Protein biomarkers of intracranial aneurysm (IA) are essential for early detection and prediction of its rupture to facilitate the diagnosis and clinical management of the disease, monitor treatment response and detect recurrence. Here, we developed a comprehensive strategy for IA biomarker discovery by analyzing tissues from an animal model (n = 4) and serum from human patients (n = 60) using isobaric tandem mass tags-based quantitative proteomics. A total of 4811 and 562 proteins were identified from aneurysm tissue and serum samples, respectively. The 223 candidate protein biomarkers were further validated in an independent serum cohort (n = 30) by multiple reaction monitoring analysis. Combined with a logistic regression model, we built a diagnostic classifier P2 (FCN2 & RARRES2) to differentiate IA from healthy controls with accuracy of 93.3%, as well as a diagnostic classifier P7 (ADAM12, APOL3, F9, C3, CEACAM1, ICAM3, KLHDC7A) to classify ruptured IA from unruptured IA with accuracy of 95.0%. Taken together, our results suggest a valuable strategy for biomarker discovery and patient stratification in IA.
Keywords: Biomarker; Intracranial aneurysms; LC-MS/MS; Proteomics; Serum proteome.
Copyright © 2021. Published by Elsevier B.V.