Uncorrected errors and correct saccades in the antisaccade task distinguish between early-stage Alzheimer's disease dementia, amnestic mild cognitive impairment, and normal aging

Alzheimer's disease (AD) dementia is a degenerative illness that is characterized by a gradual decline in cognitive abilities. Amnestic mild cognitive impairment (aMCI) is seen as a precursor to AD. The changes in antisaccade performance that can be seen in MCI may provide important clues in the early detection of AD. Therefore, the antisaccade deficits in AD and aMCI remain a research question. This study aimed to examine antisaccade responses and the relationship between antisaccade and cognitive function in AD, aMCI, and healthy controls (HC). This study included 30 patients with early-stage AD, 34 with aMCI, and 32 HC. Patients with AD showed higher rates of uncorrected error, anticipatory saccades and corrected errors, as well as decreased correct saccade rates, and shortened saccade latency compared to aMCI and HC in this study. Patients with aMCI exhibited increased rates of express saccades relative to HC. The antisaccade task and cognitive domains were found to be significantly related. Our study showed that the rate of correct saccades has the capacity to distinguish AD from HC with 87% sensitivity and 86% specificity (AUC = 0.93, p < 0.001). In addition, the rate of uncorrected errors was found to be capable of distinguishing AD from HC with 84% sensitivity and 83% specificity (AUC = 0.91, p < 0.001). This study presented promising findings that these parameters can be used clinically to differentiate AD and aMCI from healthy older individuals.

Associations of apolipoprotein E ε4 allele, regional cerebral blood flow, and serum liver function markers in patients with cognitive impairment

Introduction

The ε4 allele of the apolipoprotein E gene (APOE4) is expressed abundantly in both the brain and peripheral circulation as a genetic risk factor for Alzheimer's disease (AD). Cerebral blood flow (CBF) dysfunction is an essential feature of AD, and the liver plays an important role in the pathogenesis of dementia. However, the associations of APOE4 with CBF and liver function markers in patients with cognitive impairment remains unclear. We aimed to evaluate the associations of APOE4 with CBF measured by arterial spin labeling (ASL) magnetic resonance imaging (MRI) and serum liver function markers in participants who were diagnosed with cognitive impairment.

Methods

Fourteen participants with AD and sixteen with amnestic mild cognitive impairment (MCI) were recruited. In addition to providing comprehensive clinical information, all patients underwent laboratory tests and MRI. All participants were divided into carriers and noncarriers of the ε4 allele, and T-tests and Mann-Whitney U tests were used to observe the differences between APOE4 carriers and noncarriers in CBF and liver function markers.

Results

Regarding regional cerebral blood flow (rCBF), APOE4 carriers showed hyperperfusion in the bilateral occipital cortex, bilateral thalamus, and left precuneus and hypoperfusion in the right lateral temporal cortex when compared with noncarriers. Regarding serum liver function markers, bilirubin levels (including total, direct, and indirect) were lower in APOE4 carriers than in noncarriers.

Conclusion

APOE4 exerts a strong effect on CBF dysfunction by inheritance, representing a risk factor for AD. APOE4 may be related to bilirubin metabolism, potentially providing specific neural targets for the diagnosis and treatment of AD.

Frequency-dependent alterations in functional connectivity in patients with Alzheimer's Disease spectrum disorders

Background

In the spectrum of Alzheimer's Disease (AD) and related disorders, the resting-state functional magnetic resonance imaging (rs-fMRI) signals within the cerebral cortex may exhibit distinct characteristics across various frequency ranges. Nevertheless, this hypothesis has not yet been substantiated within the broader context of whole-brain functional connectivity. This study aims to explore potential modifications in degree centrality (DC) and voxel-mirrored homotopic connectivity (VMHC) among individuals with amnestic mild cognitive impairment (aMCI) and AD, while assessing whether these alterations differ across distinct frequency bands.

Methods

This investigation encompassed a total of 53 AD patients, 40 aMCI patients, and 40 healthy controls (HCs). DC and VMHC values were computed within three distinct frequency bands: classical (0.01-0.08 Hz), slow-4 (0.027-0.073 Hz), and slow-5 (0.01-0.027 Hz) for the three respective groups. To discern differences among these groups, ANOVA and subsequent post hoc two-sample t-tests were employed. Cognitive function assessment utilized the mini-mental state examination (MMSE) and Montreal Cognitive Assessment (MoCA). Pearson correlation analysis was applied to investigate the associations between MMSE and MoCA scores with DC and VMHC.

Results

Significant variations in degree centrality (DC) were observed among different groups across diverse frequency bands. The most notable differences were identified in the bilateral caudate nucleus (CN), bilateral medial superior frontal gyrus (mSFG), bilateral Lobule VIII of the cerebellar hemisphere (Lobule VIII), left precuneus (PCu), right Lobule VI of the cerebellar hemisphere (Lobule VI), and right Lobule IV and V of the cerebellar hemisphere (Lobule IV, V). Likewise, disparities in voxel-mirrored homotopic connectivity (VMHC) among groups were predominantly localized to the posterior cingulate gyrus (PCG) and Crus II of the cerebellar hemisphere (Crus II). Across the three frequency bands, the brain regions exhibiting significant differences in various parameters were most abundant in the slow-5 frequency band.

Conclusion

This study enhances our understanding of the pathological and physiological mechanisms associated with AD continuum. Moreover, it underscores the importance of researchers considering various frequency bands in their investigations of brain function.

Repetitive transcranial magnetic stimulation regulates effective connectivity patterns of brain networks in the spectrum of preclinical Alzheimer's disease

Objectives

Subjective cognitive decline (SCD) and amnestic mild cognitive impairment (aMCI) are considered as the spectrum of preclinical Alzheimer's disease (AD), with abnormal brain network connectivity as the main neuroimaging feature. Repetitive transcranial magnetic stimulation (rTMS) has been proven to be an effective non-invasive technique for addressing neuropsychiatric disorders. This study aims to explore the potential of targeted rTMS to regulate effective connectivity within the default mode network (DMN) and the executive control network (CEN), thereby improving cognitive function.

Methods

This study included 86 healthy controls (HCs), 72 SCDs, and 86 aMCIs. Among them, 10 SCDs and 11 aMCIs received a 2-week rTMS course of 5-day, once-daily. Cross-sectional analysis with the spectral dynamic causal model (spDCM) was used to analyze the DMN and CEN effective connectivity patterns of the three groups. Afterwards, longitudinal analysis was conducted on the changes in effective connectivity patterns and cognitive function before and after rTMS for SCD and aMCI, and the correlation between them was analyzed.

Results

Cross-sectional analysis showed different effective connectivity patterns in the DMN and CEN among the three groups. Longitudinal analysis showed that the effective connectivity pattern of the SCD had changed, accompanied by improvements in episodic memory. Correlation analysis indicated a negative relationship between effective connectivity from the left angular gyrus (ANG) to the anterior cingulate gyrus and the ANG.R to the right middle frontal gyrus, with visuospatial and executive function, respectively. In patients with aMCI, episodic memory and executive function improved, while the effective connectivity pattern remained unchanged.

Conclusion

This study demonstrates that PCUN-targeted rTMS in SCD regulates the abnormal effective connectivity patterns in DMN and CEN, thereby improving cognition function. Conversely, in aMCI, the mechanism of improvement may differ. Our findings further suggest that rTMS is more effective in preventing or delaying disease progression in the earlier stages of the AD spectrum.

Clinical Trial Registration

http://www.chictr.org.cn, ChiCTR2000034533.

Higher remnant cholesterol is associated with an increased risk of amnestic mild cognitive impairment: a community-based cross-sectional study

Background and aims

Amnestic mild cognitive impairment (aMCI) is the most common subtype of MCI, which carries a significantly high risk of transitioning to Alzheimer's disease. Recently, increasing attention has been given to remnant cholesterol (RC), a non-traditional and previously overlooked risk factor. The aim of this study was to explore the association between plasma RC levels and aMCI.

Methods

Data were obtained from Brain Health Cognitive Management Team in Wuhan (https://hbtcm.66nao.com/admin/). A total of 1,007 community-dwelling elders were recruited for this project. Based on ten tools including general demographic data, cognitive screening and some exclusion scales, these participants were divided into the aMCI (n = 401) and normal cognitive groups (n = 606). Physical examinations were conducted on all participants, with clinical indicators such as blood pressure, blood sugar, and blood lipids collected.

Results

The aMCI group had significantly higher RC levels compared to the normal cognitive group (0.64 ± 0.431 vs. 0.52 ± 0.447 mmol/L, p < 0.05). Binary logistics regression revealed that occupation (P<0.001, OR = 0.533, 95%CI: 0.423-0.673) and RC (p = 0.014, OR = 1.477, 95% CI:1.081-2.018) were associated factors for aMCI. Partial correlation analysis, after controlling for occupation, showed a significant negative correlation between RC levels and MoCA scores (r = 0.059, p = 0.046), as well as Naming scores (r = 0.070, p = 0.026). ROC curve analysis demonstrated that RC levels had an independent predictive efficacy in predicting aMCI (AUC = 0.580, 95%CI: 0.544 ~ 0.615, P < 0.001).

Conclusion

Higher RC levels were identified as an independent indicator for aMCI, particularly in the naming cognitive domain among older individuals. Further longitudinal studies are necessary to validate the predictive efficacy of RC.

Visual search in Alzheimer's disease and amnestic mild cognitive impairment: An eye-tracking study

INTRODUCTION

Visual search impairment is a potential cognitive marker for Alzheimer's disease (AD) and amnestic mild cognitive impairment (aMCI). The aim of this study is to compare eye movements during visual tracking in AD and aMCI patients versus healthy controls (HCs).

METHODS

A prospective cohort study included 32 AD and 37 aMCI patients, and 33 HCs. Each participant was asked to look at the target object in a visual stimulus containing one target and eight distractors, and eye movements were recorded with EyeLink 1000 Plus.

RESULTS

AD patients had fewer fixations and shorter target fixation duration than aMCI patients and HCs. Fixation durations were also shorter in aMCI patients compared to HCs. Also, AD patients were more fixated on distractors than HCs.

DISCUSSION

Our findings revealed that visual search is impaired in the early stages of AD and even aMCI, highlighting the importance of addressing visual processes in the Alzheimer's continuum.

HIGHLIGHTS

AD patients looked to distractors more and longer than the target compared to aMCI patients and older healthy individuals. aMCI patients had an impaired visual search pattern compared to healthy controls, just like patients with AD. The visual search task differentiated AD and aMCI patients from healthy individuals without dementia.

Prevalence, cognitive characteristics, and influencing factors of amnestic mild cognitive impairment among older adults residing in an urban community in Chengdu, China

Objective

Dementia is a significant public health concern, and mild cognitive impairment (MCI) serves as a transitional stage between normal aging and dementia. Among the various types of MCI, amnestic MCI (aMCI) has been identified as having a higher likelihood of progressing to Alzheimer's dimension. However, limited research has been conducted on the prevalence of aMCI in China. Therefore, the objective of this study is to investigate the prevalence of aMCI, examine its cognitive characteristics, and identify associated risk factors.

Methods

In this cross-sectional study, we investigated a sample of 368 older adults aged 60 years and above in the urban communities of Chengdu, China. The participants underwent a battery of neuropsychological assessments, including the Mini-Mental State Examination (MMSE), the Clinical Dementia Rating (CDR), Auditory Verbal Learning Test (AVLT), Wechsler's Logical Memory Task (LMT), Boston Naming Test (BNT) and Trail Making Test Part A (TMT-A). Social information was collected by standard questionnaire. Multiple logistic regression analysis was utilized to screen for the risk and protective factors of aMCI.

Results

The data analysis included 309 subjects with normal cognitive function and 59 with aMCI, resulting in a prevalence of 16.0% for aMCI. The average age of participants was 69.06 ± 7.30 years, with 56.0% being females. After controlling for age, gender and education, the Spearman partial correlation coefficient between various cognitive assessments and aMCI ranged from -0.52 for the long-term delayed recall scores in AVLT to 0.19 for the time-usage scores in TMT-A. The results indicated that all cognitive domains, except for naming scores (after semantic cue of BNT) and error quantity (in TMT-A), showed statistically significant associations with aMCI. Furthermore, the multiple logistic regression analysis revealed that older age (OR = 1.044, 95%CI: 1.002~1.087), lower educational level, and diabetes (OR = 2.450, 95%CI: 1.246~4.818) were risk factors of aMCI.

Conclusion

This study found a high prevalence of aMCI among older adults in Chengdu, China. Individuals with aMCI exhibited lower cognitive function in memory, language, and executive domains, with long-term delayed recall showing the strongest association. Clinicians should prioritize individuals with verbal learning and memory difficulties, especially long-term delayed recall, in clinical practice.

Predictive power of gait and gait-related cognitive measures in amnestic mild cognitive impairment: a machine learning analysis

Introduction

Gait disorders and gait-related cognitive tests were recently linked to future Alzheimer's Disease (AD) dementia diagnosis in amnestic Mild Cognitive Impairment (aMCI). This study aimed to evaluate the predictive power of gait disorders and gait-related neuropsychological performances for future AD diagnosis in aMCI through machine learning (ML).

Methods

A sample of 253 aMCI (stable, converter) individuals were included. We explored the predictive accuracy of four predictors (gait profile plus MMSE, DSST, and TMT-B) previously identified as critical for the conversion from aMCI to AD within a 36-month follow-up. Supervised ML algorithms (Support Vector Machine [SVM], Logistic Regression, and k-Nearest Neighbors) were trained on 70% of the dataset, and feature importance was evaluated for the best algorithm.

Results

The SVM algorithm achieved the best performance. The optimized training set performance achieved an accuracy of 0.67 (sensitivity = 0.72; specificity = 0.60), improving to 0.70 on the test set (sensitivity = 0.79; specificity = 0.52). Feature importance revealed MMSE as the most important predictor in both training and testing, while gait type was important in the testing phase.

Discussion

We created a predictive ML model that is capable of identifying aMCI at high risk of AD dementia within 36 months. Our ML model could be used to quickly identify individuals at higher risk of AD, facilitating secondary prevention (e.g., cognitive and/or physical training), and serving as screening for more expansive and invasive tests. Lastly, our results point toward theoretically and practically sound evidence of mind and body interaction in AD.

Decoding the diagnostic potential of T cell repertoires in peripheral blood of patients from amnestic mild cognitive impairment to Alzheimer's disease

Alzheimer's disease (AD) is currently an incurable neurodegenerative disorder and is the most common etiological cause of dementia. Consequently, it has severe burden on its patients and on their caregivers and represents a global health concern. Clinical investigations have indicated that a dysregulation of peripheral T cell immune homeostasis may be involved in the pathogenesis of AD, as well as in the early stages of AD, characterized by mild cognitive impairment (MCI). However, the characteristics and concomitant feasibility of the use of T-cell receptor (TCR) typing for disease diagnosis remains largely unknown. We employed a high-throughput sequencing and multidimensional bioinformatics analyses for the identification of TCR repertoires present in peripheral blood samples of 10 patients with amnestic MCI (aMCI), 10 patients with AD, and 10 healthy controls (HCs). Based on the characteristics of the TCR repertoires in the amount and diversity of combinations of V-J, the spectrum of immune defense, and differentially expressed genes (DEGs), single and specific TCR profiles were observed in the patient samples of aMCI and AD compared to profiles of HCs. In particular, the diversity of TCR clonotypes manifested a pattern of "decreased first and then increased" pattern during the progression from aMCI to AD, a pattern that was not observed in HC samples. Additionally, a total of 46 and 35 amino acid CDR3 sequences with consistent and reverse expressive abundance with diversity of TCR clonotypes were identified, respectively. Taken together, we provide novel and essential preliminary evidence demonstrating the presence of diversity of T cell repertoires from differentially expressed V-J gene segments and amino acid clonotypes using peripheral blood samples from patients with AD, aMCI, and from HC. Such findings have the potential to reveal potential mechanisms through which aMCI progresses to AD and provide a reference for the future development of immune-related diagnoses and therapies for AD.

Machine learning classifiers and associations of cognitive performance with hippocampal subfields in amnestic mild cognitive impairment

Background

Neuroimaging studies have demonstrated alterations in hippocampal volume and hippocampal subfields among individuals with amnestic mild cognitive impairment (aMCI). However, research on using hippocampal subfield volume modeling to differentiate aMCI from normal controls (NCs) is limited, and the relationship between hippocampal volume and overall cognitive scores remains unclear.

Methods

We enrolled 50 subjects with aMCI and 44 NCs for this study. Initially, a univariate general linear model was employed to analyze differences in the volumes of hippocampal subfields. Subsequently, two sets of dimensionality reduction methods and four machine learning techniques were applied to distinguish aMCI from NCs based on hippocampal subfield volumes. Finally, we assessed the correlation between the relative volumes of hippocampal subfields and cognitive test variables (Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment Scale (MoCA)).

Results

Significant volume differences were observed in several hippocampal subfields, notably in the left hippocampus. Specifically, the volumes of the hippocampal tail, subiculum, CA1, presubiculum, molecular layer, GC-ML-DG, CA3, CA4, and fimbria differed significantly between the two groups. The highest area under the curve (AUC) values for left and right hippocampal machine learning classifiers were 0.678 and 0.701, respectively. Moreover, the volumes of the left subiculum, left molecular layer, right subiculum, right CA1, right molecular layer, right GC-ML-DG, and right CA4 exhibited the strongest and most consistent correlations with MoCA scores.

Conclusion

Hippocampal subfield volume may serve as a predictive marker for aMCI. These findings underscore the sensitivity of hippocampal subfield volume to overall cognitive performance.

Static and dynamic functional connectivity combined with the triple network model in amnestic mild cognitive impairment and Alzheimer's disease

Background

Alzheimer's disease (AD) and amnestic mild cognitive impairment (aMCI) are characterized by abnormal functional connectivity (FC) of default-mode network (DMN), salience network (SN), and central executive network (CEN). Static FC (sFC) and dynamic FC (dFC) combined with triple network model can better study the dynamic and static changes of brain networks, and improve its potential diagnostic value in the diagnosis of AD spectrum disorders.

Methods

Differences in sFC values and dFC variability patterns among the three brain networks of the three groups (53 AD patients, 40 aMCI patients, and 40 NCs) were computed by ANOVA using Gaussian Random Field theory (GRF) correction. The correlation between FC values (sFC values and dFC variability) in the three networks and cognitive scores (MMSE and MoCA) in AD and aMCI groups was analyzed separately.

Results

Within the DMN network, there were significant differences of sFC values in right/left medial superior frontal gyrus and dFC variability in left opercular part inferior frontal gyrus and right dorsolateral superior frontal gyrus among the three groups. Within the CEN network, there were significant differences of sFC values in left superior parietal gyrus. Within the SN network, there were significant differences of dFC variability in right Cerebelum_7b and left opercular part inferior frontal gyrus. In addition, there was a significant negative correlation between FC values (sFC values of CEN and dFC variability of SN) and MMSE and MoCA scores.

Conclusion

It suggests that sFC, dFC combined with triple network model can be considered as potential biomarkers for AD and aMCI.

Textural features of the frontal white matter could be used to discriminate amnestic mild cognitive impairment patients from the normal population

OBJECTIVE

We aim to develop a radiomics model based on 3-dimensional (3D)-T1WI images to discriminate amnestic mild cognitive impairment (aMCI) patients from the normal population by measuring changes in frontal white matter.

METHODS

In this study, 126 patients with aMCI and 174 normal controls (NC) were recruited from the local community. All subjects underwent routine magnetic resonance imaging examination (including 3D-T1WI ). Participants were randomly divided into a training set (n = 242, aMCI:102, NC:140) and a testing set (n = 58, aMCI:24, NC:34). Texture features of the frontal lobe were extracted from 3D-T1WI images. The least absolute shrinkage and selection operator (LASSO) was used to reduce feature dimensions and develop a radiomics signature model. Diagnostic performance was assessed in the training and testing sets using the receiver operating characteristic (ROC) curve analysis. The area under the ROC curve (AUC), sensitivity, and specificity were also calculated. The efficacy of the radiomics model in discriminating aMCI patients from the normal population was assessed by decision curve analysis (DCA).

RESULTS

A total of 108 frontal lobe texture features were extracted from 3D-T1WI images. LASSO selected 58 radiomic features for the final model, including log-sigma (n = 18), original (n = 8), and wavelet (n = 32) features. The performance of radiomic features extracted from 3D T1 imaging for distinguishing aMCI patients from controls was: in the training set, AUC was 1.00, and the accuracy, sensitivity, and specificity were 100%, 98%, and 100%, respectively. In the testing set, AUC was 0.82 (95% CI:0.69-0.95), and the accuracy, sensitivity, and specificity were 69%, 92%, and 55%, respectively. The DCA demonstrated that the model had favorable clinical predictive value.

CONCLUSIONS

Textural features of white matter in the frontal lobe showed potential for distinguishing aMCI from the normal population, which could be a surrogate protocol to aid aMCI screening in clinical setting.

Eye movement patterns during viewing face images with neutral expressions in patients with early-stage Alzheimer's disease and amnestic mild cognitive impairment

BACKGROUND

Alzheimer's disease (AD) neuropathology affects the brain regions responsible for visuospatial skills. Accumulating evidence points to visual difficulties involving face processing in AD and amnestic mild cognitive impairment (aMCI). No study has so far examined eye movement patterns when viewing faces with neutral expressions in patients with AD.

AIM

The objective of this study aimed to examine the eye movements of patients with early-stage AD, aMCI, and healthy controls (HC) during viewing face images.

MATERIALS&METHODS

Thirty-one AD, 37 aMCI, and 33 HC were included in the study. Eye movements in facial stimuli were recorded with the EyeLink 1000 Plus eye-tracker.

RESULTS

Our findings showed that AD patients looked less at the eye area of interest than the nose and mouth areas of interest compared to aMCI and HC. Regardless of the group, all participants looked at the eye and nose areas of interest more and longer in the mouth area of interest. In addition, the first fixation duration to the eye area of interest of all participants was shorter than that of the nose and mouth.

DISCUSSION

Consistent with our study, studies in healthy adults revealed eye movement patterns that focused more on the eyes and nose. AD patients are unable to pay attention to the salient parts of faces, tending to focus instead on the non-informative parts.

CONCLUSION

Our study is the first to reveal eye movement differences in face processing in AD.

Functional gradients reveal altered functional segregation in patients with amnestic mild cognitive impairment and Alzheimer's disease

Alzheimer's disease and amnestic mild cognitive impairment are associated with disrupted functional organization in brain networks, involved with alteration of functional segregation. Connectome gradients are a new tool representing brain functional topological organization to smoothly capture the human macroscale hierarchy. Here, we examined altered topological organization in amnestic mild cognitive impairment and Alzheimer's disease by connectome gradient mapping. We further quantified functional segregation by gradient dispersion. Then, we systematically compared the alterations observed in amnestic mild cognitive impairment and Alzheimer's disease patients with those in normal controls in a two-dimensional functional gradient space from both the whole-brain level and module level. Compared with normal controls, the first gradient, which described the neocortical hierarchy from unimodal to transmodal regions, showed a more distributed and significant suppression in Alzheimer's disease than amnestic mild cognitive impairment patients. Furthermore, gradient dispersion showed significant decreases in Alzheimer's disease at both the global level and module level, whereas this alteration was limited only to limbic areas in amnestic mild cognitive impairment. Notably, we demonstrated that suppressed gradient dispersion in amnestic mild cognitive impairment and Alzheimer's disease was associated with cognitive scores. These findings provide new evidence for altered brain hierarchy in amnestic mild cognitive impairment and Alzheimer's disease, which strengthens our understanding of the progressive mechanism of cognitive decline.

Machine learning-based classification of Alzheimer's disease and its at-risk states using personality traits, anxiety, and depression

BACKGROUND

Alzheimer's disease (AD) is often preceded by stages of cognitive impairment, namely subjective cognitive decline (SCD) and mild cognitive impairment (MCI). While cerebrospinal fluid (CSF) biomarkers are established predictors of AD, other non-invasive candidate predictors include personality traits, anxiety, and depression, among others. These predictors offer non-invasive assessment and exhibit changes during AD development and preclinical stages.

METHODS

In a cross-sectional design, we comparatively evaluated the predictive value of personality traits (Big Five), geriatric anxiety and depression scores, resting-state functional magnetic resonance imaging activity of the default mode network, apoliprotein E (ApoE) genotype, and CSF biomarkers (tTau, pTau181, Aβ42/40 ratio) in a multi-class support vector machine classification. Participants included 189 healthy controls (HC), 338 individuals with SCD, 132 with amnestic MCI, and 74 with mild AD from the multicenter DZNE-Longitudinal Cognitive Impairment and Dementia Study (DELCODE).

RESULTS

Mean predictive accuracy across all participant groups was highest when utilizing a combination of personality, depression, and anxiety scores. HC were best predicted by a feature set comprised of depression and anxiety scores and participants with AD were best predicted by a feature set containing CSF biomarkers. Classification of participants with SCD or aMCI was near chance level for all assessed feature sets.

CONCLUSION

Our results demonstrate predictive value of personality trait and state scores for AD. Importantly, CSF biomarkers, personality, depression, anxiety, and ApoE genotype show complementary value for classification of AD and its at-risk stages.

Multimodal magnetic resonance imaging on brain network in amnestic mild cognitive impairment: A mini-review

Amnestic mild cognitive impairment (aMCI) is a stage between normal aging and Alzheimer disease (AD) where individuals experience a noticeable decline in memory that is greater than what is expected with normal aging, but dose not meet the clinical criteria for AD. This stage is considered a transitional phase that puts individuals at a high risk for developing AD. It is crucial to intervene during this stage to reduce the changes of AD development. Recently, advanced multimodal magnetic resonance imaging techniques have been used to study the brain structure and functional networks in individuals with aMCI. Through the use of structural magnetic resonance imaging, diffusion tensor imaging, and functional magnetic resonance imaging, abnormalities in certain brain regions have been observed in individuals with aMCI. Specifically, the default mode network, salience network, and executive control network have been found to show abnormalities in both structure and function. This review aims to provide a comprehensive understanding of the brain structure and functional networks associated with aMCI. By analyzing the existing literature on multimodal magnetic resonance imaging and aMCI, this study seeks to uncover potential biomarkers and gain insight into the underlying pathogenesis of aMCI. This knowledge can then guide the development of future treatments and interventions to delay or prevent the progression of aMCI to AD.

Functional brain activity in patients with amnestic mild cognitive impairment: an rs-fMRI study

Background

Amnestic mild cognitive impairment (aMCI) is an early stage of Alzheimer's disease (AD). Regional homogeneity (ReHo) and amplitude of low-frequency fluctuation (ALFF) are employed to explore spontaneous brain function in patients with aMCI. This study applied ALFF and ReHo indicators to analyze the neural mechanism of aMCI by resting-state functional magnetic resonance imaging (rs-fMRI).

Methods

Twenty-six patients with aMCI were included and assigned to the aMCI group. The other 26 healthy subjects were included as a healthy control (HC) group. Rs-fMRI was performed for all participants in both groups. Between-group comparisons of demographic data and neuropsychological scores were analyzed using SPSS 25.0. Functional imaging data were analyzed using DPARSF and SPM12 software based on MATLAB 2017a. Gender, age, and years of education were used as covariates to obtain ALFF and ReHo indices.

Results

Compared with HC group, ALFF decreased in the left fusiform gyrus, left superior temporal gyrus, and increased in the left cerebellum 8, left inferior temporal gyrus, left superior frontal gyrus (BA11), and right inferior temporal gyrus (BA20) in the aMCI group (p < 0.05, FWE correction). In addition, ReHo decreased in the right middle temporal gyrus and right anterior cuneiform lobe, while it increased in the left middle temporal gyrus, left inferior temporal gyrus, cerebellar vermis, right parahippocampal gyrus, left caudate nucleus, right thalamus, and left superior frontal gyrus (BA6) (p < 0.05, FWE correction). In the aMCI group, the ALFF of the left superior frontal gyrus was negatively correlated with Montreal Cognitive Assessment (MoCA) score (r = -0.437, p = 0.026), and the ALFF of the left superior temporal gyrus was positively correlated with the MoCA score (r = 0.550, p = 0.004). The ReHo of the right hippocampus was negatively correlated with the Mini-Mental State Examination (MMSE) score (r = -0.434, p = 0.027), and the ReHo of the right middle temporal gyrus was positively correlated with MMSE score (r = 0.392, p = 0.048).

Conclusion

Functional changes in multiple brain regions rather than in a single brain region have been observed in patients with aMCI. The abnormal activity of multiple specific brain regions may be a manifestation of impaired central function in patients with aMCI.

Characteristics of macroscopic sleep structure in patients with mild cognitive impairment: a systematic review

Objectives

Conducting a systematic analysis of objective measurement tools to assess the characteristics of macroscopic sleep architecture in patients with mild cognitive impairment (MCI), amnestic MCI (aMCI), and non-amnestic MCI (naMCI) in order to provide sleep disorder guidance for MCI patients.

Methods

PubMed, EMbase, Web of Science, Cochrane Library, CNKI, SinoMed, Wanfang Data, and VIP Data were examined to find literature relating to sleep in patients with MCI, aMCI, and naMCI, with a search time frame of build to April 2023. Following independent literature screening, data extraction, and quality evaluation by two researchers, statistical analysis was performed using RevMan 5.4 software.

Results

Twenty-five papers with 1,165 study subjects were included. Patients with MCI and aMCI were found to have altered total sleep time (TST), reduced sleep efficiency (SE), more wake-time after sleep onset (WASO), longer sleep latency (SL), a higher proportion of N1 stage and a lower proportion of N2 and N3 stage. naMCI was only found to have statistically significant differences in WASO.

Conclusions

The results of this study provide evidence for macroscopic sleep architecture abnormalities among MCI patients with sleep disorders. Maintaining a normal sleep time, improving SE, and reducing sleep fragmentation may have an association with a slowed development of cognitive impairment. Further exploration is required of the effects each component of macroscopic sleep structure after the intervention has on altered sleep disturbance and cognition in MCI, aMCI, and naMCI.

Systematic review registration

https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42023401937, identifier: CRD42023401937.

Impaired Emotion Recognition: A Potential Marker for Social Behavioral Problems in Patients With Amnestic Mild Cognitive Impairment and Early Alzheimer Disease?

OBJECTIVE

Emotion recognition, an important aspect of social cognition, can be impaired already in early Alzheimer disease dementia and amnestic mild cognitive impairment (aMCI) and may underly social behavioral changes, which can increase caregiver burden. However, social behavior is difficult to assess in outpatient settings. We evaluated whether impaired emotion recognition is related to proxy-rated social behavioral problems and thus can serve as a marker of these changes.

PATIENTS AND METHOD

Emotion recognition was assessed with Ekman 60 Faces Test (EFT-total, 6 separate emotions) in patients (n = 31 AD; n = 37 aMCI) and healthy controls (n = 60 HCs). Social behavioral problems were rated by proxies with the neuropsychiatric inventory (agitation, apathy, irritability, disinhibition, and a sum score). It tested whether EFT scores differed between patients with and without behavioral problems.

RESULTS

AD had worse EFT-total ( P <0.001), disgust ( P = 0.02), and fear ( P = 0.001) than HC, but not than aMCI, who did not differ from HC. AD displayed more disinhibition ( P < 0.05). EFT and neuropsychiatric inventory sum scores were not significantly correlated. Patients with apathy had lower EFT-total ( P = 0.02).

CONCLUSIONS

Measuring emotion recognition adds value: it is impaired in early neurodegeneration and associated with apathy but not necessarily related to overall changes in social behavior in this population.

Clinical observation and mechanism of acupuncture on amnestic mild cognitive impairment based on the gut-brain axis: study protocol for a randomized controlled trial

Background

Amnestic mild cognitive impairment (aMCI) is a pre-dementia condition associated with declined cognitive function dominated by memory impairment. The occurrence of aMCI is associated with the gut-brain axis. Previous studies have shown cognitive improvements in MCI after acupuncture treatment. This study evaluates whether acupuncture can produce a therapeutic effect in patients with aMCI by modulating the gut-brain axis.

Methods and design

This is a prospective, parallel, multicenter randomized controlled trial. A total of 40 patients with aMCI will be randomly assigned to an acupuncture group (AG) or a waiting-list group (WG), participants in both groups will receive health education on improving cognitive function at each visit, and acupuncture will be conducted twice a week for 12 weeks in the AG. Another 20 matched healthy volunteers will be enrolled as normal control. The primary outcome will be the change in Alzheimer's Disease Assessment Scale-cognitive scale score before and after treatment. Additionally, functional magnetic resonance imaging data, faeces, and blood will be collected from each participant to characterize the brain function, gut microbiota, and inflammatory cytokines, respectively. The differences between patients with aMCI and healthy participants, and the changes in the AG and WG groups before and after treatment will be observed. Ultimately, the correlation among brain function, gut microbiota, inflammatory cytokines, and clinical efficacy evaluation in patients with aMCI will be analyzed.

Discussion

This study will identify the efficacy and provide preliminary data on the possible mechanism of acupuncture in treating aMCI. Furthermore, it will also identify biomarkers of the gut microbiota, inflammatory cytokines, and brain function correlated with therapeutic effects. The results of this study will be published in peer-reviewed journals.

Clinical trial registration

http://www.chictr.org.cn, identifier ChiCTR2200062084.

Mapping the long-term delayed recall-based cortex-hippocampus network constrained by the structural and functional connectome: a case-control multimodal MRI study

Background

Connectome mapping may reveal new treatment targets for patients with neurological and psychiatric diseases. However, the long-term delayed recall based-network with structural and functional connectome is still largely unknown. Our objectives were to (1) identify the long-term delayed recall-based cortex-hippocampus network with structural and functional connectome and (2) investigate its relationships with various cognitive functions, age, and activities of daily living.

Methods

This case-control study enrolled 131 subjects (73 amnestic mild cognitive impairment [aMCI] patients and 58 age- and education-matched healthy controls [HCs]). All subjects completed a neuropsychological battery, activities of daily living assessment, and multimodal magnetic resonance imaging. Nodes of the cortical-hippocampal network related to long-term delayed recall were identified by probabilistic fiber tracking and functional connectivity (FC) analysis. Then, the main and interaction effects of the network on cognitive functions were assessed by a generalized linear model. Finally, the moderating effects of the network on the relationships between long-term delayed recall and clinical features were analyzed by multiple regression and Hayes’ bootstrap method. All the effects of cortex-hippocampus network were analyzed at the connectivity and network levels.

Results

The result of a generalized linear model showed that the bilateral hippocampus, left dorsolateral superior frontal gyrus, right supplementary motor area, left lingual gyrus, left superior occipital gyrus, left superior parietal gyrus, left precuneus, and right temporal pole (superior temporal gyrus) are the left and right cortex-hippocampus network nodes related to long-term delayed recall (P < 0.05). Significant interaction effects were found between the Auditory Verbal Learning Test Part 5 (AVLT 5) scores and global properties of the left cortex-hippocampus network [hierarchy, clustering coefficient, characteristic path length, global efficiency, local efficiency, Sigma and synchronization (P < 0.05 Bonferroni corrected)]. Significant interaction effects were found between the general cognitive function/executive function/language and global properties of the left cortex-hippocampus network [Sigma and synchronization (P < 0.05 Bonferroni corrected)].

Conclusion

This study introduces a novel symptom-based network and describes relationships among cognitive functions, brain function, and age. The cortex–hippocampus network constrained by the structural and functional connectome is closely related to long-term delayed recall.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13195-023-01197-7.

Functional and structural alterations of dorsal attention network in preclinical and early-stage Alzheimer's disease

OBJECTIVES

Subjective cognitive decline (SCD) and amnestic mild cognitive impairment (aMCI) are known as the preclinical and early stage of Alzheimer's disease (AD). The dorsal attention network (DAN) is mainly responsible for the "top-down" attention process. However, previous studies mainly focused on single functional modality and limited structure. This study aimed to investigate the multimodal alterations of DAN in SCD and aMCI to assess their diagnostic value in preclinical and early-stage AD.

METHODS

Resting-state functional magnetic resonance imaging (MRI) was carried out to measure the fractional amplitude of low-frequency fluctuation (fALFF), regional homogeneity (ReHo), and functional connectivity (FC). Structural MRI was used to calculate the gray matter volume (GMV) and cortical thickness. Moreover, receiver-operating characteristic (ROC) analysis was used to distinguish these alterations in SCD and aMCI.

RESULTS

The SCD and aMCI groups showed both decreased ReHo in the right middle temporal gyrus (MTG) and decreased GMV compared to healthy controls (HCs). Especially in the SCD group, there were increased fALFF and increased ReHo in the left inferior occipital gyrus (IOG), decreased fALFF and increased FC in the left inferior parietal lobule (IPL), and reduced cortical thickness in the right inferior temporal gyrus (ITG). Furthermore, functional and structural alterations in the SCD and aMCI groups were closely related to episodic memory (EM), executive function (EF), and information processing speed (IPS). The combination of multiple indicators of DAN had a high accuracy in differentiating clinical stages.

CONCLUSIONS

Our current study demonstrated functional and structural alterations of DAN in SCD and aMCI, especially in the MTG, IPL, and SPL. Furthermore, cognitive performance was closely related to these significant alterations. Our study further suggested that the combined multiple indicators of DAN could be acted as the latent neuroimaging markers of preclinical and early-stage AD for their high diagnostic value.

Associations Between Levels of Peripheral NCAPH2 Promoter Methylation and Different Stages of Alzheimer's Disease: A Cross-Sectional Study

BACKGROUND

Several studies have examined NCAPH2 methylation in amnestic mild cognitive impairment (aMCI) and Alzheimer's disease (AD), but little is known of NCAPH2 methylation in subjective cognitive decline (SCD).

OBJECTIVE

To examine whether methylation of peripheral NCAPH2 are differentially changed at various phases of AD, and whether it could serve as a diagnostic biomarker for SCD.

METHODS

A total of 40 AD patients, 52 aMCI patients, 148 SCD patients, and 193 cognitively normal controls (NCs) were recruited in the current case-control study. Besides, 54 cognitively normal individuals have received amyloid positron emission tomography (amyloid PET) scans. Using bisulfite pyrosequencing method, we measured blood DNA methylation in the NCAPH2 gene promoter.

RESULTS

The main outcomes were: 1) For SCD, there was no significant difference between SCD and NC regarding NCAPH2 methylation; 2) For aMCI, NCAPH2 methylation at CpG2 were significantly lower in aMCI compared with NC and SCD in the entire population and male subgroup; 3) For AD, NCAPH2 methylation at CpG1 were significantly lower in AD compared with NC among females; 4) A relationship with apolipoprotein E (APOE) ɛ4 status was shown. Receiver operating characteristic (ROC) analysis by combining NCAPH2 methylation, age, education, and APOEɛ4 status could distinguish between patients with aMCI (area under the curve (AUC): 0.742) and AD (AUC: 0.873) from NCs.

CONCLUSION

NCAPH2 methylation levels were altered at the aMCI and AD stage and may be convenient and cost-effective biomarkers of AD and aMCI.

Effective Connectivity Evaluation of Resting-State Brain Networks in Alzheimer's Disease, Amnestic Mild Cognitive Impairment, and Normal Aging: An Exploratory Study

(1) Background: Alzheimer's disease (AD) is a neurodegenerative disease with a high prevalence. Despite the cognitive tests to diagnose AD, there are pitfalls in early diagnosis. Brain deposition of pathological markers of AD can affect the direction and intensity of the signaling. The study of effective connectivity allows the evaluation of intensity flow and signaling pathways in functional regions, even in the early stage, known as amnestic mild cognitive impairment (aMCI). (2) Methods: 16 aMCI, 13 AD, and 14 normal subjects were scanned using resting-state fMRI and T1-weighted protocols. After data pre-processing, the signal of the predefined nodes was extracted, and spectral dynamic causal modeling analysis (spDCM) was constructed. Afterward, the mean and standard deviation of the Jacobin matrix of each subject describing effective connectivity was calculated and compared. (3) Results: The maps of effective connectivity in the brain networks of the three groups were different, and the direction and strength of the causal effect with the progression of the disease showed substantial changes. (4) Conclusions: Impaired information flow in the resting-state networks of the aMCI and AD groups was found versus normal groups. Effective connectivity can serve as a potential marker of Alzheimer's pathophysiology, even in the early stages of the disease.

Altered glutamate-glutamine and amide proton transfer-weighted values in the hippocampus of patients with amnestic mild cognitive impairment: A novel combined imaging diagnostic marker

Background and purpose

Early diagnosis of amnestic mild cognitive impairment (aMCI) and timely management to delay the onset of Alzheimer's disease (AD) would benefit patients. Pathological metabolic changes of excitatory/inhibitory neurotransmitters and abnormal protein deposition in the hippocampus of aMCI may provide a new clue to imaging diagnosis. However, the diagnostic performance using these hippocampal metabolite measurements is still unclear. We aimed to quantify right hippocampal glutamate-glutamine (Glx) and gamma-aminobutyric acid (GABA) levels as well as protein-based amide proton transfer-weighted (APTw) signals of patients with aMCI and investigate the diagnostic performance of these metabolites.

Methods

In this cross-sectional study, 20 patients with aMCI and 20 age- and gender-matched healthy controls (HCs) underwent MEGA Point Resolved Spectroscopy (MEGA-PRESS) and APTw MR imaging at 3 T. GABA+, Glx, and APTw signals were measured in the right hippocampus. The GABA+ levels, Glx levels, Glx/GABA+ ratios, and APTw values were compared between the HCs and aMCI groups using the Mann-Whitney U test. Binary logistic regression and receiver operating characteristic (ROC) curve analyses were used to evaluate MEGA-PRESS and APTw parameters' diagnostic performance.

Results

Compared with HCs, patients with aMCI had significantly lower Glx levels in the right hippocampus (7.02 ± 1.41 i.u. vs. 5.81 ± 1.33 i.u., P = 0.018). No significant changes in the GABA+ levels were observed in patients with aMCI (HCs vs. aMCI: 2.54 ± 0.28 i.u. vs. 2.47 ± 0.36 i.u., P = 0.620). In addition, Glx/GABA+ ratios between the two groups (HCs vs. aMCI: 2.79 ± 0.60 vs. 2.37 ± 0.55, P = 0.035) were significantly different. Compared with HCs, patients with aMCI showed higher APTw values in the right hippocampus (0.99 ± 0.26% vs. 1.26% ± 0.28, P = 0.006). The ROC curve analysis showed that Glx, GABA+, Glx/GABA+, and APTw values had an area under the curve (AUC) of 0.72, 0.55, 0.70, and 0.75, respectively, for diagnosing aMCI. In the ROC curve analysis, the AUC of the combination of the parameters increased to 0.88, which is much higher than that observed in the univariate analysis (P < 0.05).

Conclusion

The combination of right hippocampal Glx levels and APTw values improved the diagnostic performance for aMCI, indicating it as a promising combined imaging diagnostic marker. Our study provided a potential imaging diagnostic strategy of aMCI, which may promote early detection of aMCI and facilitate timely intervention to delay the pathological progress toward AD.

Characteristics of the Ontario Neurodegenerative Disease Research Initiative cohort

INTRODUCTION

Understanding synergies between neurodegenerative and cerebrovascular pathologies that modify dementia presentation represents an important knowledge gap.

METHODS

This multi-site, longitudinal, observational cohort study recruited participants across prevalent neurodegenerative diseases and cerebrovascular disease and assessed participants comprehensively across modalities. We describe univariate and multivariate baseline features of the cohort and summarize recruitment, data collection, and curation processes.

RESULTS

We enrolled 520 participants across five neurodegenerative and cerebrovascular diseases. Median age was 69 years, median Montreal Cognitive Assessment score was 25, median independence in activities of daily living was 100% for basic and 93% for instrumental activities. Spousal study partners predominated; participants were often male, White, and more educated. Milder disease stages predominated, yet cohorts reflect clinical presentation.

DISCUSSION

Data will be shared with the global scientific community. Within-disease and disease-agnostic approaches are expected to identify markers of severity, progression, and therapy targets. Sampling characteristics also provide guidance for future study design.

Characteristics and Potential Neural Substrates of Encoding and Retrieval During Memory Binding in Amnestic Mild Cognitive Impairment

BACKGROUND

Whether encoding or retrieval failure contributes to memory binding deficit in amnestic mild cognitive impairment (aMCI) has not been elucidated. Also, the potential brain structural substrates of memory binding remained undiscovered.

OBJECTIVE

To investigate the characteristics and brain atrophy pattern of encoding and retrieval performance during memory binding in aMCI.

METHODS

Forty-three individuals with aMCI and 37 cognitively normal controls were recruited. The Memory Binding Test (MBT) was used to measure memory binding performance. The immediate and delayed memory binding indices were computed by using the free and cued paired recall scores. Partial correlation analysis was performed to map the relationship between regional gray matter volume and memory binding performance.

RESULTS

The memory binding performance in the learning and retrieval phases was worse in the aMCI group than in the control group (F = 22.33 to 52.16, all p < 0.001). The immediate and delayed memory binding index in the aMCI group was lower than that in the control group (p < 0.05). The gray matter volume of the left inferior temporal gyrus was positively correlated with memory binding test scores (r = 0.49 to 0.61, p < 0.05) as well as the immediate (r = 0.39, p < 0.05) and delayed memory binding index (r = 0.42, p < 0.05) in the aMCI group.

CONCLUSION

aMCI may be primarily characterized by a deficit in encoding phase during the controlled learning process. Volumetric losses in the left inferior temporal gyrus may contribute to encoding failure.

Co-expression network analysis of frontal cortex during the progression of Alzheimer's disease

Mechanisms of Alzheimer's disease (AD) and its putative prodromal stage, amnestic mild cognitive impairment (aMCI), involve the dysregulation of multiple candidate molecular pathways that drive selective cellular vulnerability in cognitive brain regions. However, the spatiotemporal overlap of markers for pathway dysregulation in different brain regions and cell types presents a challenge for pinpointing causal versus epiphenomenal changes characterizing disease progression. To approach this problem, we performed Weighted Gene Co-expression Network Analysis and STRING interactome analysis of gene expression patterns quantified in frontal cortex samples (Brodmann area 10) from subjects who died with a clinical diagnosis of no cognitive impairment, aMCI, or mild/moderate AD. Frontal cortex was chosen due to the relatively protracted involvement of this region in AD, which might reveal pathways associated with disease onset. A co-expressed network correlating with clinical diagnosis was functionally associated with insulin signaling, with insulin (INS) being the most highly connected gene within the network. Co-expressed networks correlating with neuropathological diagnostic criteria (e.g., NIA-Reagan Likelihood of AD) were associated with platelet-endothelium-leucocyte cell adhesion pathways and hypoxia-oxidative stress. Dysregulation of these functional pathways may represent incipient alterations impacting disease progression and the clinical presentation of aMCI and AD.

Catastrophe Theory Applied to Neuropsychological Data: Nonlinear Effects of Depression on Financial Capacity in Amnestic Mild Cognitive Impairment and Dementia

Financial incapacity is one of the cognitive deficits observed in amnestic mild cognitive impairment and dementia, while the combined interference of depression remains unexplored. The objective of this research is to investigate and propose a nonlinear model that explains empirical data better than ordinary linear ones and elucidates the role of depression. Four hundred eighteen (418) participants with a diagnosis of amnestic MCI with varying levels of depression were examined with the Geriatric Depression Scale (GDS-15), the Functional Rating Scale for Symptoms of Dementia (FRSSD), and the Legal Capacity for Property Law Transactions Assessment Scale (LCPLTAS). Cusp catastrophe analysis was applied to the data, which suggested that the nonlinear model was superior to the linear and logistic alternatives, demonstrating depression contributes to a bifurcation effect. Depressive symptomatology induces nonlinear effects, that is, beyond a threshold value sudden decline in financial capacity is observed. Implications for theory and practice are discussed.

Identifying Amnestic Mild Cognitive Impairment With Convolutional Neural Network Adapted to the Spectral Entropy Heat Map of the Electroencephalogram

Mild cognitive impairment (MCI) is a preclinical stage of Alzheimer's disease (AD), and early diagnosis and intervention may delay its deterioration. However, the electroencephalogram (EEG) differences between patients with amnestic mild cognitive impairment (aMCI) and healthy controls (HC) subjects are not as significant compared to those with AD. This study addresses this situation by proposing a computer-aided diagnostic method that also aims to improve model performance and assess the sensitive areas of the subject's brain. The EEG data of 46 subjects (20HC/26aMCI) were enhanced with windowed moving segmentation and transformed from 1D temporal data to 2D spectral entropy images to measure the efficient information in the time-frequency domain from the point of view of information entropy; A novel convolution module is devised, which considerably reduces the number of model learning parameters and saves computing resources on the premise of ensuring diagnostic performance; One more thing, the cognitive diagnostic contribution of the corresponding channels in each brain region was measured by the weight coefficient of the input and convolution unit. Our results showed that when the segmental window overlap rate was increased from 0 to 75%, the corresponding generalization accuracy increased from 91.673 ± 0.9578% to 94.642 ± 0.4035%; Approximately 35% reduction in model learnable parameters by optimizing the network structure while maintaining accuracy; The top four channels were FP1, F7, T5, and F4, corresponding to the frontal and temporal lobes, in descending order of the mean value of the weight coefficients. This paper proposes a novel method based on spectral entropy image and convolutional neural network (CNN), which provides a new perspective for the identifying of aMCI based on EEG.

Impact of meningeal uptake and partial volume correction techniques on [18F]MK-6240 binding in aMCI patients and healthy controls

[¹⁸F]MK-6240 is a second-generation tau PET-tracer to quantify neurofibrillary tangles in-vivo. However, individually variable levels of meningeal uptake induce spill-in-effects into the cortex, complicating [¹⁸F]MK-6240 PET quantification. Group SUVR differences between age-matched HC subgroups with varying extracerebral uptake (EC-low/mixed/high), and between aMCI and each HC subgroup were assessed without and with partial volume correction (PVC). Both Müller-Gartner (MG-)PVC and region-based voxelwise (RBV-)PVC, with the latter also correcting for extracerebral spill-in-effects, were implemented. Between HC groups, where no differences are to be expected, HC EC-high showed spill-in differences compared to HC EC-low when no PVC was applied while for MG-PVC, differences were reduced and, for RBV-PVC, no statistically significant differences were observed. Between aMCI and HC, cortical SUVR differences were statistically significant, both without and with PVC, but modulated by the varying meningeal uptake in HC subgroups when no PVC was applied. After applying PVC, correlations to clinical parameters improved and effect sizes between HC and aMCI increased, independent of the HC-subgroup. Therefore, appropriate PVC with correction for extracerebral spill-in-effects is recommended to minimize the impact of varying meningeal uptake on cortical differences between HC and aMCI.

High Fall Risk Associated With Memory Deficit and Brain Lobes Atrophy Among Elderly With Amnestic Mild Cognitive Impairment and Mild Alzheimer's Disease

Objectives

This study aimed to primarily examine the association between memory deficit and increased fall risk, second, explore the underlying neuroanatomical linkage of this association in the elderly with aMCI and mild AD.

Methods

In this cross-sectional study, a total of 103 older adults were included (55 cognitively normal, CN; 48 cognitive impairment, CI, elderly with aMCI, and mild AD). Memory was assessed by the Auditory Verbal Learning Test (AVLT). Fall risk was evaluated by the Timed Up and Go (TUG) Test, heel strike angles, and stride speed, which were collected by an inertial-sensor-based wearable instrument (the JiBuEn™ gait analysis system). Brain volumes were full-automatic segmented and quantified using AccuBrain^® v1.2 from three-dimensional T1-weighted (3D T1W) MR images. Multivariable regression analysis was used to examine the extent of the association between memory deficit and fall risk, the association of brain volumes with memory, and fall risk. Age, sex, education, BMI, and HAMD scores were adjusted. Sensitivity analysis was conducted.

Results

Compared to CN, participants with aMCI and mild AD had poorer cognitive performance (p < 0.001), longer TUG time (p = 0.018), and smaller hippocampus and medial temporal volumes (p = 0.037 and 0.029). In the CI group, compared to good short delayed memory (SDM) performance (AVLT > 5), the elderly with bad SDM performance (AVLT ≤ 3) had longer TUG time, smaller heel strike angles, and slower stride speed. Multivariable regression analysis showed that elderly with poor memory had higher fall risk than relative good memory performance among cognitive impairment elderly. The TUG time increased by 2.1 s, 95% CI, 0.54∼3.67; left heel strike angle reduced by 3.22°, 95% CI, −6.05 to −0.39; and stride speed reduced by 0.09 m/s, 95% CI, −0.19 to −0.00 for the poor memory elderly among the CI group, but not found the association in CN group. In addition, serious medial temporal atrophy (MTA), small volumes of the frontal lobe and occipital lobe were associated with long TUG time and small heel strike angles; small volumes of the temporal lobe, frontal lobe, and parietal lobe were associated with slow stride speed.

Conclusion

Our findings suggested that memory deficit was associated with increased fall risk in the elderly with aMCI and mild AD. The association might be mediated by the atrophy of medial temporal, frontal, and parietal lobes. Additionally, increased fall risk, tested by TUG time, heel stride angles, and stride speed, might be objective and convenient kinematics markers for dynamic monitoring of both memory function and fall risk.

Effect of simultaneous dual-task training on regional cerebral blood flow in older adults with amnestic mild cognitive impairment

BACKGROUND

No previous study has examined the effect of dual-task training using changes in regional cerebral blood flow (rCBF) using single-photon emission computed tomography (SPECT) as an outcome.

OBJECTIVE

This study aimed to examine the effects of simultaneous dual-task training of exercise and cognitive tasks on rCBF using SPECT in older adults with amnestic mild cognitive impairment (aMCI).

METHODS

In this non-randomized control trial, 40 older adults with aMCI participated from May 2016 to April 2018. Outpatients in the intervention group (n = 22) underwent 24 sessions (12 months) of dual-task training twice a month for 60 mins per session. Participants in the control group (n = 18) continued to have regular outpatient visits. The primary outcome was rCBF at baseline and after 12 months, which was compared in each group using the two-sample t-test. The secondary outcomes were the rate of reversion and conversion from aMCI after 12 months.

RESULTS

Of the 22 participants in the intervention group, six dropped out; therefore, 16 were included in the analysis. The intervention group showed more significant increases in rCBF in multiple regions, including the bilateral frontal lobes, compared with the control group. However, the rates of reversion or conversion from mild cognitive impairment (MCI) were not significantly different.

CONCLUSION

Dual-task training for older adults with aMCI increased rCBF in the frontal gyrus but did not promote reversion from MCI to normal cognition. Future intervention studies, such as follow-up examinations after the intervention, are warranted to consider long-term prognosis.

Concurrent Structural and Functional Patterns in Patients With Amnestic Mild Cognitive Impairment

Amnestic mild cognitive impairment (aMCI) is a clinical subtype of MCI, which is known to have a high risk of developing Alzheimer's disease (AD). Although neuroimaging studies have reported brain abnormalities in patients with aMCI, concurrent structural and functional patterns in patients with aMCI were still unclear. In this study, we combined voxel-based morphometry (VBM), amplitude of low-frequency fluctuations (ALFFs), regional homogeneity (Reho), and resting-state functional connectivity (RSFC) approaches to explore concurrent structural and functional alterations in patients with aMCI. We found that, compared with healthy controls (HCs), both ALFF and Reho were decreased in the right superior frontal gyrus (SFG_R) and right middle frontal gyrus (MFG_R) of patients with aMCI, and both gray matter volume (GMV) and Reho were decreased in the left inferior frontal gyrus (IFG_L) of patients with aMCI. Furthermore, we took these overlapping clusters from VBM, ALFF, and Reho analyses as seed regions to analyze RSFC. We found that, compared with HCs, patients with aMCI had decreased RSFC between SFG_R and the right temporal lobe (subgyral) (TL_R), the MFG_R seed and left superior temporal gyrus (STG_L), left inferior parietal lobule (IPL_L), and right anterior cingulate cortex (ACC_R), the IFG_L seed and left precentral gyrus (PRG_L), left cingulate gyrus (CG_L), and IPL_L. These findings highlighted shared imaging features in structural and functional magnetic resonance imaging (MRI), suggesting that SFG_R, MFG_R, and IFG_L may play a major role in the pathophysiology of aMCI, which might be useful to better understand the underlying neural mechanisms of aMCI and AD.

Machine Learning Reveals a Multipredictor Nomogram for Diagnosing the Alzheimer's Disease Based on Chemiluminescence Immunoassay for Total Tau in Plasma

Background

Predicting amnestic mild cognitive impairment (aMCI) in conversion and Alzheimer's disease (AD) remains a daunting task. Standard diagnostic procedures for AD population are reliant on neuroimaging features (positron emission tomography, PET), cerebrospinal fluid (CSF) biomarkers (Aβ1-42, T-tau, P-tau), which are expensive or require invasive sampling. The blood-based biomarkers offer the opportunity to provide an alternative approach for easy diagnosis of AD, which would be a less invasive and cost-effective screening tool than currently approved CSF or amyloid β positron emission tomography (PET) biomarkers.

Methods

We developed and validated a sensitive and selective immunoassay for total Tau in plasma. Robust signatures were obtained based on several clinical features selected by multiple machine learning algorithms between the three participant groups. Subsequently, a well-fitted nomogram was constructed and validated, integrating clinical factors and total Tau concentration. The predictive performance was evaluated according to the receiver operating characteristic (ROC) curves and area under the curve (AUC) statistics. Decision curve analysis and calibration curves are used to evaluate the net benefit of nomograms in clinical decision-making.

Results

Under optimum conditions, chemiluminescence analysis (CLIA) displays a desirable dynamic range within Tau concentration from 7.80 to 250 pg/mL with readily achieved higher performances (LOD: 5.16 pg/mL). In the discovery cohort, the discrimination between the three well-defined participant groups according to Tau concentration was in consistent agreement with clinical diagnosis (AD vs. non-MCI: AUC = 0.799; aMCI vs. non-MCI: AUC = 0.691; AD vs. aMCI: AUC = 0.670). Multiple machine learning algorithms identified Age, Gender, EMPG, Tau, ALB, HCY, VB12, and/or Glu as robust signatures. A nomogram integrated total Tau concentration and clinical factors provided better predictive performance (AD vs. non-MCI: AUC = 0.960, AD vs. aMCI: AUC = 0.813 in discovery cohort; AD vs. non-MCI: AUC = 0.938, AD vs. aMCI: AUC = 0.754 in validation cohort).

Conclusion

The developed assay and a satisfactory nomogram model hold promising clinical potential for early diagnosis of aMCI and AD participants.

Longitudinal Study of Depression on Amnestic Mild Cognitive Impairment and Financial Capacity

OBJECTIVES

Amnestic mild cognitive impairment (aMCI) among other cognitive deficits also includes impairments in financial capacity, but so far the role of depression in time has not been examined. We aimed to examine the hypothesis that individuals with aMCI and comorbid worsening depression levels would demonstrate greater deficits in financial capacity atone year in relation to multiple-domain aMCI patients with stable levels of depression, aMCI patients without depression and healthy individuals.

METHODS

Ninety-six Greek women and 24 men aged 54 and older (multiple-domain aMCI with, stable and increased levels of depression at one year, aMCI without depressive symptoms, and cognitively intact elders with and without depression) were examined with the Mini-mental State Examination (MMSE), the Geriatric Depression Scale (GDS-15), and the Legal Capacity for Property Law Transactions Assessment Scale (LCPLTAS).

RESULTS

Bootstrapped ANCOVA was implemented. Multiple-domain aMCI patients' performance regarding financial capacity is severely impaired when depression co-exists, resembling the performance of patients with mild Alzheimer's disease, and it declines further when depression deteriorates.

CONCLUSIONS

Findings contribute to the limited evidence in financial capacity assessment when depression co-exists showing that higher depressive symptom scores are associated with reduced financial capacity scores and deterioration of depressive symptomatology worsens not only general cognitive outcome, but financial capacity in particular.

CLINICAL IMPLICATIONS

Proactive care for individuals with depression is needed as this condition severely influences financial capacity in aMCI.

Diagnostic performance and neural basis of the combination of free- and pre-drawn Clock Drawing Test

OBJECTIVES

This study aimed to clarify the diagnostic performance and neural basis of the Clock Drawing Test (CDT) combining free- and pre-drawn methods.

METHODS

This retrospective study included 165 participants (91 with Alzheimer disease [AD], 52 with amnestic mild cognitive impairment [aMCI], and 22 healthy controls [HC]), who were divided into four groups according to their free- and pre-drawn CDT scores: group 1, could do both; group 2, impaired in both; group 3, impaired in pre-drawn CDT; and group 4, impaired in free-drawn CDT. The diagnostic performances of the free-drawn, pre-drawn, and combination methods were compared using receiver operating characteristics analysis; in voxel-based morphometry analysis, the gray matter (GM) volume of groups 2-4 were compared with that of group 1.

RESULTS

The area under the curve of the combination method was greater than that of the free- or pre-drawn method alone when comparing AD with HC or aMCI. Group 2 had a significantly smaller GM volume in the bilateral temporal lobes than group 1. Group 3 had a trend toward smaller GM volumes in the right temporal lobe when a liberal threshold was applied. Group 4 had significantly smaller GM volumes in the left temporal lobe than group 1.

CONCLUSIONS

This study suggests that the combination method may be able to screen for a wider range of brain dysfunction. Combined use of free- and pre-drawn CDT may be useful for screening for AD and its early detection and treatment.

Abnormal characterization of dynamic functional connectivity in Alzheimer's disease

Numerous studies have shown abnormal brain functional connectivity in individuals with Alzheimer's disease (AD) or amnestic mild cognitive impairment (aMCI). However, most studies examined traditional resting state functional connections, ignoring the instantaneous connection mode of the whole brain. In this case-control study, we used a new method called dynamic functional connectivity (DFC) to look for abnormalities in patients with AD and aMCI. We calculated dynamic functional connectivity strength from functional magnetic resonance imaging data for each participant, and then used a support vector machine to classify AD patients and normal controls. Finally, we highlighted brain regions and brain networks that made the largest contributions to the classification. We found differences in dynamic function connectivity strength in the left precuneus, default mode network, and dorsal attention network among normal controls, aMCI patients, and AD patients. These abnormalities are potential imaging markers for the early diagnosis of AD.

Characteristics of Dysregulated Proinflammatory Cytokines and Cognitive Dysfunction in Late-Life Depression and Amnestic Mild Cognitive Impairment

Background

Late-life depression (LLD) and amnestic mild cognitive impairment (aMCI) are two different diseases associated with a high risk of developing Alzheimer's disease (AD). Both diseases are accompanied by dysregulation of inflammation. However, the differences and similarities of peripheral inflammatory parameters in these two diseases are not well understood.

Methods

We used Luminex assays to measure 29 cytokines simultaneously in the plasma of two large cohorts of subjects at high risk for AD (23 LLD and 23 aMCI) and 23 normal controls (NCs) in the community. Demographics and lifestyle factors were also collected. Cognitive function was evaluated with the Chinese versions of the Montreal Cognitive Assessment (C-MoCA) and neuropsychological test battery (NTB).

Results

We observed a remarkably increased level of IL-6 in the plasma and reduced levels of chemokines (CXCL11 and CCL13) in the LLD group compared with the aMCI group. The LLD group also showed lower levels of CXCL16 than the NC group. Furthermore, altered cytokine levels were associated with abnormal results in neuropsychological testing and Geriatric Depression Scale scores in both the LLD and aMCI groups. Notably, combinations of cytokines (IL-6 and CCL13) and two subitems of C-MoCA (orientation and short-term memory) generated the best area under the receiver operating characteristic curve (AUROC = 0.974).

Conclusion

A novel model based on proinflammatory cytokines and brief screening tests performs with fair accuracy in the discrimination between LLD and aMCI. These findings will give clues to provide new therapeutic targets for interventions or markers for two diseases with similar predementia syndromes.

Interactive Associations of Neuropsychiatry Inventory-Questionnaire Assessed Sleep Disturbance and Vascular Risk on Alzheimer's Disease Stage Progression in Clinically Normal Older Adults

Background: To determine whether sleep disturbance (SD) and vascular-risk interact to promote Alzheimer's disease (AD) stage-progression in normal, community-dwelling older adults and evaluate their combined risk beyond that of established AD biomarkers. Methods: Longitudinal data from the National Alzheimer's Coordinating Center Uniform-Dataset. SD data (i.e., SD+ vs. SD-), as characterized by the Neuropsychiatric Inventory-Questionnaire, were derived from 10,600 participants at baseline, with at-least one follow-up visit. A subset (n = 361) had baseline cerebrospinal fluid (CSF) biomarkers and MRI data. The Framingham heart study general cardiovascular disease (FHS-CVD) risk-score was used to quantify vascular risk. Amnestic mild cognitive impairment (aMCI) diagnosis during follow-up characterized AD stage-progression. Logistic mixed-effects models with random intercept and slope examined the interaction of SD and vascular risk on prospective aMCI diagnosis. Results: Of the 10,600 participants, 1,017 (9.6%) reported SD and 6,572 (62%) were female. The overall mean (SD) age was 70.5 (6.5), and follow-up time was 5.1 (2.7) years. SD and the FHS-CVD risk-score were each associated with incident aMCI (aOR: 1.42 and aOR: 2.11, p < 0.01 for both). The interaction of SD and FHS-CVD risk-score with time was significant (aOR: 2.87, p < 0.01), suggesting a synergistic effect. SD and FHS-CVD risk-score estimates remained significantly associated with incident aMCI even after adjusting for CSF (Aβ, T-tau, P-tau) and hippocampal volume (n = 361) (aOR: 2.55, p < 0.01), and approximated risk-estimates of each biomarker in the sample where data was available. Conclusions: Clinical measures of sleep and vascular risk may complement current AD biomarkers in assessing risk of cognitive decline in older adults.

The Influence of MTHFR Polymorphism on Gray Matter Volume in Patients With Amnestic Mild Cognitive Impairment

The methylenetetrahydrofolate reductase (MTHFR) gene has been associated with Alzheimer's disease (AD) pathogenesis. Amnestic mild cognitive impairment (aMCI) represents a prodromal stage of dementia and involves a high risk of progression into AD. Although the effects of the apolipoprotein E (APOE) gene on structural alterations in aMCI have been widely investigated, the effects of MTHFR C677T and interaction effects of MTHFR × APOE genotypes on gray matter atrophy in aMCI remain largely unknown. In the present study, 60 aMCI patients and 30 healthy controls were enrolled, and voxel-based morphometry analysis was performed to inspect the effects of diagnosis, different genotypes, and their interactions on gray matter atrophy. The results showed that aMCI patients had significant gray matter atrophy involving the bilateral hippocampus, the right parahippocampal gyrus, and the left superior temporal gyrus compared with healthy controls. Besides, a substantial reduction in gray matter volume was observed in the right hippocampus region in APOE ε4 carriers from the aMCI group, compared with APOE ε4 non-carriers. A significant interaction was found between diagnosis and MTHFR C677T genotype on the right precuneus in healthy controls and aMCI patients not carrying APOE ε4 allele. Our findings may provide new evidence substantiating the genetic effects of MTHFR C677T on brain structural alternation in patients with aMCI.

Acupuncture for amnestic mild cognitive impairment: A pilot multicenter, randomized, parallel controlled trial

INTRODUCTION

Patients with amnesic mild cognitive impairment (aMCI) are more likely to develop Alzheimer disease than corresponding age normal population. Because Alzheimer disease is irreversible, early intervention for aMCI patients seems important and urgent. We have designed a pilot multicenter, randomized, parallel controlled trial to assess the efficacy and safety of acupuncture on aMCI, explore the feasibility of acupuncture in the treatment of aMCI, so as to provide a reference for large-sample clinical trials in the next stage.

METHOD

We designed a pilot multicenter, randomized, parallel controlled trial. This trial aims to test the feasibility of carrying out a large-sample clinical trial. In this trial, 50 eligible patients with aMCI will be included and allocated to acupuncture group (n = 25) or sham acupuncture group (n = 25) at random. Subjects will accept treatment 2 times a week for 12 weeks continuously, with a total of 24 treatment sessions. We will select 6 acupoints (GV20, GV14, bilateral BL18, bilateral BL23). For the clinical outcomes, the primary outcome is Montreal cognitive assessment, which will be assessed from baseline to the end of this trial. And the secondary outcomes are Mini-mental State Examination, Delayed Story Recall, Clinical Dementia Rating scale, Global Deterioration Scale, Activity of Daily Life, Alzheimer Disease Assessment Scale-Cognitive Section, brain magnetic resonance imaging, brain functional magnetic resonance imaging, and event-related potential P300, which will be assessed before and after treatment. In addition, we will assess the safety outcomes from baseline to the end of this trial and feasibility outcome after treatment. We will evaluate neuropsychological assessment scale (Montreal cognitive assessment, Mini-mental State Examination, Alzheimer Disease Assessment Scale-Cognitive Section) at 3 months and 6 months after treatment.

DISCUSSION

This pilot trial aims to explore the feasibility of the trial, verify essential information of its efficacy and safety. This pilot study will provide a preliminary basis for carrying out a larger clinical trial of acupuncture on aMCI in near future.

Orientational changes of white matter fibers in Alzheimer's disease and amnestic mild cognitive impairment

White matter abnormalities represent early neuropathological events in neurodegenerative diseases such as Alzheimer's disease (AD), investigating these white matter alterations would likely provide valuable insights into pathological changes over the course of AD. Using a novel mathematical framework called "Director Field Analysis" (DFA), we investigated the geometric microstructural properties (i.e., splay, bend, twist, and total distortion) in the orientation of white matter fibers in AD, amnestic mild cognitive impairment (aMCI), and cognitively normal (CN) individuals from the Alzheimer's Disease Neuroimaging Initiative 2 database. Results revealed that AD patients had extensive orientational changes in the bilateral anterior thalamic radiation, corticospinal tract, inferior and superior longitudinal fasciculus, inferior fronto-occipital fasciculus, and uncinate fasciculus in comparison with CN. We postulate that these orientational changes of white matter fibers may be partially caused by the expansion of lateral ventricle, white matter atrophy, and gray matter atrophy in AD. In contrast, aMCI individuals showed subtle orientational changes in the left inferior longitudinal fasciculus and right uncinate fasciculus, which showed a significant association with the cognitive performance, suggesting that these regions may be preferential vulnerable to breakdown by neurodegenerative brain disorders, thereby resulting in the patients' cognitive impairment. To our knowledge, this article is the first to examine geometric microstructural changes in the orientation of white matter fibers in AD and aMCI. Our findings demonstrate that the orientational information of white matter fibers could provide novel insight into the underlying biological and pathological changes in AD and aMCI.

Amide Proton Transfer-Weighted MRI Might Help Distinguish Amnestic Mild Cognitive Impairment From a Normal Elderly Population

Objectives: To evaluate whether 3D amide proton transfer weighted (APTw) imaging based on magnetization transfer analysis can be used as a novel imaging marker to distinguish amnestic mild cognitive impairment (aMCI) patients from the normal elderly population by measuring changes in APTw signal intensity in the hippocampus and amygdala. Materials and Methods: Seventy patients with aMCI and 74 age- and sex-matched healthy volunteers were recruited for routine MRI and APT imaging examinations. Magnetic transfer ratio asymmetry (MTRasym) of the amide protons (at 3.5 ppm), or APTw values, were measured in the bilateral hippocampus and amygdala on three consecutive cross-sectional APT images and were compared between the aMCI and control groups. The independent sample t-test was used to evaluate the difference in APTw values of the bilateral hippocampus and amygdala between the aMCI and control groups. Receiver operator characteristic analysis was used to assess the diagnostic performance of the APTw. The paired t-test was used to assess the difference in APTw values between the left and right hippocampus and amygdala, in both the aMCI and control groups. Results: The APTw values of the bilateral hippocampus and amygdala in the aMCI group were significantly higher than those in the control group (left hippocampus 1.01 vs. 0.77% p < 0.001; right hippocampus 1.02 vs. 0.74%, p < 0.001; left amygdala 0.98 vs. 0.70% p < 0.001; right amygdala 0.94 vs. 0.71%, p < 0.001). The APTw values of the left amygdala had the largest AUC (0.875) at diagnosis of aMCI. There was no significant difference in APTw values between the left and right hippocampus and amygdala, in either group. (aMCI group left hippocampus 1.01 vs. right hippocampus 1.02%, p = 0.652; healthy control group left hippocampus 0.77 vs. right hippocampus 0.74%, p = 0.314; aMCI group left amygdala 0.98 vs. right amygdala 0.94%, p = 0.171; healthy control group left amygdala 0.70 vs. right amygdala 0.71%, p = 0.726). Conclusion: APTw can be used as a new imaging marker to distinguish aMCI patients from the normal elderly population by indirectly reflecting the changes in protein content in the hippocampus and amygdala.

Altered Volume and Structural Connectivity of the Hippocampus in Alzheimer's Disease and Amnestic Mild Cognitive Impairment

Background: Hippocampal atrophy is a characteristic of Alzheimer’s disease (AD). However, alterations in structural connectivity (number of connecting fibers) between the hippocampus and whole brain regions due to hippocampal atrophy remain largely unknown in AD and its prodromal stage, amnestic mild cognitive impairment (aMCI).

Methods: We collected high-resolution structural MRI (sMRI) and diffusion tensor imaging (DTI) data from 36 AD patients, 30 aMCI patients, and 41 normal control (NC) subjects. First, the volume and structural connectivity of the bilateral hippocampi were compared among the three groups. Second, correlations between volume and structural connectivity in the ipsilateral hippocampus were further analyzed. Finally, classification ability by hippocampal volume, its structural connectivity, and their combination were evaluated.

Results: Although the volume and structural connectivity of the bilateral hippocampi were decreased in patients with AD and aMCI, only hippocampal volume correlated with neuropsychological test scores. However, positive correlations between hippocampal volume and ipsilateral structural connectivity were displayed in patients with AD and aMCI. Furthermore, classification accuracy (ACC) was higher in AD vs. aMCI and aMCI vs. NC by the combination of hippocampal volume and structural connectivity than by a single parameter. The highest values of the area under the receiver operating characteristic (ROC) curve (AUC) in every two groups were all obtained by combining hippocampal volume and structural connectivity.

Conclusions: Our results showed that the combination of hippocampal volume and structural connectivity (number of connecting fibers) is a new perspective for the discrimination of AD and aMCI.

Disrupted Dynamic Functional Connectivity in Distinguishing Subjective Cognitive Decline and Amnestic Mild Cognitive Impairment Based on the Triple-Network Model

Background: Subjective cognitive decline and amnestic mild cognitive impairment (aMCI) were widely thought to be preclinical AD spectrum disorders, characterized by aberrant functional connectivity (FC) within the triple networks of the default mode network (DMN), the salience network (SN), and the executive control network (ECN). Dynamic FC (DFC) analysis can capture temporal fluctuations in brain FC during the scan, which static FC analysis cannot. The purpose of the current study was to explore the changes in dynamic FC within the triple networks of the preclinical AD spectrum and further reveal their potential diagnostic value in diagnosing preclinical AD spectrum disorders.

Methods: We collected resting-state functional magnetic resonance imaging data from 44 patients with subjective cognitive decline (SCD), 49 with aMCI, and 58 healthy controls (HCs). DFC analysis based on the sliding time-window correlation method was used to analyze DFC variability within the triple networks in the three groups. Then, correlation analysis was conducted to reveal the relationship between altered DFC variability within the triple networks and a decline in cognitive function. Furthermore, logistic regression analysis was used to assess the diagnostic accuracy of altered DFC variability within the triple networks in patients with SCD and aMCI.

Results: Compared with the HC group, the groups with SCD and aMCI both showed altered DFC variability within the triple networks. DFC variability in the right middle temporal gyrus and left inferior frontal gyrus (IFG) within the ECN were significantly different between patients with SCD and aMCI. Moreover, the altered DFC variability in the left IFG within the ECN was obviously associated with a decline in episodic memory and executive function. The logistic regression analysis showed that multivariable analysis had high sensitivity and specificity for diagnosing SCD and aMCI.

Conclusions: Subjective cognitive decline and aMCI showed varying degrees of change in DFC variability within the triple networks and altered DFC variability within the ECN involved episodic memory and executive function. More importantly, altered DFC variability and the triple-network model proved to be important biomarkers for diagnosing and identifying patients with preclinical AD spectrum disorders.

Amyloid-negative Patients with Clinically Diagnosed Alzheimer's Disease and Amnestic Mild Cognitive Impairment

BACKGROUND

A significant proportion of patients with clinically diagnosed Alzheimer's Disease (AD) and an even higher proportion of patients with amnestic mild cognitive impairment (aMCI) do not show evidence of amyloid deposition on Positron Emission Tomography (PET) with amyloid-binding tracers such as ¹¹C-labeled Pittsburgh Compound B (PiB).

OBJECTIVE

This study aimed to identify clinical, neuropsychological and neuroimaging factors that might suggest amyloid neuropathology in patients with clinically suspected AD or aMCI.

METHODS

Forty patients with mild to moderate AD and 23 patients with aMCI who were clinically diagnosed in our memory clinic and had PiB PET scans were included. Clinical, neuropsychological, and imaging characteristics, such as Medial Temporal lobe Atrophy (MTA) and White Matter Hyperintensities (WMH) on MRI and metabolic pattern on ¹⁸F-labeled fluorodeoxyglucose (FDG) PET, were compared between patients with PiB positive and negative PET results for AD, aMCI, and all subjects combined, respectively.

RESULTS

Compared with PiB positive patients, PiB negative patients had a higher prevalence of hypertension history, better performance on the Mini-Mental State Examination, the Rey Auditory Verbal Learning Test, and the Judgement of Line Orientation, lower score of MTA, and were less likely to have temporoparietal-predominant hypometabolism on FDG PET. Affective symptoms were less common in PiB negative patients diagnosed with AD, and the Animal Fluency Test score was higher in PiB negative patients diagnosed with aMCI.

CONCLUSION

In patients with clinically diagnosed AD or aMCI, absence of a history of hypertension, deficits in verbal learning and memory, visuospatial function, semantic verbal fluency, presence of affective symptoms, MTA on MRI, and temporoparietal hypometabolism on FDG PET suggested amyloid deposition in the brain.

Altered Patterns of Amplitude of Low-Frequency Fluctuations and Fractional Amplitude of Low-Frequency Fluctuations Between Amnestic and Vascular Mild Cognitive Impairment: An ALE-Based Comparative Meta-Analysis

Background: Changes in the amplitude of low-frequency fluctuations (ALFF) and the fractional amplitude of low-frequency fluctuations (fALFF) have provided stronger evidence for the pathophysiology of cognitive impairment. Whether the altered patterns of ALFF and fALFF differ in amnestic cognitive impairment (aMCI) and vascular mild cognitive impairment (vMCI) is largely unknown. The purpose of this study was to explore the ALFF/fALFF changes in the two diseases and to further explore whether they contribute to the diagnosis and differentiation of these diseases.

Methods: We searched PubMed, Ovid, and Web of Science databases for articles on studies using the ALFF/fALFF method in patients with aMCI and vMCI. Based on the activation likelihood estimation (ALE) method, connectivity modeling based on coordinate meta-analysis and functional meta-analysis was carried out.

Results: Compared with healthy controls (HCs), patients with aMCI showed increased ALFF/fALFF in the bilateral parahippocampal gyrus/hippocampus (PHG/HG), right amygdala, right cerebellum anterior lobe (CAL), left middle temporal gyrus (MTG), left cerebrum temporal lobe sub-gyral, left inferior temporal gyrus (ITG), and left cerebrum limbic lobe uncus. Meanwhile, decreased ALFF/fALFF values were also revealed in the bilateral precuneus (PCUN), bilateral cuneus (CUN), and bilateral posterior cingulate (PC) in patients with aMCI. Compared with HCs, patients with vMCI predominantly showed decreased ALFF/fALFF in the bilateral CUN, left PCUN, left PC, and right cingulate gyrus (CG).

Conclusions: The present findings suggest that ALFF and fALFF displayed remarkable altered patterns between aMCI and vMCI when compared with HCs. Thus, the findings of this study may serve as a reliable tool for distinguishing aMCI from vMCI, which may help understand the pathophysiological mechanisms of these diseases.

An Exploration of the Own-Age Effect on Facial Emotion Recognition in Normal Elderly People and Individuals with the Preclinical and Demented Alzheimer's Disease

BACKGROUND

The issue of whether there exists an own-effect on facial recognition in the elderly remains equivocal. Moreover, currently the literature of this issue in pathological aging is little.

OBJECTIVE

Our study was thus to explore the issue in both of healthy older people and patients with ADMethods:In study 1, 27 older and 31 younger healthy adults were recruited; in study 2, 27 healthy older adults and 80 patients (including subjective cognitive decline (SCD), mild cognitive impairment (MCI), and Alzheimer's disease (AD) groups) were recruited. Participants received the Taiwan Facial Emotion Recognition Task (FER Task), and a clinical neuropsychological assessment.

RESULTS

No significant differences on the FER test were found among our groups, except for sadness recognition in which our MCI and AD patients' scores were remarkably lower than their healthy counterparts. The own-age effect was not significantly evident in healthy younger and older adults, except for recognizing neutral photos. Our patients with MCI and AD tended to have the effect, particularly for the sad recognition in which the effect was significantly evident in terms of error features (mislabeling it as anger in younger-face and neutral in older-face photos).

CONCLUSION

Our results displayed no remarkable own-age effect on facial emotional recognition in the healthy elderly (including SCD). However, it did not appear the case for MCI and AD patients, especially their recognizing those sadness items, suggesting that an inclusion of the FER task particularly involving those items of low-intensity emotion in clinical neuropsychological assessment might be contributory to the early detection of AD-related pathological individuals.

Machine Learning for the Prediction of Amyloid Positivity in Amnestic Mild Cognitive Impairment

BACKGROUND

Amyloid-β (Aβ) evaluation in amnestic mild cognitive impairment (aMCI) patients is important for predicting conversion to Alzheimer's disease. However, Aβ evaluation through Aβ positron emission tomography (PET) is limited due to high cost and safety issues.

OBJECTIVE

We therefore aimed to develop and validate prediction models of Aβ positivity for aMCI using optimal interpretable machine learning (ML) approaches utilizing multimodal markers.

METHODS

We recruited 529 aMCI patients from multiple centers who underwent Aβ PET. We trained ML algorithms using a training cohort (324 aMCI from Samsung medical center) with two-phase modelling: model 1 included age, gender, education, diabetes, hypertension, apolipoprotein E genotype, and neuropsychological test scores; model 2 included the same variables as model 1 with additional MRI features. We used four-fold cross-validation during the modelling and evaluated the models on an external validation cohort (187 aMCI from the other centers).

RESULTS

Model 1 showed good accuracy (area under the receiver operating characteristic curve [AUROC] 0.837) in cross-validation, and fair accuracy (AUROC 0.765) in external validation. Model 2 led to improvement in the prediction performance with good accuracy (AUROC 0.892) in cross validation compared to model 1. Apolipoprotein E genotype, delayed recall task scores, and interaction between cortical thickness in the temporal region and hippocampal volume were the most important predictors of Aβ positivity.

CONCLUSION

Our results suggest that ML models are effective in predicting Aβ positivity at the individual level and could help the biomarker-guided diagnosis of prodromal AD.