Hippocampal dysfunction in amnestic-type mild cognitive impairment: implications for predicting Alzheimer’s risk

Hyperconnectivity of Self-Referential Network as a Predictive Biomarker of the Progression of Alzheimer's Disease

BACKGROUND

Self-referential processing is associated with the progression of Alzheimer's disease (AD), and cerebrospinal fluid (CSF) proteins have become accepted biomarkers of AD.

OBJECTIVE

Our objective in this study was to focus on the relationships between the self-referential network (SRN) and CSF pathology in AD-spectrum patients.

METHODS

A total of 80 participants, including 20 cognitively normal, 20 early mild cognitive impairment (EMCI), 20 late MCI (LMCI), and 20 AD, were recruited for this study. Independent component analysis was used to explore the topological SRN patterns, and the abnormalities of this network were identified at different stages of AD. Finally, CSF pathological characteristics (i.e., CSF Aβ, t-tau, and p-tau) that affected the abnormalities of the SRN were further determined during the progression of AD.

RESULTS

Compared to cognitively normal subjects, AD-spectrum patients (i.e., EMCI, LMCI, and AD) showed a reversing trend toward an association between CSF pathological markers and the abnormal SRN occurring during the progression of AD. However, a certain disease state (i.e., the present LMCI) with a low concentration of CSF tau could evoke more hyperconnectivity of the SRN than other patients with progressively increasing concentrations of CSF tau (i.e., EMCI and AD), and this fluctuation of CSF tau was more sensitive to the hyperconnectivity of the SRN than the dynamic changes of CSF Aβ.

CONCLUSION

The integrity of the SRN was closely associated with CSF pathological characteristics, and these findings support the view that the hyperconnectivity of the SRN will play an important role in monitoring the progression of the pre-dementia state to AD.

Promoter haplotypes of interleukin-10 gene linked to cortex plasticity in subjects with risk of Alzheimer's disease

The Alzheimer's disease (AD) aetiologic event is associated with brain inflammatory processes. In this study, we consider a haplotype of the IL-10 gene promoter region, − 1082A/− 819 T/− 592A (ATA haplotype), which is an additive and independent genetic risk factor for AD. Episodic memory change is the most striking cognitive alteration in AD. It remains unclear whether episodic memory networks can be affected by the ATA haplotype variant in amnestic mild cognitive impairment (aMCI), and if so, how this occurs. Thirty-nine aMCI patients and 30 healthy controls underwent resting-state functional magnetic resonance imaging. An imaging genetics approach was then utilized to investigate disease-related differences in episodic memory networks between the groups based on ATA haplotype-by-aMCI interactions. Gene-brain-behaviour relationships were then further examined. This study found that the ATA haplotype risk variant was associated with abnormal functional communications in the hippocampus-frontoparietal cortices, especially in the left hippocampal network. Moreover, these ATA haplotype carriers showed a distinct phase of hyperactivity in normal aging, with rapid declines of brain function in aMCI subjects when compared to non-ATA haplotype carriers. These findings added to the accumulating evidence that promoter haplotypes of IL-10 may be important modulators of the development of aMCI.

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The inflammatory factor affects the cortex-networks system in subjects with cognitive impairment

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The rapid declines of functional communications in cognitive impairment with ATA haplotype carriers

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Promoter haplotypes of interleukin-10 gene linked to cortex plasticity in cognitive impairment

Classification of Cognitive Level of Patients with Leukoaraiosis on the Basis of Linear and Non-Linear Functional Connectivity

Leukoaraiosis (LA) describes diffuse white matter abnormalities apparent in computed tomography (CT) or magnetic resonance (MR) brain scans. Patients with LA generally show varying degrees of cognitive impairment, which can be classified as cognitively normal (CN), mild cognitive impairment (MCI), and dementia. However, a consistent relationship between the degree of LA and the level of cognitive impairment has not yet been established. We used functional magnetic resonance imaging (fMRI) to explore possible neuroimaging biomarkers for classification of cognitive level in LA. Functional connectivity (FC) between brain regions was calculated using Pearson’s correlation coefficient (PCC), maximal information coefficient (MIC), and extended maximal information coefficient (eMIC). Next, FCs with high discriminative power for different cognitive levels in LA were used as features for classification based on support vector machine. CN and MCI were classified with accuracies of 75.0, 61.9, and 91.1% based on features from PCC, MIC, and eMIC, respectively. MCI and dementia were classified with accuracies of 80.1, 86.2, and 87.4% based on features from PCC, MIC, and eMIC, respectively. CN and dementia were classified with accuracies of 80.1, 89.9, and 94.4% based on features from PCC, MIC, and eMIC, respectively. Our results suggest that features extracted from fMRI were efficient for classification of cognitive impairment level in LA, especially, when features were based on a non-linear method (eMIC).

Plastic modulation of episodic memory networks in the aging brain with cognitive decline

Social-cognitive processing has been posited to underlie general functions such as episodic memory. Episodic memory impairment is a recognized hallmark of amnestic mild cognitive impairment (aMCI) who is at a high risk for dementia. Three canonical networks, self-referential processing, executive control processing and salience processing, have distinct roles in episodic memory retrieval processing. It remains unclear whether and how these sub-networks of the episodic memory retrieval system would be affected in aMCI. This task-state fMRI study constructed systems-level episodic memory retrieval sub-networks in 28 aMCI and 23 controls using two computational approaches: a multiple region-of-interest based approach and a voxel-level functional connectivity-based approach, respectively. These approaches produced the remarkably similar findings that the self-referential processing network made critical contributions to episodic memory retrieval in aMCI. More conspicuous alterations in self-referential processing of the episodic memory retrieval network were identified in aMCI. In order to complete a given episodic memory retrieval task, increases in cooperation between the self-referential processing network and other sub-networks were mobilized in aMCI. Self-referential processing mediate the cooperation of the episodic memory retrieval sub-networks as it may help to achieve neural plasticity and may contribute to the prevention and treatment of dementia.