Statistical analysis concluded that fatigue was negatively correlated with IP10, IL12p70, ESR and IgG, but positively correlated with platelets and C4 (p-value <0.05, Benjamini-Hochberg correction). Moreover, most protein levels were significantly higher in patients compared to healthy controls (p-value <0.05). An observed pattern was apparent that protein levels of patients with high fatigue lie between healthy controls and low fatigue patients. Additionally, Multiple linear regression analysis identified low IgG, high platelets and low IFNα as key predictive factors for fatigue. Furthermore, after quantitation and identification, the proteomic analysis confirmed 9 proteins to be significantly down-regulated and 3 proteins to be significantly up-regulated (p-value <0.05) in patients with high fatigue compared to those with low fatigue. The results also indicated that there was influence of confounders in the analysis, suggested by different symptoms being significantly correlated with similar proteins.