Plasma Biomarkers of Inflammation and Angiogenesis Predict Cerebral Cavernous Malformation Symptomatic Hemorrhage or Lesional Growth
Rationale: The clinical course of cerebral cavernous malformations (CCMs) is highly unpredictable, with few cross-sectional studies correlating pro-inflammatory genotypes and plasma biomarkers with prior disease severity.
Objective: We hypothesize that a panel of 24 candidate plasma biomarkers, with a reported role in the physiopathology of CCMs, may predict subsequent clinically relevant disease activity.
Methods and Results: Plasma biomarkers were assessed in non-fasting peripheral venous blood collected from consecutive CCM subjects followed for one year after initial sample collection. A first cohort (N=49) was used to define the best model of biomarker level combinations to predict a subsequent symptomatic lesional hemorrhagic expansion within a year following the blood sample. We generated the receiver operating characteristic curves and area under curves (AUC) for each biomarker individually and each weighted linear combination of relevant biomarkers. The best model to predict lesional activity was selected as that minimizing the Akaike Information Criterion (AIC). In this cohort, 11 subjects experienced symptomatic lesional hemorrhagic expansion (5 bleeds and 10 lesional growths) within a year after the blood draw. Subjects had lower soluble cluster of differentiation 14 (sCD14; p=0.05), interleukin-6 (IL-6; p=0.04), vascular endothelial growth factor (VEGF; p=0.0003) levels along with higher plasma levels of interleukin-1 beta (IL-1β; p=0.008) and roundabout guidance receptor 4 (sROBO4; p=0.03). Among the 31 weighted linear combinations of these 5 biomarkers, the best model (with the lowest AIC value=25.3) was the weighted linear combination including sCD14, IL-1β, VEGF and sROBO4, predicting a symptomatic hemorrhagic expansion with a sensitivity of 86% and specificity of 88% (AUC=0.90, p<0.0001). We then validated our best model in the second sequential independent cohort (N=28).
Conclusions: This is the first study reporting a predictive association between plasma biomarkers and subsequent CCM disease clinical activity. This may be applied in clinical prognostication, and stratification of cases in clinical trials.
- Cerebral cavernous malformation
- Plasma Biomarker
- Prognostic Biomarker
- cerebrovascular disease/stroke
- Received January 5, 2018.
- Revision received April 25, 2018.
- Accepted April 30, 2018.