Parker, Stephen C.J. Kuusisto, Johanna Pajukanta, Päivi Tuomilehto, Jaakko Collins, Francis S. Boehnke, Michael Love, Michael I. Koistinen, Heikki A. Laakso, Markku Mohlke, Karen L. Small, Kerrin S. Scott, Laura J. bioRxiv Article Complete characterization of the genetic effects on gene expression is needed to elucidate tissue biology and the etiology of complex traits. Here, we analyzed 2,344 subcutaneous adipose tissue samples and identified 34K conditionally distinct expression quantitative trait locus (eQTL) signals in 18K genes. Over half of eQTL genes exhibited at least two eQTL signals. Compared to primary signals, non-primary signals had lower effect sizes, lower minor allele frequencies, and less promoter enrichment; they corresponded to genes with higher heritability and higher tolerance for loss of function. Colocalization of eQTL with conditionally distinct genome-wide association study signals for 28 cardiometabolic traits identified 3,605 eQTL signals for 1,861 genes. Inclusion of non-primary eQTL signals increased colocalized signals by 46%. Among 30 genes with ≥2 pairs of colocalized signals, 21 showed a mediating gene dosage effect on the trait. Thus, expanded eQTL identification reveals more mechanisms underlying complex traits and improves understanding of the complexity of gene expression regulation. Cold Spring Harbor Laboratory 2023-10-27 /pmc/articles/PMC10634839/ /pubmed/37961277 http://dx.doi.org/10.1101/2023.10.26.563798 Text en https://creativecommons.org/licenses/by/4.0/This work is licensed under a Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/) , which allows reusers to distribute, remix, adapt, and build upon the material in any medium or format, so long as attribution is given to the creator. The license allows for commercial use.
spellingShingle Article
Brotman, Sarah M.
El-Sayed Moustafa, Julia S.
Guan, Li
Broadaway, K. Alaine
Wang, Dongmeng
Jackson, Anne U.
Welch, Ryan
Currin, Kevin W.
Tomlinson, Max
Vadlamudi, Swarooparani
Stringham, Heather M.
Roberts, Amy L.
Lakka, Timo A.
Oravilahti, Anniina
Silva, Lilian Fernandes
Narisu, Narisu
Erdos, Michael R.
Yan, Tingfen
Bonnycastle, Lori L.
Raulerson, Chelsea K.
Raza, Yasrab
Yan, Xinyu
Parker, Stephen C.J.
Kuusisto, Johanna
Pajukanta, Päivi
Tuomilehto, Jaakko
Collins, Francis S.
Boehnke, Michael
Love, Michael I.
Koistinen, Heikki A.
Laakso, Markku
Mohlke, Karen L.
Small, Kerrin S.
Scott, Laura J.
Adipose tissue eQTL meta-analysis reveals the contribution of allelic heterogeneity to gene expression regulation and cardiometabolic traits
title Adipose tissue eQTL meta-analysis reveals the contribution of allelic heterogeneity to gene expression regulation and cardiometabolic traits
title_full Adipose tissue eQTL meta-analysis reveals the contribution of allelic heterogeneity to gene expression regulation and cardiometabolic traits
title_fullStr Adipose tissue eQTL meta-analysis reveals the contribution of allelic heterogeneity to gene expression regulation and cardiometabolic traits
title_full_unstemmed Adipose tissue eQTL meta-analysis reveals the contribution of allelic heterogeneity to gene expression regulation and cardiometabolic traits
title_short Adipose tissue eQTL meta-analysis reveals the contribution of allelic heterogeneity to gene expression regulation and cardiometabolic traits
title_sort adipose tissue eqtl meta-analysis reveals the contribution of allelic heterogeneity to gene expression regulation and cardiometabolic traits
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10634839/
https://www.ncbi.nlm.nih.gov/pubmed/37961277
http://dx.doi.org/10.1101/2023.10.26.563798
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