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Bioinformatics and functional experiments reveal that MRC2 inhibits atrial fibrillation via the PPAR signaling pathway

BACKGROUND: Atrial fibrillation (AF) is a prevalent cardiac arrhythmia that requires improved clinical markers to increase diagnostic accuracy and provide insight into its pathogenesis. Although some biomarkers are available, new ones need to be discovered to better capture the complex physiology of...

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Autores principales: Zheng, Pengxiang, Zhang, Wenjia, Wang, Jiahong, Gong, Qunlin, Xu, Nan, Chen, Nannan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AME Publishing Company 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10636429/
https://www.ncbi.nlm.nih.gov/pubmed/37969297
http://dx.doi.org/10.21037/jtd-23-1235
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author Zheng, Pengxiang
Zhang, Wenjia
Wang, Jiahong
Gong, Qunlin
Xu, Nan
Chen, Nannan
author_facet Zheng, Pengxiang
Zhang, Wenjia
Wang, Jiahong
Gong, Qunlin
Xu, Nan
Chen, Nannan
author_sort Zheng, Pengxiang
collection PubMed
description BACKGROUND: Atrial fibrillation (AF) is a prevalent cardiac arrhythmia that requires improved clinical markers to increase diagnostic accuracy and provide insight into its pathogenesis. Although some biomarkers are available, new ones need to be discovered to better capture the complex physiology of AF. However, their limitations are still not fully addressed. Bioinformatics and functional studies can help find new clinical markers and improve the understanding of AF, meeting the need for early diagnosis and individualized treatment. METHODS: To identify AF-related differentially expressed genes (DEGs), We applied the messenger RNA (mRNA) expression profile retrieved in Series Matrix File format from the GSE143924 microarray dataset obtained from the Gene Expression Omnibus (GEO) database, and then used weighted gene co-expression network analysis (WGCNA) to identify the overlapping genes. These genes were analyzed by enrichment analysis, expression analysis and others to obtain the hub gene. Additionally, the potential signaling pathway of hub gene in AF was explored and verified by functional experiments, like quantitative real-time polymerase chain reaction (qRT-PCR), cell counting kit-8 (CCK-8), flow cytometry, and Western blotting (WB) assay. RESULTS: From the GSE143924 data (410 DEGs) and tan module (57 genes), 10 overlapping genes were identified. A central down-regulated gene in AF, MRC2, was identified through bioinformatics analysis. based on these results, it was hypothesized that the PPAR signaling pathway is related to the mechanism of action of MRC2 in AF. Moreover, over-MRC2 markedly reduced the growth speed of angiotensin II (Ang II)-induced human cardiac fibroblasts (HCFs) and increased apoptosis. Conversely, knockdown of MRC2 promoted HCFs cell proliferation number. Additionally, MRC2 over-expression increased the protein expression level of PPARα, PPARγ, CPT-1, and SIRT3 in Ang II-induced HCFs. CONCLUSIONS: While meeting the need for new biomarkers in the diagnosis and prognosis of AF, this study reveals the inherent limitations of current biomarkers. We identified MRC2 as a key player as an inhibitory gene in AF, highlighting its role in suppressing AF progression through the PPAR signaling pathway. MRC2 may not only serve as a diagnostic indicator, but also as a promising therapeutic target for patients with AF, which is expected to be applied in clinical practice and open up new avenues for individualized interventions.
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spelling pubmed-106364292023-11-15 Bioinformatics and functional experiments reveal that MRC2 inhibits atrial fibrillation via the PPAR signaling pathway Zheng, Pengxiang Zhang, Wenjia Wang, Jiahong Gong, Qunlin Xu, Nan Chen, Nannan J Thorac Dis Original Article BACKGROUND: Atrial fibrillation (AF) is a prevalent cardiac arrhythmia that requires improved clinical markers to increase diagnostic accuracy and provide insight into its pathogenesis. Although some biomarkers are available, new ones need to be discovered to better capture the complex physiology of AF. However, their limitations are still not fully addressed. Bioinformatics and functional studies can help find new clinical markers and improve the understanding of AF, meeting the need for early diagnosis and individualized treatment. METHODS: To identify AF-related differentially expressed genes (DEGs), We applied the messenger RNA (mRNA) expression profile retrieved in Series Matrix File format from the GSE143924 microarray dataset obtained from the Gene Expression Omnibus (GEO) database, and then used weighted gene co-expression network analysis (WGCNA) to identify the overlapping genes. These genes were analyzed by enrichment analysis, expression analysis and others to obtain the hub gene. Additionally, the potential signaling pathway of hub gene in AF was explored and verified by functional experiments, like quantitative real-time polymerase chain reaction (qRT-PCR), cell counting kit-8 (CCK-8), flow cytometry, and Western blotting (WB) assay. RESULTS: From the GSE143924 data (410 DEGs) and tan module (57 genes), 10 overlapping genes were identified. A central down-regulated gene in AF, MRC2, was identified through bioinformatics analysis. based on these results, it was hypothesized that the PPAR signaling pathway is related to the mechanism of action of MRC2 in AF. Moreover, over-MRC2 markedly reduced the growth speed of angiotensin II (Ang II)-induced human cardiac fibroblasts (HCFs) and increased apoptosis. Conversely, knockdown of MRC2 promoted HCFs cell proliferation number. Additionally, MRC2 over-expression increased the protein expression level of PPARα, PPARγ, CPT-1, and SIRT3 in Ang II-induced HCFs. CONCLUSIONS: While meeting the need for new biomarkers in the diagnosis and prognosis of AF, this study reveals the inherent limitations of current biomarkers. We identified MRC2 as a key player as an inhibitory gene in AF, highlighting its role in suppressing AF progression through the PPAR signaling pathway. MRC2 may not only serve as a diagnostic indicator, but also as a promising therapeutic target for patients with AF, which is expected to be applied in clinical practice and open up new avenues for individualized interventions. AME Publishing Company 2023-09-26 2023-10-31 /pmc/articles/PMC10636429/ /pubmed/37969297 http://dx.doi.org/10.21037/jtd-23-1235 Text en 2023 Journal of Thoracic Disease. All rights reserved. https://creativecommons.org/licenses/by-nc-nd/4.0/Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0 (https://creativecommons.org/licenses/by-nc-nd/4.0/) .
spellingShingle Original Article
Zheng, Pengxiang
Zhang, Wenjia
Wang, Jiahong
Gong, Qunlin
Xu, Nan
Chen, Nannan
Bioinformatics and functional experiments reveal that MRC2 inhibits atrial fibrillation via the PPAR signaling pathway
title Bioinformatics and functional experiments reveal that MRC2 inhibits atrial fibrillation via the PPAR signaling pathway
title_full Bioinformatics and functional experiments reveal that MRC2 inhibits atrial fibrillation via the PPAR signaling pathway
title_fullStr Bioinformatics and functional experiments reveal that MRC2 inhibits atrial fibrillation via the PPAR signaling pathway
title_full_unstemmed Bioinformatics and functional experiments reveal that MRC2 inhibits atrial fibrillation via the PPAR signaling pathway
title_short Bioinformatics and functional experiments reveal that MRC2 inhibits atrial fibrillation via the PPAR signaling pathway
title_sort bioinformatics and functional experiments reveal that mrc2 inhibits atrial fibrillation via the ppar signaling pathway
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10636429/
https://www.ncbi.nlm.nih.gov/pubmed/37969297
http://dx.doi.org/10.21037/jtd-23-1235
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