Altered dynamic amplitude of low-frequency fluctuation in individuals at high risk for Alzheimer's disease

The brain's dynamic spontaneous neural activity is significant in supporting cognition; however, how brain dynamics go awry in subjective cognitive decline (SCD) and mild cognitive impairment (MCI) remains unclear. Thus, the current study aimed to investigate the dynamic amplitude of low-frequency fluctuation (dALFF) alterations in patients at high risk for Alzheimer's disease and to explore its correlation with clinical cognitive assessment scales, to identify an early imaging sign for these special populations. A total of 152 participants, including 72 SCD patients, 44 MCI patients and 36 healthy controls (HCs), underwent a resting-state functional magnetic resonance imaging and were assessed with various neuropsychological tests. The dALFF was measured using sliding-window analysis. We employed canonical correlation analysis (CCA) to examine the bi-multivariate correlations between neuropsychological scales and altered dALFF among multiple regions in SCD and MCI patients. Compared to those in the HC group, both the MCI and SCD groups showed higher dALFF values in the right opercular inferior frontal gyrus (voxel P < .001, cluster P < .05, correction). Moreover, the CCA models revealed that behavioural tests relevant to inattention correlated with the dALFF of the right middle frontal gyrus and right opercular inferior frontal gyrus, which are involved in frontoparietal networks (R = .43, P = .024). In conclusion, the brain dynamics of neural activity in frontal areas provide insights into the shared neural basis underlying SCD and MCI.

Atrophy of the cholinergic regions advances from early to late mild cognitive impairment

PURPOSE

We investigated the volumetric changes in the components of the cholinergic pathway for patients with early mild cognitive impairment (EMCI) and those with late mild cognitive impairment (LMCI). The effect of patients' apolipoprotein 4 (APOE-ε4) allele status on the structural changes were analyzed.

METHODS

Structural magnetic resonance imaging data were collected. Patients' demographic information, plasma data, and validated global cognitive composite scores were included. Relevant features were extracted for constructing machine learning models to differentiate between EMCI (n = 312) and LMCI (n = 541) and predict patients' neurocognitive function. The data were analyzed primarily through one-way analysis of variance and two-way analysis of covariance.

RESULTS

Considerable differences were observed in cholinergic structural changes between patients with EMCI and LMCI. Cholinergic atrophy was more prominent in the LMCI cohort than in the EMCI cohort (P < 0.05 family-wise error corrected). APOE-ε4 differentially affected cholinergic atrophy in the LMCI and EMCI cohorts. For LMCI cohort, APOE-ε4 carriers exhibited increased brain atrophy (left amygdala: P = 0.001; right amygdala: P = 0.006, and right Ch123, P = 0.032). EMCI and LCMI patients showed distinctive associations of gray matter volumes in cholinergic regions with executive (R2 = 0.063 and 0.030 for EMCI and LMCI, respectively) and language (R2 = 0.095 and 0.042 for EMCI and LMCI, respectively) function.

CONCLUSIONS

Our data confirmed significant cholinergic atrophy differences between early and late stages of mild cognitive impairment. The impact of the APOE-ε4 allele on cholinergic atrophy varied between the LMCI and EMCI groups.

Effects of Phytoncide Fragrance on Resting-State Brain Activity in Mild Cognitive Impairment: A Randomized Double-Blind Controlled Study

Introduction: The therapeutic potential of phytoncide fragrances may be optimal for patients with mild cognitive impairment (MCI) that display complex symptomatology. This study aimed to explore the clinical value of phytoncide by evaluating its electrophysiological effects in patients with MCI. Materials and Methods: This was a double-blind, randomized controlled trial. A total of 24 community-dwelling patients were randomly assigned to either a phytoncide or no-odor group. Participants wore a dental mask, for 30 min at rest that had either the fragrance stimulus or water added to it. The quantitative electroencephalography (EEG) during the resting state was recorded before and after a single intervention. Results: There were significant interaction effects in absolute EEG-power values in the occipital (F = 6.52, p = 0.018) and parietal (F = 5.41, p = 0.030) left hemisphere at β frequency. Phytoncide odor significantly decreased low and high β activity in the occipital (corrected p = 0.009) and parietal (corrected p = 0.047) left hemisphere, respectively. In source localization, phytoncide odor significantly decreased deep source activation in the left inferior and middle frontal gyri at β 2 frequency band compared with the no-odor group (threshold = 4.25, p < 0.05). Conclusions: Reductions in β, indicative of anxiety, depression, and stress, suggest relief from emotion-related symptoms that are common in patients with MCI. Trial Registration: Clinical Trials Registry Korea (registration: KCT0007317).

Artificial intelligence approaches for early detection of neurocognitive disorders among older adults

Introduction

Dementia is one of the major global health issues among the aging population, characterized clinically by a progressive decline in higher cognitive functions. This paper aims to apply various artificial intelligence (AI) approaches to detect patients with mild cognitive impairment (MCI) or dementia accurately.

Methods

Quantitative research was conducted to address the objective of this study using randomly selected 343 Saudi patients. The Chi-square test was conducted to determine the association of the patient's cognitive function with various features, including demographical and medical history. Two widely used AI algorithms, logistic regression and support vector machine (SVM), were used for detecting cognitive decline. This study also assessed patients' cognitive function based on gender and developed the predicting models for males and females separately.

Results

Fifty four percent of patients have normal cognitive function, 34% have MCI, and 12% have dementia. The prediction accuracies for all the developed models are greater than 71%, indicating good prediction capability. However, the developed SVM models performed the best, with an accuracy of 93.3% for all patients, 94.4% for males only, and 95.5% for females only. The top 10 significant predictors based on the developed SVM model are education, bedtime, taking pills for chronic pain, diabetes, stroke, gender, chronic pains, coronary artery diseases, and wake-up time.

Conclusion

The results of this study emphasize the higher accuracy and reliability of the proposed methods in cognitive decline prediction that health practitioners can use for the early detection of dementia. This research can also stipulate substantial direction and supportive intuitions for scholars to enhance their understanding of crucial research, emerging trends, and new developments in future cognitive decline studies.

Anodal transcranial direct current stimulation (atDCS) and functional transcranial Doppler sonography (fTCD) in healthy elderly and patients with MCI: modulation of age-related changes in word fluency and language lateralization

Introduction: In addition to age-related changes in language, hemispheric lateralization of language functions steadily declines with age. Also, performance on word fluency tasks declines and is sensitive to the expression of dementia-related changes. The aim of this study is to evaluate the effect of anodal tDCS combined with a word fluency training on language lateralization and word fluency performance in healthy elderly subjects and in persons with mild cognitive impairment (MCI). Methods: The effect of anodal tDCS over the left inferio frontal gyrus (IFG) was measured in a group of healthy elderly up to the age of 67 years (YG, Ø = 63.9 ± 3.02), a group of healthy elderly aged 68 years and older (OG, Ø = 78.1, ± 4.85), and a group of patients with MCI (Ø = 81.18, ± 7.35) by comparing performance in phonological and semantic word fluency tasks before and after 3 days of tDCS. Half of the experimental participants received sham stimulation. In addition, language lateralization was determined using a lateralization index (LI) measured with functional transcranial Doppler sonography (fTCD) before and after the stimulation period. Results: Anodal tDCS was associated with significantly higher scores in phonological but not semantic word fluency in both YG and OG. In MCI patients, no difference was measured between the tDCS and sham groups in either word fluency task. fTCD showed significantly increased left lateralization in all three groups after the training phase. However, this effect was independent of tDCS and the degree of lateralization could not be predicted by word fluency performance in any of the groups. Discussion: Phonological word fluency can be increased with atDCS in healthy elderly people by stimulating the IFG in a 3-day training. When cognitive decline has reached a certain stage, as is the case with MCI, this paradigm does not seem to be effective enough.

Mild cognitive impairment prediction and cognitive score regression in the elderly using EEG topological data analysis and machine learning with awareness assessed in affective reminiscent paradigm

Introduction

The main objective of this study is to evaluate working memory and determine EEG biomarkers that can assist in the field of health neuroscience. Our ultimate goal is to utilize this approach to predict the early signs of mild cognitive impairment (MCI) in healthy elderly individuals, which could potentially lead to dementia. The advancements in health neuroscience research have revealed that affective reminiscence stimulation is an effective method for developing EEG-based neuro-biomarkers that can detect the signs of MCI.

Methods

We use topological data analysis (TDA) on multivariate EEG data to extract features that can be used for unsupervised clustering, subsequent machine learning-based classification, and cognitive score regression. We perform EEG experiments to evaluate conscious awareness in affective reminiscent photography settings.

Results

We use EEG and interior photography to distinguish between healthy cognitive aging and MCI. Our clustering UMAP and random forest application accurately predict MCI stage and MoCA scores.

Discussion

Our team has successfully implemented TDA feature extraction, MCI classification, and an initial regression of MoCA scores. However, our study has certain limitations due to a small sample size of only 23 participants and an unbalanced class distribution. To enhance the accuracy and validity of our results, future research should focus on expanding the sample size, ensuring gender balance, and extending the study to a cross-cultural context.

Visual art therapy and its effects in older people with mild cognitive impairment: A systematic review

INTRODUCTION

Mild cognitive impairment (MCI) is a known risk factor for the development of dementia. The potential benefits on cognition from non-pharmacological measures such as art-based interventions are of increasing interest. This systematic review examines the evidence for the impact of one form of art-based intervention, visual art therapy (VAT), on the cognition and psychological wellbeing of older people with MCI.

METHODS

Randomised controlled and quasi-experimental trials evaluating the efficacy of VAT in older persons aged over 60 years with MCI were included. A search was performed on electronic databases: MEDLINE, CINAHL, Embase and PsycINFO. Joanna Briggs Institute critical appraisal and extraction tools were utilised for risk of bias assessment and data extraction, respectively. A narrative descriptive approach was used to outline the findings.

RESULTS

Seven studies were identified from 4311 articles screened. Improvement in cognition was reported in five studies, with two of these reporting sustained improvement at 6-9 months, while the remaining three studies showed improvement only at the immediate post-intervention period. A positive impact was reported in four of six studies that examined the effect of VAT on participant psychological wellbeing. The overall methodological quality of the studies ranged from moderate in four of five RCTs, to high in the quasi-experimental studies and one RCT. However, the low study power in the context of small sample sizes limits the applicability of these studies to the population of interest.

CONCLUSIONS

VAT is potentially an effective non-pharmacological intervention that may enhance cognition and provide benefits for psychological wellbeing in older persons with MCI. Given the limited studies available, with the majority emerging over the last 5 years, further research is required to confirm these reported benefits, as well as to determine whether VAT impacts on the progression of cognitive decline in MCI.

Abnormalities of Rest-Activity and Light Exposure Rhythms Associated with Cognitive Function in Patients with Mild Cognitive Impairment (MCI)

We aimed to examine the difference in rest-activity rhythm (RAR) and light exposure rhythm (LER) between patients with mild cognitive impairment (MCI) and normal controls (NC), and to verify their relationships with cognitive functions. The neuropsychological battery was administered to participants above 50 years old. The MCI diagnosis was made according to Petersen's criteria. Ten patients with MCI (77.90 ± 6.95 years) and eight NC (74.75 ± 5.06 years) were studied. Actigraphy (Actiwatch 2; Philips Respironics) was recorded at home for 5 days. RAR and LER variables, including interdaily stability (IS), intradaily variability (IV) and relative amplitude, were calculated using nonparametric analyses. The associations between cognitive performance and RAR and LER variables were explored using generalized linear models. There were no significant differences in RAR or LER variables between MCI and NC. There was a significant main effect of RAR-IS on the Stroop Color and Word Test (SCWT), indicating a positive relationship between RAR stability and SCWT performance. There was a significant group by RAR-IS interaction on Trail Making Test-A, indicating a negative relationship in MCI compared to NC. There was a significant group by LER-IV interaction on the Boston Naming Test, indicating a positive relationship in MCI compared to NC. There was no disruption in RAR and LER in patients with MCI. Our study showed that circadian rhythm abnormality was associated with a decline in executive function. However, circadian rhythm abnormality was not associated with declines in processing speed and language function in patients with MCI, implying an altered pathophysiology compared to NC.

Home-based, Remotely Supervised, 6-Week tDCS in Patients With Both MCI and Depression: A Randomized Double-Blind Placebo-Controlled Trial

As depressive symptom is considered a prodrome, a risk factor for progression from mild cognitive impairment (MCI) to dementia, improving depressive symptoms should be considered a clinical priority in patients with MCI undergoing transcranial direct current stimulation (tDCS) intervention. We aimed to comprehensively evaluate the efficacy of the home-based and remotely monitored tDCS in patients with both MCI and depression, by integrating cognitive, psychological, and electrophysiological indicators. In a 6-week, randomized, double blind, and sham-controlled study, 37 community-dwelling patients were randomly assigned to either an active or a sham stimulation group, and received 30 home-based sessions of 2 mA tDCS for 30 min with the anode located over the left and cathode over the right dorsolateral prefrontal cortex. We measured depressive symptoms, neurocognitive function, and resting-state electroencephalography. In terms of effects of both depressive symptoms and cognitive functions, active tDCS was not significantly different from sham tDCS. However, compared to sham stimulation, active tDCS decreased and increased the activation of delta and beta frequencies, respectively. Moreover, the increase in beta activity was correlated with the cognitive enhancement only in the active group. It was not possible to reach a definitive conclusion regarding the efficacy of tDCS on depression and cognition in patients with both MCI and depression. Nevertheless, the relationship between the changes of electrophysiology and cognitive performance suggests potential neuroplasticity enhancement implicated in cognitive processes by tDCS.

Investigating the spontaneous brain activities of patients with subjective cognitive decline and mild cognitive impairment: an amplitude of low-frequency fluctuation functional magnetic resonance imaging study

Background

Subjective cognitive decline (SCD) and mild cognitive impairment (MCI) are neurodegenerative processing stages of Alzheimer's disease (AD). Cognitive decline is thought to manifest in intrinsic brain activity changes, but research results yielded conflicting and few studies have explored the roles of brain regions in cognitive decline, and sensitivity of the cognitive field to changes in the altered intrinsic brain activity.

Methods

In this cross-sectional study, 158 elderly participants were recruited from the memory clinic of the First Affiliated Hospital of Nanjing Medical University from July 2019 to May 2021, and grouped into SCD (n=73), MCI (n=46), and normal controls (NC) (n=39). The amplitude of low-frequency fluctuation (ALFF) was calculated and evaluated among the groups. Then canonical correlation analysis (CCA) was conducted to investigate the associations between imaging outcomes and cognitive behaviors.

Results

Neuropsychological tests in different cognitive dimensions and ALFF values of the prefrontal, parietal, and temporal gyrus, were significantly different (P<0.05) among the three groups, with no appreciable decline in daily activity. The changes in intrinsic activities were closely related to the decline in cognitive function (R=0.73, P=0.002). ALFF values in the left middle occipital gyrus, right middle frontal gyrus, left superior frontal gyrus, left angular gyrus, and superior temporal gyrus played significant roles in the analysis, while the Montreal Cognitive Assessment (MoCA) and Auditory-Verbal Learning Test scores were found to be more sensitive to changes in ALFF values.

Conclusions

Spontaneous brain activity is a stable imaging biomarker of cognitive impairment. ALFF changes of the prefrontal, occipital, left angular, and temporal gyrus were sensitive to identifying cognitive decline, and the scores of the Auditory-Verbal Learning Test and MoCA could predict the abnormal intrinsic activities.

Memory performance mediates subjective sleep quality associations with cerebrospinal fluid Alzheimer's disease biomarker levels and hippocampal volume among individuals with mild cognitive symptoms

Sleep disturbances are prevalent in Alzheimer's disease (AD), affecting individuals during its early stages. We investigated associations between subjective sleep measures and cerebrospinal fluid (CSF) biomarkers of AD in adults with mild cognitive symptoms from the European Prevention of Alzheimer's Dementia Longitudinal Cohort Study, considering the influence of memory performance. A total of 442 participants aged >50 years with a Clinical Dementia Rating (CDR) score of 0.5 completed the Pittsburgh Sleep Quality Index questionnaire and underwent neuropsychological assessment, magnetic resonance imaging acquisition, and CSF sampling. We analysed the relationship of sleep quality with CSF AD biomarkers and cognitive performance in separated multivariate linear regression models, adjusting for covariates. Poorer cross-sectional sleep quality was associated with lower CSF levels of phosphorylated tau and total tau alongside better immediate and delayed memory performance. After adjustment for delayed memory scores, associations between CSF biomarkers and sleep quality became non-significant, and further analysis revealed that memory performance mediated this relationship. In post hoc analyses, poorer subjective sleep quality was associated with lesser hippocampal atrophy, with memory performance also mediating this association. In conclusion, worse subjective sleep quality is associated with less altered AD biomarkers in adults with mild cognitive symptoms (CDR score 0.5). These results could be explained by a systematic recall bias affecting subjective sleep assessment in individuals with incipient memory impairment. Caution should therefore be exercised when interpreting subjective sleep quality measures in memory-impaired populations, emphasising the importance of complementing subjective measures with objective assessments.

Multi-domain cognition dysfunction accompanies frontoparietal and temporal amyloid accumulation in the elderly

It is helpful to understand the pathology of Alzheimer's disease by exploring the relationship between amyloid-β accumulation and cognition. The study explored the relationship between regional amyloid-β accumulation and multiple cognitions and study their application value in the Alzheimer's disease diagnosis. 135 participants completed 18F-florbetapir Positron Emission Tomography (PET), structural MRI, and a cognitive battery. Partial correlation was used to examine the relationship between global and regional amyloid-β accumulation and cognitions. Then, a support vector machine was applied to determine whether cognition-related accumulation regions can adequately distinguish the cognitively normal controls (76 participants) and mild cognitive impairment (30 participants) groups or mild cognitive impairment and Alzheimer's disease (29 participants) groups. The result showed that amyloid-β accumulation regions were mainly located in the frontoparietal cortex, calcarine fissure, and surrounding cortex and temporal pole regions. Episodic memory-related regions included the frontoparietal cortices; executive function-related regions included the frontoparietal, temporal, and occipital cortices; and processing speed-related regions included the frontal and occipital cortices. Support vector machine analysis showed that only episodic memory-related amyloid-β accumulation regions had better classification performance during the progression of Alzheimer's disease. Assessing regional changes in amyloid, particularly in frontoparietal regions, can aid in the early detection of amyloid-related decline in cognitive function.

"I guess you can interpret it in a number of ways like kind of a milder or the mildest form of dementia?": Multi-stakeholder perceptions of cognitive impairment

INTRODUCTION

Mild cognitive impairment (MCI) has a high prevalence and is a risk factor for dementia. Furthering understanding of MCI has been identified as a public health priority. This research aimed to explore views about the causes of cognitive impairment and identify associations between cognitive impairment, dementia, and normative ageing.

METHOD

Semi-structured qualitative interviews were conducted with 22 participants with different stakeholder perspectives on the area of MCI in England, and analysed thematically.

RESULTS

Our analysis focuses on two main themes: 1) causes of cognitive impairment, and 2) ageing, dementia, and dying. Most participants viewed cognitive impairment as a transitional state between normative ageing and dementia. Participants expressed their fear of cognitive impairment and dementia, and made clear links between cognitive impairment and dying. Participants also showed an awareness of the links between lifestyle factors and cognitive health. However, linkage between lifestyle and cognition was discussed only when explicitly asked, suggesting that this was not especially salient for participants when considering the causes and risk factors for cognitive impairment.

CONCLUSION

The results of this study highlight key areas for future public health initiatives, such as a focus on the multitude of benefits offered by adopting a healthy diet and physical exercise in reducing risk of cognitive impairment.

C1q is increased in cerebrospinal fluid-derived extracellular vesicles in Alzheimer's disease: A multi-cohort proteomics and immuno-assay validation study

INTRODUCTION

Extracellular vesicles (EVs) may propagate and modulate Alzheimer's disease (AD) pathology. We aimed to comprehensively characterize the proteome of cerebrospinal fluid (CSF) EVs to identify proteins and pathways altered in AD.

METHODS

CSF EVs were isolated by ultracentrifugation (Cohort 1) or Vn96 peptide (Cohort 2) from non-neurodegenerative controls (n = 15, 16) and AD patients (n = 22, 20, respectively). EVs were subjected to untargeted quantitative mass spectrometry-based proteomics. Results were validated by enzyme-linked immunosorbent assay (ELISA) in Cohorts 3 and 4, consisting of controls (n = 16, n = 43, (Cohort3, Cohort4)), and patients with AD (n = 24, n = 100).

RESULTS

We found > 30 differentially expressed proteins in AD CSF EVs involved in immune-regulation. Increase of C1q levels in AD compared to non-demented controls was validated by ELISA (∼ 1.5 fold, p (Cohort 3) = 0.03, p (Cohort 4) = 0.005).

DISCUSSION

EVs may be utilized as a potential biomarker and may play a so far unprecedented role in immune-regulation in AD.

Predictive ability of the clock drawing test to detect mild cognitive impairment and dementia over time: Results from the HELIAD study

Objective: We investigated the diagnostic accuracy of the Clock Drawing Test (CDT) in discriminating Mild Cognitive Impairment (MCI) and dementia from normal cognition. Additionally, its clinical utility in predicting the transition from normal cognition to MCI and dementia over the course of several years was explored. Method: In total, 1037 older adults (633 women) who completed the CDT in a baseline assessment were drawn from the population-based HELIAD cohort. Among these, 848 participants were identified as cognitively normal, 142 as having MCI and 47 with dementia during the baseline assessment. Of these individuals, 565 attended the follow-up assessment (mean interval: 3.21 years). ROC curve and binary logistic regression analyses were performed. Results: The CDT exhibited good diagnostic accuracy for the discrimination between dementia and normal cognition (AUC = .879, SN = .813, SP = .778, LR+ = 3.66, LR- = .240, < .001, d = 1.655) and acceptable diagnostic accuracy for the discrimination between dementia and MCI (AUC=.761, SN= .750, SP= .689, LR+ = 2.41, LR- = .362, p < .001, d = 1.003). We found limited diagnostic accuracy, however, for the discrimination between MCI and normal cognition (AUC = .686, SN = .764, SP = .502, LR+ = 1.53, LR- = .470, p < .001, d = .685). Moreover, the CDT significantly predicted the transition from normal cognition to dementia [Exp(B)= 1.257, p = .022], as well as the transition from MCI to normal cognition [Exp(B) = 1.334, p = .023] during the longitudinal investigation. Conclusions: The CDT is a neuropsychological test with acceptable diagnostic accuracy for the discrimination of dementia from MCI and normal cognition. Furthermore, it has an important predictive value for the transition from normal cognition to dementia and from MCI to normal cognition.

Neuropsychological evaluation of phenoconversion risk in REM sleep behaviour disorder: A scoping review

The objective of this study was to assess the role of cognitive evaluation in the prediction of phenoconversion in polysomnography-confirmed idiopathic or isolated rapid eye movement sleep behaviour disorder, through a scoping review focussing on a longitudinal comprehensive neuropsychological assessment of patients with idiopathic REM sleep behaviour disorder. A literature search (2006-2022) yielded 1034 records, and 20 were selected for analysis. The sample included 899 patients from eight different cohorts and five countries. We extracted data on clinical evolution, mild cognitive impairment diagnosis, neuropsychological tests used, and classification of cognitive domains. Tests, cognitive domains, and mild cognitive impairment definitions were heterogeneous across the studies, precluding a meta-analysis. Ten studies (50%) evaluated the presence of mild cognitive impairment; 14 studies (70%) grouped neuropsychological tests into between three (6 studies, 21.4%) and seven (1 study, 7.1%) cognitive domains. The most frequently used tests were semantic fluency, Stroop colour word test, trail making test A and B, digit span, Rey auditory verbal learning test, and Rey-Osterrieth figure. All except digit span showed a role in predicting phenoconversion. The authors did not consistently assign tests to specific cognitive domains. In conclusion, we discuss methodological differences between the studies and highlight the need for a standardised framework for neuropsychological data acquisition and presentation, based on a multilevel approach covering test selection, domain assignment, and mild cognitive impairment diagnostic criteria.

Atrophy of specific amygdala subfields in subjects converting to mild cognitive impairment

Introduction

Accumulating evidence indicates that the amygdala exhibits early signs of Alzheimer's disease (AD) pathology. However, it is still unknown whether the atrophy of distinct subfields of the amygdala also participates in the transition from healthy cognition to mild cognitive impairment (MCI).

Methods

Our sample was derived from the AD Neuroimaging Initiative 3 and consisted of 97 cognitively healthy (HC) individuals, sorted into two groups based on their clinical follow-up: 75 who remained stable (s-HC) and 22 who converted to MCI within 48 months (c-HC). Anatomical magnetic resonance (MR) images were analyzed using a semi-automatic approach that combines probabilistic methods and a priori information from ex vivo MR images and histology to segment and obtain quantitative structural metrics for different amygdala subfields in each participant. Spearman's correlations were performed between MR measures and baseline and longitudinal neuropsychological measures. We also included anatomical measurements of the whole amygdala, the hippocampus, a key target of AD-related pathology, and the whole cortical thickness as a test of spatial specificity.

Results

Compared with s-HC individuals, c-HC subjects showed a reduced right amygdala volume, whereas no significant difference was observed for hippocampal volumes or changes in cortical thickness. In the amygdala subfields, we observed selected atrophy patterns in the basolateral nuclear complex, anterior amygdala area, and transitional area. Macro-structural alterations in these subfields correlated with variations of global indices of cognitive performance (measured at baseline and the 48-month follow-up), suggesting that amygdala changes shape the cognitive progression to MCI.

Discussion

Our results provide anatomical evidence for the early involvement of the amygdala in the preclinical stages of AD.

Highlights

Amygdala's atrophy marks elderly progression to mild cognitive impairment (MCI).Amygdala's was observed within the basolateral and amygdaloid complexes.Macro-structural alterations were associated with cognitive decline.No atrophy was found in the hippocampus and cortex.

Mild Cognitive Impairment among Elderly Persons Residing in an Urban Resettlement Colony in Delhi

Background

Mild cognitive impairment (MCI) is a transitional state between normal cognition and clinical dementia. MCI is associated with an increased risk of dementia and mortality. Progression of MCI to dementia can be prevented by cognitive and lifestyle interventions. There is limited evidence on the burden and risk factors associated with MCI in India. To estimate the prevalence of MCI among elderly persons, and to study the factors associated with MCI.

Materials and Methods

This community-based cross-sectional study was carried out among 365 persons aged 60 years or older, residing in an urban resettlement colony of Delhi. Participants with dementia (score <23 on the Hindi version of the Mini-Mental State Examination) were excluded. Objective cognitive impairment and functional disability were assessed by the Montreal Cognitive Impairment-Basic (MoCA-B) tool and Barthel's Activities of Daily Living, respectively. The prevalence of MCI was estimated by Petersen's criteria, i.e., subjective memory impairment, objective cognitive impairment (MoCA score 19-25), functional independence, and absence of dementia. Univariate analysis was performed, followed by stepwise multivariate logistic regression. The association of socio-demographic and other health conditions with MCI was assessed.

Results

The prevalence of MCI was 9.3% [95% confidence interval (CI) 6.7-12.7], 13.3% (95% CI 8.8-19.7) among men, and 6.5% (95% CI 3.9-10.6) among women. The risk of MCI was higher among current smokers.

Conclusions

MCI was common among the elderly. Early detection of MCI may be included in health programs for elderly persons.

Families of patients with Alzheimer's disease dementia notice progression from symptoms of disorientation and visual memory disturbance

BACKGROUND

Alzheimer's disease dementia (ADD) is the most common cognitive disease, but patients' families may notice some symptoms yet not recognise that they indicate ADD. This study investigated the symptoms that families notice as ADD as the disease progresses.

METHODS

New outpatients diagnosed with ADD (n = 315) at five memory clinics completed two cognitive assessments, the Revised Hasegawa Dementia Scale (HDS-R) and Mini-Mental State Examination (MMSE). During an interview, family members completed the Functional Assessment Staging Test (FAST), an observational assessment tool that classifies ADD progression into seven stages. We then examined the relationship of the family-assessed FAST score with clinician-assessed HDS-R and MMSE domain scores by comparing between patients with FAST 1-3 and FAST 4-7. Next, we divided the FAST 4-7 group into the FAST 4-5 and FAST 6-7 subgroups and divided the FAST 1-3 group into the FAST 1-2 and FAST 3 subgroups.

RESULTS

Surprisingly, half of the families did not recognise that the symptoms indicated ADD. Scores for orientation of time and place on the HDS-R and MMSE and for visual memory on the HDS-R were significantly related to family-assessed FAST score. Moreover, the orientation of time and place score on both scales and visual memory on the HDS-R were significantly worse in the FAST 4-7 group than in FAST 1-3 group. In the FAST 4-7 group, scores for age on the HDS-R and for reading and drawing on the MMSE were significantly worse in the FAST 6-7 subgroup. In the analysis of the FAST 1-3 group, there was no significant difference among the HDS-R and MMSE domains between the FAST 1-2 and FAST 3 subgroups.

CONCLUSIONS

Family members of patients with ADD tend to notice the progression of ADD from the symptoms of disorientation and visual memory.

A holo-spectral EEG analysis provides an early detection of cognitive decline and predicts the progression to Alzheimer's disease

Aims

Our aim was to differentiate patients with mild cognitive impairment (MCI) and Alzheimer's disease (AD) from cognitively normal (CN) individuals and predict the progression from MCI to AD within a 3-year longitudinal follow-up. A newly developed Holo-Hilbert Spectral Analysis (HHSA) was applied to resting state EEG (rsEEG), and features were extracted and subjected to machine learning algorithms.

Methods

A total of 205 participants were recruited from three hospitals, with CN (n = 51, MMSE > 26), MCI (n = 42, CDR = 0.5, MMSE ≥ 25), AD1 (n = 61, CDR = 1, MMSE < 25), AD2 (n = 35, CDR = 2, MMSE < 16), and AD3 (n = 16, CDR = 3, MMSE < 16). rsEEG was also acquired from all subjects. Seventy-two MCI patients (CDR = 0.5) were longitudinally followed up with two rsEEG recordings within 3 years and further subdivided into an MCI-stable group (MCI-S, n = 36) and an MCI-converted group (MCI-C, n = 36). The HHSA was then applied to the rsEEG data, and features were extracted and subjected to machine-learning algorithms.

Results

(a) At the group level analysis, the HHSA contrast of MCI and different stages of AD showed augmented amplitude modulation (AM) power of lower-frequency oscillations (LFO; delta and theta bands) with attenuated AM power of higher-frequency oscillations (HFO; beta and gamma bands) compared with cognitively normal elderly controls. The alpha frequency oscillation showed augmented AM power across MCI to AD1 with a reverse trend at AD2. (b) At the individual level of cross-sectional analysis, implementation of machine learning algorithms discriminated between groups with good sensitivity (Sen) and specificity (Spec) as follows: CN elderly vs. MCI: 0.82 (Sen)/0.80 (Spec), CN vs. AD1: 0.94 (Sen)/0.80 (Spec), CN vs. AD2: 0.93 (Sen)/0.90 (Spec), and CN vs. AD3: 0.75 (Sen)/1.00 (Spec). (c) In the longitudinal MCI follow-up, the initial contrasted HHSA between MCI-S and MCI-C groups showed significantly attenuated AM power of alpha and beta band oscillations. (d) At the individual level analysis of longitudinal MCI groups, deploying machine learning algorithms with the best seven features resulted in a sensitivity of 0.9 by the support vector machine (SVM) classifier, with a specificity of 0.8 yielded by the decision tree classifier.

Conclusion

Integrating HHSA into EEG signals and machine learning algorithms can differentiate between CN and MCI as well as also predict AD progression at the MCI stage.

Human hippocampal astrocytes: Computational dissection of their transcriptome, sexual differences and exosomes across ageing and mild-cognitive impairment

The role of astrocytes in Alzheimer's disease is often disregarded. Hence, characterization of astrocytes along their early evolution toward Alzheimer would be greatly beneficial. However, due to their exquisite responsiveness, in vivo studies are difficult. So public microarray data of hippocampal homogenates from (healthy) young, (healthy) elder and elder with mild cognitive impairment (MCI) were subjected to re-analysis by a multi-step computational pipeline. Ontologies and pathway analyses were compared after determining the differential genes that, belonging to astrocytes, have splice forms. Likewise, the subset of molecules exportable to exosomes was also determined. The results showed that astrocyte's phenotypes changed significantly. While already 'activated' astrocytes were found in the younger group, major changes occurred during ageing (increased vascular remodelling and response to mechanical stimulus, diminished long-term potentiation and increased long-term depression). MCI's astrocytes showed some 'rejuvenated' features, but their sensitivity to shear stress was markedly lost. Importantly, most of the changes showed to be sex biassed. Men's astrocytes are enriched in a type 'endfeet-astrocytome', whereas women's astrocytes appear close to the 'scar-forming' type (prone to endothelial dysfunction, hypercholesterolemia, loss of glutamatergic synapses, Ca+2 dysregulation, hypoxia, oxidative stress and 'pro-coagulant' phenotype). In conclusion, the computational dissection of the networks based on the hippocampal gene isoforms provides a relevant proxy to in vivo astrocytes, also revealing the occurrence of sexual differences. Analyses of the astrocytic exosomes did not provide an acceptable approximation to the overall functioning of astrocytes in the hippocampus, probably due to the selective cellular mechanisms which charge the cargo molecules.

Topological properties of individual gray matter morphological networks in identifying the preclinical stages of Alzheimer's disease: a preliminary study

Background

Subjective cognitive decline (SCD) and mild cognitive impairment (MCI) are preclinical stages of Alzheimer's disease (AD). Individual biomarkers are essential for evaluating altered neurological outcomes at both SCD and MCI stages for early diagnosis and intervention of AD. In this study, we aimed to investigate the relationships between topological properties of the individual brain morphological network and clinical cognitive performances among healthy controls (HCs) and patients with SCD or MCI.

Methods

The topological measurements of individual morphological networks were analyzed using graph theory, and inter-group differences of standard graph topology were correlated and regressed to scores of clinical cognitive functions.

Results

Compared with HCs, the topology of the individual morphological networks in SCD and MCI patients was significantly altered. At the global level, altered topology was characterized by lower global efficiency, shorter characteristics path length, and normalized characteristics path length [all P<0.05, false discovery rate (FDR) corrected]. In addition, at the regional level, SCD and MCI patients exhibited abnormal degree centrality in the caudate nucleus and nodal efficiency in the caudate nucleus, right insula, lenticular nucleus, and putamen (all P<0.05, FDR corrected).

Conclusions

The topological features of individual gray matter morphological networks may serve as biomarkers to improve disease prognosis and intervention in the early stages of AD, namely SCD and MCI. Moreover, these findings may further elucidate the relationships between brain morphological alterations and cognitive dysfunctions in SCD and MCI.

Analytical Validation of a Novel MicroRNA Panel for Risk Stratification of Cognitive Impairment

We have been developing a novel approach to identify cognitive impairment-related biomarkers by profiling brain-enriched and inflammation-associated microRNA (miRNA) in plasma specimens of cognitively unimpaired and cognitively impaired patients. Here, we present an analytical validation of the novel miRNA panel, CogniMIR^®, using two competing quantitative PCR technologies for the expression analysis of 24 target miRNAs. Total RNA from the plasma specimens was isolated using the MagMAX mirVana Kit, and RT-qPCR was performed using stem-loop-based TaqMan and LNA-based qPCR assays. Evaluation of RNA dilution series for our target 24 miRNAs, performed by two operators on two different days, demonstrated that all CogniMIR^® panel miRNAs can be reliably and consistently detected by both qPCR technologies, with sample input as low as 20 copies in a qPCR reaction. Intra-run and inter-run repeatability and reproducibility analyses using RNA specimens demonstrated that both operators generated repeatable and consistent Cts, with R² values of 0.94 to 0.99 and 0.96 to 0.97, respectively. The study results clearly indicate the suitability of miRNA profiling of plasma specimens using either of the qPCR technologies. However, the LNA-based qPCR technology appears to be more operationally friendly and better suited for a CAP/CLIA-certified clinical laboratory.

Altered structural covariance of locus coeruleus in individuals with significant memory concern and patients with mild cognitive impairment

The locus coeruleus (LC) is the site where tau accumulation is preferentially observed pathologically in Alzheimer's disease (AD) patients, but the changes in gray matter co-alteration patterns between the LC and the whole brain in the predementia phase of AD remain unclear. In this study, we estimated and compared the gray matter volume of the LC and its structural covariance (SC) with the whole brain among 161 normal healthy controls (HCs), 99 individuals with significant memory concern (SMC) and 131 patients with mild cognitive impairment (MCI). We found that SC decreased in MCI groups, which mainly involved the salience network and default mode network. These results imply that seeding from LC, the gray matter network disruption and disconnection appears early in the MCI group. The altered SC network seeding from the LC can serve as an imaging biomarker for discriminating the patients in the potential predementia phase of AD from the normal subjects.

The correlation between changes in gray matter microstructure and cerebral blood flow in Alzheimer's disease

Objective

To investigate the relationship between changes in cerebral blood flow (CBF) and gray matter (GM) microstructure in Alzheimer's disease (AD) and mild cognitive impairment (MCI).

Methods

A recruited cohort of 23 AD patients, 40 MCI patients, and 37 normal controls (NCs) underwent diffusional kurtosis imaging (DKI) for microstructure evaluation and pseudo-continuous arterial spin labeling (pCASL) for CBF assessment. We investigated the differences in diffusion- and perfusion-related parameters across the three groups, including CBF, mean diffusivity (MD), mean kurtosis (MK), and fractional anisotropy (FA). These quantitative parameters were compared using volume-based analyses for the deep GM and surface-based analyses for the cortical GM. The correlation between CBF, diffusion parameters, and cognitive scores was assessed using Spearman coefficients, respectively. The diagnostic performance of different parameters was investigated with k-nearest neighbor (KNN) analysis, using fivefold cross-validation to generate the mean accuracy (mAcc), mean precision (mPre), and mean area under the curve (mAuc).

Results

In the cortical GM, CBF reduction primarily occurred in the parietal and temporal lobes. Microstructural abnormalities were predominantly noted in the parietal, temporal, and frontal lobes. In the deep GM, more regions showed DKI and CBF parametric changes at the MCI stage. MD showed most of the significant abnormalities among all the DKI metrics. The MD, FA, MK, and CBF values of many GM regions were significantly correlated with cognitive scores. In the whole sample, the MD, FA, and MK were associated with CBF in most evaluated regions, with lower CBF values associated with higher MD, lower FA, or lower MK values in the left occipital lobe, left frontal lobe, and right parietal lobe. CBF values performed best (mAuc = 0.876) for distinguishing the MCI from the NC group. Last, MD values performed best (mAuc = 0.939) for distinguishing the AD from the NC group.

Conclusion

Gray matter microstructure and CBF are closely related in AD. Increased MD, decreased FA, and MK are accompanied by decreased blood perfusion throughout the AD course. Furthermore, CBF values are valuable for the predictive diagnosis of MCI and AD. GM microstructural changes are promising as novel neuroimaging biomarkers of AD.

Does Alzheimer's disease with mesial temporal lobe epilepsy represent a distinct disease subtype?

Alzheimer's disease (AD) patients have a high risk of developing mesial temporal lobe epilepsy (MTLE) and subclinical epileptiform activity. MTLE in AD worsens outcomes. Therefore, we need to understand the overlap between these disease processes. We hypothesize that AD with MTLE represents a distinct subtype of AD, with the interplay between tau and epileptiform activity at its core. We discuss shared pathological features including histopathology, an initial mesial temporal lobe (MTL) hyperexcitability followed by MTL dysfunction and involvement of same networks in memory (AD) and seizures (MTLE). We provide evidence that tau accumulation linearly increases neuronal hyperexcitability, neuronal hyper-excitability increases tau secretion, tau can provoke seizures, and tau reduction protects against seizures. We speculate that AD genetic mutations increase tau, which causes proportionate neuronal loss and/or hyperexcitability, leading to seizures. We discuss that tau burden in MTLE predicts cognitive deficits among (1) AD and (2) MTLE without AD. Finally, we explore the possibility that anti-seizure medications improve cognition by reducing neuronal hyper-excitability, which reduces seizures and tau accumulation and spread. HIGHLIGHTS: We hypothesize that patients with Alzheimer's disease (AD) and mesial temporal lobe epilepsy (MTLE) represents a distinct subtype of AD. AD and MTLE share histopathological features and involve overlapping neuronal and cortical networks. Hyper-phosphorylated tau (pTau) increases neuronal excitability and provoke seizures, neuronal excitability increases pTau, and pTau reduction reduces neuronal excitability and protects against seizures. The pTau burden in MTL predicts cognitive deficits among (1) AD and (2) MTLE without AD. We speculate that anti-seizure medications improve cognition by reducing neuronal excitability, which reduces seizures and pTau.

Serum cortisol is negatively related to hippocampal volume, brain structure, and memory performance in healthy aging and Alzheimer's disease

Objective

Elevated cortisol levels have been frequently reported in Alzheimer's disease (AD) and linked to brain atrophy, especially of the hippocampus. Besides, high cortisol levels have been shown to impair memory performance and increase the risk of developing AD in healthy individuals. We investigated the associations between serum cortisol levels, hippocampal volume, gray matter volume and memory performance in healthy aging and AD.

Methods

In our cross-sectional study, we analyzed the relationships between morning serum cortisol levels, verbal memory performance, hippocampal volume, and whole-brain voxel-wise gray matter volume in an independent sample of 29 healthy seniors (HS) and 29 patients along the spectrum of biomarker-based AD.

Results

Cortisol levels were significantly elevated in patients with AD as compared to HS, and higher cortisol levels were correlated with worse memory performance in AD. Furthermore, higher cortisol levels were significantly associated with smaller left hippocampal volumes in HS and indirectly negatively correlated to memory function through hippocampal volume. Higher cortisol levels were further related to lower gray matter volume in the hippocampus and temporal and parietal areas in the left hemisphere in both groups. The strength of this association was similar in HS and AD.

Conclusion

In AD, cortisol levels are elevated and associated with worse memory performance. Furthermore, in healthy seniors, higher cortisol levels show a detrimental relationship with brain regions typically affected by AD. Thus, increased cortisol levels seem to be indirectly linked to worse memory function even in otherwise healthy individuals. Cortisol may therefore not only serve as a biomarker of increased risk for AD, but maybe even more importantly, as an early target for preventive and therapeutic interventions.

Transcranial Electrical Stimulation for Associative Memory Enhancement: State-of-the-Art from Basic to Clinical Research

Associative memory (AM) is the ability to bind new information into complex memory representations. Noninvasive brain stimulation (NIBS), especially transcranial electric stimulation (tES), has gained increased interest in research of associative memory (AM) and its impairments. To provide an overview of the current state of knowledge, we conducted a systematic review following PRISMA guidelines covering basic and clinical research. Out of 374 identified records, 41 studies were analyzed-twenty-nine in healthy young adults, six in the aging population, three comparing older and younger adults, as well as two studies on people with MCI, and one in people with Alzheimer's dementia. Studies using transcranial direct current stimulation (tDCS), transcranial alternating current stimulation (tACS) as well as oscillatory (otDCS) and high-definition protocols (HD-tDCS, HD-tACS) have been included. The results showed methodological heterogeneity in terms of study design, stimulation type, and parameters, as well as outcome measures. Overall, the results show that tES is a promising method for AM enhancement, especially if the stimulation is applied over the parietal cortex and the effects are assessed in cued recall paradigms.

Regional spectral ratios as potential neural markers to identify mild cognitive impairment related to Alzheimer's disease

OBJECTIVE

Alzheimer's disease (AD) has prolonged asymptomatic or mild symptomatic periods. Given that there is an increase in treatment options and that early intervention could modify the disease course, it is desirable to devise biological indices that may differentiate AD and nonAD at mild cognitive impairment (MCI) stage.

METHODS

Based on two well-acknowledged observations of background slowing (attenuation in alpha power and enhancement in theta and delta powers) and early involvement of posterior cingulate cortex (PCC, a neural hub of default-mode network), this study devised novel neural markers, namely, spectral ratios of alpha1 to delta and alpha1 to theta in the PCC.

RESULTS

We analysed 46 MCI patients, with 22 ADMCI and 24 nonADMCI who were matched in age, education, and global cognitive capability. Concordant with the prediction, the regional spectral ratios were lower in the ADMCI group, suggesting its clinical application potential.

CONCLUSION

Previous research has verified that neural markers derived from clinical electroencephalography may be informative in differentiating AD from other neurological conditions. We believe that the spectral ratios in the neural hubs that show early pathological changes can enrich the instrumental assessment of brain dysfunctions at the MCI (or pre-clinical) stage.

Relationship between Brain-Derived Neurotrophic Factor and Cognitive Decline in Patients with Mild Cognitive Impairment and Dementia

In the last decade, increasing evidence has emerged linking alterations in the brain-derived neurotrophic factor (BDNF) expression with the development of Alzheimer's disease (AD). Because of the important role of BDNF in cognition and its association with AD pathogenesis, the aim of this study was to evaluate the potential difference in plasma BDNF concentrations between subjects with mild cognitive impairment (MCI; N = 209) and AD patients (N = 295) and to determine the possible association between BDNF plasma levels and the degree of cognitive decline in these individuals. The results showed a significantly higher (p < 0.001) concentration of plasma BDNF in subjects with AD (1.16; 0.13-21.34) compared with individuals with MCI (0.68; 0.02-19.14). The results of the present study additionally indicated a negative correlation between cognitive functions and BDNF plasma concentrations, suggesting higher BDNF levels in subjects with more pronounced cognitive decline. The correlation analysis revealed a significant negative correlation between BDNF plasma levels and both Mini-Mental State Examination (p < 0.001) and Clock Drawing test (p < 0.001) scores. In conclusion, the results of our study point towards elevated plasma BDNF levels in AD patients compared with MCI subjects, which may be due to the body's attempt to counteract the early and middle stages of neurodegeneration.

Comparison of Machine Learning-based Approaches to Predict the Conversion to Alzheimer's Disease from Mild Cognitive Impairment

In Mild Cognitive Impairment (MCI), identifying a high risk of conversion to Alzheimer's Disease Dementia (AD) is a primary goal for patient management. Machine Learning (ML) algorithms are widely employed to pursue data-driven diagnostic and prognostic goals. An agreement on the stability of these algorithms -when applied to different biomarkers and other conditions- is far from being reached. In this study, we compared the different prognostic performances of three supervised ML algorithms fed with multimodal biomarkers of MCI subjects obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. Random Forest, Gradient Boosting, and eXtreme Gradient Boosting algorithms predict MCI conversion to AD. They can also be simultaneously employed -with the voting procedure- to improve predictivity. AD prediction accuracy is influenced by the nature of the data (i.e., neuropsychological test scores, cerebrospinal fluid AD-related proteins and APOE ε4, cerebral structural MRI (sMRI) data). In our study, independent of the applied ML algorithms, sMRI data showed the lowest accuracy (0.79) compared to other classes. Multimodal data were helpful in the algorithms' performances by combining clinical and biological measures. Accordingly, using the three ML algorithms, the highest accuracy (0.90) was reached by employing neuropsychological and AD-related biomarkers. Finally, the feature selection procedure indicated that the most critical variables in the respective classes were the ADAS-Cog-13 scale, the medial temporal lobe and hippocampus atrophy, and the ratio between phosphorylated Tau and Aβ42 proteins. In conclusion, our data support the notion that using multiple ML algorithms and multimodal biomarkers helps make more accurate and solid predictions.

The Value of Clock Drawing Process Assessment in Screening for Mild Cognitive Impairment and Alzheimer's Dementia

Many clock drawing test (CDT) scoring systems focus on drawing results and lack drawing process assessments. This study created a CDT scoring procedure with drawing process assessment and explored its diagnostic value in screening for mild cognitive impairment (MCI) and early Alzheimer's disease (AD) from normal control (NC). We used logistic regression and receiver operating characteristic (ROC) curves to determine a new, sensitive scoring system for AD and MCI patients in a derivation cohort. The new scoring method was then compared to two common scoring systems and externally validated in a second cohort. We developed a new scoring system named CDT5, which contained one process assessment item: remember setting time without asking. Compared with two published scoring systems, CDT5 had better discriminatory power in distinguishing AD patients from NCs in derivation (area under the ROC curve [area under the curve, AUC] = .890) and validation (AUC = .867) cohorts. Three scoring systems had poor diagnostic accuracy at discriminating MCI patients from controls, with CDT5 being the most sensitive (78.57%). Adding the drawing process in CDT helps accurately detect patients with early AD, but its role in identifying patients with MCI needs to be further explored.

Visual-spatial processing impairment in the occipital-frontal connectivity network at early stages of Alzheimer's disease

Introduction

Alzheimer's disease (AD) is the leading cause of dementia worldwide, but its pathophysiological phenomena are not fully elucidated. Many neurophysiological markers have been suggested to identify early cognitive impairments of AD. However, the diagnosis of this disease remains a challenge for specialists. In the present cross-sectional study, our objective was to evaluate the manifestations and mechanisms underlying visual-spatial deficits at the early stages of AD.

Methods

We combined behavioral, electroencephalography (EEG), and eye movement recordings during the performance of a spatial navigation task (a virtual version of the Morris Water Maze adapted to humans). Participants (69-88 years old) with amnesic mild cognitive impairment-Clinical Dementia Rating scale (aMCI-CDR 0.5) were selected as probable early AD (eAD) by a neurologist specialized in dementia. All patients included in this study were evaluated at the CDR 0.5 stage but progressed to probable AD during clinical follow-up. An equal number of matching healthy controls (HCs) were evaluated while performing the navigation task. Data were collected at the Department of Neurology of the Clinical Hospital of the Universidad de Chile and the Department of Neuroscience of the Faculty of Universidad de Chile.

Results

Participants with aMCI preceding AD (eAD) showed impaired spatial learning and their visual exploration differed from the control group. eAD group did not clearly prefer regions of interest that could guide solving the task, while controls did. The eAD group showed decreased visual occipital evoked potentials associated with eye fixations, recorded at occipital electrodes. They also showed an alteration of the spatial spread of activity to parietal and frontal regions at the end of the task. The control group presented marked occipital activity in the beta band (15-20 Hz) at early visual processing time. The eAD group showed a reduction in beta band functional connectivity in the prefrontal cortices reflecting poor planning of navigation strategies.

Discussion

We found that EEG signals combined with visual-spatial navigation analysis, yielded early and specific features that may underlie the basis for understanding the loss of functional connectivity in AD. Still, our results are clinically promising for early diagnosis required to improve quality of life and decrease healthcare costs.

A systematic review and meta-analysis of the prevalence and correlation of mild cognitive impairment in sarcopenia

Sarcopenia is a progressive skeletal muscle disorder involving the loss of muscle mass and function, associated with an increased risk of disability and frailty. Though its prevalence in dementia has been studied, its occurrence in mild cognitive impairment (MCI) has not been well established. As MCI is often a prelude to dementia, our study aims to investigate the prevalence of MCI among individuals with sarcopenia and to also ascertain whether sarcopenia is independently associated with MCI. The Cochrane Library, PubMed, Ovid, Embase and Web of Science were systematically searched for articles on MCI and/or sarcopenia published from inception to 1 February 2022. We reviewed the available literature on the number of individuals with MCI and/or sarcopenia and calculated odds ratios (ORs) of sarcopenia in MCI and MCI in sarcopenia, respectively. Statistical analyses were performed using the meta package in Stata, Version 12.0. A total of 13 studies and 27 428 patients were included in our analysis. The pooled prevalence of MCI in participants with sarcopenia was 20.5% (95% confidence interval [CI]: 0.140-0.269) in a total sample of 2923 cases with a high level of heterogeneity (P < 0.001; I²  = 95.4%). The overall prevalence of sarcopenia with MCI was 9.1% (95% CI: 0.047-0.134, P < 0.001; I²  = 93.0%). For overall ORs, there were 23 364 subjects with a mean age of 73 years; the overall adjusted OR between MCI and sarcopenia was 1.46 (95% CI: 1.31-1.62). Slight heterogeneity in both adjusted ORs (P = 0.46; I²  = 0%) was noted across the studies. The prevalence of MCI is relatively high in patients with sarcopenia, and sarcopenia may be a risk factor for MCI.

Mini-Mental State Examination: Optimal Cut-Off Levels for Mild and Severe Cognitive Impairment

Considering the need to intercept neurocognitive damage as soon as possible, it would be useful to extend cognitive test screening throughout the population. Here, we propose differential cut-off levels that can be used to identify mild and severe cognitive impairment with a simple and widely used first-level neurocognitive screening test: the Mini-Mental State Examination (MMSE). We studied a population of 262 patients referred for cognitive impairment testing using the MMSE and Repeatable Battery for the Assessment of Neuropsychological Status (RBANS), a neuropsychological battery. The sample consisted of 262 participants with mean age 73.8 years (60-87), of whom 154 (58.8%) women. No significant gender-related differences in cognitive ability were identified. The two tests (MMSE and RBANS) showed a moderate correlation in identifying cognitive deficit. We used RBANS as a categorial variable to identify different degrees of cognitive impairment. Youden's J indexes were used to consider the better sensitivity/specificity balance in the 24-point cut-off score for severe cognitive deficit, 29.7-point score for mild cognitive deficit, and 26.1-point score for both mild and severe cognitive deficit. The study shows that the MMSE does not identify early cognitive impairment. Though different cut-offs are needed to discriminate different impairment degrees, the 26.1-point score seems to be preferable to the others.

The Synergic Effect of AT(N) Profiles and Depression on the Risk of Conversion to Dementia in Patients with Mild Cognitive Impairment

Few studies have addressed the impact of the association between Alzheimer's disease (AD) biomarkers and NPSs in the conversion to dementia in patients with mild cognitive impairment (MCI), and no studies have been conducted on the interaction effect of these two risk factors. AT(N) profiles were created using AD-core biomarkers quantified in cerebrospinal fluid (CSF) (normal, brain amyloidosis, suspected non-Alzheimer pathology (SNAP) and prodromal AD). NPSs were assessed using the Neuropsychiatric Inventory Questionnaire (NPI-Q). A total of 500 individuals with MCI were followed-up yearly in a memory unit. Cox regression analysis was used to determine risk of conversion, considering additive and multiplicative interactions between AT(N) profile and NPSs on the conversion to dementia. A total of 224 participants (44.8%) converted to dementia during the 2-year follow-up study. Pathologic AT(N) groups (brain amyloidosis, prodromal AD and SNAP) and the presence of depression and apathy were associated with a higher risk of conversion to dementia. The additive combination of the AT(N) profile with depression exacerbates the risk of conversion to dementia. A synergic effect of prodromal AD profile with depressive symptoms is evidenced, identifying the most exposed individuals to conversion among MCI patients.

Common Neuropsychiatric S ymptoms in Alzheimer's Disease, Mild Cognitive Impairment, and Subjective Memory Complaints: A Unified Framework

The Alzheimer's disease (AD) continuum is a unique spectrum of cognitive impairment that typically involves the stages of subjective memory complaints (SMC), mild cognitive impairment (MCI), and AD dementia. Neuropsychiatric symptoms (NPS), such as apathy, anxiety, stress, and depression, are highly common throughout the AD continuum. However, there is a dearth of research on how these NPS vary across the AD continuum, especially SMC. There is also disagreement on the effects of specific NPS on each stage of the AD continuum due to their collinearity with other NPS, cognitive decline, and environmental factors (e.g., stress). In this article, we conduct a novel perspective review of the scientific literature to understand the presence of NPS across the AD continuum. Specifically, we review the effects of apathy, depression, anxiety, and stress in AD, MCI, and SMC. We then build on this knowledge by proposing two theories of NPS' occurrence across the AD continuum. Consequently, we highlight the current landscape, limitations (e.g., differing operationalization), and contentions surrounding the NPS literature. We also outline theories that could clear up contention and inspire future NPS research.

Prefrontal EEG slowing, synchronization, and ERP peak latency in association with predementia stages of Alzheimer's disease

Background

Early screening of elderly individuals who are at risk of dementia allows timely medical interventions to prevent disease progression. The portable and low-cost electroencephalography (EEG) technique has the potential to serve it.

Objective

We examined prefrontal EEG and event-related potential (ERP) variables in association with the predementia stages of Alzheimer's disease (AD).

Methods

One hundred elderly individuals were recruited from the GARD cohort. The participants were classified into four groups according to their amyloid beta deposition (A+ or A-) and neurodegeneration status (N+ or N-): cognitively normal (CN; A-N-, n = 27), asymptomatic AD (aAD; A + N-, n = 15), mild cognitive impairment (MCI) with AD pathology (pAD; A+N+, n = 16), and MCI with non-AD pathology (MCI(-); A-N+, n = 42). Prefrontal resting-state eyes-closed EEG measurements were recorded for five minutes and auditory ERP measurements were recorded for 8 min. Three variables of median frequency (MDF), spectrum triangular index (STI), and positive-peak latency (PPL) were employed to reflect EEG slowing, temporal synchrony, and ERP latency, respectively.

Results

Decreasing prefrontal MDF and increasing PPL were observed in the MCI with AD pathology. Interestingly, after controlling for age, sex, and education, we found a significant negative association between MDF and the aAD and pAD stages with an odds ratio (OR) of 0.58. Similarly, PPL exhibited a significant positive association with these AD stages with an OR of 2.36. Additionally, compared with the MCI(-) group, significant negative associations were demonstrated by the aAD group with STI and those in the pAD group with MDF with ORs of 0.30 and 0.42, respectively.

Conclusion

Slow intrinsic EEG oscillation is associated with MCI due to AD, and a delayed ERP peak latency is likely associated with general cognitive impairment. MCI individuals without AD pathology exhibited better cortical temporal synchronization and faster EEG oscillations than those with aAD or pAD.

Significance

The EEG/ERP variables obtained from prefrontal EEG techniques are associated with early cognitive impairment due to AD and non-AD pathology. This result suggests that prefrontal EEG/ERP metrics may serve as useful indicators to screen elderly individuals' early stages on the AD continuum as well as overall cognitive impairment.

Disrupted Balance of Gray Matter Volume and Directed Functional Connectivity in Mild Cognitive Impairment and Alzheimer's Disease

BACKGROUND

Alterations in functional connectivity have been demonstrated in Alzheimer's disease (AD), an age-progressive neurodegenerative disorder that affects cognitive function; however, directional information flow has never been analyzed.

OBJECTIVE

This study aimed to determine changes in resting-state directional functional connectivity measured using a novel approach, granger causality density (GCD), in patients with AD, and mild cognitive impairment (MCI) and explore novel neuroimaging biomarkers for cognitive decline detection.

METHODS

In this study, structural MRI, resting-state functional magnetic resonance imaging, and neuropsychological data of 48 Alzheimer's Disease Neuroimaging Initiative participants were analyzed, comprising 16 patients with AD, 16 with MCI, and 16 normal controls. Volume-based morphometry (VBM) and GCD were used to calculate the voxel-based gray matter (GM) volumes and directed functional connectivity of the brain. We made full use of voxel-based between-group comparisons of VBM and GCD values to identify specific regions with significant alterations. In addition, Pearson's correlation analysis was conducted between directed functional connectivity and several clinical variables. Furthermore, receiver operating characteristic (ROC) analysis related to classification was performed in combination with VBM and GCD.

RESULTS

In patients with cognitive decline, abnormal VBM and GCD (involving inflow and outflow of GCD) were noted in default mode network (DMN)-related areas and the cerebellum. GCD in the DMN midline core system, hippocampus, and cerebellum was closely correlated with the Mini- Mental State Examination and Functional Activities Questionnaire scores. In the ROC analysis combining VBM with GCD, the neuroimaging biomarker in the cerebellum was optimal for the early detection of MCI, whereas the precuneus was the best in predicting cognitive decline progression and AD diagnosis.

CONCLUSION

Changes in GM volume and directed functional connectivity may reflect the mechanism of cognitive decline. This discovery could improve our understanding of the pathology of AD and MCI and provide available neuroimaging markers for the early detection, progression, and diagnosis of AD and MCI.

From attention-deficit hyperactivity disorder to sporadic Alzheimer's disease-Wnt/mTOR pathways hypothesis

Alzheimer's disease (AD) is the most common neurodegenerative disorder with the majority of patients classified as sporadic AD (sAD), in which etiopathogenesis remains unresolved. Though sAD is argued to be a polygenic disorder, apolipoprotein E (APOE) ε4, was found three decades ago to pose the strongest genetic risk for sAD. Currently, the only clinically approved disease-modifying drugs for AD are aducanumab (Aduhelm) and lecanemab (Leqembi). All other AD treatment options are purely symptomatic with modest benefits. Similarly, attention-deficit hyperactivity disorder (ADHD), is one of the most common neurodevelopmental mental disorders in children and adolescents, acknowledged to persist in adulthood in over 60% of the patients. Moreover, for ADHD whose etiopathogenesis is not completely understood, a large proportion of patients respond well to treatment (first-line psychostimulants, e.g., methylphenidate/MPH), however, no disease-modifying therapy exists. Interestingly, cognitive impairments, executive, and memory deficits seem to be common in ADHD, but also in early stages of mild cognitive impairment (MCI), and dementia, including sAD. Therefore, one of many hypotheses is that ADHD and sAD might have similar origins or that they intercalate with one another, as shown recently that ADHD may be considered a risk factor for sAD. Intriguingly, several overlaps have been shown between the two disorders, e.g., inflammatory activation, oxidative stress, glucose and insulin pathways, wingless-INT/mammalian target of rapamycin (Wnt/mTOR) signaling, and altered lipid metabolism. Indeed, Wnt/mTOR activities were found to be modified by MPH in several ADHD studies. Wnt/mTOR was also found to play a role in sAD and in animal models of the disorder. Moreover, MPH treatment in the MCI phase was shown to be successful for apathy including some improvement in cognition, according to a recent meta-analysis. In several AD animal models, ADHD-like behavioral phenotypes have been observed indicating a possible interconnection between ADHD and AD. In this concept paper, we will discuss the various evidence in human and animal models supporting the hypothesis in which ADHD might increase the risk for sAD, with common involvement of the Wnt/mTOR-pathway leading to lifespan alteration at the neuronal levels.

Estimating effective connectivity in Alzheimer's disease progression: A dynamic causal modeling study

Introduction

Alzheimer's disease (AD) affects the whole brain from the cellular level to the entire brain network structure. The causal relationship among brain regions concerning the different AD stages is not yet investigated. This study used Dynamic Causal Modeling (DCM) method to assess effective connectivity (EC) and investigate the changes that accompany AD progression.

Methods

We included the resting-state fMRI data of 34 AD patients, 31 late mild cognitive impairment (LMCI) patients, 34 early MCI (EMCI) patients, and 31 cognitive normal (CN) subjects selected from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. The parametric Empirical Bayes (PEB) method was used to infer the effective connectivities and the corresponding probabilities. A linear regression analysis was carried out to test if the connection strengths could predict subjects' cognitive scores.

Results

The results showed that the connections reduced from full connection in the CN group to no connection in the AD group. Statistical analysis showed the connectivity strengths were lower for later-stage patients. Linear regression analysis showed that the connection strengths were partially predictive of the cognitive scores.

Discussion

Our results demonstrated the dwindling connectivity accompanying AD progression on causal relationships among brain regions and indicated the potential of EC as a loyal biomarker in AD progression.

Differential impact of body mass index and leptin on baseline and longitudinal positron emission tomography measurements of the cerebral metabolic rate for glucose in amnestic mild cognitive impairment

Introduction

Several studies have suggested that greater adiposity in older adults is associated with a lower risk of Alzheimer's disease (AD) related cognitive decline, some investigators have postulated that this association may be due to the protective effects of the adipose tissue-derived hormone leptin. In this study we sought to demonstrate that higher body mass indices (BMIs) are associated with greater baseline FDG PET measurements of the regional cerebral metabolic rate for glucose (rCMRgl), a marker of local neuronal activity, slower rCMRgl declines in research participants with amnestic mild cognitive impairment (aMCI). We then sought to clarify the extent to which those relationships are attributable to cerebrospinal fluid (CSF) or plasma leptin concentrations.

Materials and methods

We used baseline PET images from 716 73 ± 8 years-old aMCI participants from the AD Neuroimaging Initiative (ADNI) of whom 453 had follow up images (≥6 months; mean follow up time 3.3 years). For the leptin analyses, we used baseline CSF samples from 81 of the participants and plasma samples from 212 of the participants.

Results

As predicted, higher baseline BMI was associated with greater baseline CMRgl measurements and slower declines within brain regions preferentially affected by AD. In contrast and independently of BMI, CSF, and plasma leptin concentrations were mainly related to less baseline CMRgl within mesocorticolimbic brain regions implicated in energy homeostasis.

Discussion

While higher BMIs are associated with greater baseline CMRgl and slower declines in persons with aMCI, these associations appear not to be primarily attributable to leptin concentrations.

Dual-targeted repetitive transcranial magnetic stimulation modulates brain functional network connectivity to improve cognition in mild cognitive impairment patients

Background: Mild cognitive impairment (MCI) is a condition between normal aging and dementia; nearly 10-15% of MCI patients develop dementia annually. There are no effective interventions for MCI progression. Repetitive transcranial magnetic stimulation (rTMS) is a non-invasive brain stimulation technique that has attempted to improve the overall cognitive function of MCI patients. However, it does not affect episodic memory improvement. Methods: In this study, we engaged 15 clinically diagnosed MCI patients and normal controls to explore the effect of dual-targeted rTMS on progressing cognitive function, particularly episodic memory in MCI patients. Resting-state EEG recordings and neuropsychological assessments were conducted before and after the intervention. EEG features were extracted using an adaptive algorithm to calculate functional connectivity alterations in relevant brain regions and the mechanisms of altered brain functional networks in response to dual-target rTMS. Results: The study revealed that the functional brain connectivity between the right posterior cingulate gyrus (PCC) and the right dorsal caudate nucleus (DC) was significantly reduced in MCI patients compared to normal controls (p < 0.001). Dual-target rTMS increased the strength of the reduced functional connectivity (p < 0.001), which was related to cognitive enhancement (p < 0.05). Conclusion: This study provides a new stimulation protocol for rTMS intervention. Improving the functional connectivity of the right PCC to the right DC is a possible mechanism by which rTMS improves overall cognitive and memory function in MCI patients.

Factors associated with dropout in the longitudinal Vogel study of cognitive decline

Dementia, including Alzheimer's disease, is a growing problem worldwide. Prevention or early detection of the disease or a prodromal cognitive decline is necessary. By means of our long-term follow-up 'Vogel study', we aim to predict the pathological cognitive decline of a German cohort (mean age was 73.9 ± 1.55 years at first visit) with three measurement time points within 6 years per participant. Especially in samples of the elderly and subjects with chronic or co-morbid diseases, dropouts are one of the biggest problems of long-term studies. In contrast to the large number of research articles conducted on the course of dementia, little research has been done on the completion of treatment. To ensure unbiased and reliable predictors of cognitive decline from study completers, our objective was to determine predictors of dropout. We conducted multivariate analyses of covariance and multinomial logistic regression analyses to compare and predict the subject's dropout behaviour at the second visit 3 years after baseline (full participation, partial participation and no participation/dropout) with neuropsychiatric, cognitive, blood and lifestyle variables. Lower performance in declarative memory, attention and visual-spatial processing predicted dropout rather than full participation. Lower performance in visual-spatial processing predicted partial participation as opposed to full participation. Furthermore, lower performance in mini-mental status examination predicted whether subjects dropped out or participated partially instead of full participation. Baseline cognitive parameters are associated with dropouts at follow-up with a loss of impaired participants. We expect a bias into a healthier sample over time.

A modified Cued Recall Test for detecting prodromal AD in adults with Down syndrome

Introduction

The development of valid methods to diagnose prodromal Alzheimer's disease (AD) in adults with Down syndrome (DS) is one of the many goals of the Alzheimer's Biomarkers Consortium-Down Syndrome (ABC-DS).

Methods

The diagnostic utility of a modified Cued Recall Test (mCRT) was evaluated in 332 adults with DS ranging from 25 to 81 years of age. Total recall was selected a priori, as the primary indicator of performance. Multiple regression and receiver-operating characteristic (ROC) analyses were used to compare diagnostic groups.

Results

Performance on the mCRT, as indicated by the total recall score, was highly sensitive to differences between diagnostic groups. ROC areas under the curve (AUCs) ranging from 0.843 to 0.955, were observed.

Discussion

The mCRT has strong empirical support for its use in clinical settings, as a valuable tool in studies targeting biomarkers of AD, and as a potential outcome measure in clinical trials targeting AD in this high-risk population.

Relationships between urinary metals concentrations and cognitive performance among U.S. older people in NHANES 2011-2014

Background

Epidemiological evidence on Urine metals and cognitive impairment in older individuals is sparse and limited. The goal of this study was to analyze if there was a link between urinary metal levels and cognitive performance in U.S. people aged 60 and up.

Methods

The National Health and Nutrition Examination Survey (NHANES) data from 2011 to 2014 were utilized in this cross-sectional analysis. Memory function was quantified using the following methods: Established Consortium for Word Learning in Alzheimer's Disease (CERAD-WL) (immediate learning and recall and delayed recall), Animal Fluency Test (AFT), and Digit Symbol Substitution Test (DSST). An inductively coupled plasma mass spectrometry (ICP-MS) was used to estimate urine metal concentrations. The connection of Urine metals level with cognitive function was investigated employing binary logistic regression and restricted cubic spline models.

Results

A total of 840 participants aged 60 years and over were enrolled in this study. After controlling for confounders, the association between cadmium, barium, cobalt, cesium, manganese, and thallium and poor cognitive performance showed significance in multiple logistic regression compared to the lowest quartile of metals. In the DSST test, the weighted multivariate adjusted ORs (95% CI) for cadmium in the highest quartile, barium and cesium in the third quartile were 2.444 (1.310-4.560), 0.412 (0.180-0.942) and 0.440 (0.198-0.979), respectively. There were L-shaped associations between urine cesium, barium, or manganese and low cognitive performance in DSST. Urine lead, molybdenum and uranium did not show any significant relationships with cognitive impairment, respectively, compared to the respective lowest quartile concentrations.

Conclusion

The levels of barium (Ba), cobalt (Co), cesium (Cs), manganese (Mn), and thallium (Tl) in urine were found to be negatively related to the prevalence of impaired cognitive performance in our cross-sectional investigation. Higher cadmium (Cd) levels were associated with cognitive impairment.