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Integrative network analysis interweaves the missing links in cardiomyopathy diseasome
Cardiomyopathies are progressive disease conditions that give rise to an abnormal heart phenotype and are a leading cause of heart failures in the general population. These are complex diseases that show co-morbidity with other diseases. The molecular interaction network in the localised disease nei...
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/PMC9668833/ https://www.ncbi.nlm.nih.gov/pubmed/36385157 http://dx.doi.org/10.1038/s41598-022-24246-x |
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author | Chauhan, Pankaj Kumar Sowdhamini, Ramanathan |
author_facet | Chauhan, Pankaj Kumar Sowdhamini, Ramanathan |
author_sort | Chauhan, Pankaj Kumar |
collection | PubMed |
description | Cardiomyopathies are progressive disease conditions that give rise to an abnormal heart phenotype and are a leading cause of heart failures in the general population. These are complex diseases that show co-morbidity with other diseases. The molecular interaction network in the localised disease neighbourhood is an important step toward deciphering molecular mechanisms underlying these complex conditions. In this pursuit, we employed network medicine techniques to systematically investigate cardiomyopathy’s genetic interplay with other diseases and uncover the molecular players underlying these associations. We predicted a set of candidate genes in cardiomyopathy by exploring the DIAMOnD algorithm on the human interactome. We next revealed how these candidate genes form association across different diseases and highlighted the predominant association with brain, cancer and metabolic diseases. Through integrative systems analysis of molecular pathways, heart-specific mouse knockout data and disease tissue-specific transcriptomic data, we screened and ascertained prominent candidates that show abnormal heart phenotype, including NOS3, MMP2 and SIRT1. Our computational analysis broadens the understanding of the genetic associations of cardiomyopathies with other diseases and holds great potential in cardiomyopathy research. |
format | Online Article Text |
id | pubmed-9668833 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-96688332022-11-18 Integrative network analysis interweaves the missing links in cardiomyopathy diseasome Chauhan, Pankaj Kumar Sowdhamini, Ramanathan Sci Rep Article Cardiomyopathies are progressive disease conditions that give rise to an abnormal heart phenotype and are a leading cause of heart failures in the general population. These are complex diseases that show co-morbidity with other diseases. The molecular interaction network in the localised disease neighbourhood is an important step toward deciphering molecular mechanisms underlying these complex conditions. In this pursuit, we employed network medicine techniques to systematically investigate cardiomyopathy’s genetic interplay with other diseases and uncover the molecular players underlying these associations. We predicted a set of candidate genes in cardiomyopathy by exploring the DIAMOnD algorithm on the human interactome. We next revealed how these candidate genes form association across different diseases and highlighted the predominant association with brain, cancer and metabolic diseases. Through integrative systems analysis of molecular pathways, heart-specific mouse knockout data and disease tissue-specific transcriptomic data, we screened and ascertained prominent candidates that show abnormal heart phenotype, including NOS3, MMP2 and SIRT1. Our computational analysis broadens the understanding of the genetic associations of cardiomyopathies with other diseases and holds great potential in cardiomyopathy research. Nature Publishing Group UK 2022-11-16 /pmc/articles/PMC9668833/ /pubmed/36385157 http://dx.doi.org/10.1038/s41598-022-24246-x 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Chauhan, Pankaj Kumar Sowdhamini, Ramanathan Integrative network analysis interweaves the missing links in cardiomyopathy diseasome |
title | Integrative network analysis interweaves the missing links in cardiomyopathy diseasome |
title_full | Integrative network analysis interweaves the missing links in cardiomyopathy diseasome |
title_fullStr | Integrative network analysis interweaves the missing links in cardiomyopathy diseasome |
title_full_unstemmed | Integrative network analysis interweaves the missing links in cardiomyopathy diseasome |
title_short | Integrative network analysis interweaves the missing links in cardiomyopathy diseasome |
title_sort | integrative network analysis interweaves the missing links in cardiomyopathy diseasome |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9668833/ https://www.ncbi.nlm.nih.gov/pubmed/36385157 http://dx.doi.org/10.1038/s41598-022-24246-x |
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