Cerebral cavernous malformations (CCMs), one of the most common vascular malformations, are characterized by abnormally dilated intracranial capillaries resulting in increased susceptibility to hemorrhagic stroke. As an autosomal dominant disorder with incomplete penetrance, the majority of CCMs gene mutation carriers are largely asymptomatic but when symptoms occur, the disease has typically reached the stage of focal hemorrhage with irreversible brain damage. Currently, the invasive neurosurgery removal of CCM lesions is the only treatment option, despite the recurrence of symptoms after surgery. Therefore, there is a grave need for prognostic/monitoring biomarkers as risk predictors for stroke prevention. The goal is to develop a set of blood prognostic biomarkers as risk predictors for stroke prevention. The objective of this project is to validate novel serum biomarkers identified in Ccm animal models in human blood that could predict the risk of hemorrhagic events. The central hypothesis is that quantitative detection of certain serum biomarkers can be utilized to predict the timing of hemorrhagic events. The hypothesis has been formulated based on the recent findings of five serum etiological biomarkers associated with disruption of the Blood-Brain Barrier (BBB), which could lead to hemorrhagic events. Taking advantage of the research team's expertise in Ccm pathology and serum biomarkers, the central hypothesis will be tested to achieve the study goal by pursuing the following three revolutionary aims in two phases, starting from the phase 1 with the first two biomarker discovery aims (1, 2):

1. Validate blood prognostic/monitoring biomarkers with the optimized detection platform for hemorrhagic stroke prevention. The working hypothesis is that expression levels of certain blood molecules are correlated with the progression of a disrupted BBB. In this aim, serum biomarkers identified in Ccms mice will be validated in the blood samples of CCM patients to evaluate their feasibility and reliability. The correlation functions between the serum/plasma levels of biomarkers and the progression of a disrupted BBB identified in Ccms mice will be tested using the "gold standard", enzyme-linked immunosorbent assay (ELISA) platform in CCM patients for 1a). Clinical preparation for large cohort CCM analysis; 1b). Validating serum progesterone (PRG) as a biomarker, and 1c). Validating 4 etiological serum peptide biomarkers with the optimized ELISA platform in CCM patients.
2. To optimize the sensitivity, specificity, dynamic range, and reliability of biomarkers using the cutting-edge multiplex platform to predict risks of hemorrhagic stroke. The working hypothesis is that the measurement parameters of blood biomarkers, such as sensitivity, specificity, dynamic working range, and inter/intra variability, can be drastically improved with a larger sample size, improved clinical definitions, and better detection platforms. High-performance ELISAs will be continuously utilized for validating etiological biomarkers. To ensure the highest sensitivity and specificity, a robust automatic multiplex platform for the repetitive analysis of large cohorts is essential to validate biomarkers for hemorrhagic strokes. Linear or logistic regression analysis will be performed to delineate the correlation between validated biomarkers and those of clinical criteria. In this aim, the will 2a). Improve sensitivity and specificity of candidate blood biomarkers through correlation equations were optimized with increased CCM blood sample sizes and updated clinical information; 2b). Define new biomarkers using high-throughput omic approaches, and 2c). Improve sensitivity and increase dynamic working range of blood biomarkers with a multiplex bead array assay (MBAA) platform and optimized protocols.

Phase-2 Aim: 3) Improve clinical utility of validated prognostic/monitoring biomarkers with optimized algorithms in larger cohorts in preparation for human clinical trials. The working hypothesis is that clinical sensitivity and specificity of blood biomarkers can be further improved through a blindly test-retest approach in larger independent human cohorts. This aim will provide sufficient proof that the clinical utility of blood biomarkers can be improved and utilized to predict the risk of hemorrhagic stroke, laying the groundwork for future clinical trials and possible future revolutionary clinical applications. The research team will continue to 3a). Improve clinical utility by optimizing the precision of prognostic/monitoring algorithms of validated biomarker(s)/panel(s) using larger cohorts; 3b). Further improve clinical utility by confirming reliability of validated biomarker(s)/panel(s) in a larger cohort; and 3c). Confirm validated prognostic/monitoring biomarker(s)/panel(s) are ready for future clinical trials.