Abstract
The skeletal muscle is highly susceptible to injury in daily life. Severe skeletal muscle injuries often result in incomplete regeneration, leading to functional impairment. In clinical practice, understanding the extent of skeletal muscle injury in limb trauma patients is crucial for selecting treatment modalities and assessing prognosis. Currently, there is a lack of specific indicators for evaluating the severity of mechanical skeletal muscle injury. Therefore, the aim of this study is to develop biomarkers for the early evaluation of different degrees of skeletal muscle injury. A rat model of skeletal muscle mechanical compression injury was established with varying degrees of injury severity, one control group, and two compression groups (Mild Injury and Severe Injury Group). LC-MS/MS-4D-DIA quantitative proteomics technology was used to detect the plasma proteome profile of rats in different injury groups at 3 hours post-injury, followed by bioinformatics analysis for data decoding. Rats in the mild and severe injury groups exhibited completely different degrees of injury and prognosis. The proteomic results of the plasma revealed that the relative quantification of 37 proteins increased along with the increase in injury, while 2 proteins decreased. These differentially expressed proteins (DEPs) included not only muscle-specific structural proteins but also metabolic-related proteins that might play crucial roles in tissue injury control, repair, and regeneration. Overall, the study has identified several potential protein biomarkers that can distinguish different degrees of skeletal muscle injury at an early stage. These protein biomarkers may be further developed to help clinicians identify patients with varying degrees of skeletal muscle injury, paving the way for personalized treatments.