A plasma protein signature for cerebral amyloid angiopathy

Abstract

Cerebral amyloid angiopathy (CAA) is a cerebrovascular disorder characterized by the deposition of amyloid-β (Aβ) in the walls of leptomeningeal and cortical blood vessels that increases risk of intracerebral hemorrhages and progressive cognitive decline. More than 90% of individuals with Alzheimer’s disease (AD) exhibit some level of CAA. Notably, in the new era of disease-modifying treatments for AD, CAA is a significant risk factor for amyloid-related imaging abnormalities (ARIA), an adverse event associated with anti-amyloid treatments. Therefore, there is great need for accessible, reliable and accurate in vivo biomarkers (e.g., blood-based) to improve antemortem identification of CAA that would improve risk stratification and reduce symptomatic ARIA. In this study, we employed the Nucleic Acid-Linked Immuno-Sandwich Assay (NULISA™) central nervous system panel for exploratory biomarker quantification in antemortem plasma of participants with neuropathological assessments for CAA from the Banner Sun Health Research Institute Brain and Body Donation Program (N = 251) and independently validated in the University of California Irvine Alzheimer Disease Research Center cohort (N = 110). We evaluated the differential protein expression in antemortem plasma sample taken < 5 years (mean 1.76 ± 1.3) from death using a logistic regression model. We further compared multi-biomarker models and found that a combination of CRP, IL4, CCL11, NPY and PDLIM5, plus demographic covariates showed an area under the curve (AUC) of 0.90 (95% CI 0.86–0.94) to identify neuropathologically confirmed CAA in the discovery cohort. In our independent replication, the antemortem plasma signature performed better than the basic demographics model showing a potential to predict CAA. The exploration and validation in antemortem plasma indicate that a multi-analyte panel, when combined with in vivo blood biomarkers for AD pathology, may be capable of identifying the presence of CAA and could have an meaningful impact on the clinical evaluation of patients under the investigation for cognitive decline. Further developments in biomarkers for this condition are crucial so that CAA identification could inform treatment decisions by highlighting ARIA risk.