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Application of multimodal imaging brain biomarkers in large cohort studies to understand the mixed cerebral pathologies of the aging brain

Subject Area Clinical Neurology; Neurosurgery and Neuroradiology
Human Cognitive and Systems Neuroscience
Term from 2014 to 2016
Project identifier Deutsche Forschungsgemeinschaft (DFG) - Project number 258735457
 
Final Report Year 2018

Final Report Abstract

During my research fellowship in the Jagust lab at UC Berkeley, CA, USA I performed five projects focusing on (i) the association between early cerebral small vessel disease (CSVD) and β-amyloid (Aβ) retention, (ii) the interaction between lifestyle, brain structure and cognition, (iii) the equality of various intravital Aβ measures and their ability to predict the course of cognitive function in mild cognitive impairment (MCI), (iv) the comparison of MCI with Alzheimer’s disease (AD) signature neurodegeneration but with or without β-amyloid retention and on (v) the question if imaging measures of neurodegeneration have the potential to mirror postmortal neurofibrillary tangle (NFT) Braak stages. My findings can be summarized as follows: (i) I failed to demonstrate a relationship between CSVD and Aβ, (ii) lifestyle is a complex construct of several co-varying variables, (iii) high cognitive activity together with low vascular risk relates to lower β-amyloid levels, (iv) high education/socioeconomic status together with low smoking prevalence is associated with better preserved cognitive function, which is mediated by larger hippocampal volume, (v) there is high concordance between visual and quantitative amyloid PET measures and cerebrospinal fluid (CSF) Aβ concentrations, with (vi) Aβ positivity relates to worse longitudinal cognitive function, (vii) in MCI with AD signature neurodegeneration Aβ negativity compared to Aβ positivity is related to better sustained glucose metabolism and gray matter volume as well as to better preserved longitudinal cognitive function, and (viii) NFT Braak stages can be best mapped on fluorodeoxyglucose (FDG) PET images using a voxelwise thresholding approach.

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