SELDI-TOF plasma profiles distinguish individuals in a protein C-deficient family with thrombotic episodes occurring before age 40.
We tested the hypothesis that differences in the low-molecular-weight (500-20,000 Da) proteomic profile of plasma may be detectable between members of a protein C-deficient family who have suffered thrombotic events before age 40 compared to family members without a history of venous thrombosis. Unfractionated plasma samples from members of a previously described large thrombophilic kindred with type I protein C deficiency were applied to ProteinChip weak cation exchange interaction arrays (WCX2; Ciphergen Biosystems, Fremont, CA, USA) and subjected to SELDI-TOF (surface-enhanced laser desorption/ionization time-of-flight) mass spectrometry using the Ciphergen PBSII ProteinChip System (Ciphergen Biosystems). Profiles were analyzed by a boosted decision-tree algorithm. When individuals who had presented with deep venous thrombosis (DVT) before the age of 40 (n = 21) were compared to age-matched, healthy family members (n = 50), the proteomic patterns defined by the decision-tree analysis could classify the entity of DVT before age 40 with 67% sensitivity, at a specificity of 86%. When a small group of cases with history of superficial venous thrombosis (n = 6) was added to the case group, the sensitivity was 87.5% at a specificity of 80%. These data support the hypothesis that members of the protein C deficient Vermont kindred II who suffer a thrombotic event before age 40 display significant differences in low-molecular-weight proteomics profile compared to those who remain disease-free. This is the first study to apply SELDI-TOF technology in conjunction with a bioinformatics tool to analyze low-molecular-weight proteomic patterns in patients with venous thrombosis.
Svensson
Annika M
AM
Department of Pathology, University of Vermont College of Medicine, Burlington, Vermont, USA.
Whiteley
Gordon R
GR
Callas
Peter W
PW
Bovill
Edwin G
EG
D000328:Adult; D017677:Age Distribution; D000367:Age Factors; D000375:Aging; D000465:Algorithms; D015415:Biomarkers / Q000097:blood; D016022:Case-Control Studies; D003663:Decision Trees; D006801:Humans; D008970:Molecular Weight; D010375:Pedigree; D040081:Protein Array Analysis; D020151:Protein C Deficiency / Q000097:blood* / Q000150:complications; D011506:Proteins / Q000737:chemistry / Q000378:metabolism*; D040901:Proteomics / Q000379:methods; D012307:Risk Factors; D012680:Sensitivity and Specificity; D019032:Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization; D020246:Venous Thrombosis / Q000209:etiology*
D015415:Biomarkers; D011506:Proteins