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Biomarkers. 2018 Dec;23(8):793-803. doi: 10.1080/1354750X.2018.1499130. Epub 2018 Aug 23.

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

Author information

a Department of Neurosciences , Stroke Rapid Assessment Clinic, Island Health Authority , Victoria , Canada.
b Department of Research and Capacity Building , Island Health Authority , Victoria , Canada.
c Departments of Clinical Neurosciences, Radiology, and Community Health Services , University of Calgary , Calgary , Canada.
d Department of Mathematics and Statistics , University of Victoria , Victoria , Canada.
e George & Fay Yee Centre for Healthcare Innovation , University of Manitoba , Winnipeg , Canada.
f Division of Medical Sciences , University of Victoria , Victoria , Canada.
g Genome British Columbia Proteomics Centre, University of Victoria , Victoria , Canada.
h Department of Medicine , University of Toronto , Toronto , Canada.
i Department of Radiology , Foothills Medical Centre , Calgary , Canada.
j Department of Clinical Neurosciences , University of Calgary , Calgary , Canada.
k Department of Laboratory Medicine, Pathology & Medical Genetics , Island Health Authority , Victoria , Canada.
l Department of Biochemistry and Microbiology , University of Victoria , Victoria , Canada.
m Gerald Bronfman Department of Oncology , McGill University , Montreal , Canada.
n Proteomics Centre, Segal Cancer Centre , Lady Davis Institute , Montreal , Canada.



To validate our previously developed 16 plasma-protein biomarker panel to differentiate between transient ischaemic attack (TIA) and non-cerebrovascular emergency department (ED) patients.


Two consecutive cohorts of ED patients prospectively enrolled at two urban medical centers into the second phase of SpecTRA study (training, cohort 2A, nā€‰=ā€‰575; test, cohort 2B, nā€‰=ā€‰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.


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.


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.


TIA; TIA biomarkers; plasma biomarkers; stroke biomarkers; stroke proteomic; transient ischaemic attack

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