已发表论文

创伤后肘关节僵硬发病机制的新临床见解:人类收缩关节囊的表达谱分析

 

Authors Liu N, Dong J, Li L, Xu J, Yang C , Yu Z , Liu F 

Received 9 October 2024

Accepted for publication 31 December 2024

Published 6 January 2025 Volume 2025:18 Pages 167—182

DOI https://doi.org/10.2147/JIR.S499986

Checked for plagiarism Yes

Review by Single anonymous peer review

Peer reviewer comments 4

Editor who approved publication: Professor Ning Quan

Nan Liu,1 Jinlei Dong,1 Lianxin Li,1 Jiajun Xu,1 Changhao Yang,1 Zhanchuan Yu,2 Fanxiao Liu1 

1Department of Shandong Trauma Center, Shandong Provincial Hospital affiliated to Shandong First Medical University, Jinan, Shandong, 250014, People’s Republic of China; 2Department of Shandong Trauma Center, Shandong Provincial Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, 250014, People’s Republic of China

Correspondence: Fanxiao Liu, Department of Shandong Trauma Center, Shandong Provincial Hospital affiliated to Shandong First Medical University, Jingshi str. 9677, Jinan, Shandong, 250014, People’s Republic of China, Tel/Fax +86-0531-68773195, Email woshi631@126.com; liufanxiao@sdfmu.edu.cn

Background: Posttraumatic elbow stiffness is a complex complication with two characteristics of capsular contracture and heterotopic ossification. Currently, genomic mechanisms and pathogenesis of posttraumatic elbow stiffness remain inadequately understood. This study aims to identify differentially expressed genes (DEGs) and elucidate molecular networks of posttraumatic elbow stiffness, providing novel insights into disease mechanisms at transcriptome level.
Methods: Global transcriptome sequencing was conducted on six capsular samples from individuals with posttraumatic elbow stiffness and three control capsular samples from individuals with elbow fractures. Differentially expressed genes (DEGs), microRNAs, and long non-coding RNAs (LncRNAs) were identified and analyzed. Functional enrichment analysis was performed, and the associated protein–protein interaction (PPI) network was constructed. MicroRNAs targeting these DEGs were identified, and transcription factors (TFs) targeting DEGs were predicted using the ENCODE database. Finally, key DEGs were validated by quantitative real-time polymerase chain reaction (qRT-PCR).
Results: A total of 4909 DEGs associated with protein-coding, LncRNA and microRNA were detected, including 2124 upregulated and 2785 downregulated. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis revealed that the DEGs were significantly enriched in 36 signaling pathways, notably involving inflammatory responses and extracellular matrix (ECM) receptor interactions. The protein–protein interaction (PPI) network analysis highlighted genes such as SPP1, IBSP, MMP13 and MYO1A as having higher degrees of connectivity. Key microRNAs (hsa-miR-186-5p, hsa-miR-515-5p, and hsa-miR-590-3p) and transcription factors (TFDP1 and STAT3) were predicted to be implicated in the pathogenesis of posttraumatic elbow stiffness through the microRNA-transcription factor regulatory network analysis.
Conclusion: The study provided insights into the molecular mechanisms underlying the changes in the contracted capsules associated with posttraumatic elbow stiffness. Hub genes including SPP1, IBSP, MMP13, and MYO1A, key microRNAs (has-miR-186-5p, has-miR-515-5p, hsa-miR-590-3p) and TFs (TFDP1 and STAT3) may serve as prognostic and therapeutic targets of posttraumatic elbow stiffness, and provide a new idea for the future research direction of clinical treatment.

Keywords: posttraumatic elbow stiffness, capsules, transcriptome sequencing, bioinformatic analysis, key candidate genes