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多组学分析结合机器学习确定平滑肌细胞中的脂肪酸结合蛋白4(FABP4)是动脉粥样硬化的致病因素。

Multi-Omics Analysis Combined with Machine Learning Identified FABP4 in Smooth Muscle Cells as a Pathogenic Factor in Atherosclerosis.

作者信息

Wang Yinyu, Shang Tingting, Cai Rui, Wang Cuiping

机构信息

Department of Cardiology, Affiliated Hospital of Jiangsu University, Zhenjiang, People's Republic of China.

Department of Cardiology, The Affiliated Yancheng Maternity & Child Health Hospital of Yangzhou University, Yancheng, People's Republic of China.

出版信息

J Inflamm Res. 2025 Jul 26;18:10029-10049. doi: 10.2147/JIR.S519114. eCollection 2025.

DOI:10.2147/JIR.S519114
PMID:40740974
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12309571/
Abstract

BACKGROUND

Atherosclerosis is the pathological basis of coronary heart disease, stroke, and peripheral arterial disease. Smooth muscle cells (SMCs) play a crucial role in atherosclerotic pathogenesis. However, effective drugs and therapy targeting SMCs for treating atherosclerosis are still lacking.

METHODS

We utilized single-cell RNA sequencing (scRNA-seq) (GSE155512 and GSE159677) and array data (GSE43292 and GSE125771) to identify Scissor+ SMCs (SMCs positively associated with atherosclerosis) and Scissor- SMCs (SMCs negatively associated with atherosclerosis) by using Scissor package. We analyzed their functional changes, cell-cell communication, and differentiation potential. Machine learning techniques were employed to analyze the marker in SMCs of atherosclerosis. qRT-PCR was used to examine the expression of these genes in MOVAS stimulated by ox-LDL. Potential inhibitors of the identified proteins were predicted, and their binding sites were analyzed.

RESULTS

We identified 475 Scissor+ SMCs and 1363 Scissor- SMCs. Functional enrichment analysis revealed that Scissor+ SMCs exhibited downregulation of Rho-related pathways, while pro-inflammatory pathways were upregulated. Cell-cell communication analysis indicated tighter interactions between SMCs and endothelial cells. Differential expression analysis identified 20 genes highly expressed in both scRNA-seq and array data. The LASSO regression, random forest, support vector machine and receiver operating characteristic curve suggested a strong correlation between fatty acid-binding protein 4 (FABP4) and atherosclerosis. The qRT-PCR results showed that FABP4 was highly expressed in MOVAS stimulated by ox-LDL. Drug prediction revealed that (S)-RP-6306 acted as an inhibitor, via forming a polar bond with Arg-126. In vitro experiments confirmed that (S)-RP-6306 significantly reduced the expression of FABP4.

CONCLUSION

Scissor+ SMCs differed significantly from Scissor- SMCs in cellular function, cell-cell communication, and differentiation potential. The high expression of FABP4 in this subgroup of SMCs presented a promising therapeutic target for atherosclerosis, with (S)-RP-6306 showing potential as a drug targeting FABP4.

摘要

背景

动脉粥样硬化是冠心病、中风和外周动脉疾病的病理基础。平滑肌细胞(SMC)在动脉粥样硬化发病机制中起关键作用。然而,针对SMC治疗动脉粥样硬化的有效药物和疗法仍然缺乏。

方法

我们利用单细胞RNA测序(scRNA-seq)(GSE155512和GSE159677)和阵列数据(GSE43292和GSE125771),通过使用Scissor软件包来识别Scissor+ SMC(与动脉粥样硬化呈正相关的SMC)和Scissor- SMC(与动脉粥样硬化呈负相关的SMC)。我们分析了它们的功能变化、细胞间通讯和分化潜能。采用机器学习技术分析动脉粥样硬化SMC中的标志物。qRT-PCR用于检测氧化型低密度脂蛋白(ox-LDL)刺激的MOVAS中这些基因的表达。预测了所鉴定蛋白质的潜在抑制剂,并分析了它们的结合位点。

结果

我们鉴定出475个Scissor+ SMC和1363个Scissor- SMC。功能富集分析显示,Scissor+ SMC的Rho相关通路下调,而促炎通路上调。细胞间通讯分析表明SMC与内皮细胞之间的相互作用更紧密。差异表达分析确定了20个在scRNA-seq和阵列数据中均高表达的基因。套索回归、随机森林、支持向量机和受试者工作特征曲线表明脂肪酸结合蛋白4(FABP4)与动脉粥样硬化之间存在强相关性。qRT-PCR结果显示,FABP4在ox-LDL刺激的MOVAS中高表达。药物预测显示,(S)-RP-6306作为抑制剂,通过与Arg-126形成极性键发挥作用。体外实验证实,(S)-RP-6306显著降低了FABP4的表达。

结论

Scissor+ SMC在细胞功能、细胞间通讯和分化潜能方面与Scissor- SMC有显著差异。该亚组SMC中FABP4的高表达为动脉粥样硬化提供了一个有前景的治疗靶点,(S)-RP-6306显示出作为靶向FABP4的药物的潜力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8e5/12309571/abb3298f141d/JIR-18-10029-g0009.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8e5/12309571/f6e1c29a6b49/JIR-18-10029-g0006.jpg
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