Verification of a proteomic biomarker panel to diagnose minor stroke and transient ischaemic attack: phase 1 of SpecTRA, a large scale translational study.

OBJECTIVE: To derive a plasma biomarker protein panel from a list of 141 candidate proteins which can differentiate transient ischaemic attack (TIA)/minor stroke from non-cerebrovascular (mimic) conditions in emergency department (ED) settings. DESIGN: Prospective clinical study (#NCT03050099) with up to three timed blood draws no more than 36 h following symptom onset. Plasma samples analysed by multiple reaction monitoring-mass spectrometry (MRM-MS). PARTICIPANTS: Totally 545 participants suspected of TIA enrolled in the EDs of two urban medical centres. OUTCOMES: 90-day, neurologist-adjudicated diagnosis of TIA informed by clinical and radiological investigations. RESULTS: The final protein panel consists of 16 proteins whose patterns show differential abundance between TIA and mimic patients. Nine of the proteins were significant univariate predictors of TIA [odds ratio (95% confidence interval)]: L-selectin [0.726 (0.596-0.883)]; Insulin-like growth factor-binding protein 3 [0.727 (0.594-0.889)]; Coagulation factor X [0.740 (0.603-0.908)]; Serum paraoxonase/lactonase 3 [0.763 (0.630-0.924)]; Thrombospondin-1 [1.313 (1.081-1.595)]; Hyaluronan-binding protein 2 [0.776 (0.637-0.945)]; Heparin cofactor 2 [0.775 (0.634-0.947)]; Apolipoprotein B-100 [1.249 (1.037-1.503)]; and von Willebrand factor [1.256 (1.034-1.527)]. The scientific plausibility of the panel proteins is discussed. CONCLUSIONS: Our panel has the potential to assist ED physicians in distinguishing TIA from mimic patients.

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

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.