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Multiple Feature Selection Strategies Identified Novel Cardiac Gene Expression Signature for Heart Failure
Heart failure (HF) is a serious condition in which the support of blood pumped by the heart is insufficient to meet the demands of body at a normal cardiac filling pressure. Approximately 26 million patients worldwide are suffering from heart failure and about 17–45% of patients with heart failure d...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2020
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7693561/ https://www.ncbi.nlm.nih.gov/pubmed/33304275 http://dx.doi.org/10.3389/fphys.2020.604241 |
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author | Li, Dan Lin, Hong Li, Luyifei |
author_facet | Li, Dan Lin, Hong Li, Luyifei |
author_sort | Li, Dan |
collection | PubMed |
description | Heart failure (HF) is a serious condition in which the support of blood pumped by the heart is insufficient to meet the demands of body at a normal cardiac filling pressure. Approximately 26 million patients worldwide are suffering from heart failure and about 17–45% of patients with heart failure die within 1-year, and the majority die within 5-years admitted to a hospital. The molecular mechanisms underlying the progression of heart failure have been poorly studied. We compared the gene expression profiles between patients with heart failure (n = 177) and without heart failure (n = 136) using multiple feature selection strategies and identified 38 HF signature genes. The support vector machine (SVM) classifier based on these 38 genes evaluated with leave-one-out cross validation (LOOCV) achieved great performance with sensitivity of 0.983 and specificity of 0.963. The network analysis suggested that the hub gene SMOC2 may play important roles in HF. Other genes, such as FCN3, HMGN2, and SERPINA3, also showed great promises. Our results can facilitate the early detection of heart failure and can reveal its molecular mechanisms. |
format | Online Article Text |
id | pubmed-7693561 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-76935612020-12-09 Multiple Feature Selection Strategies Identified Novel Cardiac Gene Expression Signature for Heart Failure Li, Dan Lin, Hong Li, Luyifei Front Physiol Physiology Heart failure (HF) is a serious condition in which the support of blood pumped by the heart is insufficient to meet the demands of body at a normal cardiac filling pressure. Approximately 26 million patients worldwide are suffering from heart failure and about 17–45% of patients with heart failure die within 1-year, and the majority die within 5-years admitted to a hospital. The molecular mechanisms underlying the progression of heart failure have been poorly studied. We compared the gene expression profiles between patients with heart failure (n = 177) and without heart failure (n = 136) using multiple feature selection strategies and identified 38 HF signature genes. The support vector machine (SVM) classifier based on these 38 genes evaluated with leave-one-out cross validation (LOOCV) achieved great performance with sensitivity of 0.983 and specificity of 0.963. The network analysis suggested that the hub gene SMOC2 may play important roles in HF. Other genes, such as FCN3, HMGN2, and SERPINA3, also showed great promises. Our results can facilitate the early detection of heart failure and can reveal its molecular mechanisms. Frontiers Media S.A. 2020-11-11 /pmc/articles/PMC7693561/ /pubmed/33304275 http://dx.doi.org/10.3389/fphys.2020.604241 Text en Copyright © 2020 Li, Lin and Li. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Physiology Li, Dan Lin, Hong Li, Luyifei Multiple Feature Selection Strategies Identified Novel Cardiac Gene Expression Signature for Heart Failure |
title | Multiple Feature Selection Strategies Identified Novel Cardiac Gene Expression Signature for Heart Failure |
title_full | Multiple Feature Selection Strategies Identified Novel Cardiac Gene Expression Signature for Heart Failure |
title_fullStr | Multiple Feature Selection Strategies Identified Novel Cardiac Gene Expression Signature for Heart Failure |
title_full_unstemmed | Multiple Feature Selection Strategies Identified Novel Cardiac Gene Expression Signature for Heart Failure |
title_short | Multiple Feature Selection Strategies Identified Novel Cardiac Gene Expression Signature for Heart Failure |
title_sort | multiple feature selection strategies identified novel cardiac gene expression signature for heart failure |
topic | Physiology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7693561/ https://www.ncbi.nlm.nih.gov/pubmed/33304275 http://dx.doi.org/10.3389/fphys.2020.604241 |
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