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Identification and analysis of lipid metabolism-related genes in allergic rhinitis
BACKGROUND: Studies have shown that the lipid metabolism mediator leukotriene and prostaglandins are associated with the pathogenesis of allergic rhinitis (AR). The aim of this study was to identify key lipid metabolism-related genes (LMRGs) related to the diagnosis and treatment of AR. MATERIALS AN...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2023
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10362667/ https://www.ncbi.nlm.nih.gov/pubmed/37480069 http://dx.doi.org/10.1186/s12944-023-01825-z |
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author | Tao, Qilei Zhu, Yajing Wang, Tianyu Deng, Yue Liu, Huanhai Wu, Jian |
author_facet | Tao, Qilei Zhu, Yajing Wang, Tianyu Deng, Yue Liu, Huanhai Wu, Jian |
author_sort | Tao, Qilei |
collection | PubMed |
description | BACKGROUND: Studies have shown that the lipid metabolism mediator leukotriene and prostaglandins are associated with the pathogenesis of allergic rhinitis (AR). The aim of this study was to identify key lipid metabolism-related genes (LMRGs) related to the diagnosis and treatment of AR. MATERIALS AND METHODS: AR-related expression datasets (GSE75011, GSE46171) were downloaded through the Gene Expression Omnibus (GEO) database. First, weighted gene co-expression network analysis (WGCNA) was used to get AR-related genes (ARRGs). Next, between control and AR groups in GSE75011, differentially expressed genes (DEGs) were screened, and DEGs were intersected with LMRGs to obtain lipid metabolism-related differentially expressed genes (LMR DEGs). Protein-protein interaction (PPI) networks were constructed for these LMR DEGs. Hub genes were then identified through stress, radiality, closeness and edge percolated component (EPC) analysis and intersected with the ARRGs to obtain candidate genes. Biomarkers with diagnostic value were screened via receiver operating characteristic (ROC) curves. Differential immune cells screened between control and AR groups were then assessed for correlation with the diagnostic genes, and clinical correlation analysis and enrichment analysis were performed. Finally, real-time fluorescence quantitative polymerase chain reaction (RT-qPCR) was made on blood samples from control and AR patients to validate these identified diagnostic genes. RESULTS: 73 LMR DEGs were obtained, which were involved in biological processes such as metabolism of lipids and lipid biosynthetic processes. 66 ARRGs and 22 hub genes were intersected to obtain four candidate genes. Three diagnostic genes (LPCAT1, SGPP1, SMARCD3) with diagnostic value were screened according to the AUC > 0.7, with markedly variant between control and AR groups. In addition, two immune cells, regulatory T cells (Treg) and T follicular helper cells (TFH), were marked variations between control and AR groups, and SMARCD3 was significantly associated with TFH. Moreover, SMARCD3 was relevant to immune-related pathways, and correlated significantly with clinical characteristics (age and sex). Finally, RT-qPCR results indicated that changes in the expression of LPCAT1 and SMARCD3 between control and AR groups were consistent with the GSE75011 and GSE46171. CONCLUSION: LPCAT1, SGPP1 and SMARCD3 might be used as biomarkers for AR. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12944-023-01825-z. |
format | Online Article Text |
id | pubmed-10362667 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-103626672023-07-23 Identification and analysis of lipid metabolism-related genes in allergic rhinitis Tao, Qilei Zhu, Yajing Wang, Tianyu Deng, Yue Liu, Huanhai Wu, Jian Lipids Health Dis Research BACKGROUND: Studies have shown that the lipid metabolism mediator leukotriene and prostaglandins are associated with the pathogenesis of allergic rhinitis (AR). The aim of this study was to identify key lipid metabolism-related genes (LMRGs) related to the diagnosis and treatment of AR. MATERIALS AND METHODS: AR-related expression datasets (GSE75011, GSE46171) were downloaded through the Gene Expression Omnibus (GEO) database. First, weighted gene co-expression network analysis (WGCNA) was used to get AR-related genes (ARRGs). Next, between control and AR groups in GSE75011, differentially expressed genes (DEGs) were screened, and DEGs were intersected with LMRGs to obtain lipid metabolism-related differentially expressed genes (LMR DEGs). Protein-protein interaction (PPI) networks were constructed for these LMR DEGs. Hub genes were then identified through stress, radiality, closeness and edge percolated component (EPC) analysis and intersected with the ARRGs to obtain candidate genes. Biomarkers with diagnostic value were screened via receiver operating characteristic (ROC) curves. Differential immune cells screened between control and AR groups were then assessed for correlation with the diagnostic genes, and clinical correlation analysis and enrichment analysis were performed. Finally, real-time fluorescence quantitative polymerase chain reaction (RT-qPCR) was made on blood samples from control and AR patients to validate these identified diagnostic genes. RESULTS: 73 LMR DEGs were obtained, which were involved in biological processes such as metabolism of lipids and lipid biosynthetic processes. 66 ARRGs and 22 hub genes were intersected to obtain four candidate genes. Three diagnostic genes (LPCAT1, SGPP1, SMARCD3) with diagnostic value were screened according to the AUC > 0.7, with markedly variant between control and AR groups. In addition, two immune cells, regulatory T cells (Treg) and T follicular helper cells (TFH), were marked variations between control and AR groups, and SMARCD3 was significantly associated with TFH. Moreover, SMARCD3 was relevant to immune-related pathways, and correlated significantly with clinical characteristics (age and sex). Finally, RT-qPCR results indicated that changes in the expression of LPCAT1 and SMARCD3 between control and AR groups were consistent with the GSE75011 and GSE46171. CONCLUSION: LPCAT1, SGPP1 and SMARCD3 might be used as biomarkers for AR. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12944-023-01825-z. BioMed Central 2023-07-21 /pmc/articles/PMC10362667/ /pubmed/37480069 http://dx.doi.org/10.1186/s12944-023-01825-z Text en © The Author(s) 2023, corrected publication 2023 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/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Tao, Qilei Zhu, Yajing Wang, Tianyu Deng, Yue Liu, Huanhai Wu, Jian Identification and analysis of lipid metabolism-related genes in allergic rhinitis |
title | Identification and analysis of lipid metabolism-related genes in allergic rhinitis |
title_full | Identification and analysis of lipid metabolism-related genes in allergic rhinitis |
title_fullStr | Identification and analysis of lipid metabolism-related genes in allergic rhinitis |
title_full_unstemmed | Identification and analysis of lipid metabolism-related genes in allergic rhinitis |
title_short | Identification and analysis of lipid metabolism-related genes in allergic rhinitis |
title_sort | identification and analysis of lipid metabolism-related genes in allergic rhinitis |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10362667/ https://www.ncbi.nlm.nih.gov/pubmed/37480069 http://dx.doi.org/10.1186/s12944-023-01825-z |
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