Validation of a proteomic biomarker panel to diagnose minor-stroke and transient ischaemic attack: phase 2 of SpecTRA, a large scale translational study. (17th November 2018)

• Record Type: Journal Article
• Authors: Penn, Andrew M.; Bibok, Maximilian B.; Saly, Viera K.; Coutts, Shelagh B.; Lesperance, Mary L.; Balshaw, Robert F.; Votova, Kristine; Croteau, Nicole S.; Trivedi, Anurag; Jackson, Angela M.; Hegedus, Janka; Klourfeld, Evgenia; Yu, Amy Y. X.; Zerna, Charlotte; Modi, Jayesh; Barber, Philip A.; Hoag, Gordon; Borchers, Christoph H.
• Is Part Of: Biomarkers. Volume 23:Number 8(2018)
• Page Start: 793
• Page End: 803
• Publication Date: 2018-11-17
• Subjects: TIA -- transient ischaemic attack -- TIA biomarkers -- stroke biomarkers -- stroke proteomic -- plasma biomarkers; Biochemical markers -- Periodicals; 610.28
• DOI: 10.1080/1354750X.2018.1499130
• Languages: English
• ISSNs: 1354-750X

Abstract

Abstract: OBJECTIVE: To validate our previously developed 16 plasma-protein biomarker panel to differentiate between transient ischaemic attack (TIA) and non-cerebrovascular emergency department (ED) patients. METHOD: Two consecutive cohorts of ED patients prospectively enrolled at two urban medical centers into the second phase of SpecTRA study (training, cohort 2A, n = 575; test, cohort 2B, n = 528). Plasma samples were analyzed using liquid chromatography/multiple reaction monitoring-mass spectrometry. Logistic regression models which fit cohort 2A were validated on cohort 2B. RESULTS: Three of the panel proteins failed quality control and were removed from the panel. During validation, panel models did not outperform a simple motor/speech (M/S) deficit variable. Post-hoc analyses suggested the measured behaviour of L-selectin and coagulation factor V contributed to poor model performance. Removal of these proteins increased the external performance of a model containing the panel and the M/S variable. CONCLUSIONS: Univariate analyses suggest insulin-like growth factor-binding protein 3 and serum paraoxonase/lactonase 3 are reliable and reproducible biomarkers for TIA status. Logistic regression models indicated L-selectin, apolipoprotein B-100, coagulation factor IX, and thrombospondin-1 to be significant multivariate predictors of TIA. We discuss multivariate feature subset analyses as an exploratory technique to better understand a panel's full predictive potential.