Dataset Information

Brain Small-Worldness Properties and Perceived Fatigue in Mild Cognitive Impairment.

ABSTRACT:

Background

Perceived fatigue is among the most common complaints in older adults and is substantially influenced by diminished resources or impaired structure of widespread cortical and subcortical regions. Alzheimer's disease and its preclinical stage-mild cognitive impairment (MCI)-are considered a brain network disease. It is unknown, however, whether those with MCI will therefore perceive worse fatigue, and whether an impaired global brain network will worsen their experience of fatigue.

Methods

In this pilot case-control study of age-, sex-, and education-matched MCI and their cognitively healthy counterparts (HCs), perceived fatigue was measured using Multidimensional Fatigue Inventory, and diffusion tensor imaging tractography data were analyzed using graph theory methods to explore small-worldness properties: segregation and integration.

Results

Perceived fatigue was more severe in MCI than HCs. Despite a trend for greater network alterations in MCI, there were no significant group differences in integration or segregation. Greater perceived fatigue was related to higher segregation across groups; more perceived fatigue was related to higher segregation and lower integration in MCI but not HCs.

Conclusion

Findings of this study support the notion that altered whole-brain small-worldness properties in brain aging or neurodegeneration may underpin perceived fatigue.

SUBMITTER: Kukla B

PROVIDER: S-EPMC8893186 | biostudies-literature | 2022 Mar

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Brain Small-Worldness Properties and Perceived Fatigue in Mild Cognitive Impairment.

Kukla Bennett B Anthony Mia M Chen Shuyi S Turnbull Adam A Baran Timothy M TM Lin Feng V FV

The journals of gerontology. Series A, Biological sciences and medical sciences 20220301 3

<h4>Background</h4>Perceived fatigue is among the most common complaints in older adults and is substantially influenced by diminished resources or impaired structure of widespread cortical and subcortical regions. Alzheimer's disease and its preclinical stage-mild cognitive impairment (MCI)-are considered a brain network disease. It is unknown, however, whether those with MCI will therefore perceive worse fatigue, and whether an impaired global brain network will worsen their experience of fati ...[more]

PMID: 33733662

Similar Datasets

Project description:OBJECTIVE:To identify a neuroimaging signature predictive of brain amyloidosis as a screening tool to identify individuals with mild cognitive impairment (MCI) that are most likely to have high levels of brain amyloidosis or to be amyloid-free. METHODS:The prediction model cohort included 62 MCI subjects screened with structural magnetic resonance imaging (MRI) and (11) C-labeled Pittsburgh compound B positron emission tomography (PET). We identified an anatomical shape variation-based neuroimaging predictor of brain amyloidosis and defined a structural MRI-based brain amyloidosis score (sMRI-BAS). Amyloid beta positivity (A?(+) ) predictive power of sMRI-BAS was validated on an independent cohort of 153 MCI patients with cerebrospinal fluid A?1-42 biomarker data but no amyloid PET scans. We compared the A?(+) predictive power of sMRI-BAS to those of apolipoprotein E (ApoE) genotype and hippocampal volume, the 2 most relevant candidate biomarkers for the prediction of brain amyloidosis. RESULTS:Anatomical shape variations predictive of brain amyloidosis in MCI embraced a characteristic spatial pattern known for high vulnerability to Alzheimer disease pathology, including the medial temporal lobe, temporal-parietal association cortices, posterior cingulate, precuneus, hippocampus, amygdala, caudate, and fornix/stria terminals. A?(+) prediction performance of sMRI-BAS and ApoE genotype jointly was significantly better than the performance of each predictor separately (area under the curve [AUC] = 0.88 vs AUC = 0.70 and AUC = 0.81, respectively) with >90% sensitivity and specificity at 20% false-positive rate and false-negative rate thresholds. Performance of hippocampal volume as an independent predictor of brain amyloidosis in MCI was only marginally better than random chance (AUC = 0.56). INTERPRETATION:As one of the first attempts to use an imaging technique that does not require amyloid-specific radioligands for identification of individuals with brain amyloidosis, our findings could lead to development of multidisciplinary/multimodality brain amyloidosis biomarkers that are reliable, minimally invasive, and widely available.

Dataset Information

Brain Small-Worldness Properties and Perceived Fatigue in Mild Cognitive Impairment.

Background

Methods

Results

Conclusion

Publications

Brain Small-Worldness Properties and Perceived Fatigue in Mild Cognitive Impairment.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets