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一种用于识别参与心房颤动的关键调节因子和生物标志物的综合生物信息学方法。

An integrated bioinformatics approach for identification of key modulators and biomarkers involved in atrial fibrillation.

作者信息

Thahiem Summan, Ishtiaq Ayesha, Iftekhar Faisal, Jan Muhammad Ishtiaq, Murtaza Iram

机构信息

Department of Biochemistry, Faculty of Biological Sciences, Quaid-i-Azam University, Islamabad, Pakistan.

Department of Cardiovascular Surgery, Lady Reading Hospital Peshawar, Peshawar, Pakistan.

出版信息

J Cardiovasc Thorac Res. 2025 Jun 28;17(2):109-120. doi: 10.34172/jcvtr.025.33347. eCollection 2025 Jun.

DOI:10.34172/jcvtr.025.33347
PMID:40862099
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12375429/
Abstract

INTRODUCTION

Atrial fibrillation (AFib) is a sustained form of cardiac arrythmia that occurs due to sympathetic overdrive, neurohumoral and electrophysiological changes. Sympatho-renal modulatory approach via miRNA-based therapeutics is likely to be an important treatment option for AFib. The study was aimed to unravel the common miRNAs as therapeutic targets involved in sympatho- renovascular axis to combat AFib.

METHODS

We employed the bioinformatics approach to discover differentially expressed genes (DEGs) from microarray gene expression datasets GSE41177 and GSE79768 of AFib patients. Concomitantly, genes associated with sympathetic cardio-renal axis, from Genetic Testing Registry (GTR) of National Center for Biotechnology Information (NCBI) were also analyzed. Overlapping miRNAs that target the maximum number of genes across all three pathological conditions perpetuating AFib were shortlisted. To confirm the reliability of the identified miRNAs, differential expression analysis was performed on miRNA expression profiles GSE190898, GSE68475, GSE70887 and GSE28954 derived from AFib patient samples.

RESULTS

ShinyGO analysis revealed enrichment in beta-adrenergic signaling, calcium signaling, as well as G protein-coupled receptor (GPCR) signaling involved in post synaptic membrane potential. The intersection of top 10 modules in miRNA-mRNA network revealed hub miRNAs having highest node degree, maximum neighborhood component (MNC), and maximal clique centrality (MCC) scores. Differential expression analysis revealed hub miRNAs identified through integrated approach were found to be significantly dysregulated in AFib patients.

CONCLUSION

This integrated approach identified 6 hub miRNAs, 4 reported (miR-101-3p, miR-23-3p, miR-27-3p, miR-25-3p) and 2 novel (miR-32-5p, miR-92-3p) miRNAs that might act as putative biomarkers for AFib.

摘要

引言

心房颤动(AFib)是一种持续性心律失常,由交感神经过度兴奋、神经体液和电生理变化引起。基于微小RNA(miRNA)的治疗方法通过调节交感神经-肾脏系统,可能成为治疗AFib的重要选择。本研究旨在揭示参与交感神经-肾血管轴、可作为治疗靶点对抗AFib的常见miRNA。

方法

我们采用生物信息学方法,从AFib患者的微阵列基因表达数据集GSE41177和GSE79768中发现差异表达基因(DEG)。同时,还分析了来自美国国立生物技术信息中心(NCBI)遗传检测注册库(GTR)中与交感神经-心脏-肾脏轴相关的基因。筛选出在导致AFib的所有三种病理状况下靶向最多基因的重叠miRNA。为了确认所鉴定miRNA的可靠性,对来自AFib患者样本的miRNA表达谱GSE190898、GSE68475、GSE70887和GSE28954进行差异表达分析。

结果

ShinyGO分析显示,在β-肾上腺素能信号传导、钙信号传导以及参与突触后膜电位的G蛋白偶联受体(GPCR)信号传导方面存在富集。miRNA - mRNA网络中前10个模块的交集揭示了具有最高节点度、最大邻域成分(MNC)和最大团中心性(MCC)分数的枢纽miRNA。差异表达分析显示,通过综合方法鉴定的枢纽miRNA在AFib患者中存在明显失调。

结论

这种综合方法鉴定出6种枢纽miRNA,其中4种已有报道(miR - 101 - 3p、miR - 23 - 3p、miR - 27 - 3p、miR - 25 - 3p),2种为新发现的(miR - 32 - 5p、miR - 92 - 3p)miRNA,它们可能作为AFib的潜在生物标志物。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a382/12375429/4b08c3345279/jcvtr-17-109-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a382/12375429/68d3e39ab97d/jcvtr-17-109-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a382/12375429/fa31d37a3cdc/jcvtr-17-109-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a382/12375429/8d0d6a543286/jcvtr-17-109-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a382/12375429/f3db7785de68/jcvtr-17-109-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a382/12375429/c6bc27c16e55/jcvtr-17-109-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a382/12375429/33700079a5b3/jcvtr-17-109-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a382/12375429/99dc12d32e42/jcvtr-17-109-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a382/12375429/923bc2a23817/jcvtr-17-109-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a382/12375429/4b65e3073ed6/jcvtr-17-109-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a382/12375429/4b08c3345279/jcvtr-17-109-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a382/12375429/68d3e39ab97d/jcvtr-17-109-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a382/12375429/fa31d37a3cdc/jcvtr-17-109-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a382/12375429/8d0d6a543286/jcvtr-17-109-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a382/12375429/f3db7785de68/jcvtr-17-109-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a382/12375429/c6bc27c16e55/jcvtr-17-109-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a382/12375429/33700079a5b3/jcvtr-17-109-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a382/12375429/99dc12d32e42/jcvtr-17-109-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a382/12375429/923bc2a23817/jcvtr-17-109-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a382/12375429/4b65e3073ed6/jcvtr-17-109-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a382/12375429/4b08c3345279/jcvtr-17-109-g010.jpg

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