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Aggregative trans-eQTL analysis detects trait-specific target gene sets in whole blood
Large scale genetic association studies have identified many trait-associated variants and understanding the role of these variants in the downstream regulation of gene-expressions can uncover important mediating biological mechanisms. Here we propose ARCHIE, a summary statistic based sparse canonic...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9325868/ https://www.ncbi.nlm.nih.gov/pubmed/35882830 http://dx.doi.org/10.1038/s41467-022-31845-9 |
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author | Dutta, Diptavo He, Yuan Saha, Ashis Arvanitis, Marios Battle, Alexis Chatterjee, Nilanjan |
author_facet | Dutta, Diptavo He, Yuan Saha, Ashis Arvanitis, Marios Battle, Alexis Chatterjee, Nilanjan |
author_sort | Dutta, Diptavo |
collection | PubMed |
description | Large scale genetic association studies have identified many trait-associated variants and understanding the role of these variants in the downstream regulation of gene-expressions can uncover important mediating biological mechanisms. Here we propose ARCHIE, a summary statistic based sparse canonical correlation analysis method to identify sets of gene-expressions trans-regulated by sets of known trait-related genetic variants. Simulation studies show that compared to standard methods, ARCHIE is better suited to identify “core”-like genes through which effects of many other genes may be mediated and can capture disease-specific patterns of genetic associations. By applying ARCHIE to publicly available summary statistics from the eQTLGen consortium, we identify gene sets which have significant evidence of trans-association with groups of known genetic variants across 29 complex traits. Around half (50.7%) of the selected genes do not have any strong trans-associations and are not detected by standard methods. We provide further evidence for causal basis of the target genes through a series of follow-up analyses. These results show ARCHIE is a powerful tool for identifying sets of genes whose trans-regulation may be related to specific complex traits. |
format | Online Article Text |
id | pubmed-9325868 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-93258682022-07-28 Aggregative trans-eQTL analysis detects trait-specific target gene sets in whole blood Dutta, Diptavo He, Yuan Saha, Ashis Arvanitis, Marios Battle, Alexis Chatterjee, Nilanjan Nat Commun Article Large scale genetic association studies have identified many trait-associated variants and understanding the role of these variants in the downstream regulation of gene-expressions can uncover important mediating biological mechanisms. Here we propose ARCHIE, a summary statistic based sparse canonical correlation analysis method to identify sets of gene-expressions trans-regulated by sets of known trait-related genetic variants. Simulation studies show that compared to standard methods, ARCHIE is better suited to identify “core”-like genes through which effects of many other genes may be mediated and can capture disease-specific patterns of genetic associations. By applying ARCHIE to publicly available summary statistics from the eQTLGen consortium, we identify gene sets which have significant evidence of trans-association with groups of known genetic variants across 29 complex traits. Around half (50.7%) of the selected genes do not have any strong trans-associations and are not detected by standard methods. We provide further evidence for causal basis of the target genes through a series of follow-up analyses. These results show ARCHIE is a powerful tool for identifying sets of genes whose trans-regulation may be related to specific complex traits. Nature Publishing Group UK 2022-07-26 /pmc/articles/PMC9325868/ /pubmed/35882830 http://dx.doi.org/10.1038/s41467-022-31845-9 Text en © The Author(s) 2022 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 Dutta, Diptavo He, Yuan Saha, Ashis Arvanitis, Marios Battle, Alexis Chatterjee, Nilanjan Aggregative trans-eQTL analysis detects trait-specific target gene sets in whole blood |
title | Aggregative trans-eQTL analysis detects trait-specific target gene sets in whole blood |
title_full | Aggregative trans-eQTL analysis detects trait-specific target gene sets in whole blood |
title_fullStr | Aggregative trans-eQTL analysis detects trait-specific target gene sets in whole blood |
title_full_unstemmed | Aggregative trans-eQTL analysis detects trait-specific target gene sets in whole blood |
title_short | Aggregative trans-eQTL analysis detects trait-specific target gene sets in whole blood |
title_sort | aggregative trans-eqtl analysis detects trait-specific target gene sets in whole blood |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9325868/ https://www.ncbi.nlm.nih.gov/pubmed/35882830 http://dx.doi.org/10.1038/s41467-022-31845-9 |
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