Literature DB >> 28675110

Metabolic regional and network changes in Alzheimer's disease subtypes.

Karl Herholz1,2, Cathleen Haense1, Alex Gerhard1,2,3,4, Matthew Jones2,3, José Anton-Rodriguez1, Shailendra Segobin1, Julie S Snowden2,3, Jennifer C Thompson2,3, Christopher Kobylecki2,3.   

Abstract

Clinical variants of Alzheimer's disease (AD) include the common amnestic subtype as well as subtypes characterised by leading visual processing impairments or by multimodal neurocognitive deficits. We investigated regional metabolic patterns and networks between AD subtypes. The study comprised 9 age-matched controls and 25 patients with mild to moderate AD. Methods included clinical and neuropsychological assessment, high-resolution FDG PET and T1-weighted 3D MR imaging with PET-MR coregistration, grey matter segmentation, atlas-based regions-of-interest, linear mixed effects and regional correlation analysis. Regional metabolic patterns differed significantly between groups, but significant hypometabolism in the posterior cingulate cortex (PCC) was common to all subtypes. The most distinctive regional abnormality was occipital hypometabolism in the visual subtype. In controls, two large clusters of positive regional metabolic correlations were observed. The most pronounced breakdown of the normal correlation pattern was found in amnestic patients who, in contrast, showed the least regional focal metabolic deficits. The normal positive correlation between PCC and hippocampus was lost in all subtypes. In conclusion, PCC hypometabolism and metabolic correlation breakdown between PCC and hippocampus are the common functional core of all AD subtypes. Network alterations exceed focal regional impairment and are most prominent in the amnestic subtype.

Entities:  

Keywords:  Alzheimer’s disease; brain imaging; dementia; energy metabolism; positron emission tomography

Mesh:

Year:  2017        PMID: 28675110      PMCID: PMC6168902          DOI: 10.1177/0271678X17718436

Source DB:  PubMed          Journal:  J Cereb Blood Flow Metab        ISSN: 0271-678X            Impact factor:   6.200


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