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Genetic overlap for ten cardiovascular diseases: A comprehensive gene-centric pleiotropic association analysis and Mendelian randomization study
Recent studies suggest that pleiotropic effects may explain the genetic architecture of cardiovascular diseases (CVDs). We conducted a comprehensive gene-centric pleiotropic association analysis for ten CVDs using genome-wide association study (GWAS) summary statistics to identify pleiotropic genes...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10613921/ https://www.ncbi.nlm.nih.gov/pubmed/37908310 http://dx.doi.org/10.1016/j.isci.2023.108150 |
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author | Liu, Zeye Xu, Jing Tan, Jiangshan Li, Xiaofei Zhang, Fengwen Ouyang, Wenbin Wang, Shouzheng Huang, Yuan Li, Shoujun Pan, Xiangbin |
author_facet | Liu, Zeye Xu, Jing Tan, Jiangshan Li, Xiaofei Zhang, Fengwen Ouyang, Wenbin Wang, Shouzheng Huang, Yuan Li, Shoujun Pan, Xiangbin |
author_sort | Liu, Zeye |
collection | PubMed |
description | Recent studies suggest that pleiotropic effects may explain the genetic architecture of cardiovascular diseases (CVDs). We conducted a comprehensive gene-centric pleiotropic association analysis for ten CVDs using genome-wide association study (GWAS) summary statistics to identify pleiotropic genes and pathways that may underlie multiple CVDs. We found shared genetic mechanisms underlying the pathophysiology of CVDs, with over two-thirds of the diseases exhibiting common genes and single-nucleotide polymorphisms (SNPs). Significant positive genetic correlations were observed in more than half of paired CVDs. Additionally, we investigated the pleiotropic genes shared between different CVDs, as well as their functional pathways and distribution in different tissues. Moreover, six hub genes, including ALDH2, XPO1, HSPA1L, ESR2, WDR12, and RAB1A, as well as 26 targeted potential drugs, were identified. Our study provides further evidence for the pleiotropic effects of genetic variants on CVDs and highlights the importance of considering pleiotropy in genetic association studies. |
format | Online Article Text |
id | pubmed-10613921 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-106139212023-10-31 Genetic overlap for ten cardiovascular diseases: A comprehensive gene-centric pleiotropic association analysis and Mendelian randomization study Liu, Zeye Xu, Jing Tan, Jiangshan Li, Xiaofei Zhang, Fengwen Ouyang, Wenbin Wang, Shouzheng Huang, Yuan Li, Shoujun Pan, Xiangbin iScience Article Recent studies suggest that pleiotropic effects may explain the genetic architecture of cardiovascular diseases (CVDs). We conducted a comprehensive gene-centric pleiotropic association analysis for ten CVDs using genome-wide association study (GWAS) summary statistics to identify pleiotropic genes and pathways that may underlie multiple CVDs. We found shared genetic mechanisms underlying the pathophysiology of CVDs, with over two-thirds of the diseases exhibiting common genes and single-nucleotide polymorphisms (SNPs). Significant positive genetic correlations were observed in more than half of paired CVDs. Additionally, we investigated the pleiotropic genes shared between different CVDs, as well as their functional pathways and distribution in different tissues. Moreover, six hub genes, including ALDH2, XPO1, HSPA1L, ESR2, WDR12, and RAB1A, as well as 26 targeted potential drugs, were identified. Our study provides further evidence for the pleiotropic effects of genetic variants on CVDs and highlights the importance of considering pleiotropy in genetic association studies. Elsevier 2023-10-06 /pmc/articles/PMC10613921/ /pubmed/37908310 http://dx.doi.org/10.1016/j.isci.2023.108150 Text en © 2023 The Author(s) https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Article Liu, Zeye Xu, Jing Tan, Jiangshan Li, Xiaofei Zhang, Fengwen Ouyang, Wenbin Wang, Shouzheng Huang, Yuan Li, Shoujun Pan, Xiangbin Genetic overlap for ten cardiovascular diseases: A comprehensive gene-centric pleiotropic association analysis and Mendelian randomization study |
title | Genetic overlap for ten cardiovascular diseases: A comprehensive gene-centric pleiotropic association analysis and Mendelian randomization study |
title_full | Genetic overlap for ten cardiovascular diseases: A comprehensive gene-centric pleiotropic association analysis and Mendelian randomization study |
title_fullStr | Genetic overlap for ten cardiovascular diseases: A comprehensive gene-centric pleiotropic association analysis and Mendelian randomization study |
title_full_unstemmed | Genetic overlap for ten cardiovascular diseases: A comprehensive gene-centric pleiotropic association analysis and Mendelian randomization study |
title_short | Genetic overlap for ten cardiovascular diseases: A comprehensive gene-centric pleiotropic association analysis and Mendelian randomization study |
title_sort | genetic overlap for ten cardiovascular diseases: a comprehensive gene-centric pleiotropic association analysis and mendelian randomization study |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10613921/ https://www.ncbi.nlm.nih.gov/pubmed/37908310 http://dx.doi.org/10.1016/j.isci.2023.108150 |
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