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Identification of the differentially expressed genes associated with familial combined hyperlipidemia using bioinformatics analysis
The aim of the present study was to screen the differentially expressed genes (DEGs) associated with familial combined hyperlipidemia (FCHL) and examine the changing patterns. The transcription profile of GSE18965 was obtained from the NCBI Gene Expression Omnibus database, including 12 FCHL samples...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
D.A. Spandidos
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4394960/ https://www.ncbi.nlm.nih.gov/pubmed/25625967 http://dx.doi.org/10.3892/mmr.2015.3263 |
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author | LUO, XIAOLI YU, CHANGQING FU, CHUNJIANG SHI, WEIBIN WANG, XUKAI ZENG, CHUNYU WANG, HONGYONG |
author_facet | LUO, XIAOLI YU, CHANGQING FU, CHUNJIANG SHI, WEIBIN WANG, XUKAI ZENG, CHUNYU WANG, HONGYONG |
author_sort | LUO, XIAOLI |
collection | PubMed |
description | The aim of the present study was to screen the differentially expressed genes (DEGs) associated with familial combined hyperlipidemia (FCHL) and examine the changing patterns. The transcription profile of GSE18965 was obtained from the NCBI Gene Expression Omnibus database, including 12 FCHL samples and 12 control specimens. The DEGs were identified using a linear models for microarray data package in the R programming language. Gene Ontology (GO) function and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis was also performed. Protein-protein interaction (PPI) networks of the DEGs were constructed using the EnrichNet online tool. In addition, cluster analysis of the genes in networks was performed using ClusterONE. A total of 879 DEGs were screened, including 394 upregulated and 485 downregulated genes. Enrichment analysis identified four important KEGG pathways associated with FCHL: One carbon pool by folate, α-linolenic acid metabolism, asthma and the glycosphingolipid biosynthesis-globo series. GO annotation identified 12 enriched biological processes, including one associated with hematopoiesis and four associated with bone cell differentiation. This identification was in accordance with clinical data and experiments into hyperlipidemia and bone lesions. Based on PPI networks, these DEGs had a close association with immune responses, hormone responses and cytokine-cytokine receptors. In conclusion, these DEGs may be used as specific therapeutic molecular targets in the treatment of FCHL. The present findings may provide the basis for understanding the pathogenesis of FCHL in future studies. However, further experiments are required to confirm these results. |
format | Online Article Text |
id | pubmed-4394960 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | D.A. Spandidos |
record_format | MEDLINE/PubMed |
spelling | pubmed-43949602015-04-17 Identification of the differentially expressed genes associated with familial combined hyperlipidemia using bioinformatics analysis LUO, XIAOLI YU, CHANGQING FU, CHUNJIANG SHI, WEIBIN WANG, XUKAI ZENG, CHUNYU WANG, HONGYONG Mol Med Rep Articles The aim of the present study was to screen the differentially expressed genes (DEGs) associated with familial combined hyperlipidemia (FCHL) and examine the changing patterns. The transcription profile of GSE18965 was obtained from the NCBI Gene Expression Omnibus database, including 12 FCHL samples and 12 control specimens. The DEGs were identified using a linear models for microarray data package in the R programming language. Gene Ontology (GO) function and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis was also performed. Protein-protein interaction (PPI) networks of the DEGs were constructed using the EnrichNet online tool. In addition, cluster analysis of the genes in networks was performed using ClusterONE. A total of 879 DEGs were screened, including 394 upregulated and 485 downregulated genes. Enrichment analysis identified four important KEGG pathways associated with FCHL: One carbon pool by folate, α-linolenic acid metabolism, asthma and the glycosphingolipid biosynthesis-globo series. GO annotation identified 12 enriched biological processes, including one associated with hematopoiesis and four associated with bone cell differentiation. This identification was in accordance with clinical data and experiments into hyperlipidemia and bone lesions. Based on PPI networks, these DEGs had a close association with immune responses, hormone responses and cytokine-cytokine receptors. In conclusion, these DEGs may be used as specific therapeutic molecular targets in the treatment of FCHL. The present findings may provide the basis for understanding the pathogenesis of FCHL in future studies. However, further experiments are required to confirm these results. D.A. Spandidos 2015-06 2015-01-27 /pmc/articles/PMC4394960/ /pubmed/25625967 http://dx.doi.org/10.3892/mmr.2015.3263 Text en Copyright © 2015, Spandidos Publications http://creativecommons.org/licenses/by/3.0 This is an open-access article licensed under a Creative Commons Attribution-NonCommercial 3.0 Unported License. The article may be redistributed, reproduced, and reused for non-commercial purposes, provided the original source is properly cited. |
spellingShingle | Articles LUO, XIAOLI YU, CHANGQING FU, CHUNJIANG SHI, WEIBIN WANG, XUKAI ZENG, CHUNYU WANG, HONGYONG Identification of the differentially expressed genes associated with familial combined hyperlipidemia using bioinformatics analysis |
title | Identification of the differentially expressed genes associated with familial combined hyperlipidemia using bioinformatics analysis |
title_full | Identification of the differentially expressed genes associated with familial combined hyperlipidemia using bioinformatics analysis |
title_fullStr | Identification of the differentially expressed genes associated with familial combined hyperlipidemia using bioinformatics analysis |
title_full_unstemmed | Identification of the differentially expressed genes associated with familial combined hyperlipidemia using bioinformatics analysis |
title_short | Identification of the differentially expressed genes associated with familial combined hyperlipidemia using bioinformatics analysis |
title_sort | identification of the differentially expressed genes associated with familial combined hyperlipidemia using bioinformatics analysis |
topic | Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4394960/ https://www.ncbi.nlm.nih.gov/pubmed/25625967 http://dx.doi.org/10.3892/mmr.2015.3263 |
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