Fabrizio Tagliavini (Italy)
Neurological Institute C. Besta IRCCS Foundation Scientific DirectionAuthor Of 1 Presentation
BRAIN METABOLISM, AMYLOID LOAD AND NEUROPSYCHOLOGICAL CORRELATES IN PRECLINICAL DEMENTIA STAGES
- Giacomo Tondo (Italy)
Abstract
Background and Aims:
This multicenter study aimed to investigate the presence of early cognitive, behavioural and brain changes in individuals with subjective cognitive decline (SCD) and pre-Mild Cognitive Impairment (pre-MCI).
Methods:
Data were derived from the RETE-AD project (NET‐2011‐02346784). Ninety-eight subjects (SCD=46; pre-MCI=52) underwent baseline neuropsychological/neurobehavioral evaluation and FDG-PET. Sixty-eight underwent also amyloid-PET. Neuropsychological/Neuropsychiatric measures were analyzed by implementing a Principal Component Analysis (PCA) to identify the emergence of principal clinical profiles.
Results:
FDG-PET revealed brain hypometabolism in 65% of subjects, with a frontal-like pattern as the most frequent (28%). Neuropsychiatric symptoms were highly prevalent in the whole sample (79%). Only 25% of subjects were classified as amyloid-positive. The PCA showed three neuropsychological factors: 1) mnemonic, correlating with hypometabolism in temporal-parietal regions; 2) executive/visuo-motor, correlating with hypometabolism in frontal, occipital cortex and basal ganglia; 3) visuo-spatial/constructional, correlating with metabolism in fronto-parietal cortices. Two neuropsychiatric factors emerged: 1) affective, correlating with hypometabolism in orbito-frontal, cingulate cortex, insula; 2) hyperactive/psychotic, correlating with hypometabolism in widespread frontal, temporal and parietal areas.
Conclusions:
FDG-PET demonstrated altered brain metabolism already in the preclinical dementia phase, amyloid positivity was uncommon. Different neuropsychological/neuropsychiatric profiles emerged in this stage, correlating with neuronal dysfunction in specific brain regions. SCD and pre-MCI represent heterogeneous populations with different possible underlying etiologies, including normal and reverting conditions, brain dysfunctional correlates, as well as neurodegenerative diseases, such as Alzheimer’s disease, frontotemporal degeneration, other tauopathies. All the above indicates the importance of an extensive clinical and instrumental approach for the correct identification of different prognostic patterns.