To systematically explore potential biomarkers which can predict disease severity in COVID-19 patients and prevent the occurrence or development of severe COVID-19, the levels of 440 factors were analyzed in patients categorized according to COVID-19 disease severity; including asymptomatic, mild, moderate, severe, convalescent and healthy control groups. Factor candidates were validated by ELISA and functional relevance was uncovered by bioinformatics analysis. To identify potential biomarkers of occurrence or development of COVID-19, patient sera from three different severity groups (moderate, severe, and critical) at three time points (admission, remission, and discharge) and the expression levels of candidate biomarkers were measured. Eleven differential factors associated with disease severity were pinpointed from 440 factors across 111 patients of differing disease severity. The dynamic changes of GDF15 reflect the progression of the disease, while the other differential factors include TRAIL R1, IGFBP-1, IGFBP-4, VCAM-1, sFRP-3, FABP2, Transferrin, GDF15, IL-1F7, IL-5R alpha, and CD200. Elevation of white blood cell count, neutrophil count, neutrophil-lymphocyte ratio (NLR), Alanine aminotransferase and Aspartate aminotransferase, low lymphocyte and eosinophil counts in the severe group were associated with the severity of COVID-19. GDF15 levels were observed to be associated with the severity of COVID-19 and the dynamic change of GDF15 levels was closely associated with the COVID-19 disease progression. Therefore, GDF15 might serve as an indicator of disease severity in COVID-19 patients.