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Detection of Neuritic Plaques in Alzheimer's Disease Mouse Model
Published on: July 26, 2011
Plasma S100β is a predictor for pathology and cognitive decline in Alzheimer's disease
Geetika Nehra1, Bryan J Maloney1, Rebecca R Smith1
1Sanders-Brown Center on Aging, College of Medicine, University of Kentucky, 760 Press Ave, 124 HKRB, Lexington, KY, 40536-0679, USA.
Background:
Blood-brain barrier dysfunction is one characteristic of Alzheimer's disease (AD) and is recognized as both a cause and consequence of the pathological cascade leading to cognitive decline. The goal of this study was to assess markers for barrier dysfunction in postmortem tissue samples from research participants who were either cognitively normal individuals (CNI) or diagnosed with AD at the time of autopsy and determine to what extent these markers are associated with AD neuropathologic changes (ADNC) and cognitive impairment.
Methods:
We used postmortem brain tissue and plasma samples from 19 participants: 9 CNI and 10 AD dementia patients who had come to autopsy from the University of Kentucky AD Research Center (UK-ADRC) community-based cohort; all cases with dementia had confirmed severe ADNC. Plasma samples were obtained within 2 years of autopsy. Aβ40, Aβ42, and tau levels in brain tissue samples were quantified by ELISA. Cortical brain sections were cleared using the X-CLARITY™ system and immunostained for neurovascular unit-related proteins. Brain slices were then imaged using confocal microscopy and analyzed for microvascular diameters and immunoreactivity coverage using Fiji/ImageJ. Isolated human brain microvessels were assayed for tight-junction protein expression using the JESS™ automated Western blot system. S100 calcium-binding protein B (S100β), matrix metalloproteinase (MMP)-2, MMP-9, and neuron-specific enolase (NSE) levels in plasma were quantified by ELISA. All outcomes were assessed for linear associations with global cognitive function (MMSE, CDR) and cerebral atrophy scores by Pearson, polyserial, or polychoric correlation, as appropriate, along with generalized linear modeling or generalized linear mixed-level modeling.
Results:
As expected, we detected elevated Aβ and tau pathology in brain tissue sections from AD patients compared to CNI. However, we found no differences in microvascular diameters in cleared AD and CNI brain tissue sections. We also observed no differences in claudin-5 protein levels in capillaries isolated from AD and CNI tissue samples. Plasma biomarker analysis showed that AD patients had 12.4-fold higher S100β plasma levels, twofold lower NSE plasma levels, 2.4-fold higher MMP-9 plasma levels, and 1.2-fold lower MMP-2 plasma levels than CNI. Data analysis revealed that elevated S100β plasma levels were predictive of AD pathology and cognitive impairment.
Conclusion:
Our data suggest that among different markers relevant to barrier dysfunction, plasma S100β is the most promising diagnostic biomarker for ADNC. Further investigation is necessary to assess how plasma S100β levels relate to these changes and whether they may predict clinical outcomes, particularly in the prodromal and early stages of AD.
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