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Functional Characterization of Atrophy Patterns Related to Cognitive Impairment.

ABSTRACT: Introduction: Mild cognitive impairment (MCI) is a heterogenous syndrome considered as a risk factor for developing dementia. Previous work examining morphological brain changes in MCI has identified a temporo-parietal atrophy pattern that suggests a common neuroanatomical denominator of cognitive impairment. Using functional connectivity analyses of structurally affected regions in MCI, we aimed to investigate and characterize functional networks formed by these regions that appear to be particularly vulnerable to disease-related disruptions. Methods: Areas of convergent atrophy in MCI were derived from a quantitative meta-analysis and encompassed left and right medial temporal (i.e., hippocampus, amygdala), as well as parietal regions (precuneus), which were defined as seed regions for connectivity analyses. Both task-based meta-analytical connectivity modeling (MACM) based on the BrainMap database and task-free resting-state functional MRI in a large cohort of older adults from the 1000BRAINS study were applied. We additionally assessed behavioral characteristics associated with the seed regions using BrainMap meta-data and investigated correlations of resting-state connectivity with age. Results: The left temporal seed showed stronger associations with a fronto-temporal network, whereas the right temporal atrophy cluster was more linked to cortico-striatal regions. In accordance with this, behavioral analysis indicated an emphasis of the left temporal seed on language generation, and the right temporal seed was associated with the domains of emotion and attention. Task-independent co-activation was more pronounced in the parietal seed, which demonstrated stronger connectivity with a frontoparietal network and associations with introspection and social cognition. Correlation analysis revealed both decreasing and increasing functional connectivity with higher age that may add to pathological processes but also indicates compensatory mechanisms of functional reorganization with increasing age. Conclusion: Our findings provide an important pathophysiological link between morphological changes and the clinical relevance of major structural damage in MCI. Multimodal analysis of functional networks related to areas of MCI-typical atrophy may help to explain cognitive decline and behavioral alterations not tractable by a mere anatomical interpretation and therefore contribute to prognostic evaluations.

SUBMITTER: Schnellbacher GJ

PROVIDER: S-EPMC6993791 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Functional Characterization of Atrophy Patterns Related to Cognitive Impairment.

Schnellbächer Gereon J GJ Hoffstaedter Felix F Eickhoff Simon B SB Caspers Svenja S Nickl-Jockschat Thomas T Fox Peter T PT Laird Angela R AR Schulz Jörg B JB Reetz Kathrin K Dogan Imis I

Frontiers in neurology 20200124

<b>Introduction:</b> Mild cognitive impairment (MCI) is a heterogenous syndrome considered as a risk factor for developing dementia. Previous work examining morphological brain changes in MCI has identified a temporo-parietal atrophy pattern that suggests a common neuroanatomical denominator of cognitive impairment. Using functional connectivity analyses of structurally affected regions in MCI, we aimed to investigate and characterize functional networks formed by these regions that appear to be ...[more]

PMID: 32038473

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Project description:BackgroundAmyloid pathology in subjects with mild cognitive impairment (MCI) is an important risk factor for progression to dementia due to Alzheimer's disease. Predicting the onset of dementia is challenging even in the presence of amyloid, as time to progression varies considerably among patients and depends on the onset of neurodegeneration. Survival analysis can account for variability in time to event, but has not often been applied to MRI measurements beyond singular predefined brain regions such as the hippocampus. Here we used a voxel-wise survival analysis to identify in an unbiased fashion brain regions where decreased gray matter volume is associated with time to dementia, and assessed the effects of amyloid on these associations.MethodsWe included 276 subjects with MCI (mean age 67?±?8, 41% female, mean Mini-Mental State Examination 26.6?±?2.4), baseline 3D T1-weighted structural MRI, baseline cerebrospinal fluid (CSF) biomarkers, and prospective clinical follow-up. We fitted for each voxel a proportional Cox hazards regression model to study whether decreased gray matter volume predicted progression to dementia in the total sample, and stratified for baseline amyloid status.ResultsDementia at follow-up occurred in 122 (44%) subjects over an average follow-up period of 2.5?±?1.5 years. Baseline amyloid positivity was associated with progression to dementia (hazard ratio 2.4, p?<?0.001). Within amyloid-positive subjects, decreased gray matter volume in the hippocampal, temporal, parietal, and frontal regions was associated with more rapid progression to dementia (median (interquartile range) hazard ratio across significant voxels 1.35 (1.32-1.40)). Repeating the analysis in amyloid-negative subjects revealed similar patterns (median (interquartile range) hazard ratio 1.76 (1.66-1.91)).ConclusionsIn subjects with MCI, both abnormal amyloid CSF and decreased gray matter volume were associated with future progression to dementia. The spatial pattern of decreased gray matter volume associated with progression to dementia was consistent for amyloid-positive and amyloid-negative subjects.

Dataset Information

Functional Characterization of Atrophy Patterns Related to Cognitive Impairment.

Publications

Functional Characterization of Atrophy Patterns Related to Cognitive Impairment.

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