Comparison of cortical thickness in patients with early-stage versus late-stage amnestic mild cognitive impairment

Central Auditory Processing Disorder in Patients with Amnestic Mild Cognitive Impairment

Background

This study was conducted to comprehensively examine the central auditory processing (CAP) abilities of patients with amnestic mild cognitive impairment (aMCI) as well as to compare the results with cognitively normal elderly controls.

Methods

A total of 78 participants were screened through pure-tone audiometry and word recognition score in order to exclude peripheral auditory dysfunction. Forty-five people passed screening tests, and 33 people failed. Finally, 25 aMCI (mean age = 71.52 ± 4.8; male : female = 24 : 76) and 20 controls (mean age = 73.45 ± 4.32; male : female = 45 : 55) were enrolled in the study. Seven CAP tests (frequency pattern test, duration pattern test, Gap-In-Noise^© test, dichotic digits test, low-pass filtered word test, speech perception in noise test, and binaural fusion test) were conducted only after the two groups passed the screening. A linear mixed model was applied to analyze CAP tests except for the binaural fusion test. For the binaural fusion test, the independent t-test was used to compare the means of test score between two groups.

Results

The aMCI group had a decrease in the mean score of the frequency pattern test, duration pattern test, Gaps-In-Noise^© test, dichotic digits test, and speech perception in noise test compared with the control group.

Conclusion

The aMCI group's CAP abilities were significantly lower than those of the control group. Thus, if the cognitive assessment and hearing evaluation are conducted in combination, the sensitivity of the diagnostic process for aMCI will be increased.

Triple Network Model-Based Analysis on Abnormal Core Brain Functional Network Dynamics in Different Stage of Amnestic Mild Cognitive Impairment

Background: Amnestic mild cognitive impairment (aMCI) is considered to be a transitional stage of Alzheimer’s disease (AD) because it has the same clinical symptoms as AD but with lower severity. Studies have confirmed that patients with aMCI are more likely to develop to AD. Although studies on resting state functional connectivity have revealed the abnormal organization of brain networks, the dynamic changes of the functional connectivity across the scans have been ignored. Objective: Dynamic functional connectivity is a novel method to reveal the temporal variation of brain networks. This paper aimed to investigate the dynamic characteristics of brain functional connectivity in the early and late phases of aMCI. Methods: Based on the “triple network” model, we used the sliding time window approach to construct dynamical functional networks and then analyzed the dynamic characteristics of the functional connectivity across the entire scan. Results: The results showed that patients with aMCI had longer dwell times in weaker network connection than in the strong network. The transitions between different states become more frequent, and the stability of the patient’s brain core network deteriorates. This study also found the correlation between the altered dynamic properties of the core functional networks and the patient’s clinical Mini-Mental State Examination assessment scale sores. Conclusion: This study revealed that the characteristics of dynamic functional networks constructed by the core cognitive networks varied in distinct ways at different stages of aMCI, which could provide a new idea for exploring the neuro-mechanisms of neurological disorders.

Differentiating amnestic from non-amnestic mild cognitive impairment subtypes using graph theoretical measures of electroencephalography

The purpose of this study was to explore different patterns of functional networks between amnestic mild cognitive impairment (aMCI) and non-aMCI (naMCI) using electroencephalography (EEG) graph theoretical analysis. The data of 197 drug-naïve individuals who complained cognitive impairment were reviewed. Resting-state EEG data was acquired. Graph analyses were performed and compared between aMCI and naMCI, as well as between early and late aMCI. Correlation analyses were conducted between the graph measures and neuropsychological test results. Machine learning algorithms were applied to determine whether the EEG graph measures could be used to distinguish aMCI from naMCI. Compared to naMCI, aMCI showed higher modularity in the beta band and lower radius in the gamma band. Modularity was negatively correlated with scores on the semantic fluency test, and the radius in the gamma band was positively correlated with visual memory, phonemic, and semantic fluency tests. The naïve Bayes algorithm classified aMCI and naMCI with 89% accuracy. Late aMCI showed inefficient and segregated network properties compared to early aMCI. Graph measures could differentiate aMCI from naMCI, suggesting that these measures might be considered as predictive markers for progression to Alzheimer’s dementia in patients with MCI.

Association between structural brain features and gene expression by weighted gene co-expression network analysis in conversion from MCI to AD

Alzheimer's disease (AD) is a neurodegenerative disease. Mild cognitive impairment (MCI) represents a state of cognitive function between normal cognition and dementia. Longitudinal studies showed that some MCI patients remained in a state of MCI, and some developed AD. The reason for these different conversions from MCI remains to be investigated. 180 MCI participants were followed for eight years. 143 MCI patients maintained the MCI state (MCI_S), and the remaining thirty-seven MCI patients were re-evaluated as having AD (MCI_AD). We obtained 1,036 structural brain characteristics and 15,481 gene expression values from the 180 MCI participants and applied weighted gene co-expression network analysis (WGCNA) to explore the relationship between structural brain features and gene expression. Regulating mediator effect analysis was employed to explore the relationships among gene expression, brain region measurements and clinical phenotypes. We found that 60 genes from the MCI_S group and 18 genes from the MCI_AD group respectively had the most significant correlations with left paracentral lobule and sulcus (L.PTS) and right subparietal sulcus (R.SubPS) thickness; CTCF, UQCR11 and WDR5B were the mutual genes between the two groups. The expression of CTCF gene and clinical score are completely mediated by L.PTS thickness, and the UQCR11 and WDR5B gene expression levels significantly regulate the mediating effect pathway. In conclusion, the factors affecting the different conversions from MCI are closely related to L.PTS thickness and the CTCF, UQCR11 and WDR5B gene expression levels. Our results add a theoretical foundation of imaging genetics for conversion from MCI to AD.

Mild Cognitive Impairment and Decline in Resting State Functional Connectivity after Total Knee Arthroplasty with General Anesthesia

BACKGROUND

Research shows that older adults can have a decline in three key resting state networks (default mode network, central executive network, and salience network) after total knee arthroplasty and that patients' pre-surgery brain and cognitive integrity predicts decline.

OBJECTIVES

First, to assess resting state network connectivity decline from the perspective of nodal connectivity changes in a larger older adult surgery sample. Second, to compare pre-post functional connectivity changes in mild cognitive impairment (MCI) versus non-MCI.

METHODS

Surgery (n = 69) and non-surgery (n = 65) peers completed a comprehensive preoperative neuropsychological evaluation and pre- and acute (within 48 hours) post-surgery/pseudo-surgery functional brain magnetic resonance imaging scan. MCI was classified within both (MCI surgery, n = 13; MCI non-surgery, n = 10). Using standard coordinates, we defined default mode network, salience network, central executive network, and the visual network (serving as a control network). The functional connectivity of these networks and brain areas (nodes) that make up these networks were examined for pre-post-surgery changes through paired samples t-test and ANOVA.

RESULTS

There was a decline in RSN connectivity after surgery (p < 0.05) only in the three cognitive networks (not the visual network). The default mode and salience network showed nodal connectivity changes (p < 0.01). MCI surgery had greater functional connectivity decline in DMN and SN. Non-surgery participants showed no significant functional connectivity change.

CONCLUSION

Surgery with general anesthesia selectively alters functional connectivity in major cognitive resting state networks particularly in DMN and SN. Participants with MCI appear more vulnerable to these functional changes.

Executive functions in the elderly with mild cognitive impairment: a systematic review on motor and cognitive inhibition, conflict control and cognitive flexibility

Background: Mild Cognitive Impairment (MCI) is a syndrome characterised by mild cognitive decline, on one or more domains, but which does not compromise daily functions. Several studies have investigated the relationship between MCI and deficit in executive functions (EFs) but, unlike robust evidence in the mnestic domain, the nature of executive deficits in the MCI population remains uncertain.Objectives: This systematic review aims to evaluate EFs in patients with MCI, considering inhibition (motor and cognitive), conflict control and cognitive flexibility.Method: The databases used for the search were PUBMED, PsycINFO, PsycARTICLES and MEDLINE. Eligibility criteria: use of specific paradigms for EFs assessment ('Wisconsin Card Sorting Test', 'Stroop Task', 'Go/No-Go Task', 'Flanker Task'); age over 65, studies published in English. Exclusion criteria: presence of dementia; psychiatric disorders; stroke; cranial trauma; inclusion of participants with MCI in groups with healthy elderly or those with dementia.Results: Fifty-five studies were selected, namely: Stroop Task (N = 30), WCST (N = 14), Go/No-Go (N = 9), Flanker Task (N = 2). Results have shown in people with MCI deficits in all the EFs considered.Conclusions: The results of this review support the applicability of the four experimental tasks examined for the study of EFs in people with MCI. These paradigms are useful in research, diagnosis and therapeutic purposes, allowing obtaining an articulated EFs profile that can compromise the daily life in elderly. These EFs are not generally evaluated by standard assessment of MCI, but their evaluation can lead to a better knowledge of MCI and help in the diagnosis and treatment.

Mild Cognitive Impairment Staging Yields Genetic Susceptibility, Biomarker, and Neuroimaging Differences

Introduction

While Alzheimer’s disease (AD) is divided into severity stages, mild cognitive impairment (MCI) remains a solitary construct despite clinical and prognostic heterogeneity. This study aimed to characterize differences in genetic, cerebrospinal fluid (CSF), neuroimaging, and neuropsychological markers across clinician-derived MCI stages.

Methods

Vanderbilt Memory & Aging Project participants with MCI were categorized into 3 severity subtypes at screening based on neuropsychological assessment, functional assessment, and Clinical Dementia Rating interview, including mild (n = 18, 75 ± 8 years), moderate (n = 89 72 ± 7 years), and severe subtypes (n = 18, 78 ± 8 years). At enrollment, participants underwent neuropsychological testing, 3T brain magnetic resonance imaging (MRI), and optional fasting lumbar puncture to obtain CSF. Neuropsychological testing and MRI were repeated at 18-months, 3-years, and 5-years with a mean follow-up time of 3.3 years. Ordinary least square regressions examined cross-sectional associations between MCI severity and apolipoprotein E (APOE)-ε4 status, CSF biomarkers of amyloid beta (Aβ), phosphorylated tau, total tau, and synaptic dysfunction (neurogranin), baseline neuroimaging biomarkers, and baseline neuropsychological performance. Longitudinal associations between baseline MCI severity and neuroimaging and neuropsychological trajectory were assessed using linear mixed effects models with random intercepts and slopes and a follow-up time interaction. Analyses adjusted for baseline age, sex, race/ethnicity, education, and intracranial volume for MRI models.

Results

Stages differed at baseline on APOE-ε4 status (early < middle = late; p-values < 0.03) and CSF Aβ (early > middle = late), phosphorylated and total tau (early = middle < late; p-values < 0.05), and neurogranin concentrations (early = middle < late; p-values < 0.05). MCI stage related to greater longitudinal cognitive decline, hippocampal atrophy, and inferior lateral ventricle dilation (early < late; p-values < 0.03).

Discussion

Clinician staging of MCI severity yielded longitudinal cognitive trajectory and structural neuroimaging differences in regions susceptible to AD neuropathology and neurodegeneration. As expected, participants with more severe MCI symptoms at study entry had greater cognitive decline and gray matter atrophy over time. Differences are likely attributable to baseline differences in amyloidosis, tau, and synaptic dysfunction. MCI staging may provide insight into underlying pathology, prognosis, and therapeutic targets.

Frontal-executive dysfunction affects dementia conversion in patients with amnestic mild cognitive impairment

Among mild cognitive impairment (MCI) patients, those with memory impairment (amnestic MCI, aMCI) are at a high risk of dementia. However, the precise cognitive domain, beside memory, that predicts dementia conversion is unclear. Therefore, we investigated the cognitive domain that predicts dementia conversion in a longitudinal aMCI cohort. We collected data of 482 aMCI patients who underwent neuropsychological tests and magnetic resonance imaging at baseline and were followed for at least 1 year. The patients were categorized according to number (1-4) and type of impaired cognitive domains (memory, language, visuospatial, and frontal-executive function). We evaluated dementia conversion risk in each group when compared to single-domain aMCI after controlling for age, education, diabetes and dyslipidemia. Baseline cortical thickness of each group was compared to that of 410 cognitively normal controls (NCs) after controlling for age, intracranial volume, diabetes and dyslipidemia. Compared to single-domain aMCI, aMCI patients with frontal-executive dysfunction at baseline had a higher risk of dementia conversion than aMCI patients with visuospatial or language dysfunction. Compared to NCs, aMCI patients with frontal-executive dysfunction had overall cortical thinning including frontal areas. Our findings suggest that aMCI patients with frontal-executive dysfunction have poor prognosis and,thus, should be considered for intervention therapy with a higher priority among aMCI patients.

Staging the cognitive continuum in prodromal Alzheimer's disease with episodic memory

It is unclear whether episodic memory is an appropriate descriptor of the cognitive continuum in mild cognitive impairment (MCI). Here, we investigated the ability of episodic memory to track cognitive changes in patients with MCI with biomarker evidence of Alzheimer's disease (AD). We examined 387 MCI amyloid-positive subjects, cognitively staged as "early" or "late" on the basis of episodic memory impairment. Cross-sectional and longitudinal comparisons between these 2 groups were performed for each amyloid, tau, and neurodegeneration (AT(N)) profile. Cross-sectional analyses indicate that "early" MCI represents a transitional phase between normal cognition and "late" MCI in the AD biomarker pathway. After adjusting by confounders and levels of A, T, and (N), "late" MCI progressed significantly faster than "early" MCI only in profiles with both abnormal amyloid and tau markers (A+T+(N)- p < 0.05, A+T+(N)+ p < 0.001). Episodic memory staging is useful for describing symptoms in prodromal AD and complements the AT(N) profiles. Our findings might have implications for the Numeric Clinical staging scheme of the National Institute on Aging and Alzheimer's Association research framework.

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.

Data-driven prognostic features of cognitive trajectories in patients with amnestic mild cognitive impairments

BACKGROUND

Although amnestic mild cognitive impairment (aMCI) is generally considered to be a prodromal stage of Alzheimer's disease, patients with aMCI show heterogeneous patterns of progression. Moreover, there are few studies investigating data-driven cognitive trajectory in aMCI. We therefore classified patients with aMCI based on their cognitive trajectory, measured by clinical dementia rating sum of boxes (CDR-SOB). Then, we compared the clinical and neuroimaging features among groups classified by cognitive trajectory.

METHODS

We retrospectively recruited 278 patients with aMCI who underwent three or more timepoints of neuropsychological testing. They also had magnetic resonance imaging (MRI) including structured three-dimensional volume images. Cortical thickness was measured using surface-based methods. We performed trajectory analyses to classify our aMCI patients according to their progression and investigate their cognitive trajectory using CDR-SOB.

RESULTS

Trajectory analyses showed that patients with aMCI were divided into three groups: stable (61.8%), slow decliner (31.7%), and fast decliner (6.5%). Changes throughout a mean follow-up duration of 3.7 years in the CDR-SOB for the subgroups of stable/slow/fast decliners were 1.3-, 6.4-, and 12-point increases, respectively. Decliners were older and carried apolipoprotein E4 (APOE4) genotypes more frequently than stable patients. Compared with the stable group, decliners showed a higher frequency of aMCI patients with both visual and verbal memory dysfunction, late stage aMCI, and multiple domain dysfunction. In addition, compared with the stable group, the slow decliners showed cortical thinning predominantly in bilateral parietotemporal areas, while the fast decliners showed cortical thinning predominantly in bilateral frontotemporal areas. Both decliner groups showed worse cognitive function in attention, language, visuospatial, memory, and frontal/executive domains than the stable group.

CONCLUSIONS

Our data-driven trajectory analysis provides new insights into heterogeneous cognitive trajectories of aMCI and further suggests that baseline clinical and neuroimaging profiles might predict aMCI patients with poor prognosis.

Lateral Ventricle Enlargement and Cortical Thinning in Idiopathic Normal-pressure Hydrocephalus Patients

We utilized three-dimensional, surface-based, morphometric analysis to investigate ventricle shape between 2 groups: (1) idiopathic normal-pressure hydrocephalus (INPH) patients who had a positive response to the cerebrospinal fluid tap test (CSFTT) and (2) healthy controls. The aims were (1) to evaluate the location of INPH-related structural abnormalities of the lateral ventricles and (2) to investigate relationships between lateral ventricular enlargement and cortical thinning in INPH patients. Thirty-three INPH patients and 23 healthy controls were included in this study. We used sparse canonical correlation analysis to show correlated regions of ventricular surface expansion and cortical thinning. Significant surface expansion in the INPH group was observed mainly in clusters bilaterally located in the superior portion of the lateral ventricles, adjacent to the high convexity of the frontal and parietal regions. INPH patients showed a significant bilateral expansion of both the temporal horns of the lateral ventricles and the medial aspects of the frontal horns of the lateral ventricles to surrounding brain regions, including the medial frontal lobe. Ventricular surface expansion was associated with cortical thinning in the bilateral orbitofrontal cortex, bilateral rostral anterior cingulate cortex, left parahippocampal cortex, left temporal pole, right insula, right inferior temporal cortex, and right fusiform gyrus. These results suggest that patients with INPH have unique patterns of ventricular surface expansion. Our findings encourage future studies to elucidate the underlying mechanism of lateral ventricular morphometric abnormalities in INPH patients.

Prediction Model of Conversion to Dementia Risk in Subjects with Amnestic Mild Cognitive Impairment: A Longitudinal, Multi-Center Clinic-Based Study

BACKGROUND

Patients with amnestic mild cognitive impairment (aMCI) have an increased risk of dementia. However, conversion rate varies. Therefore, predicting the dementia conversion in these patients is important.

OBJECTIVE

We aimed to develop a nomogram to predict dementia conversion in aMCI subjects using neuropsychological profiles.

METHODS

A total of 338 aMCI patients from two hospital-based cohorts were used in analysis. All patients were classified into 1) verbal, visual, or both, 2) early or late, and 3) single or multiple-domain aMCI according to the modality, severity of memory dysfunction, and multiplicity of involved cognitive domains, respectively. Patients were followed up, and conversion to dementia within 3 years was defined as the primary outcome. Our patients were divided into a training data set and a validation data set. The associations of potential covariates with outcome were tested, and nomogram was constructed by logistic regression model. We also developed another model with APOE data, which included 242 patients.

RESULTS

In logistic regression models, both modalities compared with visual only (OR 4.44, 95% CI 1.83-10.75, p = 0.001), late compared to early (OR 2.59, 95% CI 1.17-5.72, p = 0.019), and multiple compared to single domain (OR 3.51, 95% CI 1.62-7.60, p = 0.002) aMCI were significantly associated with dementia conversion within 3 years. A nomogram incorporating these clinical variables was constructed on the training data set and validated on the validation data set. Both nomograms with and without APOE data showed good prediction performance (c-statistics ≥ 0.75).

CONCLUSIONS

This study showed that several neuropsychological profiles of aMCI are significantly associated with imminent dementia conversion, and a nomogram incorporating these clinical subtypes is simple and useful to help to predict disease progression.

Longitudinal cortical thinning and cognitive decline in patients with early- versus late-stage subcortical vascular mild cognitive impairment

BACKGROUND AND PURPOSE

Biomarker changes in cognitively impaired patients with small vessel disease are largely unknown. The rate of amyloid/lacune progression, cortical thinning and cognitive decline were evaluated in subcortical vascular mild cognitive impairment (svMCI) patients.

METHODS

Seventy-two svMCI patients were divided into early stage (ES-svMCI, n = 39) and late stage (LS-svMCI, n = 33) according to their Clinical Dementia Rating Sum of Boxes score. Patients were annually followed up with neuropsychological tests and brain magnetic resonance imaging for 3 years, and underwent a second [¹¹ C] Pittsburgh compound B (PiB) positron emission tomography scan within a mean interval of 32.4 months.

RESULTS

There was no difference in the rate of increase in PiB uptake or lacune number between the ES-svMCI and LS-svMCI. However, LS-svMCI showed more rapid cortical thinning and cognitive decline than did the ES-svMCI.

CONCLUSIONS

We suggest that, whilst the rate of change in pathological burden did not differ between ES-svMCI and LS-svMCI, cortical thinning and cognitive decline progressed more rapidly in the LS-svMCI.

Volume Loss of the Nucleus Basalis of Meynert is Associated with Atrophy of Innervated Regions in Mild Cognitive Impairment

Extensive research suggests that basal forebrain (BF) cholinergic neurons are selectively vulnerable to Alzheimer's disease (AD). However, it remains unknown whether volume loss of BF cholinergic compartments parallels structural changes of their innervated regions in prodromal AD. To this aim, we have correlated volume of each BF compartment with cortical thickness and hippocampus/amygdala volume in 106 healthy older (HO) adults and 106 amnestic mild cognitive impairment (aMCI) patients. Correlations were limited to regions affected by atrophy in aMCI. The volume of the nucleus basalis of Meynert (NBM/Ch4) was positively correlated with thickness of the temporal cortex in aMCI, and with volume of amygdala in HO and aMCI, separately. Volume of the medial septum/diagonal band of Broca (Ch1-Ch3) was also positively correlated with volume of the hippocampus within the 2 groups. Only correlations between the NBM and their innervated regions showed diagnostic value. Unlike men, aMCI women showed a stronger association between volume of the NBM and thickness of the temporal lobe when compared with HO women. Altogether, these results reveal, for the first time in humans, that atrophy of NBM is associated with structural changes of their innervated regions in prodromal AD, being this relationship more evident in women.

Conversion Discriminative Analysis on Mild Cognitive Impairment Using Multiple Cortical Features from MR Images

Neuroimaging measurements derived from magnetic resonance imaging provide important information required for detecting changes related to the progression of mild cognitive impairment (MCI). Cortical features and changes play a crucial role in revealing unique anatomical patterns of brain regions, and further differentiate MCI patients from normal states. Four cortical features, namely, gray matter volume, cortical thickness, surface area, and mean curvature, were explored for discriminative analysis among three groups including the stable MCI (sMCI), the converted MCI (cMCI), and the normal control (NC) groups. In this study, 158 subjects (72 NC, 46 sMCI, and 40 cMCI) were selected from the Alzheimer's Disease Neuroimaging Initiative. A sparse-constrained regression model based on the l2-1-norm was introduced to reduce the feature dimensionality and retrieve essential features for the discrimination of the three groups by using a support vector machine (SVM). An optimized strategy of feature addition based on the weight of each feature was adopted for the SVM classifier in order to achieve the best classification performance. The baseline cortical features combined with the longitudinal measurements for 2 years of follow-up data yielded prominent classification results. In particular, the cortical thickness produced a classification with 98.84% accuracy, 97.5% sensitivity, and 100% specificity for the sMCI–cMCI comparison; 92.37% accuracy, 84.78% sensitivity, and 97.22% specificity for the cMCI–NC comparison; and 93.75% accuracy, 92.5% sensitivity, and 94.44% specificity for the sMCI–NC comparison. The best performances obtained by the SVM classifier using the essential features were 5–40% more than those using all of the retained features. The feasibility of the cortical features for the recognition of anatomical patterns was certified; thus, the proposed method has the potential to improve the clinical diagnosis of sub-types of MCI and predict the risk of its conversion to Alzheimer's disease.

Subcortical Shape Changes, Hippocampal Atrophy and Cortical Thinning in Future Alzheimer's Disease Patients

Efficacy of future treatments depends on biomarkers identifying patients with mild cognitive impairment at highest risk for transitioning to Alzheimer's disease. Here, we applied recently developed analysis techniques to investigate cross-sectional differences in subcortical shape and volume alterations in patients with stable mild cognitive impairment (MCI) (n = 23, age range 59–82, 47.8% female), future converters at baseline (n = 10, age range 66–84, 90% female) and at time of conversion (age range 68–87) compared to group-wise age and gender matched healthy control subjects (n = 23, age range 61–81, 47.8% female; n = 10, age range 66–82, 80% female; n = 10, age range 68–82, 70% female). Additionally, we studied cortical thinning and global and local measures of hippocampal atrophy as known key imaging markers for Alzheimer's disease. Apart from bilateral striatal volume reductions, no morphometric alterations were found in cognitively stable patients. In contrast, we identified shape alterations in striatal and thalamic regions in future converters at baseline and at time of conversion. These shape alterations were paralleled by Alzheimer's disease like patterns of left hemispheric morphometric changes (cortical thinning in medial temporal regions, hippocampal total and subfield atrophy) in future converters at baseline with progression to similar right hemispheric alterations at time of conversion. Additionally, receiver operating characteristic curve analysis indicated that subcortical shape alterations may outperform hippocampal volume in identifying future converters at baseline. These results further confirm the key role of early cortical thinning and hippocampal atrophy in the early detection of Alzheimer's disease. But first and foremost, and by distinguishing future converters but not patients with stable cognitive abilities from cognitively normal subjects, our results support the value of early subcortical shape alterations and reduced hippocampal subfield volumes as potential markers for the early detection of Alzheimer's disease.

Multistage Grading of Amnestic Mild Cognitive Impairment: The Associated Brain Gray Matter Volume and Cognitive Behavior Characterization

Background and Purpose: It is well known that there is a wide range of different pathological stages related to Alzheimer's disease (AD) among patients with amnestic mild cognitive impairment (aMCI). Further refinement of the stages based on neuropsychological and neuroimaging methods is important for earlier disease detection, as well as for the development and evaluation of disease-modifying interventions.

Materials and Methods: In this cross-sectional study, 125 aMCI patients were classified into declined progressively three stages of mild, moderate and severe, utilizing the extreme groups approach (EGA) based on their memory function. Fifty-two patients, in addition to 24 cognitively normal subjects, were included in further structural MRI analyses. Characteristics of cognitive functions and brain structures across these newly defined stages were explored through general linear models.

Results: Almost all the non-memory cognitive functions showed progressive decline as memory function deteriorated. In addition, medial structures including the right hippocampus, right lingual and left fusiform gyrus, presented with greater gray matter (GM) atrophy during the later stages of aMCI (corrected p < 0.05). Correlations were found between GM volume of the lingual gyrus and processing speed (r = 0.419, p = 0.003) and between the fusiform gyrus and general cognitive function (r = 0.281, p = 0.046). Moreover, both cognitive function and GM volume presented non-linear trajectories over stages of aMCI.

Conclusion: Our study characterized the cognitive profiles along with the degree of episodic memory impairment, and these three stages of aMCI showed non-linear progressive decline in cognitive functions and GM volumes.

Volumetric and shape analysis of the thalamus and striatum in amnestic mild cognitive impairment

Alterations in brain structures, including progressive neurodegeneration, are a hallmark in patients with Alzheimer's disease (AD). However, pathological mechanisms, such as the accumulation of amyloid and the proliferation of tau, are thought to begin years, even decades, before the initial clinical manifestations of AD. In this study, we compare the brain anatomy of amnestic mild cognitive impairment patients (aMCI, n = 16) to healthy subjects (CS, n = 22) using cortical thickness, subcortical volume, and shape analysis, which we believe to be complimentary to volumetric measures. We were able to replicate "classical" cortical thickness alterations in aMCI in the hippocampus, amygdala, putamen, insula, and inferior temporal regions. Additionally, aMCI showed significant thalamic and striatal shape differences. We observed higher global amyloid deposition in aMCI, a significant correlation between striatal displacement and global amyloid, and an inverse correlation between executive function and right-hemispheric thalamic displacement. In contrast, no volumetric differences were detected in thalamic, striatal, and hippocampal regions. Our results provide new evidence for early subcortical neuroanatomical changes in patients with aMCI, which are linked to cognitive abilities and amyloid deposition. Hence, shape analysis may aid in the identification of structural biomarkers for identifying individuals at highest risk of conversion to AD.

Different reserve proxies confer overlapping and unique endurance to cortical thinning in healthy middle-aged adults

AIM

To investigate different proxies of brain and cognitive reserve as potential mediators of the effect of cortical thinning on cognition in healthy middle-aged adults.

METHODS

Eighty-two middle-aged individuals were included (mean(SD) age=45.1(3.9)years). Cortical thickness was calculated for multiple brain regions using FreeSurfer. Cognitive measures sensitive to early cognitive decline were selected, including Block Design from the Wechsler Adult Intelligence Scale-III (WAIS-III), Judgment of Line Orientation Test (JLOT), Color Trails Test (CTT), and first learning trial of TAVEC (the Spanish version of the California Verbal Learning Test, CVLT). Brain reserve was operationalized as total intracranial volume (TIV); and cognitive reserve was estimated by means of Years of Education, WAIS-III Vocabulary subtest, WAIS-III Information subtest, and a Cognitive Reserve Questionnaire (CRQ). Mediation effects were investigated with multiple linear regression and bootstrapping analysis.

RESULTS

Information and Vocabulary showed the greatest mediation capacity. All the observed mediations were positive indicating that higher levels of reserve attenuate the effect of reduced cortical thickness on cognition. Information, Vocabulary and TIV buffered the effect of frontal thinning on Block Design; Vocabulary and Years of Education buffered the effect of frontal thinning on JLOT; and CRQ buffered the effect of temporal thinning on CTT.

CONCLUSION

Higher reserve buffers the effect of cortical thinning on cognition in healthy middle-aged adults. The investigated proxies might be underpinned by slightly different neural networks. Advancing in the understanding of the influences of reserve in healthy middle-aged adults is crucial to facilitate early interventions.

Abnormal Changes of Brain Cortical Anatomy and the Association with Plasma MicroRNA107 Level in Amnestic Mild Cognitive Impairment

MicroRNA107 (Mir107) has been thought to relate to the brain structure phenotype of Alzheimer's disease. In this study, we evaluated the cortical anatomy in amnestic mild cognitive impairment (aMCI) and the relation between cortical anatomy and plasma levels of Mir107 and beta-site amyloid precursor protein (APP) cleaving enzyme 1 (BACE1). Twenty aMCI (20 aMCI) and 24 cognitively normal control (NC) subjects were recruited, and T1-weighted MR images were acquired. Cortical anatomical measurements, including cortical thickness (CT), surface area (SA), and local gyrification index (LGI), were assessed. Quantitative RT-PCR was used to examine plasma expression of Mir107, BACE1 mRNA. Thinner cortex was found in aMCI in areas associated with episodic memory and language, but with thicker cortex in other areas. SA decreased in aMCI in the areas associated with working memory and emotion. LGI showed a significant reduction in aMCI in the areas involved in language function. Changes in Mir107 and BACE1 messenger RNA plasma expression were correlated with changes in CT and SA. We found alterations in key left brain regions associated with memory, language, and emotion in aMCI that were significantly correlated with plasma expression of Mir107 and BACE1 mRNA. This combination study of brain anatomical alterations and gene information may shed lights on our understanding of the pathology of AD.

CLINICAL TRIAL REGISTRATION

http://www.ClinicalTrials.gov, identifier NCT01819545.

Five-year biomarker progression variability for Alzheimer's disease dementia prediction: Can a complex instrumental activities of daily living marker fill in the gaps?

Introduction

Biomarker progressions explain higher variability in cognitive decline than baseline values alone. This study examines progressions of established biomarkers along with a novel marker in a longitudinal cognitive decline.

Methods

A total of 215 subjects were used with a diagnosis of normal, mild cognitive impairment (MCI) or Alzheimer's disease (AD) at baseline. We calculated standardized biomarker progression rates and used them as predictors of outcome within 5 years.

Results

Early cognitive declines were more strongly explained by fluorodeoxyglucose-positron emission tomography, precuneus and medial temporal cortical thickness, and the complex instrumental activities of daily living (iADL) marker progressions. Using Cox proportional hazards model, we found that these progressions were a significant risk factor for conversion from both MCI to AD (adjusted hazard ratio 1.45; 95% confidence interval 1.20–1.93; P = 1.23 × 10⁻⁵) and cognitively normal to MCI (adjusted hazard ratio 1.76; 95% confidence interval 1.32–2.34; P = 1.55 × 10⁻⁵).

Discussion

Compared with standard biological biomarkers, complex functional iADL markers could also provide predictive information for cognitive decline during the presymptomatic stage. This has important implications for clinical trials focusing on prevention in asymptomatic individuals.

Pathomechanisms of atrophy in insular cortex in Alzheimer's disease

The insular cortex is associated with neuropsychiatric symptoms, changes in cardiovascular and autonomic control, and mortality in Alzheimer's dementia. However, the insular cortex does not provide information on the contribution of the other cortices to cognitive decline. We hypothesized that the factors that affect to atrophy in insular cortex are different from other cortical regions. A total of 42 patients with probable Alzheimer's dementia were included in the analyses. The manual drawing of regions of interest was used to detect insular cortex located in the deep gray matter and to avoid coatrophy. Covariates, which could affect to the atrophy of the cerebral cortex, were selected based on previous studies. Any of the demographic factors, vascular risk factors, and the severity scales of dementia was not associated with any insular volume ratio. We suggest that the pathomechanisms of atrophy in insular cortex are different from those of other cortex regions in Alzheimer's disease.

Risk Factors and Consequences of Cortical Thickness in an Asian Population

Cortical thickness has been suggested to be one of the most important markers of cortical atrophy. In this study, we examined potential risk factors of cortical thickness and its association with cognition in an elderly Asian population from Singapore. This is a cross-sectional study among 572 Chinese and Malay patients from the ongoing Epidemiology of Dementia in Singapore (EDIS) Study, who underwent comprehensive examinations including neuropsychological testing and brain magnetic resonance imaging (MRI). Cortical thickness (in micrometers) was measured using a model-based automated procedure. Cognitive function was expressed as composite and domain-specific Z-scores. Cognitive impairment was categorized into cognitive impairment no dementia (CIND)-mild, CIND-moderate, and dementia in accordance with accepted criteria. Linear regression models were used to examine the association between various risk factors and cortical thickness. With respect to cognition as outcome, both linear (for Z-scores) and logistic (for CIND/dementia) regression models were constructed. Initial adjustments were made for age, sex, and education, and subsequently for other cardiovascular risk factors and MRI markers. Out of 572 included patients, 171 (29.9%) were diagnosed with CIND-mild, 197 (34.4%) with CIND-moderate, and 28 (4.9%) with dementia. Risk factors related to a smaller cortical thickness were increased age, male sex, Malay ethnicity, higher blood glucose, and body mass index levels and presence of lacunar infarcts on MRI. Smaller cortical thickness was associated with CIND moderate/dementia [odds ratio (OR) per standard deviation (SD) decrease: 1.70; 95% confidence interval (CI): 1.19-2.44, P = 0.004] and with composite Z-score reflecting global cognitive functioning [mean difference per SD decrease: -0.094; 95% CI: -0.159; -0.030, P = 0.004]. In particular, smaller cortical thicknesses in the occipital and temporal lobes were related to cognitive impairment. Finally, in terms of specific cognitive domains, the most significant associations were found for executive function, visuoconstruction, and visual memory. Smaller cortical thickness is significantly associated with cognitive impairment, suggesting a contribution of diffuse cortical atrophy beyond the medial temporal lobe to cognitive function. These findings suggest that cortical thinning is a biomarker of neurodegenerative changes in the brain not only in dementia, but also in its preclinical stages.

Biomarker progressions explain higher variability in stage-specific cognitive decline than baseline values in Alzheimer disease

BACKGROUND

It is unknown which commonly used Alzheimer disease (AD) biomarker values-baseline or progression-best predict longitudinal cognitive decline.

METHODS

526 subjects from the Alzheimer's Disease Neuroimaging Initiative (ADNI). ADNI composite memory and executive scores were the primary outcomes. Individual-specific slope of the longitudinal trajectory of each biomarker was first estimated. These estimates and observed baseline biomarker values were used as predictors of cognitive declines. Variability in cognitive declines explained by baseline biomarker values was compared with variability explained by biomarker progression values.

RESULTS

About 40% of variability in memory and executive function declines was explained by ventricular volume progression among mild cognitive impairment patients. A total of 84% of memory and 65% of executive function declines were explained by fluorodeoxyglucose positron emission tomography (FDG-PET) score progression and ventricular volume progression, respectively, among AD patients.

CONCLUSIONS

For most biomarkers, biomarker progressions explained higher variability in cognitive decline than biomarker baseline values. This has important implications for clinical trials targeted to modify AD biomarkers.