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Development and verification of the nomogram for dilated cardiomyopathy gene diagnosis
Dilated cardiomyopathy (DCM) is a primary myocardial disease of unclear mechanism and poor prevention. The purpose of this study is to explore the potential molecular mechanisms and targets of DCM via bioinformatics methods and try to diagnose and prevent disease progression early. We screened 333 g...
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/PMC9135684/ https://www.ncbi.nlm.nih.gov/pubmed/35618744 http://dx.doi.org/10.1038/s41598-022-13135-y |
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author | Zhou, Li-qiang Liu, Chuan Zou, Yeqing Chen, Zhi-qing |
author_facet | Zhou, Li-qiang Liu, Chuan Zou, Yeqing Chen, Zhi-qing |
author_sort | Zhou, Li-qiang |
collection | PubMed |
description | Dilated cardiomyopathy (DCM) is a primary myocardial disease of unclear mechanism and poor prevention. The purpose of this study is to explore the potential molecular mechanisms and targets of DCM via bioinformatics methods and try to diagnose and prevent disease progression early. We screened 333 genes differentially expressed between DCM and normal heart samples from GSE141910, and further used Weighted correlation network analysis to identify 197 DCM-related genes. By identifying the key modules in the protein–protein interaction network and Least Absolute Shrinkage and Selection Operator regression analysis, seven hub DCM genes (CX3CR1, AGTR2, ADORA3, CXCL10, CXCL11, CXCL9, SAA1) were identified. Calculating the area under the receiver’s operating curve revealed that these 7 genes have an excellent ability to diagnose and predict DCM. Based on this, we built a logistic regression model and drew a nomogram. The calibration curve showed that the actual incidence is basically the same as the predicted incidence; while the C-index values of the nomogram and the four external validation data sets are 0.95, 0.90, 0.96, and 0.737, respectively, showing excellent diagnostic and predictive ability; while the decision curve indicated the wide applicability of the nomogram is helpful for clinicians to make accurate decisions. |
format | Online Article Text |
id | pubmed-9135684 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-91356842022-05-28 Development and verification of the nomogram for dilated cardiomyopathy gene diagnosis Zhou, Li-qiang Liu, Chuan Zou, Yeqing Chen, Zhi-qing Sci Rep Article Dilated cardiomyopathy (DCM) is a primary myocardial disease of unclear mechanism and poor prevention. The purpose of this study is to explore the potential molecular mechanisms and targets of DCM via bioinformatics methods and try to diagnose and prevent disease progression early. We screened 333 genes differentially expressed between DCM and normal heart samples from GSE141910, and further used Weighted correlation network analysis to identify 197 DCM-related genes. By identifying the key modules in the protein–protein interaction network and Least Absolute Shrinkage and Selection Operator regression analysis, seven hub DCM genes (CX3CR1, AGTR2, ADORA3, CXCL10, CXCL11, CXCL9, SAA1) were identified. Calculating the area under the receiver’s operating curve revealed that these 7 genes have an excellent ability to diagnose and predict DCM. Based on this, we built a logistic regression model and drew a nomogram. The calibration curve showed that the actual incidence is basically the same as the predicted incidence; while the C-index values of the nomogram and the four external validation data sets are 0.95, 0.90, 0.96, and 0.737, respectively, showing excellent diagnostic and predictive ability; while the decision curve indicated the wide applicability of the nomogram is helpful for clinicians to make accurate decisions. Nature Publishing Group UK 2022-05-26 /pmc/articles/PMC9135684/ /pubmed/35618744 http://dx.doi.org/10.1038/s41598-022-13135-y 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 Zhou, Li-qiang Liu, Chuan Zou, Yeqing Chen, Zhi-qing Development and verification of the nomogram for dilated cardiomyopathy gene diagnosis |
title | Development and verification of the nomogram for dilated cardiomyopathy gene diagnosis |
title_full | Development and verification of the nomogram for dilated cardiomyopathy gene diagnosis |
title_fullStr | Development and verification of the nomogram for dilated cardiomyopathy gene diagnosis |
title_full_unstemmed | Development and verification of the nomogram for dilated cardiomyopathy gene diagnosis |
title_short | Development and verification of the nomogram for dilated cardiomyopathy gene diagnosis |
title_sort | development and verification of the nomogram for dilated cardiomyopathy gene diagnosis |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9135684/ https://www.ncbi.nlm.nih.gov/pubmed/35618744 http://dx.doi.org/10.1038/s41598-022-13135-y |
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