Neuroanatomical and Neuropsychological Markers of Amnestic MCI: A Three-Year Longitudinal Study in Individuals Unaware of Cognitive Decline

Alterations in Gray Matter Structural Networks in Amnestic Mild Cognitive Impairment: A Source-Based Morphometry Study

Background

Amnestic mild cognitive impairment (aMCI), considered as the prodromal stage of Alzheimer's disease, is characterized by isolated memory impairment and cerebral gray matter volume (GMV) alterations. Previous structural MRI studies in aMCI have been mainly based on univariate statistics using voxel-based morphometry.

Objective

We investigated structural network differences between aMCI patients and cognitively normal older adults by using source-based morphometry, a multivariate approach that considers the relationship between voxels of various parts of the brain.

Methods

Ninety-one aMCI patients and 80 cognitively normal controls underwent structural MRI and neuropsychological assessment. Spatially independent components (ICs) that covaried between participants were estimated and a multivariate analysis of covariance was performed with ICs as dependent variables, diagnosis as independent variable, and age, sex, education level, and site as covariates.

Results

aMCI patients exhibited reduced GMV in the precentral, temporo-cerebellar, frontal, and temporal network, and increased GMV in the left superior parietal network compared to controls (pFWER < 0.05, Holm-Bonferroni correction). Moreover, we found that diagnosis, more specifically aMCI, moderated the positive relationship between occipital network and Mini-Mental State Examination scores (pFWER < 0.05, Holm-Bonferroni correction).

Conclusions

Our results showed GMV alterations in temporo-fronto-parieto-cerebellar networks in aMCI, extending previous results obtained with univariate approaches.

Patterns of longitudinal subcortical atrophy over one year in amnestic mild cognitive impairment and its impact on cognitive performance: a preliminary study

Background/aim

Amnestic mild cognitive impairment (aMCI) is a risk factor for dementia, and thus, it is of interest to enlighten specific brain atrophy patterns in aMCI patients. We aim to define the longitudinal atrophy pattern in subcortical structures and its effect on cognition in patients with aMCI.

Materials and methods

Twenty patients with aMCI and 20 demographically matched healthy controls with baseline and longitudinal structural magnetic resonance imaging scans and neuropsychological assessments were studied. The algorithm FIRST (FMRIB's integrated registration and segmentation tool) was used to obtain volumes of subcortical structures (thalamus, putamen, caudate nucleus, nucleus accumbens, globus pallidus, hippocampus, and amygdala). Correlations between volumes and cognitive performance were assessed.

Results

Compared with healthy controls, aMCI demonstrated subcortical atrophies in the hippocampus (p = 0.001), nucleus accumbens (p = 0.003), and thalamus (p = 0.003) at baseline. Significant associations were found for the baseline volumes of the thalamus, nucleus accumbens, and hippocampus with memory, the thalamus with visuospatial skills.

Conclusion

aMCI demonstrated subcortical atrophies associated with cognitive deficits. The thalamus, nucleus accumbens, and hippocampus may provide additional diagnostic information for aMCI.

Amidst an amygdala renaissance in Alzheimer's disease

The amygdala was highlighted as an early site for neurofibrillary tau tangle pathology in Alzheimer's disease in the seminal 1991 article by Braak and Braak. This knowledge has, however, only received traction recently with advances in imaging and image analysis techniques. Here, we provide a cross-disciplinary overview of pathology and neuroimaging studies on the amygdala. These studies provide strong support for an early role of the amygdala in Alzheimer's disease and the utility of imaging biomarkers of the amygdala in detecting early changes and predicting decline in cognitive functions and neuropsychiatric symptoms in early stages. We summarize the animal literature on connectivity of the amygdala, demonstrating that amygdala nuclei that show the earliest and strongest accumulation of neurofibrillary tangle pathology are those that are connected to brain regions that also show early neurofibrillary tangle accumulation. Additionally, we propose an alternative pathway of neurofibrillary tangle spreading within the medial temporal lobe between the amygdala and the anterior hippocampus. The proposed existence of this pathway is strengthened by novel experimental data on human functional connectivity. Finally, we summarize the functional roles of the amygdala, highlighting the correspondence between neurofibrillary tangle accumulation and symptomatic profiles in Alzheimer's disease. In summary, these findings provide a new impetus for studying the amygdala in Alzheimer's disease and a unique perspective to guide further study on neurofibrillary tangle spreading and the occurrence of neuropsychiatric symptoms in Alzheimer's disease.

Fine-grained features characterize hippocampal and amygdaloid change pattern in Parkinson's disease and discriminate cognitive-deficit subtype

AIMS

To extract vertex-wise features of the hippocampus and amygdala in Parkinson's disease (PD) with mild cognitive impairment (MCI) and normal cognition (NC) and further evaluate their discriminatory efficacy.

METHODS

High-resolution 3D-T1 data were collected from 68 PD-MCI, 211 PD-NC, and 100 matched healthy controls (HC). Surface geometric features were captured using surface conformal representation, and surfaces were registered to a common template using fluid registration. The statistical tests were performed to detect differences between groups. The disease-discriminatory ability of features was also tested in the ensemble classifiers.

RESULTS

The amygdala, not the hippocampus, showed significant overall differences among the groups. Compared with PD-NC, the right amygdala in MCI patients showed expansion (anterior cortical, anterior amygdaloid, and accessory basal areas) and atrophy (basolateral ventromedial area) subregions. There was notable atrophy in the right CA1 and hippocampal subiculum of PD-MCI. The accuracy of classifiers with multivariate morphometry statistics as features exceeded 85%.

CONCLUSION

PD-MCI is associated with multiscale morphological changes in the amygdala, as well as subtle atrophy in the hippocampus. These novel metrics demonstrated the potential to serve as biomarkers for PD-MCI diagnosis. Overall, these findings from this study help understand the role of subcortical structures in the neuropathological mechanisms of PD cognitive impairment.

Poor sleep accelerates hippocampal and posterior cingulate volume loss in cognitively normal healthy older adults

Poor sleep quality is a known risk factor for Alzheimer's disease. This longitudinal imaging study aimed to determine the acceleration in the rates of tissue loss in cognitively critical brain regions due to poor sleep in healthy elderly individuals. Cognitively-normal healthy individuals, aged ≥60 years, reported Pittsburgh Sleep Quality Index (PSQI) and underwent baseline and 2-year follow-up magnetic resonance imaging brain scans. The links between self-reported sleep quality, rates of tissue loss in cognitively-critical brain regions, and white matter hyperintensity load were assessed. A total of 48 subjects were classified into normal (n = 23; PSQI score <5) and poor sleepers (n = 25; PSQI score ≥5). The two groups were not significantly different in terms of age, gender, years of education, ethnicity, handedness, body mass index, and cognitive performance. Compared to normal sleepers, poor sleepers exhibited much faster rates of volume loss, over threefold in the right hippocampus and fivefold in the right posterior cingulate over 2 years. In contrast, there were no significant differences in the rates of volume loss in the cerebral and cerebellar grey and white matter between the two groups. Rates of volume loss in the right posterior cingulate were negatively associated with global PSQI scores. Poor sleep significantly accelerates volume loss in the right hippocampus and the right posterior cingulate cortex. These findings demonstrate that self-reported sleep quality explains inter-individual differences in the rates of volume loss in cognitively-critical brain regions in healthy older adults and provide a strong impetus to offer sleep interventions to cognitively normal older adults who are poor sleepers.

Structural Alteration of Medial Temporal Lobe Subfield in the Amnestic Mild Cognitive Impairment Stage of Alzheimer’s Disease

Objective. Volume reduction and structural abnormality is the most replicated finding in neuroimaging studies of Alzheimer’s disease (AD). Amnestic mild cognitive impairment (aMCI) is the early stage of AD development. Thus, it is necessary to investigate the link between atrophy of regions of interest (ROIs) in medial temporal lobe, the variation trend of ROI densities and volumes among patients with cognitive impairment, and the distribution characteristics of ROIs in the aMCI group, Alzheimer’s disease (AD) group, and normal control (NC) group. Methods. 30 patients with aMCI, 16 patients with AD, and 30 NC are recruited; magnetic resonance imaging (MRI) brain scans are conducted. Voxel-based morphometry was employed to conduct the quantitative measurement of gray matter densities of the hippocampus, amygdala, entorhinal cortex, and mammillary body (MB). FreeSurfer was utilized to automatically segment the hippocampus into 21 subregions and the amygdala into 9 subregions. Then, their subregion volumes and total volume were calculated. Finally, the ANOVA and multiple comparisons were performed on the above-mentioned data from these three groups. Results. AD had lower GM densities than MCI, and MCI had lower GM densities than NC, but not all of the differences were statistically significant. In the comparisons of AD-aMCI-NC, AD-aMCI, and AD-NC, the hippocampus, amygdala, and entorhinal cortex showed differences in the gray matter densities ( $p<0.05$ ); the differences of mammillary body densities were not significant in the random comparison between these three groups ( $p>0.05$ ). The hippocampus densities and volumes of the subjects from the aMCI group and the AD group were bilaterally symmetric. The gray matter densities of the right side of the entorhinal cortex inside each group and the hippocampus from the NC group were higher than those of the left side ( $p<0.05$ ), and the gray matter densities of the amygdala and mammillary body were bilaterally symmetric in the three groups ( $p>0.05$ ). There were no gender differences of four ROIs in the AD, aMCI, and NC groups ( $p>0.05$ ). The volume differences of the hippocampus presubiculum-body and parasubiculum manifest no statistical significance ( $p>0.05$ ) in the random comparison between these three groups. Volume differences of the left amygdala basal nucleus, the left lateral nucleus, the left cortical amygdala transitional area, the left paravamnion nucleus, and bilateral hippocampal amygdala transition area (HATA) had statistical differences only between the AD group and the NC group ( $p<0.05$ ). Conclusion. Structural defects of medial temporal lobe subfields were revealed in the aMCI and AD groups. Decreased gray matter densities of the hippocampus, entorhinal cortex, and amygdala could distinguish patients with early stage of AD between aMCI and NC. Volume decline of the hippocampus and amygdala subfields could only distinguish AD between NC.

Prediction of the progression from mild cognitive impairment to Alzheimer's disease using a radiomics-integrated model

Objective:

This study aimed to build and validate a radiomics-integrated model with whole-brain magnetic resonance imaging (MRI) to predict the progression of mild cognitive impairment (MCI) to Alzheimer’s disease (AD).

Methods:

357 patients with MCI were selected from the ADNI database, which is an open-source database for AD with multicentre cooperation, of which 154 progressed to AD during the 48-month follow-up period. Subjects were divided into a training and test group. For each patient, the baseline T₁WI MR images were automatically segmented into white matter, gray matter and cerebrospinal fluid (CSF), and radiomics features were extracted from each tissue. Based on the data from the training group, a radiomics signature was built using logistic regression after dimensionality reduction. The radiomics signatures, in combination with the apolipoprotein E4 (APOE4) and baseline neuropsychological scales, were used to build an integrated model using machine learning. The receiver operating characteristics (ROC) curve and data of the test group were used to evaluate the diagnostic accuracy and reliability of the model, respectively. In addition, the clinical prognostic efficacy of the model was evaluated based on the time of progression from MCI to AD.

Results:

Stepwise logistic regression analysis showed that the APOE4, clinical dementia rating, AD assessment scale, and radiomics signature were independent predictors of MCI progression to AD. The integrated model was constructed based on independent predictors using machine learning. The ROC curve showed that the accuracy of the model in the training and the test sets was 0.814 and 0.807, with a specificity of 0.671 and 0.738, and a sensitivity of 0.822 and 0.745, respectively. In addition, the model had the most significant diagnostic efficacy in predicting MCI progression to AD within 12 months, with an AUC of 0.814, sensitivity of 0.726, and specificity of 0.798.

Conclusion:

The integrated model based on whole-brain radiomics can accurately identify and predict the high-risk population of MCI patients who may progress to AD. Radiomics biomarkers are practical in the precursory stage of such disease.

Differential neural structures, intrinsic functional connectivity, and episodic memory in subjective cognitive decline and healthy controls

The neural correlates of subjective cognitive decline (SCD; i.e., without objectifiable deficit) remain to be elucidated. Possible causes of SCD include early neurodegeneration related to Alzheimer's disease or functional and structural changes related to sub-clinical depression. We investigated the relationship between episodic memory performance or memory complaints and structural or functional magnetic resonance imaging (MRI) measures in participants with SCD (n=18) but without psychiatric disorders and healthy controls (n=31). In SCD, memory complaints were not associated with memory performance but with sub-clinical depression and executive functions. SCD-associated memory complaints correlated with higher amygdala and parahippocampal gyrus (specifically subiculum) gray matter density. In controls, but not in SCD, mesiotemporal gray matter density and superior frontal gyrus functional connectivity predicted memory performance. In contrast, in SCD, only a trend toward a correlation between memory performance and gray matter density in the parietooccipital lobes was observed. In our memory-clinic sample of SCD, we did not observe incipient neurodegeneration (limited to structural and functional MRI) but rather sub-clinical depression underlying subjective cognitive complaints.

Nocturnal Hypoxemia Is Associated with Altered Parahippocampal Functional Brain Connectivity in Older Adults at Risk for Dementia

BACKGROUND

Obstructive sleep apnea is associated with an increased risk of developing mild cognitive impairment and dementia. Intermittent nocturnal hypoxemia in obstructive sleep apnea is associated with brain changes in key regions that underpin memory.

OBJECTIVE

To determine whether older adults with severe nocturnal hypoxemia would exhibit reduced functional connectivity within these regions, with associated deficits in memory.

METHODS

Seventy-two participants 51 years and over underwent polysomnography with continuous blood oxygen saturation recorded via oximetry. The oxygen desaturation index (ODI, 3% dips in oxygen levels per hour) was the primary outcome measure. ODI was split into tertiles, with analyses comparing the lowest and highest tertiles (N = 48). Thirty-five of the 48 participants from these two tertiles had mild cognitive impairment. Participants also underwent resting-state fMRI and comprehensive neuropsychological, medical, and psychiatric assessment.

RESULTS

The highest ODI tertile group demonstrated significantly reduced connectivity between the left and right parahippocampal cortex, relative to the lowest ODI tertile group (t(42) = -3.26, p = 0.041, beta = -1.99).The highest ODI tertile group also had poorer working memory performance. In the highest ODI tertile group only, higher left-right parahippocampal functional connectivity was associated with poorer visual memory recall (between-groups z = -2.93, p = 0.0034).

CONCLUSIONS

Older adults with severe nocturnal hypoxemia demonstrate impaired functional connectivity in medial temporal structures, key regions involved in sleep memory processing and implicated in dementia pathophysiology. Oxygen desaturation and functional connectivity in these individuals each relate to cognitive performance. Research is now required to further elucidate these findings.

Fear acquisition and extinction deficits in amnestic mild cognitive impairment and early Alzheimer's disease

Impaired learning and memory functioning are prime markers for Alzheimer's disease (AD). Although initial evidence points to impaired fear acquisition in later AD, no study has investigated fear conditioning in early stages and amnestic mild cognitive impairment (aMCI), a condition often preceding AD. The present study examined if fear conditioning gradually decays from healthy elderly to patients with aMCI, to patients with AD. Patients with AD (n = 43), patients with aMCI (n = 43), and matched healthy controls (n = 40) underwent a classical fear conditioning paradigm. During acquisition, a neutral face (conditioned stimulus, CS+) was paired with an electrical stimulus, whereas another face (unconditioned stimulus, CS-) was unpaired. Conditioned responses were measured by unconditioned stimulus expectancy, valence, and skin conductance. Compared to healthy controls, both patient groups showed less differential (CS+ vs. CS-) fear acquisition across all measures. Patients further displayed slowed extinction indexed by higher unconditioned stimulus expectancy and reduced positive valence for CS+, declining from aMCI to AD. Groups did not differ in responses during a preconditioning habituation phase and in unconditioned responding. Diminished differential fear acquisition and slowed extinction could represent prognostic markers for AD onset.

Effect of sleep quality on amnestic mild cognitive impairment vulnerable brain regions in cognitively normal elderly individuals

STUDY OBJECTIVES

This study aims to evaluate the extent to which sleep quality impacts amnestic mild cognitive impairment (aMCI)-related brain regions in a cognitively normal cohort of individuals.

METHODS

Seventy-four participants were rigorously evaluated using a battery of cognitive tests and a detailed clinical assessment to verify normal cognitive status. We then screened for sleep quality using the Pittsburgh Sleep Quality Index (PSQI) and depressive symptoms using the Geriatric Depression Scale (GDS). Five subjects were excluded due to mild depression. Overall 38 individuals with mean age 70.7 ± 7 were classified as poor sleepers and 31 with mean age of 69.6 ± 6 years as normal sleepers. Structural MRI and Freesurfer brain parcellation were used to measure aMCI-related brain regions.

RESULTS

Relative to normal sleepers, poor sleepers exhibited significant reductions in cortical and subcortical volumes bilaterally in the hippocampi, as well as in the superior parietal lobules and left amygdala. The effects were strongest in the left superior parietal lobule (p < .015), followed by the hippocampi. Diffuse patterns of cortical thinning were observed in the frontal lobes, but significant effects were concentrated in the right mesial frontal cortex. Lower sleep duration was most correlated with cortical volume and thickness reductions among all subjects.

CONCLUSIONS

Atrophy related to poor sleep quality impacted a number of regions implicated in aMCI and Alzheimer's disease (AD). As such, interventions targeted towards improving sleep quality amongst the elderly may prove an effective tool for modulating the course of aMCI and AD.

Early versus late MCI: Improved MCI staging using a neuropsychological approach

INTRODUCTION

The Alzheimer's Disease Neuroimaging Initiative (ADNI) separates "early" and "late" mild cognitive impairment (MCI) based on a single memory test. We compared ADNI's MCI classifications to our neuropsychological approach, which more broadly assesses cognitive abilities.

METHODS

Three hundred thirty-six ADNI-2 participants were classified as "early" or "late" MCI. Cluster analysis was performed on neuropsychological test data, and participants were reclassified based on cluster results. These two staging approaches were compared on progression rates, cerebrospinal fluid biomarkers, and cortical thickness profiles.

RESULTS

There was little correspondence between the two staging methods. ADNI's early MCI group included a large proportion of false-positive diagnostic errors. The reclassified neuropsychological MCI groups showed steeper survival curves and more abnormal biomarkers.

CONCLUSIONS

Our novel neuropsychological approach improved the staging of MCI by (1) capturing individuals at an early symptomatic stage, (2) minimizing false-positive cases, and (3) identifying a late MCI group further along the disease trajectory.

Increasing Inaccuracy of Self-Reported Subjective Cognitive Complaints Over 24 Months in Empirically Derived Subtypes of Mild Cognitive Impairment

OBJECTIVES

Although subjective cognitive complaints (SCC) are an integral component of the diagnostic criteria for mild cognitive impairment (MCI), previous findings indicate they may not accurately reflect cognitive ability. Within the Alzheimer's Disease Neuroimaging Initiative, we investigated longitudinal change in the discrepancy between self- and informant-reported SCC across empirically derived subtypes of MCI and normal control (NC) participants.

METHODS

Data were obtained for 353 MCI participants and 122 "robust" NC participants. Participants were classified into three subtypes at baseline via cluster analysis: amnestic MCI, mixed MCI, and cluster-derived normal (CDN), a presumptive false-positive group who performed within normal limits on neuropsychological testing. SCC at baseline and two annual follow-up visits were assessed via the Everyday Cognition Questionnaire (ECog), and discrepancy scores between self- and informant-report were calculated. Analysis of change was conducted using analysis of covariance.

RESULTS

The amnestic and mixed MCI subtypes demonstrated increasing ECog discrepancy scores over time. This was driven by an increase in informant-reported SCC, which corresponded to participants' objective cognitive decline, despite stable self-reported SCC. Increasing unawareness was associated with cerebrospinal fluid Alzheimer's disease biomarker positivity and progression to Alzheimer's disease. In contrast, CDN and NC groups over-reported cognitive difficulty and demonstrated normal cognition at all time points.

CONCLUSIONS

MCI participants' discrepancy scores indicate progressive underappreciation of their evolving cognitive deficits. Consistent over-reporting in the CDN and NC groups despite normal objective cognition suggests that self-reported SCC do not predict impending cognitive decline. Results demonstrate that self-reported SCC become increasingly misleading as objective cognitive impairment becomes more pronounced. (JINS, 2018, 24, 842-853).