Proteomic Fingerprints for Potential Application to Early Diagnosis of Severe Acute Respiratory Syndrome

Background: Definitive early-stage diagnosis of severe acute respiratory syndrome (SARS) is important despite the number of laboratory tests that have been developed to complement clinical features and epidemiologic data in case definition. Pathologic changes in response to viral infection might be reflected in proteomic patterns in sera of SARS patients. Methods: We developed a mass spectrometric decision tree classification algorithm using surface-enhanced la-ser desorption/ionization time-of-flight mass spectrom-etry. Serum samples were grouped into acute SARS (n 74; <7 days after onset of fever) and non-SARS [n 1067; fever and influenza A (n 203), pneumonia (n 176); lung cancer (n 29); and healthy controls (n 659)] cohorts. Diluted samples were applied to WCX-