RESUMEN
AIMS: The objective of this study is to provide a reliable strategy for the diagnosis of sarcopenia based on a complementary combination of biomarkers from various approaches. MATERIAL AND METHODS: A total of 30 C57BL/6J mice were used for the experiment, in which 15 young mice (YM) at 24 weeks old and 15 aged mice (AM) at 88 weeks old. Extracted features-based digital biomarkers from the electromyography activity of tibialis anterior muscles were evaluated by using receiver operating characteristic analysis. Extracted tissular proteins and circulating hormones based chemical biomarkers were investigated by using immunoblotting and enzyme-linked immunosorbent assay. KEY FINDINGS: In terms of digital biomarkers, the feature-based classification of mice groups showed good performance (Feature A: AUC = 0.986, accuracy = 0.928) and (Feature B: AUC = 0.999, accuracy = 0.990). On the other hand, muscle-specific protein levels based chemical biomarkers (e.g. MuRF1, FoxO1, and perilipin2) were observed significantly increase with age. Pro-inflammatory cytokines based biomarkers extracted from muscle tissue and circulating plasma (e.g. TNF-α, IL-6, and IL-8) were significantly higher in case of AM group compared to YM group. Circulating hormone-based chemical biomarkers (e.g. cortisol/DHEA ratio and cathepsin D) presented a significant increase in concentrations with age. Circulating neurotransmitter based biomarkers (e.g. acetylcholine, serotonin, and histamine) also increased significantly in concentrations from YM to AM. SIGNIFICANCE: A complementary combination of digital and chemical biomarkers covers multiple domains of sarcopenia to provide an effective strategy for the early diagnosis of sarcopenia.