Amyloid-independent functional neural correlates of episodic memory in amnestic mild cognitive impairment

Increased anterior insula connectivity associated with cognitive maintenance in amnestic mild cognitive impairment: a longitudinal study

The insula, a crucial hub of the human brain network, can be divided into anterior and posterior regions. Previous studies have reported that different insula subregions play various roles in amnestic mild cognitive impairment (aMCI). However, the longitudinal changes in the functional connectivity (FC) of each insula subregion in aMCI patients over time remain unclear. Twenty aMCI patients and 20 healthy controls (HCs) were recruited and underwent resting-state functional magnetic resonance imaging (fMRI) scans and neuropsychological assessments at baseline and at the 15-month follow-up. FMRI data were preprocessed using SPM 12 and the CONN toolbox. Two-way analysis of covariance was used to compare longitudinal changes in the FC of each insula subregion with covariates including sex, age, education, follow-up interval, volume of gray matter, and global correlation (GCOR). Pearson's correlation was used to evaluate the relationship between insula subregional FC and neuropsychological performance in aMCI patients. In aMCI patients, the right anterior insula exhibited significantly increased FC with the left anterior cingulate cortex, whereas the left posterior insula exhibited decreased FC with the right precuneus compared with HCs. Furthermore, FC between the right anterior insula and left anterior cingulate cortex was significantly correlated with global cognition at follow-up. The current findings revealed different functional alterations in the insula subregions and provided new insights into the neurodegenerative process in aMCI patients.

The cognitive dysfunction of claustrum on Alzheimer's disease: A mini-review

Alzheimer's disease (AD) is one of the most common neurodegenerative diseases characterized by cognitive deficits and dementia. AD entails predominant pathological characteristics including amyloid beta (Aβ) plaque formation, neurofibrillary entanglements, and brain atrophy, which gradually result in cognitive dysfunctions. Studies showed that these pathological changes are found in a myriad of brain structures, including the claustrum (CLA), a nucleus that penetrates deeply into the brain and is extensively interconnected to various brain structures. The CLA modulates many aspects of cognitive functions, with attention, executive function, visuospatial ability, language, and memory in particular. It is also implicated in multiple neuropsychiatric disorders, of which one worthy of particular attention is AD-related cognitive impairments. To inspire novel AD treatment strategies, this review has summarized the CLA functionality in discriminative cognitive dysfunctions in AD. And then propose an array of potential mechanisms that might contribute to the cognitive impairments caused by an abnormal CLA physiology. We advocate that the CLA might be a new promising therapeutic target in combination with existing anti-AD drugs and brain stimulation approaches for future AD treatment.

Harnessing forgetfulness: can episodic-memory tests predict early Alzheimer's disease?

A rapid increase in the number of patients with Alzheimer's disease (AD) is expected over the next decades. Accordingly, there is a critical need for early-stage AD detection methods that can enable effective treatment strategies. In this study, we consider the ability of episodic-memory measures to predict mild cognitive impairment (MCI) to AD conversion and thus, detect early-stage AD. For our analysis, we studied 307 participants with MCI across four years using data from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Using a binary logistic regression, we compared episodic-memory tests to each other and to prominent neuroimaging methods in MCI converter (MCI participants who developed AD) and MCI non-converter groups (MCI participants who did not develop AD). We also combined variables to test the accuracy of mixed-predictor models. Our results indicated that the best predictors of MCI to AD conversion were the following: a combined episodic-memory and neuroimaging model in year one (59.8%), the Rey Auditory Verbal Learning Test in year two (71.7%), a mixed episodic-memory predictor model in year three (77.7%) and the Logical Memory Test in year four (77.2%) of ADNI. Overall, we found that individual episodic-memory measure and mixed models performed similarly when predicting MCI to AD conversion. Comparatively, individual neuroimaging measures predicted MCI conversion worse than chance. Accordingly, our results indicate that episodic-memory tests could be instrumental in detecting early-stage AD and enabling effective treatment.

Determining affected memory domains in patients with amnestic mild cognitive impairment using computerized and interactive tests

This study explores different episodic memory domains, namely object, temporal and spatial memory, affected in patients with a clinical diagnosis of single domain amnestic mild cognitive impairment (aMCI). 15 aMCI patients and 25 healthy controls were recruited and tested. Object, spatial, and temporal memory were tested using computerized tasks and again in interactive, real-world tasks. Controls outperformed patients on the object computerized task and showed a trend toward significance for the computerized spatial and temporal tasks, but there was no difference in spatial and temporal memory when using the interactive tasks, indicating the employment of compensatory mechanisms in patients to overcome some of the memory impairments associated with aMCI. These findings highlight that aMCI patients might delay seeking help due to compensatory mechanisms which mask their deficits in real-world situations.

Altered Insular Subregional Connectivity Associated With Cognitions for Distinguishing the Spectrum of Pre-clinical Alzheimer's Disease

Background: Subjective cognitive decline (SCD) and amnestic mild cognitive impairment (aMCI) are regarded as part of the pre-clinical Alzheimer's disease (AD) spectrum. The insular subregional networks are thought to have diverse intrinsic connectivity patterns that are involved in cognitive and emotional processing. We set out to investigate convergent and divergent altered connectivity patterns of the insular subregions across the spectrum of pre-clinical AD and evaluated how well these patterns can differentiate the pre-clinical AD spectrum.

Method: Functional connectivity (FC) analyses in insular subnetworks were carried out among 38 patients with SCD, 56 patients with aMCI, and 55 normal controls (CNs). Logistic regression analyses were used to construct models for aMCI and CN, as well as SCD and CN classification. Finally, we conducted correlation analyses to measure the relationship between FCs of altered insular subnetworks and cognition.

Results: Patients with SCD presented with reduced FC in the bilateral cerebellum posterior lobe and increased FC in the medial frontal gyrus and the middle temporal gyrus. On the other hand, patients with aMCI largely presented with decreased FC in the bilateral inferior parietal lobule, the cerebellum posterior lobe, and the anterior cingulate cortex, as well as increased FC in the medial and inferior frontal gyrus, and the middle and superior temporal gyrus. Logistic regression analyses indicated that a model composed of FCs among altered insular subnetworks in patients with SCD was able to appropriately classify 83.9% of patients with SCD and CN, with an area under the receiver operating characteristic (ROC) curve (AUC) of 0.876, 81.6% sensitivity, and 81.8% specificity. A model consisting of altered insular subnetwork FCs in patients with aMCI was able to appropriately classify 86.5% of the patients with aMCI and CNs, with an AUC of 0.887, 80.4% sensitivity, and 83.6% specificity. Furthermore, some of the FCs among altered insular subnetworks were significantly correlated with episodic memory and executive function.

Conclusions: Patients with SCD and aMCI are likely to share similar convergent and divergent altered intrinsic FC patterns of insular subnetworks as the pre-clinical AD spectrum, and presented with abnormalities among subnetworks. Based on these abnormalities, individuals can be correctly differentiated in the pre-clinical AD spectrum. These results suggest that alterations in insular subnetworks can be utilized as a potential biomarker to aid in conducting a clinical diagnosis of the spectrum of pre-clinical AD.

Apolipoprotein E ε4 Allele Is Associated with Reduced Retention of the "Where" Memory Component in Cognitively Intact Older Adults

OBJECTIVE

The present study investigated the effect of the apolipoprotein E (ApoE) ε4 allele on the four memory components (i.e., who, when, where, and what) among cognitively intact older adults.

METHODS

Participants comprised 47 cognitively intact older adults, who were classified into 2 groups based on the presence or absence of at least 1 ApoE ε4 allele. All participants completed standardized neuropsychological tests, including the Logical Memory subtest of the Wechsler Memory Scale-III with a revised scoring method.

RESULTS

The results revealed that recollection for each component followed a pattern of who > what > when = where. Furthermore, a significant group-by-component-by-condition interaction indicated that the presence of the ApoE ε4 allele resulted in a disproportionately detrimental effect on the where component retention in the verbal episodic memory task; this finding was significantly correlated with hippocampal volumes.

CONCLUSION

These results highlighted the importance of evaluating the subcomponents of verbal episodic memory to detect subtle cognitive differences related to ApoE ε4 status, which could help elucidate the mechanism behind the cascades caused by ApoE ε4 in the trajectories of cognitive aging.

Distinct Neural Correlates of Executive Function by Amyloid Positivity and Associations with Clinical Progression in Mild Cognitive Impairment

PURPOSE

This study aimed to identify the neural basis of executive function (EF) in amnestic mild cognitive impairment (aMCI) according to beta-amyloid (Aβ) positivity. Furthermore, we explored if the identified brain areas could serve as predictors for clinical progression.

MATERIALS AND METHODS

We included individuals with aMCI using data from [¹⁸F]-florbetapir-positron emission tomography (PET), fluorodeoxyglucose-PET, and EF scores, as well as follow-up clinical severity scores at 1 and 5 years from baseline from the Alzheimer's Disease Neuroimaging Initiative database. The correlations between EF score and regional cerebral glucose metabolism (rCMglc) were analyzed separately for aMCI with low Aβ burden (aMCI Aβ-, n=230) and aMCI with high Aβ burden (aMCI Aβ+, n=268). Multiple linear regression analysis was conducted to investigate the associations between rCMglc and clinical progression.

RESULTS

Longitudinal courses differed between aMCI Aβ- and aMCI Aβ+ groups. On average, aMCI Aβ- subjects maintained their level of clinical severity, whereas aMCI Aβ+ subjects showed progression. EF impairment in aMCI Aβ- was related to the anterior cingulate cortex (ACC), whereas that in aMCI Aβ+ was related to Alzheimer's Disease-vulnerable brain regions. ACC and the posterior cingulate cortex were associated with clinical progression in aMCI Aβ- and aMCI Aβ+, respectively.

CONCLUSION

Our findings suggest that although MCI subjects showed similar behavioral phenotypes at the time of diagnosis, EF and further progression were associated with different brain regions according to Aβ burden. Clarification of the etiologies and nature of EF impairment in aMCI are critical for disease prognosis and management.

Intrinsic Functional Hypoconnectivity in Core Neurocognitive Networks Suggests Central Nervous System Pathology in Patients with Myalgic Encephalomyelitis: A Pilot Study

Exact low resolution electromagnetic tomography (eLORETA) was recorded from nineteen EEG channels in nine patients with myalgic encephalomyelitis (ME) and 9 healthy controls to assess current source density and functional connectivity, a physiological measure of similarity between pairs of distributed regions of interest, between groups. Current source density and functional connectivity were measured using eLORETA software. We found significantly decreased eLORETA source analysis oscillations in the occipital, parietal, posterior cingulate, and posterior temporal lobes in Alpha and Alpha-2. For connectivity analysis, we assessed functional connectivity within Menon triple network model of neuropathology. We found support for all three networks of the triple network model, namely the central executive network (CEN), salience network (SN), and the default mode network (DMN) indicating hypo-connectivity in the Delta, Alpha, and Alpha-2 frequency bands in patients with ME compared to controls. In addition to the current source density resting state dysfunction in the occipital, parietal, posterior temporal and posterior cingulate, the disrupted connectivity of the CEN, SN, and DMN appears to be involved in cognitive impairment for patients with ME. This research suggests that disruptions in these regions and networks could be a neurobiological feature of the disorder, representing underlying neural dysfunction.

Altered Functional Connectivity of the Basal Nucleus of Meynert in Mild Cognitive Impairment: A Resting-State fMRI Study

Background: Cholinergic dysfunction plays an important role in mild cognitive impairment (MCI). The basal nucleus of Meynert (BNM) provides the main source of cortical cholinergic innervation. Previous studies have characterized structural changes of the cholinergic basal forebrain in individuals at risk of developing Alzheimer’s disease (AD). However, whether and how functional connectivity of the BNM (BNM-FC) is altered in MCI remains unknown.

Objective: The aim of this study was to identify alterations in BNM-FC in individuals with MCI as compared to healthy controls (HCs), and to examine the relationship between these alterations with neuropsychological measures in individuals with MCI.

Method: One-hundred-and-one MCI patients and 103 HCs underwent resting-state functional magnetic resonance imaging (rs-fMRI). Imaging data were processed with SPM8 and CONN software. BNM-FC was examined via correlation in low frequency fMRI signal fluctuations between the BNM and all other brain voxels. Group differences were examined with a covariance analysis with age, gender, education level, mean framewise displacement (FD) and global correlation (GCOR) as nuisance covariates. Pearson’s correlation was conducted to evaluate the relationship between the BNM-FC and clinical assessments.

Result: Compared with HCs, individuals with MCI showed significantly decreased BNM-FC in the left insula extending into claustrum (insula/claustrum). Furthermore, greater decrease in BNM-FC with insula/claustrum was associated with more severe impairment in immediate recall during Auditory Verbal Learning Test (AVLT) in MCI patients.

Conclusion: MCI is associated with changes in BNM-FC to the insula/claustrum in relation to cognitive impairments. These new findings may advance research of the cholinergic bases of cognitive dysfunction during healthy aging and in individuals at risk of developing AD.

Recent publications from the Alzheimer's Disease Neuroimaging Initiative: Reviewing progress toward improved AD clinical trials

INTRODUCTION

The Alzheimer's Disease Neuroimaging Initiative (ADNI) has continued development and standardization of methodologies for biomarkers and has provided an increased depth and breadth of data available to qualified researchers. This review summarizes the over 400 publications using ADNI data during 2014 and 2015.

METHODS

We used standard searches to find publications using ADNI data.

RESULTS

(1) Structural and functional changes, including subtle changes to hippocampal shape and texture, atrophy in areas outside of hippocampus, and disruption to functional networks, are detectable in presymptomatic subjects before hippocampal atrophy; (2) In subjects with abnormal β-amyloid deposition (Aβ+), biomarkers become abnormal in the order predicted by the amyloid cascade hypothesis; (3) Cognitive decline is more closely linked to tau than Aβ deposition; (4) Cerebrovascular risk factors may interact with Aβ to increase white-matter (WM) abnormalities which may accelerate Alzheimer's disease (AD) progression in conjunction with tau abnormalities; (5) Different patterns of atrophy are associated with impairment of memory and executive function and may underlie psychiatric symptoms; (6) Structural, functional, and metabolic network connectivities are disrupted as AD progresses. Models of prion-like spreading of Aβ pathology along WM tracts predict known patterns of cortical Aβ deposition and declines in glucose metabolism; (7) New AD risk and protective gene loci have been identified using biologically informed approaches; (8) Cognitively normal and mild cognitive impairment (MCI) subjects are heterogeneous and include groups typified not only by "classic" AD pathology but also by normal biomarkers, accelerated decline, and suspected non-Alzheimer's pathology; (9) Selection of subjects at risk of imminent decline on the basis of one or more pathologies improves the power of clinical trials; (10) Sensitivity of cognitive outcome measures to early changes in cognition has been improved and surrogate outcome measures using longitudinal structural magnetic resonance imaging may further reduce clinical trial cost and duration; (11) Advances in machine learning techniques such as neural networks have improved diagnostic and prognostic accuracy especially in challenges involving MCI subjects; and (12) Network connectivity measures and genetic variants show promise in multimodal classification and some classifiers using single modalities are rivaling multimodal classifiers.

DISCUSSION

Taken together, these studies fundamentally deepen our understanding of AD progression and its underlying genetic basis, which in turn informs and improves clinical trial design.