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Sarcopenia is a gradual loss of skeletal muscle mass and function with aging. As sarcopenia has been recognized as a disease entity after being established of ICD-10-CM (M62.84) in September, 2016, development of an appropriate tool for diagnosis and prognosis attracts attention. Currently, various working groups on sarcopenia suggest clinical diagnostic criteria of sarcopenia based on quantification of muscle mass and function. However, these ways are complex and applicable only after the onset or progression of disease. Therefore molecular biomarkers are essential for early diagnosis and prognosis of sarcopenia. We recruited 46 normal subjects and 50 subjects with moderate sarcopenia aged 60 years and older. Sarcopenia was clinically identified on the basis of appendicular skeletal muscle index by applying the cutoff values from the Asian Working Group for Sarcopenia. The serum levels of 21 potential biomarkers were analyzed. Interleukin 6, macrophage migration inhibitory factor, secreted protein acidic and rich in cysteine and insulin-like growth factor 1 levels were statistically different between normal and sarcopenic group. However, the area under the receiver operating characteristics curve (AUC) below 0.7 indicated that the individual markers were not accurate alone to be used for prediction of sarcopenia. Therefore, we combined the measurements of these biomarkers into one single risk score based on logistic regression coefficients, which enhanced the accuracy of diagnosis with 0.763 of AUC. The cutoff value of 1.529 had 70.0% of sensitivity and 78.3% of specificity (95 % CI, 2.80-21.69, p<0.0001). Combination of the selected multiple biomarkers can be utilized in early diagnosis and prognosis of sarcopenia.