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Apolipoprotein E allele 4 effects on Single-Subject Gray Matter Networks in Mild Cognitive Impairment.

ABSTRACT: There is evidence that gray matter networks are disrupted in Mild Cognitive Impairment (MCI) and associated with cognitive impairment and faster disease progression. However, it remains unknown how these alterations are related to the presence of Apolipoprotein E isoform E4 (ApoE4), the most prominent genetic risk factor for late-onset Alzheimer's disease (AD). To investigate this topic at the individual level, we explore the impact of ApoE4 and the disease progression on the Single-Subject Gray Matter Networks (SSGMNets) using the graph theory approach. Our data sample comprised 200 MCI patients selected from the ADNI database, classified as non-Converters and Converters (will progress into AD). Each group included 50 ApoE4-positive ('Carriers', ApoE4 + ) and 50 ApoE4-negative ('non-Carriers', ApoE4-). The SSGMNets were estimated from structural MRIs at two-time points: baseline and conversion. We investigated whether altered network topological measures at baseline and their rate of change (RoC) between baseline and conversion time points were associated with ApoE4 and disease progression. We also explored the correlation of SSGMNets attributes with general cognition score (MMSE), memory (ADNI-MEM), and CSF-derived biomarkers of AD (Aβ42, T-tau, and P-tau). Our results showed that ApoE4 and the disease progression modulated the global topological network properties independently but not in their RoC. MCI converters showed a lower clustering index in several regions associated with neurodegeneration in AD. The SSGMNets' topological organization was revealed to be able to predict cognitive and memory measures. The findings presented here suggest that SSGMNets could indeed be used to identify MCI ApoE4 Carriers with a high risk for AD progression.

SUBMITTER: Sanabria-Diaz G

PROVIDER: S-EPMC8405842 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Background: Voxel-based morphometry (VBM) has been widely used to investigate structural alterations in amnesia mild cognitive impairment (aMCI). However, inconsistent results have hindered our understanding of the exact neuropathology related to aMCI. Objectives: Our aim was to systematically review the literature reporting VBM on aMCI to elucidate consistent gray matter alterations, their functional characterization, and corresponding co-activation patterns. Methods: The PubMed, Web of Science, and EMBASE databases were searched for VBM studies on aMCI published from inception up to June 2020. Peak coordinates were extracted from clusters that showed significant gray matter differences between aMCI patients and healthy controls (HC). Meta-analysis was performed using seed-based d mapping with the permutation of subject images (SDM-PSI), a newly improved meta-analytic method. Functional characterization and task-based co-activation patterns using the BrainMap database were performed on significant clusters to explore their functional roles. Finally, VBM was performed based on the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset to further support the findings. Results: A total of 31 studies with 681 aMCI patients and 837 HC were included in this systematic review. The aMCI group showed significant gray matter atrophy in the left amygdala and right hippocampus, which was consistent with results from the ADNI dataset. Functional characterization revealed that these regions were mainly associated with emotion, cognition, and perception. Further, meta-regression analysis demonstrated that gray matter atrophy in the left inferior frontal gyrus and the left angular gyrus was significantly associated with cognitive impairment in the aMCI group. Conclusions: The findings of gray matter atrophy in the left amygdala and right hippocampus are highly consistent and robust, and not only offer a better understanding of the underlying neuropathology but also provide accurate potential biomarkers for aMCI.

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Apolipoprotein E allele 4 effects on Single-Subject Gray Matter Networks in Mild Cognitive Impairment.

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