A 2 miRNAs-based signature for the diagnosis of atherosclerosis.
A 2 miRNAs-based signature for the diagnosis of atherosclerosis.
复制标题
用于诊断动脉粥样硬化的基于2 miRNA的特征。
DOI：
10.1186/s12872-021-01960-4
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发表时间：
2021-03-24
影响因子：
2.1
通讯作者：
Gao S
中科院分区：
文献类型：
--
作者：
Han X;Wang H;Li Y;Liu L;Gao S
动脉粥样硬化（AS）是世界范围内血管疾病的主要原因。MicroRNAs (miRNAs)在AS的发展中起着至关重要的作用。然而，基于mirnas的诊断AS的生物标志物仍然有限。在此，我们旨在识别与AS显著相关的mirna，并基于这些mirna构建预测模型，以区分AS患者与健康病例。分别从Gene expression Omnibus （GEO）数据库的GSE59421和GSE20129中获取AS患者和健康患者血液样本的miRNA和mRNA表达微阵列数据。采用加权基因共表达网络分析（Weighted Gene Co-expression Network Analysis， WGCNA）评估miRNAs和mrna与AS的相关性，并鉴定与AS显著相关的miRNAs和mrna。通过功能富集分析进一步优化了潜在的关键mirna。基于这些优化的mirna构建逻辑回归模型，并通过三重交叉验证方法进行验证。WGCNA共发现42个mirna和532个基因与AS显著相关。功能富集分析鉴定了AS患者的12个关键mirna。此外，我们利用逐步回归模型从已鉴定的12种mirna中选择了6种mirna，其中通过多元回归分析进一步鉴定了hsa-miR-654-5p、hsa-miR-409-3p、hsa-miR-485-5p和hsa-miR-654-3p这4种mirna。三倍交叉验证方法显示，基于这4种mirna的logistic回归模型的AUC分别为0.7308、0.8258和0.7483，平均AUC为0.7683。我们共鉴定出四种mirna，包括hsa-miR-654-5p和hsa-miR-409-3p，被鉴定为as的潜在关键生物标志物。基于鉴定的2个mirna的logistic回归模型能够可靠地区分AS患者和正常病例。在线版本包含补充材料，可在10.1186/s12872-021-01960-4获得。
Atherosclerosis (AS) is a leading cause of vascular disease worldwide. MicroRNAs (miRNAs) play an essential role in the development of AS. However, the miRNAs-based biomarkers for the diagnosis of AS are still limited. Here, we aimed to identify the miRNAs significantly related to AS and construct the predicting model based on these miRNAs for distinguishing the AS patients from healthy cases. The miRNA and mRNA expression microarray data of blood samples from patients with AS and healthy cases were obtained from the GSE59421 and GSE20129 of Gene Expression Omnibus (GEO) database, respectively. Weighted Gene Co-expression Network Analysis (WGCNA) was performed to evaluate the correlation of the miRNAs and mRNAs with AS and identify the miRNAs and mRNAs significantly associated with AS. The potentially critical miRNAs were further optimized by functional enrichment analysis. The logistic regression models were constructed based on these optimized miRNAs and validated by threefold cross-validation method. WGCNA revealed 42 miRNAs and 532 genes significantly correlated with AS. Functional enrichment analysis identified 12 crucial miRNAs in patients with AS. Moreover, 6 miRNAs among the identified 12 miRNAs, were selected using a stepwise regression model, in which four miRNAs, including hsa-miR-654-5p, hsa-miR-409-3p, hsa-miR-485-5p and hsa-miR-654-3p, were further identified through multivariate regression analysis. The threefold cross-validation method showed that the AUC of logistic regression model based on the four miRNAs was 0.7308, 0.8258, and 0.7483, respectively, with an average AUC of 0.7683. We identified a total of four miRNAs, including hsa-miR-654-5p and hsa-miR-409-3p, are identified as the potentially critical biomarkers for AS. The logistic regression model based on the identified 2 miRNAs could reliably distinguish the patients with AS from normal cases. The online version contains supplementary material available at 10.1186/s12872-021-01960-4.
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影响因子：
4.6
作者：
Huang, Chiang-Ching;Lloyd-Jones, Donald M.;Liu, Kiang
通讯作者：
Liu, Kiang
影响因子：
3
作者：
El-Samahy, Mona Husein;Adly, Amira AbdelMoneam;Mohammed, Hossam Hassan
通讯作者：
Mohammed, Hossam Hassan
来自成熟树突状细胞的外泌体通过膜 TNF-α 介导的 NF-κ B 途径增加内皮炎症和动脉粥样硬化
影响因子：
5.3
作者：
Gao W;Liu H;Yuan J;Wu C;Huang D;Ma Y;Zhu J;Ma L;Guo J;Shi H;Zou Y;Ge J
通讯作者：
Ge J
影响因子：
20.1
作者：
Bentzon, Jacob Fog;Otsuka, Fumiyuki;Falk, Erling
通讯作者：
Falk, Erling
影响因子：
20.1
作者：
Di Gregoli K;Mohamad Anuar NN;Bianco R;White SJ;Newby AC;George SJ;Johnson JL
通讯作者：
Johnson JL