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Identification of genes associated with sudden cardiac death: a network- and pathway-based approach
BACKGROUND: Sudden cardiac death (SCD) accounts for a large proportion of the total deaths across different age groups. Although numerous candidate genes related to SCD have been identified by genetic association studies and genome wide association studies (GWAS), the molecular mechanisms underlying...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
AME Publishing Company
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8264674/ https://www.ncbi.nlm.nih.gov/pubmed/34277054 http://dx.doi.org/10.21037/jtd-21-361 |
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author | Wei, Jinhuan Ni, Xuejun Dai, Yanfei Chen, Xi Ding, Sujun Bao, Jingyin Xing, Lingyan |
author_facet | Wei, Jinhuan Ni, Xuejun Dai, Yanfei Chen, Xi Ding, Sujun Bao, Jingyin Xing, Lingyan |
author_sort | Wei, Jinhuan |
collection | PubMed |
description | BACKGROUND: Sudden cardiac death (SCD) accounts for a large proportion of the total deaths across different age groups. Although numerous candidate genes related to SCD have been identified by genetic association studies and genome wide association studies (GWAS), the molecular mechanisms underlying SCD are still unclear, and the biological functions and interactions of these genes remain obscure. To clarify this issue, we performed a comprehensive and systematic analysis of SCD-related genes by a network and pathway-based approach. METHODS: By screening the publications deposited in the PubMed and Gene-Cloud Biotechnology Information (GCBI) databases, we collected the genes genetically associated with SCD, which were referred to as the SCD-related gene set (SCDgset). To analyze the biological processes and biochemical pathways of the SCD-related genes, functional analysis was performed. To explore interlinks and interactions of the enriched pathways, pathway crosstalk analysis was implemented. To construct SCD-specific molecular networks, Markov cluster algorithm and Steiner minimal tree algorithm were employed. RESULTS: We collected 257 genes that were reported to be associated with SCD and summarized them in the SCDgset. Most of the biological processes and biochemical pathways were related to heart diseases, while some of the biological functions may be noncardiac causes of SCD. The enriched pathways could be roughly grouped into two modules. One module was related to calcium signaling pathway and the other was related to MAPK pathway. Moreover, two different SCD-specific molecular networks were inferred, and 23 novel genes potentially associated with SCD were also identified. CONCLUSIONS: In summary, by means of a network and pathway-based methodology, we explored the pathogenetic mechanism underlying SCD. Our results provide valuable information in understanding the pathogenesis of SCD and include novel biomarkers for diagnosing potential patients with heart diseases; these may help in reducing the corresponding risks and even aid in preventing SCD. |
format | Online Article Text |
id | pubmed-8264674 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | AME Publishing Company |
record_format | MEDLINE/PubMed |
spelling | pubmed-82646742021-07-16 Identification of genes associated with sudden cardiac death: a network- and pathway-based approach Wei, Jinhuan Ni, Xuejun Dai, Yanfei Chen, Xi Ding, Sujun Bao, Jingyin Xing, Lingyan J Thorac Dis Original Article BACKGROUND: Sudden cardiac death (SCD) accounts for a large proportion of the total deaths across different age groups. Although numerous candidate genes related to SCD have been identified by genetic association studies and genome wide association studies (GWAS), the molecular mechanisms underlying SCD are still unclear, and the biological functions and interactions of these genes remain obscure. To clarify this issue, we performed a comprehensive and systematic analysis of SCD-related genes by a network and pathway-based approach. METHODS: By screening the publications deposited in the PubMed and Gene-Cloud Biotechnology Information (GCBI) databases, we collected the genes genetically associated with SCD, which were referred to as the SCD-related gene set (SCDgset). To analyze the biological processes and biochemical pathways of the SCD-related genes, functional analysis was performed. To explore interlinks and interactions of the enriched pathways, pathway crosstalk analysis was implemented. To construct SCD-specific molecular networks, Markov cluster algorithm and Steiner minimal tree algorithm were employed. RESULTS: We collected 257 genes that were reported to be associated with SCD and summarized them in the SCDgset. Most of the biological processes and biochemical pathways were related to heart diseases, while some of the biological functions may be noncardiac causes of SCD. The enriched pathways could be roughly grouped into two modules. One module was related to calcium signaling pathway and the other was related to MAPK pathway. Moreover, two different SCD-specific molecular networks were inferred, and 23 novel genes potentially associated with SCD were also identified. CONCLUSIONS: In summary, by means of a network and pathway-based methodology, we explored the pathogenetic mechanism underlying SCD. Our results provide valuable information in understanding the pathogenesis of SCD and include novel biomarkers for diagnosing potential patients with heart diseases; these may help in reducing the corresponding risks and even aid in preventing SCD. AME Publishing Company 2021-06 /pmc/articles/PMC8264674/ /pubmed/34277054 http://dx.doi.org/10.21037/jtd-21-361 Text en 2021 Journal of Thoracic Disease. All rights reserved. https://creativecommons.org/licenses/by-nc-nd/4.0/Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0 (https://creativecommons.org/licenses/by-nc-nd/4.0/) . |
spellingShingle | Original Article Wei, Jinhuan Ni, Xuejun Dai, Yanfei Chen, Xi Ding, Sujun Bao, Jingyin Xing, Lingyan Identification of genes associated with sudden cardiac death: a network- and pathway-based approach |
title | Identification of genes associated with sudden cardiac death: a network- and pathway-based approach |
title_full | Identification of genes associated with sudden cardiac death: a network- and pathway-based approach |
title_fullStr | Identification of genes associated with sudden cardiac death: a network- and pathway-based approach |
title_full_unstemmed | Identification of genes associated with sudden cardiac death: a network- and pathway-based approach |
title_short | Identification of genes associated with sudden cardiac death: a network- and pathway-based approach |
title_sort | identification of genes associated with sudden cardiac death: a network- and pathway-based approach |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8264674/ https://www.ncbi.nlm.nih.gov/pubmed/34277054 http://dx.doi.org/10.21037/jtd-21-361 |
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