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

doi:10.3892/mmr.2015.3263

Identification of the differentially expressed genes associated with familial combined hyperlipidemia using bioinformatics analysis

Authors:
- Xiaoli Luo
- Changqing Yu
- Chunjiang Fu
- Weibin Shi
- Xukai Wang
- Chunyu Zeng
- Hongyong Wang
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Affiliations: Department of Cardiology, Daping Hospital, The Third Military Medical University, Chongqing Institute of Cardiology, Chongqing 400042, P.R. China
Published online on: January 27, 2015 https://doi.org/10.3892/mmr.2015.3263
Pages: 4032-4038
Copyright: © Luo et al. This is an open access article distributed under the terms of Creative Commons Attribution License [CC BY_NC 3.0].

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Abstract

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.

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