title: Serum proteomic fingerprints of adult patients with severe acute respiratory syndrome.
abstract: BACKGROUND
  Severe acute respiratory syndrome (SARS) is an emerging infectious disease caused by a new coronavirus strain, SARS-CoV. Specific proteomic patterns might be present in serum in response to the infection and could be useful for early detection of the disease.
  
  
  METHODS
  Using surface-enhanced laser desorption/ionization (SELDI) ProteinChip technology, we profiled and compared serum proteins of 39 patients with early-stage SARS infection and 39 non-SARS patients who were suspected cases during the SARS outbreak period. Proteomic patterns associated with SARS were identified by bioinformatic and biostatistical analyses. Features of interest were then purified and identified by tandem mass spectrometry.
  
  
  RESULTS
  Twenty proteomic features were significantly different between the 2 groups. Fifteen were increased in the SARS group, and 5 were decreased. Their concentrations were correlated with 2 or more clinical and/or biochemical variables. Two were correlated with the SARS-CoV viral load. Hierarchical clustering analysis showed that a majority of the SARS patients (95%) had similar serum proteomic profiles and identified 2 subgroups with poor prognosis. ROC curve analysis identified individual features as potential biomarkers for SARS diagnosis (areas under ROC curves, 0.733-0.995). ROC curve areas were largest for an N-terminal fragment of complement C3c alpha chain (m/z 28 119) and an internal fragment of fibrinogen alpha-E chain (m/z 5908). Immunoglobulin kappa light chain (m/z 24 505) positively correlated with viral load.
  
  
  CONCLUSIONS
  Specific proteomic fingerprints in the sera of adult SARS patients could be used to identify SARS cases early during onset with high specificity and sensitivity.
authors.affiliation: Centre for Emerging Infectious Diseases, Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, NT, Hong Kong SAR.
authors.forename: Ronald T K
authors.initials: RT
authors.lastname: Pang
authors.forename: Terence C W
authors.initials: TC
authors.lastname: Poon
authors.forename: K C Allen
authors.initials: KC
authors.lastname: Chan
authors.forename: Nelson L S
authors.initials: NL
authors.lastname: Lee
authors.forename: Rossa W K
authors.initials: RW
authors.lastname: Chiu
authors.forename: Yu-Kwan
authors.initials: YK
authors.lastname: Tong
authors.forename: Ronald M Y
authors.initials: RM
authors.lastname: Wong
authors.forename: Stephen S C
authors.initials: SS
authors.lastname: Chim
authors.forename: Sai M
authors.initials: SM
authors.lastname: Ngai
authors.forename: Joseph J Y
authors.initials: JJ
authors.lastname: Sung
authors.forename: Y M Dennis
authors.initials: YM
authors.lastname: Lo
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D015415:Biomarkers / Q000097:blood; D016000:Cluster Analysis; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D040081:Protein Array Analysis; D020543:Proteome / Q000378:metabolism*; D012372:ROC Curve; D045473:Severe acute respiratory syndrome-related coronavirus; D044967:Serum; D045169:Severe Acute Respiratory Syndrome / Q000097:blood* / Q000175:diagnosis / Q000821:virology; D019032:Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization / Q000379:methods
chemical_list: D015415:Biomarkers; D020543:Proteome