Neuroanatomic changes and their association with cognitive decline in mild cognitive impairment: a meta-analysis
Mild cognitive impairment (MCI) is an acquired syndrome characterised by cognitive decline not affecting activities of daily living. Using a quantitative meta-analytic approach, we aimed to identify consistent neuroanatomic correlates of MCI and how they are related to cognitive dysfunction. The meta-analysis enrols 22 studies, involving 917 MCI (848 amnestic MCI) patients and 809 healthy controls. Only studies investigating local changes in grey matter and reporting whole-brain results in stereotactic coordinates were included and analysed using the activation likelihood estimation approach. Probabilistic cytoarchitectonic maps were used to compare the localization of the obtained significant effects to histological areas. A correlation between the probability of grey matter changes and cognitive performance of MCI patients was performed. In MCI patients, the meta-analysis revealed three significant clusters of convergent grey matter atrophy, which were mainly situated in the bilateral amygdala and hippocampus, extending to the left medial temporal pole and thalamus, as well as in the bilateral precuneus. A sub-analysis in only amnestic MCI revealed a similar pattern. A voxel-wise analysis revealed a correlation between grey matter reduction and cognitive decline in the right hippocampus and amygdala as well as in the left thalamus. This study provides convergent evidence of a distinct neuroanatomical pattern in MCI. The correlation analysis with cognitive-mnestic decline further highlights the impact of limbic structures and the linkage with data from a functional neuroimaging database provides additional insight into underlying functions. Although different pathologies are underlying MCI, the observed neuroanatomical pattern of structural changes may reflect the common clinical denominator of cognitive impairment.
KeywordsMild cognitive impairment Meta-analysis Voxel-based morphometry Cognitive impairment Activation likelihood estimation approach Mini-mental state examination
ARL, PTF, and SBE were funded by the Human Brain Project (R01-MH074457) and the Initiative and Networking Fund of the Helmholtz Association within the Helmholtz Alliance on Systems Biology (Human Brain Model). JBS received research support from grants of the German Ministry of Education and Research (BMBF) for the projects GeneMove (01GM0503), NGFNplus and Competence Network Degenerative Dementias. SBE and KR were funded by the DFG (Deutsche Forschungsgemeinschaft) Translational Brain Research in Psychiatry and Neurology (DFG ZUK32/1).
Conflict of interest
The authors declare that they have no conflict of interest.
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