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通过多组学分析破译异位骨化中与迁移体相关细胞亚群的调控网络

Deciphering the Regulatory Networks of the Migrasome-Associated Cell Subpopulation in Heterotopic Ossification via Multi-Omics Analysis.

作者信息

Li Guanzhi, Deng Xiao, Li Tong, Liu Yuchen, Tan Lei, Zhang Kairui, Yu Bin

机构信息

Division of Orthopaedics and Traumatology, Department of Orthopaedics, Nanfang Hospital, Southern Medical University, Guangzhou, China.

Guangdong Provincial Key Laboratory of Bone and Cartilage Regenerative Medicine, Nanfang Hospital, Southern Medical University, Guangzhou, China.

出版信息

FASEB J. 2025 Jun 30;39(12):e70749. doi: 10.1096/fj.202500965R.

Abstract

Heterotopic ossification (HO) is a pathological process where bone forms in extraskeletal tissues, often occurring as a complication of tissue repair following injury. This condition can lead to movement limitations, pain, and functional impairment. However, the underlying pathomechanisms remain poorly understood. This study aims to elucidate key biomolecular networks involved in HO through a comprehensive multi-omics analysis. Single-cell, bulk, and spatial transcriptome datasets were obtained from the Gene Expression Omnibus (GEO) database. Migrasome score analysis identified a critical cell subtype associated with HO. Key genes were identified through high-dimensional weighted gene co-expression network analysis (hdWGCNA), machine learning, and dataset validation from clinical samples. Then we analyzed immune infiltration, microRNA (miRNA) networks, co-expression networks, transcription factor (TF) regulatory networks, and signaling pathways to investigate potential regulatory mechanisms of HO. Spatial transcriptomics revealed the spatial patterns of cell subpopulation distribution and key molecule expression. Experimental validation further confirmed the expression patterns of key molecules in HO. As a result, we identified mesenchymal lineage cells (MLin) as the key migrasome-associated cell subtype and determined peptidylprolyl isomerase B (Ppib) and transgelin (Tagln) as the key molecules. We constructed a regulatory network of these biomolecules and clarified their spatial distribution. Notably, the expression of Ppib and Tagln is temporally correlated with HO progression. Collectively, the identification of Ppib and Tagln, along with the construction of key biomolecular networks, facilitates the discovery of novel biomarkers for HO, offering promising potential for the development of preventive and therapeutic strategies.

摘要

异位骨化(HO)是一种病理过程,其中骨骼在骨骼外组织中形成,常作为损伤后组织修复的并发症出现。这种情况可导致运动受限、疼痛和功能障碍。然而,其潜在的发病机制仍知之甚少。本研究旨在通过全面的多组学分析阐明参与HO的关键生物分子网络。从基因表达综合数据库(GEO)获得单细胞、整体和空间转录组数据集。迁移体评分分析确定了一种与HO相关的关键细胞亚型。通过高维加权基因共表达网络分析(hdWGCNA)、机器学习以及临床样本的数据集验证来鉴定关键基因。然后我们分析了免疫浸润、微小RNA(miRNA)网络、共表达网络、转录因子(TF)调控网络和信号通路,以研究HO的潜在调控机制。空间转录组学揭示了细胞亚群分布和关键分子表达的空间模式。实验验证进一步证实了HO中关键分子的表达模式。结果,我们确定间充质谱系细胞(MLin)为与迁移体相关的关键细胞亚型,并确定肽基脯氨酰异构酶B(Ppib)和转胶蛋白(Tagln)为关键分子。我们构建了这些生物分子的调控网络并阐明了它们的空间分布。值得注意的是,Ppib和Tagln的表达在时间上与HO进展相关。总体而言,Ppib和Tagln的鉴定以及关键生物分子网络的构建有助于发现HO的新型生物标志物,为预防和治疗策略的开发提供了有希望的潜力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5890/12180572/631a20bc88e1/FSB2-39-e70749-g007.jpg

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