Sarcopenia is a serious public health problem associated with the loss of muscle mass and function. The purpose of this study was to identify molecular markers and construct a ceRNA pathway as a significant predictor of sarcopenia. We designed a prediction model to select important differentially expressed mRNAs (DEMs), and constructed a sarcopenia associated ceRNA network. After correlation analysis of each element in the ceRNA network based on clinical samples and GTEX database, C2C12 mouse myoblasts were used as a model to verify the identified ceRNA pathways. A new model for predicting sarcopenia based on four molecular markers SEPP1, SV2A, GOT1, and GFOD1 was developed. The model was used to construct a ceRNA network and showed high accuracy. Correlation analysis showed that the expression levels of lncDLEU2, SEPP1, and miR-181a were closely associated with a high risk of sarcopenia. lncDLEU2 inhibits muscle differentiation and regeneration by acting as a miR-181a sponge regulating SEPP1 expression. In this study, a highly accurate prediction tool was developed to improve the prediction outcomes of sarcopenia. These findings suggest that the lncDLEU2-miR-181a-SEPP1 pathway inhibits muscle differentiation and regeneration. This pathway may be a new therapeutic target for the treatment of sarcopenia.
Keywords: DLEU2; SELENOP protein (SEPP1); competing endogenous RNA (ceRNA); miR-181a; sarcopenia.