Background: Sarcopenia is a serious public health problem. The ceRNA network has been demonstrated vital in the development of skeletal muscle, but there is currently no effective method to assess the risk of sarcopenia. The purpose of this research is to create and authenticate a ceRNA pathway based on a predictive model of sarcopenia. Methods: A clinical prediction model for sarcopenia was established using the RNAs (validated by clinical data ) that are co-differentially expressed in the database, and a ceRNA network was constructed. The correlation analysis of each element in the ceRNA network was performed according to the clinical samples and the GTEX database, and the possible key ceRNA pathways were screened. C2C12 mouse myoblast Cells experiments were used to verify these ceRNA pathways. Findings: Based on four molecular markers of SEPP1, SV2A, GOT1 and GFOD1, we developed a new model for predicting sarcopenia with well accuracy, and constructed a ceRNA network accordingly. Clinical sample showed that the expression levels of lncDLEU2, SEPP1, and miR-181a were closely related to the risk of sarcopenia. The C2C12 mouse myoblast cells were cultivated to verify that lncDLEU2 inhibits muscle proliferation and differentiation by acting as a miR-181a sponge regulated SEPP1. Interpretation: Our research developed a highly accurate prediction tool for the risk of sarcopenia. These findings suggest that lncDLEU2-miR-181a-SEPP1 pathway inhibits muscle differentiation and regeneration. This pathway may uncover some new therapeutic targets for the treatment of sarcopenia caused by aging. ### Competing Interest Statement The authors have declared no competing interest.
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