Translational validation of shotgun proteomics findings in cerebrospinal fluid of sporadic cerebral amyloid angiopathy patients

Abstract

AbstractBackgroundPrior research conducted in model rats of CAA Type 1 (rTg-DI) identified a range of cerebrospinal fluid biomarker candidates associated with sCAA pathology. This list of potential biomarkers includes the lysosomal proteases cathepsins B and S (CTSB/CTSS) and hexosaminidase B (HEXB). It is yet unknown if these findings obtained in rTg-DI rats translate to differential protein levels and/or enzyme activities in cerebrospinal fluid (CSF) of sCAA patients. In this study, we attempted to validate CTSB, CTSS and HEXB in CSF as potential biomarkers for sCAA in a human population.Materials and methodsWe have included sCAA patients (n = 34) and control participants (n = 27) from our BIONIC/CAFE cohort. We analysed the CSF of these participants with ELISA for protein levels of CTSB and CTSS. Additionally, we used in-house enzyme assays to determine activity levels of total hexosaminidase and hexosaminidase A (HEXA) in CSF. The proportion of HEXA activity to total HEX activity was used as a proxy for HEXB activity.ResultsCSF CTSB and CTSS protein levels were not significantly different between sCAA and controls (p = 0.21 and p = 0.34). Total HEX activity was unaltered as well (p = 0.11), whereas a significant decrease was observed in HEXA activity levels (p = 0.05). HEXA / total HEX activity levels (as a proxy for HEXB activity) were unaltered between sCAA patients and controls (p = 0.19). Additionally, CTSB and CTSS protein levels positively associated with total HEX activity (rsp= 0.37, p = 0.005; rsp= 0.40, p = 0.003).ConclusionThe contrasting results between biomarker discovery in rats and validation in human participants highlight the challenges and complexities of biomarker research. These findings offer valuable insights into the nuances of disease and the difficulties in translating laboratory findings using animal models to clinical practice. Understanding these discrepancies is essential for improving the precision of biomarker translation, ensuring clinical relevance, and developing comprehensive biomarker panels for CAA and related conditions.