Abstract

Introduction: Cerebral amyloid angiopathy (CAA) is a cerebral small vessel disease featuring beta-amyloid deposits within the cerebral vasculature. It is a major cause of cognitive decline and intracerebral hemorrhage in the elderly. This study evaluated whether gene expression profiles in peripheral blood can differentiate patients with CAA from vascular risk factor and healthy controls. Methods: In 27 patients with CAA blood cell gene expression was compared to 55 controls. Total RNA was isolated from PAXgene tubes and measured by RNA sequencing. Differentially expressed genes between CAA and controls were identified by ANOVA adjusting for age and sex. Functional pathway analysis identified pathways associated with CAA. A prediction model to distinguish CAA from controls was developed using linear discriminant analysis with feature selection by forward selection. Model performance was evaluated by 10-fold leave-one-out cross validation. Results: 686 differentially expressed genes were identified (p<0.05, fold change >|1.2|), of interest ADAM15, CAMK1D, CAP1 and TGFB1 . Canonical pathway analysis identified cell movement of phagocytes, activation of phagocytes, CREB, degranulation of leukocytes, immune response of cells, inflammatory response, and IL-23 signaling. A 24 gene panel differentiated patients with CAA from controls with >95% sensitivity and specificity. The identified genes reveal differences in immune system regulation in patients with CAA compared to vascular risk factor and healthy control patients. Differences identified include a potential shift in beta-amyloid uptake by phagocytes ( TGFB1, CREB, CAMK1D ), an increase in vascular extracellular matrix disruption ( ADAM15, CAP1 ), and a possible alteration in amyloid precursor processing ( BRI3BP, SORCS3 ). Conclusion: Differences in peripheral leukocyte gene expression are present in patients with CAA compared to control patients. These relate to differences in immune activation and signaling associated with CAA. The differences in blood cell gene expression shows promise to distinguish CAA from controls, though further evaluation in larger cohorts is required to further evaluate potential diagnostic utility of this gene expression profile.

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