Biology subjects

Verbeek, M. M.

Publications and source records attributed to Verbeek, M. M..

3 recordsLinked to original sources

bioRxiv2024

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

BackgroundPrior 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.

neuroscience↗

bioRxiv2023

Reinforcement learning in Parkinson disease is not associated with inflammatory tone

Parkinsons disease (PD) is associated with large variability in the development and severity of both motor and nonmotor symptoms, including depression and impulse control disorder. Neuroinflammation might contribute to this heterogeneity, given its association with dopaminergic signalling, neuropsychiatric symptoms, and reward versus punishment learning. Here, we assessed the effect of inflammatory tone on probabilistic reinforcement learning and impulse control disorders in PD. We measured computational learning model-based neural reward prediction error and expected value signals in frontostriatal circuity during reinforcement learning using functional MRI. In addition, we acquired cerebral spinal fluid of 74 PD patients and screened for 13 inflammatory factors, including our primary marker of interest IL-6, previously implicated in reward learning signaling in the ventral striatum. In contrast to our prediction, we found no association between inflammatory tone and any of the behavioural or neural reinforcement learning parameters. Furthermore, we did we not find any correlation between inflammatory tone and depressive or impulsive PD symptoms. Exploratory analyses revealed a negative association between MCP-1 and reward prediction error signals in the ventral striatum, an observation that should be replicated in future work. The null findings might reflect the fact that measurements were taken ON medication, or that our sample consists of an early disease stage cohort that may be too small to detect these effects, or that IL-6 is a suboptimal marker for inflammatory tone, or a combination of these factors.

neuroscience↗

bioRxiv2023

Divergent associations of slow-wave sleep vs. REM sleep with plasma amyloid-beta

BackgroundRecent evidence shows that during slow-wave sleep (SWS), the brain is cleared from potentially toxic metabolites, such as the amyloid-beta protein. Poor sleep or elevated cortisol levels can worsen amyloid-beta clearance, potentially leading to the formation of amyloid plaques, a neuropathological hallmark of Alzheimers disease. Here, we explore how nocturnal neural and endocrine activity affects amyloid-beta fluctuations in the peripheral blood as a reflection of cerebral clearance. MethodsSimultaneous polysomnography and all-night blood sampling were acquired in 60 healthy volunteers aged 20-68 years old. Nocturnal plasma concentrations of two amyloid-beta species (amyloid-beta-40 and amyloid-beta-42), cortisol, and growth hormone were assessed every 20 minutes from 23:00-7:00. Amyloid-beta fluctuations were modeled with sleep stages, (non)-oscillatory power, and hormones as predictors while controlling for age and multiple comparisons. Time lags between the predictors and amyloid-beta ranged from 20 to 120min. FindingsThe amyloid-beta-40 and amyloid-beta-42 levels correlated positively with growth hormone concentrations, SWS proportion, slow-wave (0.3-4Hz) oscillatory and high-band (30-48Hz) non-oscillatory power, but negatively with cortisol concentrations and rapid eye movement sleep (REM) proportion measured 40-100min before (all t-values>|3|, p-values<0.003). Older participants showed higher amyloid-beta-40 levels. InterpretationSlow-wave oscillations are associated with higher plasma amyloid-beta levels, reflecting their contribution to cerebral amyloid-beta clearance across the blood-brain barrier. REM sleep is related to decreased amyloid-beta plasma levels; however, this link may reflect passive aftereffects of SWS and not REMs effects per se. Strong associations between cortisol, growth hormone, and amyloid-beta presumably reflect the sleep-regulating role of the corresponding releasing hormones. A positive association between age and amyloid-beta-40 may indicate that peripheral clearance becomes less efficient with age. Our study provides important insights into the specificity of different sleep features effects on brain clearance and suggests that cortisol nocturnal fluctuations may serve as a new marker of clearance efficiency.

neuroscience↗