Magnetic resonance imaging characterization of brain structure and function in mild cognitive impairment: a review

Efficacy and Safety of Panax ginseng Sprout Extract in Subjective Memory Impairment: A Randomized, Double-Blind, Placebo-Controlled Clinical Trial

Sprout ginseng extract (ThinkGIN™) manufactured through a smart farm system has been shown to improve memory in preclinical studies. This study conducted a 12-week randomized, double-blind, placebo-controlled clinical trial to evaluate the efficacy and safety of ThinkGIN™ for improving memory in subjective memory impairment (SMI). Subjects aged 55 to 75 years with SMI participated in this study. A total of 80 subjects who met the inclusion/exclusion criteria were assigned to the ThinkGIN™ group (n = 40, 450 mg ThinkGIN™/day) or a placebo group (n = 40). Efficacy and safety evaluations were conducted before intervention and at 12 weeks after intervention. As a result of 12 weeks of ThinkGIN™ intake, significant differences in SVLT, RCFT, MoCA-K, PSQI-K, and AChE were observed between the two groups. Safety evaluation (AEs, laboratory tests, vital signs, and electrocardiogram) revealed that ThinkGIN™ was safe with no clinically significant changes. Therefore, ThinkGIN™ has the potential to be used as a functional food to improve memory.

Automatic detection of cognitive impairment in patients with white matter hyperintensity and causal analysis of related factors using artificial intelligence of MRI

PURPOSE

White matter hyperintensity (WMH) is a common feature of brain aging, often linked with cognitive decline and dementia. This study aimed to employ deep learning and radiomics to develop models for detecting cognitive impairment in WMH patients and to analyze the causal relationships among cognitive impairment and related factors.

MATERIALS AND METHODS

A total of 79 WMH patients from hospital 1 were randomly divided into a training set (62 patients) and a testing set (17 patients). Additionally, 29 patients from hospital 2 were included as an independent testing set. All participants underwent formal neuropsychological assessments to determine cognitive status. Automated identification and segmentation of WMH were conducted using VB-net, with extraction of radiomics features from cortex, white matter, and nuclei. Four machine learning classifiers were trained on the training set and validated on the testing set to detect cognitive impairment. Model performances were evaluated and compared. Causal analyses were conducted among cortex, white matter, nuclei alterations, and cognitive impairment.

RESULTS

Among the models, the logistic regression (LR) model based on white matter features demonstrated the highest performance, achieving an AUC of 0.819 in the external test dataset. Causal analyses indicated that age, education level, alterations in cortex, white matter, and nuclei were causal factors of cognitive impairment.

CONCLUSION

The LR model based on white matter features exhibited high accuracy in detecting cognitive impairment in WMH patients. Furthermore, the possible causal relationships among alterations in cortex, white matter, nuclei, and cognitive impairment were elucidated.

Comparison of approaches to control for intracranial volume in research on the association of brain volumes with cognitive outcomes

Most neuroimaging studies linking regional brain volumes with cognition correct for total intracranial volume (ICV), but methods used for this correction differ across studies. It is unknown whether different ICV correction methods yield consistent results. Using a brain-wide association approach in the MRI substudy of UK Biobank (N = 41,964; mean age = 64.5 years), we used regression models to estimate the associations of 58 regional brain volumetric measures with eight cognitive outcomes, comparing no correction and four ICV correction approaches. Approaches evaluated included: no correction; dividing regional volumes by ICV (proportional approach); including ICV as a covariate in the regression (adjustment approach); and regressing the regional volumes against ICV in different normative samples and using calculated residuals to determine associations (residual approach). We used Spearman-rank correlations and two consistency measures to quantify the extent to which associations were inconsistent across ICV correction approaches for each possible brain region and cognitive outcome pair across 2320 regression models. When the association between brain volume and cognitive performance was close to null, all approaches produced similar estimates close to the null. When associations between a regional volume and cognitive test were not null, the adjustment and residual approaches typically produced similar estimates, but these estimates were inconsistent with results from the crude and proportional approaches. For example, when using the crude approach, an increase of 0.114 (95% confidence interval [CI]: 0.103-0.125) in fluid intelligence was associated with each unit increase in hippocampal volume. However, when using the adjustment approach, the increase was 0.055 (95% CI: 0.043-0.068), while the proportional approach showed a decrease of -0.025 (95% CI: -0.035 to -0.014). Different commonly used methods to correct for ICV yielded inconsistent results. The proportional method diverges notably from other methods and results were sometimes biologically implausible. A simple regression adjustment for ICV produced biologically plausible associations.

Cortical thickness alterations and systemic inflammation define long-COVID patients with cognitive impairment

As the heterogeneity of symptoms is increasingly recognized among long-COVID patients, it appears highly relevant to study potential pathophysiological differences along the different subtypes. Preliminary evidence suggests distinct alterations in brain structure and systemic inflammatory patterns in specific groups of long-COVID patients. To this end, we analyzed differences in cortical thickness and peripheral immune signature between clinical subgroups based on 3 T-MRI scans and signature inflammatory markers in n = 120 participants comprising healthy never-infected controls (n = 30), healthy COVID-19 survivors (n = 29), and subgroups of long-COVID patients with (n = 26) and without (n = 35) cognitive impairment according to screening with Montreal Cognitive Assessment. Whole-brain comparison of cortical thickness between the 4 groups was conducted by surface-based morphometry. We identified distinct cortical areas showing a progressive increase in cortical thickness across different groups, starting from healthy individuals who had never been infected with COVID-19, followed by healthy COVID-19 survivors, long-COVID patients without cognitive deficits (MoCA ≥ 26), and finally, long-COVID patients exhibiting significant cognitive deficits (MoCA < 26). These findings highlight the continuum of cortical thickness alterations associated with COVID-19, with more pronounced changes observed in individuals experiencing cognitive impairment (p < 0.05, FWE-corrected). Affected cortical regions covered prefrontal and temporal gyri, insula, posterior cingulate, parahippocampal gyrus, and parietal areas. Additionally, we discovered a distinct immunophenotype, with elevated levels of IL-10, IFNγ, and sTREM2 in long-COVID patients, especially in the group suffering from cognitive impairment. We demonstrate lingering cortical and immunological alterations in healthy and impaired subgroups of COVID-19 survivors. This implies a complex underlying pathomechanism in long-COVID and emphasizes the necessity to investigate the whole spectrum of post-COVID biology to determine targeted treatment strategies targeting specific sub-groups.

Disentangling Accelerated Cognitive Decline from the Normal Aging Process and Unraveling Its Genetic Components: A Neuroimaging-Based Deep Learning Approach

Background

The progressive cognitive decline, an integral component of Alzheimer's disease (AD), unfolds in tandem with the natural aging process. Neuroimaging features have demonstrated the capacity to distinguish cognitive decline changes stemming from typical brain aging and AD between different chronological points.

Objective

To disentangle the normal aging effect from the AD-related accelerated cognitive decline and unravel its genetic components using a neuroimaging-based deep learning approach.

Methods

We developed a deep-learning framework based on a dual-loss Siamese ResNet network to extract fine-grained information from the longitudinal structural magnetic resonance imaging (MRI) data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) study. We then conducted genome-wide association studies (GWAS) and post-GWAS analyses to reveal the genetic basis of AD-related accelerated cognitive decline.

Results

We used our model to process data from 1,313 individuals, training it on 414 cognitively normal people and predicting cognitive assessment for all participants. In our analysis of accelerated cognitive decline GWAS, we identified two genome-wide significant loci: APOE locus (chromosome 19 p13.32) and rs144614292 (chromosome 11 p15.1). Variant rs144614292 (G > T) has not been reported in previous AD GWA studies. It is within the intronic region of NELL1, which is expressed in neurons and plays a role in controlling cell growth and differentiation. The cell-type-specific enrichment analysis and functional enrichment of GWAS signals highlighted the microglia and immune-response pathways.

Conclusions

Our deep learning model effectively extracted relevant neuroimaging features and predicted individual cognitive decline. We reported a novel variant (rs144614292) within the NELL1 gene.

Neuropsychiatric disturbances in mild cognitive impairment: A scientometric analysis

Behavioral and psychological symptoms of dementia (BPSD) have been extensively studied in dementia than its prodromal stage, known as mild cognitive impairment (MCI). A scientometric study on BPSD in MCI would be valuable in synthesizing the existing body of research and providing insights into the trends, networks, and influencers within this area. We searched for related literature in the Web of Science database and extracted complete text and citation records of each publication. The primary objective was to map the research evolution of BPSD in MCI and highlight dominant research themes. The secondary objective was to identify research network characteristics (authors, journals, countries, and institutions) and abundances. A total of 12,369 studies published between 1980 and 2022 were included in the analysis. We found 51 distinct clusters from the co-cited reference network that were highly credible with significant modularity (Q = 0.856) and silhouette scores (S = 0.932). Five major research domains were identified: symptoms, diagnosis, brain substrates, biochemical pathways, and interventions. In recent years, the research focus in this area has been on gut microbiota, e-health, COVID-19, cognition, and delirium. Collectively, findings from this scientometric analysis can help clarify the scope and direction of future research and clinical practices.

Association Between Acoustic Features and Brain Volumes: the Framingham Heart Study

Introduction

Although brain magnetic resonance imaging (MRI) is a valuable tool for investigating structural changes in the brain associated with neurodegeneration, the development of non-invasive and cost-effective alternative methods for detecting early cognitive impairment is crucial. The human voice has been increasingly used as an indicator for effectively detecting cognitive disorders, but it remains unclear whether acoustic features are associated with structural neuroimaging.

Methods

This study aims to investigate the association between acoustic features and brain volume and compare the predictive power of each for mild cognitive impairment (MCI) in a large community-based population. The study included participants from the Framingham Heart Study (FHS) who had at least one voice recording and an MRI scan. Sixty-five acoustic features were extracted with the OpenSMILE software (v2.1.3) from each voice recording. Nine MRI measures were derived according to the FHS MRI protocol. We examined the associations between acoustic features and MRI measures using linear regression models adjusted for age, sex, and education. Acoustic composite scores were generated by combining acoustic features significantly associated with MRI measures. The MCI prediction ability of acoustic composite scores and MRI measures were compared by building random forest models and calculating the mean area under the receiver operating characteristic curve (AUC) of 10-fold cross-validation.

Results

The study included 4,293 participants (age 57 ± 13 years, 53.9% women). During 9.3±3.7 years follow-up, 106 participants were diagnosed with MCI. Seven MRI measures were significantly associated with more than 20 acoustic features after adjusting for multiple testing. The acoustic composite scores can improve the AUC for MCI prediction to 0.794, compared to 0.759 achieved by MRI measures.

Discussion

We found multiple acoustic features were associated with MRI measures, suggesting the potential for using acoustic features as easily accessible digital biomarkers for the early diagnosis of MCI.

Enhanced Harris hawks optimization-based fuzzy k-nearest neighbor algorithm for diagnosis of Alzheimer's disease

In order to stop deterioration and give patients with Alzheimer's disease (AD) early therapy, it is crucial to correctly diagnose AD and its early stage, mild cognitive impairment (MCI). A framework for diagnosing AD is presented in this paper, which includes magnetic resonance imaging (MRI) image preprocessing, feature extraction, and the Fuzzy k-nearest neighbor algorithm (FKNN) model. In particular, the framework's novelty lies in the use of an improved Harris Hawks Optimization (HHO) algorithm named SSFSHHO, which integrates the Sobol sequence and Stochastic Fractal Search (SFS) mechanisms for optimizing the parameters of FKNN. The HHO method improves the quality of the initial population overall by incorporating the Sobol sequence, and the SFS mechanism increases the algorithm's capacity to get out of the local optimum solution. Comparisons with other classical meta-heuristic algorithms, state-of-the-art HHO variants in low and high dimensions, and enhanced meta-heuristic algorithms on 30 typical IEEE CEC2014 benchmark test problems show that the overall performance of SSFSHHO is significantly better than other comparative algorithms. Moreover, the created framework based on the SSFSHHO-FKNN model is employed to classify AD and MCI using MRI scans from the ADNI dataset, achieving high classification performance for 6 representative cases. Experimental findings indicate that the proposed algorithm performs better than a number of high-performance optimization algorithms and classical machine learning algorithms, thus offering a promising approach for AD classification. Additionally, the proposed strategy can successfully identify relevant features and enhance classification performance for AD diagnosis.

Disentangling accelerated cognitive decline from the normal aging process and unraveling its genetic components: A neuroimaging-based deep learning approach

Background

The progressive cognitive decline that is an integral component of AD unfolds in tandem with the natural aging process. Neuroimaging features have demonstrated the capacity to distinguish cognitive decline changes stemming from typical brain aging and Alzheimer's disease between different chronological points.

Methods

We developed a deep-learning framework based on dual-loss Siamese ResNet network to extract fine-grained information from the longitudinal structural magnetic resonance imaging (MRI) data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) study. We then conducted genome-wide association studies (GWAS) and post-GWAS analyses to reveal the genetic basis of AD-related accelerated cognitive decline.

Results

We used our model to process data from 1,313 individuals, training it on 414 cognitively normal people and predicting cognitive assessment for all participants. In our analysis of accelerated cognitive decline GWAS, we identified two genome-wide significant loci: APOE locus (chromosome 19 p13.32) and rs144614292 (chromosome 11 p15.1). Variant rs144614292 (G>T) has not been reported in previous AD GWA studies. It is within the intronic region of NELL1, which is expressed in neuron and plays a role in controlling cell growth and differentiation. In addition, MUC7 and PROL1/OPRPNon chromosome 4 were significant at the gene level. The cell-type-specific enrichment analysis and functional enrichment of GWAS signals highlighted the microglia and immune-response pathways. Furthermore, we found that the cognitive decline slope GWAS was positively correlated with previous AD GWAS.

Conclusion

Our deep learning model was demonstrated effective on extracting relevant neuroimaging features and predicting individual cognitive decline. We reported a novel variant (rs144614292) within the NELL1 gene. Our approach has the potential to disentangle accelerated cognitive decline from the normal aging process and to determine its related genetic factors, leveraging opportunities for early intervention.

Occupational and Environmental Noise Exposure and Extra-Auditory Effects on Humans: A Systematic Literature Review

Noise is a common harmful factor in our work and the environment. Most studies have investigated the auditory effects of noise exposure; however, few studies have focused on the extra-auditory effects of exposure to occupational or environmental noise. This study aimed to systematically review published studies on the extra-auditory effects of noise exposure. We reviewed literature from PubMed and Google Scholar databases up to July 2022, using the Patient, Intervention, Comparison, and Outcome criteria and Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines to identify studies that reported extra-auditory effects of occupational or environmental noise exposure. Studies were evaluated utilizing validated reporting tools (CONSORT, STROBE) appropriate to study design. A total of 263 articles were identified, of which 36 were finally selected and reviewed. Upon conducting a review of the articles, exposure to noise can elicit a variety of extra-auditory effects on humans. These effects include circulatory effects linked to higher risk of cardiovascular disease and decreased endothelial function, nervous system effects correlated with sleep disturbance, cognitive impairment, and mental health problems, immunological and endocrinal effects connected to increased physiological stress response and metabolic disorders, oncological and respiratory effects associated with an elevated risk of acoustic neuroma and respiratory disorders, gastrointestinal effects linked to an increased risk of gastric or duodenal ulcer, and obstetric effects connected to the risk of preterm birth. Our review suggests that there are numerous extra-auditory effects of noise exposure on human, and further investigations are needed to fully understand these effects.

A Deep Spatiotemporal Attention Network for Mild Cognitive Impairment Identification

Mild cognitive impairment (MCI) is a nervous system disease, and its clinical status can be used as an early warning of Alzheimer's disease (AD). Subtle and slow changes in brain structure between patients with MCI and normal controls (NCs) deprive them of effective diagnostic methods. Therefore, the identification of MCI is a challenging task. The current functional brain network (FBN) analysis to predict human brain tissue structure is a new method emerging in recent years, which provides sensitive and effective medical biomarkers for the diagnosis of neurological diseases. Therefore, to address this challenge, we propose a novel Deep Spatiotemporal Attention Network (DSTAN) framework for MCI recognition based on brain functional networks. Specifically, we first extract spatiotemporal features between brain functional signals and FBNs by designing a spatiotemporal convolution strategy (ST-CONV). Then, on this basis, we introduce a learned attention mechanism to further capture brain nodes strongly correlated with MCI. Finally, we fuse spatiotemporal features for MCI recognition. The entire network is trained in an end-to-end fashion. Extensive experiments show that our proposed method significantly outperforms current baselines and state-of-the-art methods, with a classification accuracy of 84.21%.

Multiomics Analysis of Structural Magnetic Resonance Imaging of the Brain and Cerebrospinal Fluid Metabolomics in Cognitively Normal and Impaired Adults

INTRODUCTION

Integrating brain imaging with large scale omics data may identify novel mechanisms of mild cognitive impairment (MCI) and early Alzheimer's disease (AD). We integrated and analyzed brain magnetic resonance imaging (MRI) with cerebrospinal fluid (CSF) metabolomics to elucidate metabolic mechanisms and create a "metabolic map" of the brain in prodromal AD.

METHODS

In 145 subjects (85 cognitively normal controls and 60 with MCI), we derived voxel-wise gray matter volume via whole-brain structural MRI and conducted high-resolution untargeted metabolomics on CSF. Using a data-driven approach consisting of partial least squares discriminant analysis, a multiomics network clustering algorithm, and metabolic pathway analysis, we described dysregulated metabolic pathways in CSF mapped to brain regions associated with MCI in our cohort.

RESULTS

The multiomics network algorithm clustered metabolites with contiguous imaging voxels into seven distinct communities corresponding to the following brain regions: hippocampus/parahippocampal gyrus (three distinct clusters), thalamus, posterior thalamus, parietal cortex, and occipital lobe. Metabolic pathway analysis indicated dysregulated metabolic activity in the urea cycle, and many amino acids (arginine, histidine, lysine, glycine, tryptophan, methionine, valine, glutamate, beta-alanine, and purine) was significantly associated with those regions (P < 0.05).

CONCLUSION

By integrating CSF metabolomics data with structural MRI data, we linked specific AD-susceptible brain regions to disrupted metabolic pathways involving nitrogen excretion and amino acid metabolism critical for cognitive function. Our findings and analytical approach may extend drug and biomarker research toward more multiomics approaches.

Assessment of Cognitive Reserve using Near Infrared Spectroscopy

Cognitive reserve (CR) is the ability to preserve cognitive functions in the presence of brain pathology. In the context of Alzheimer's disease (AD), patients with higher CR show better cognitive performance relative to brain damage therefore higher CR reduces the risk of dementia. There is a strong need to develop a neurophysiological biomarker of CR given the growing interest in understanding protective brain mechanisms in AD. FMRI studies indicate that frontoparietal network plays an important role in cognitive reserve. We calculated intraregional functional connectivity of lateral prefrontal cortex (FC LPFC) using functional near infrared spectroscopy (fNIRS) in the resting state of 13 healthy individuals who were also assessed for IQ and motoric skills (the Purdue Pegboard test, PPT). FC LPFC was found to positively correlate with IQ (a proxy measure of cognitive reserve) while showing a lack of or negative correlation with the PPT scores. The results demonstrate that the cost-effective, noninvasive and widely applicable fNIRS technology can be used to evaluate cognitive reserve in individuals at risk for and patients with AD with possible numerous applications in the context of healthy aging and other age-related cognitive disorders.

Apolipoprotein E homozygous ε4 allele status: Effects on cortical structure and white matter integrity in a young to mid-age sample

Apolipoprotein E (APOE) genotype is the strongest single gene predictor of Alzheimer's disease (AD) and has been frequently associated with AD-related brain structural alterations before the onset of dementia. While previous research has primarily focused on hippocampal morphometry in relation to APOE, sporadic recent findings have questioned the specificity of the hippocampus and instead suggested more global effects on the brain. With the present study we aimed to investigate associations between homozygous APOE ε4 status and cortical gray matter structure as well as white matter microstructure. In our study, we contrasted n = 31 homozygous APOE ε4 carriers (age=34.47 years, including a subsample of n = 12 subjects with depression) with a demographically matched sample without an ε4 allele (resulting total sample: N = 62). Morphometry analyses included a) Freesurfer based cortical segmentations of thickness and surface area measures and b) tract based spatial statistics of DTI measures. We found pronounced and widespread reductions in cortical surface area of ε4 homozygotes in 57 out of 68 cortical brain regions. In contrast, no differences in cortical thickness were observed. Furthermore, APOE ε4 homozygous carriers showed significantly lower fractional anisotropy in the corpus callosum, the right internal and external capsule, the left corona radiata and the right fornix. The present findings support a global rather than regionally specific effect of homozygous APOE ε4 allele status on cortical surface area and white matter microstructure. Future studies should aim to delineate the clinical implications of these findings.

Brain Entropy Mapping in Healthy Aging and Alzheimer's Disease

Alzheimer's disease (AD) is a progressive neurodegenerative disease, for which aging remains the major risk factor. Aging is under a consistent pressure of increasing brain entropy (BEN) due to the progressive brain deteriorations. Noticeably, the brain constantly consumes a large amount of energy to maintain its functional integrity, likely creating or maintaining a big "reserve" to counteract the high entropy. Malfunctions of this latent reserve may indicate a critical point of disease progression. The purpose of this study was to characterize BEN in aging and AD and to test an inverse-U-shape BEN model: BEN increases with age and AD pathology in normal aging but decreases in the AD continuum. BEN was measured with resting state fMRI and compared across aging and the AD continuum. Associations of BEN with age, education, clinical symptoms, and pathology were examined by multiple regression. The analysis results highlighted resting BEN in the default mode network, medial temporal lobe, and prefrontal cortex and showed that: (1) BEN increased with age and pathological deposition in normal aging but decreased with age and pathological deposition in the AD continuum; (2) AD showed catastrophic BEN reduction, which was related to more severe cognitive impairment and daily function disability; and (3) BEN decreased with education years in normal aging, but not in the AD continuum. BEN evolution follows an inverse-U trajectory when AD progresses from normal aging to AD dementia. Education is beneficial for suppressing the entropy increase potency in normal aging.

A feasibility study on the association between residential greenness and neurocognitive function in middle-aged Bulgarians

Recent research has indicated that exposure to residential vegetation ("greenness") may be protective against cognitive decline and may support the integrity of the corresponding brain structures. However, not much is known about these effects, especially in less affluent countries and in middle-aged populations. In this study, we investigated the associations between greenness and neurocognitive function. We used a convenience sample of 112 middle-aged Bulgarians and two cognitive tests: the Consortium to Establish a Registry for Alzheimer's Disease Neuropsychological Battery (CERAD-NB) and the Montreal Cognitive Assessment (MoCA). In addition, structural brain imaging data were available for 25 participants. Participants' home address was used to link cognition scores to the normalised difference vegetation index (NDVI), a measure of overall neighbourhood vegetation level (radii from 100 to 1,000 m). Results indicated that higher NDVI was consistently associated with higher CERAD-NB and MoCA scores across radial buffers and adjustment scenarios. Lower waist circumference mediated the effect of NDVI on CERAD-NB. NDVI100-m was positively associated with average cortical thickness across both hemispheres, but these correlations turned marginally significant (P<0.1) after correction for false discovery rate due to multiple comparisons. In conclusion, living in a greener neighbourhood might be associated with better cognitive function in middle-aged Bulgarians, with lower central adiposity partially accounting for this effect. Tentative evidence suggests that greenness might also contribute to structural integrity in the brain regions regulating cognitive functions. Future research should build upon our findings and investigate larger and more representative population groups.

Resting State Abnormalities of the Default Mode Network in Mild Cognitive Impairment: A Systematic Review and Meta-Analysis

BACKGROUND

Large-scale brain networks such as the default mode network (DMN) are often disrupted in Alzheimer's disease (AD). Numerous studies have examined DMN functional connectivity in those with mild cognitive impairment (MCI), a presumed AD precursor, to discover a biomarker of AD risk. Prior reviews were qualitative or limited in scope or approach.

OBJECTIVE

We aimed to systematically and quantitatively review DMN resting state fMRI studies comparing MCI and healthy comparison (HC) groups.

METHODS

PubMed was searched for relevant articles. Study characteristics were abstracted and the number of studies showing no group difference or hyper- versus hypo-connnectivity in MCI was tallied. A voxel-wise (ES-SDM) meta-analysis was conducted to identify regional group differences.

RESULTS

Qualitatively, our review of 57 MCI versus HC comparisons suggests substantial inconsistency; 9 showed no group difference, 8 showed MCI > HC and 22 showed HC > MCI across the brain, and 18 showed regionally-mixed directions of effect. The meta-analysis of 31 studies revealed areas of significant hypo- and hyper-connectivity in MCI, including hypoconnectivity in the posterior cingulate cortex/precuneus (z = -3.1, p < 0.0001). Very few individual studies, however, showed patterns resembling the meta-analytic results. Methodological differences did not appear to explain inconsistencies.

CONCLUSIONS

The pattern of altered resting DMN function or connectivity in MCI is complex and variable across studies. To date, no index of DMN connectivity qualifies as a useful biomarker of MCI or risk for AD. Refinements to MCI diagnosis, including other biological markers, or longitudinal studies of progression to AD, might identify DMN alterations predictive of AD risk.

Determining the effects of LLD and MCI on brain decline according to machine learning and a structural covariance network analysis

BACKGROUND

Late-life depression (LLD) and mild cognitive impairment (MCI) are risk factors for Alzheimer disease (AD). However, the interactive effect between LLD and MCI in the progression to AD remains unknown. The purpose of this research is to clarify whether this interaction exists and determined the characteristics of the structural change patterns in LLD and MCI.

METHOD

To address this question, a total 225 participants (91 with intact cognitive function (IC), 34 with MCI, 35 with LLD-IC, 47 with LLD-MCI and 18 with AD) were recruited for the current study and their T1 scanning were acquired. Machine learning was applied to estimate the brain's age gap according to grey matter information (thickness and volume was calculated based on the Human Connectome Project Multi-Modal Parcellation version 1.0 and the Desikan atlas). A structural covariance network (SCN) was constructed based on grey matter volume. Rich-club analysis, global network properties and the Jaccard distance were utilized to describe the topological features in each cohort. Their cognitive functions (executive function, processing speed and memory) were evaluated by a full-scale battery of neuropsychological tests.

RESULT

The interactive effect between LLD and MCI was detected through the brain age gap. The estimated age was positively correlated with processing speed and memory in LLD and non-LLD subjects. In the SCN analysis, the rich-club coefficient and global network properties were disrupted in the MCI group, but remained normal in the LLD-IC, LLD-MCI and AD groups. There was a significant discrepancy in brain structural change patterns between the AD and other cohorts by the Jaccard distance.

CONCLUSION

The application of machine learning reflects that synergies between LLD and MCI could increase the risk of developing AD. According to the SCN, the structural coordination was disrupted in MCI and was kept normal in the other cohorts, while the discrepancies in brain structural change patterns appeared in AD. Overall, the brain age gap could be a potential predictor of AD, and the Jaccard distance has the potential to be a new type of SCN analysis indicator.

Distinct structural correlates of the dominant and nondominant languages in bilinguals with Alzheimer's disease (AD)

Structural adaptations in brain regions involved in domain-general cognitive control are associated with life-long bilingualism and may contribute to the executive function advantage of bilinguals over monolinguals. To the degree that these adaptations support bilingualism, their disruption by Alzheimer's disease (AD) may compromise the ability to maintain proficiency in two languages, particularly in the less proficient, or nondominant, language that has greater control demands. The present study assessed this possibility in Spanish-English bilinguals with AD (n = 21) and cognitively normal controls (n = 30) by examining the brain correlates of dominant versus nondominant language performance on the Multilingual Naming Test (MINT), adjusting for age and education. There were no significant structural correlates of naming performance for either language in controls. In patients with AD, dominant language MINT performance was associated with cortical thickness of the entorhinal cortex and middle temporal gyrus, consistent with previous findings of temporal atrophy and related decline of naming abilities in AD. Nondominant language MINT performance, in contrast, was correlated with thickness of the left caudal anterior cingulate cortex (ACC), a central cognitive control region involved in error monitoring and task switching. The relationship between naming in the nondominant language and ACC in patients with AD but not in controls may reflect increased reliance on the ACC for nondominant language use in the face of atrophy of other control network components. The results are consistent with the possibility that the increased burden nondominant language use places on cognitive control systems compromised in AD may account for faster nondominant than dominant language decline in AD.

The mediating role of hippocampal networks on stress regulation in amnestic mild cognitive impairment

Objectives

To examine the role of the hippocampus in stress regulation in older adults with amnestic mild cognitive impairment (aMCI).

Methods

This study combined resting-state functional MRI, structural MRI, self-reported chronic stress exposure, and an electrocardiography-based acute stress protocol to compare aMCI group (n = 17) to their cognitively healthy counterparts (HC, n = 22).

Results

For the entire sample, there was a positive correlation between chronic stress exposure and acute stress regulation. The aMCI group showed significantly smaller volumes in the right hippocampus than HC. The two groups did not differ in chronic stress exposure or acute stress regulation. In the HC group, the left hippocampal connectivity with inferior parietal lobe was significantly correlated with both the chronic stress and acute stress. In the aMCI group, the left hippocampal connectivity with both the right insula and the left precentral gyrus was significantly correlated to chronic stress exposure and acute stress regulation. Additionally, the left hippocampal connectivity with right insula significantly mediated the relationship between chronic stress exposure and acute stress regulation in aMCI group.

Conclusions

Extra hippocampal networks may be recruited as compensation to attend the maintenance of relatively normal stress regulation in aMCI by alleviating the detrimental effects of chronic stress exposure on acute stress regulation.

A Retrospective Belgian Multi-Center MRI Biomarker Study in Alzheimer's Disease (REMEMBER)

Background:

Magnetic resonance imaging (MRI) acquisition/processing techniques assess brain volumes to explore neurodegeneration in Alzheimer’s disease (AD).

Objective:

We examined the clinical utility of MSmetrix and investigated if automated MRI volumes could discriminate between groups covering the AD continuum and could be used as a predictor for clinical progression.

Methods:

The Belgian Dementia Council initiated a retrospective, multi-center study and analyzed whole brain (WB), grey matter (GM), white matter (WM), cerebrospinal fluid (CSF), cortical GM (CGM) volumes, and WM hyperintensities (WMH) using MSmetrix in the AD continuum. Baseline (n = 887) and follow-up (FU, n = 95) T1-weighted brain MRIs and time-linked neuropsychological data were available.

Results:

The cohort consisted of cognitively healthy controls (HC, n = 93), subjective cognitive decline (n = 102), mild cognitive impairment (MCI, n = 379), and AD dementia (n = 313). Baseline WB and GM volumes could accurately discriminate between clinical diagnostic groups and were significantly decreased with increasing cognitive impairment. MCI patients had a significantly larger change in WB, GM, and CGM volumes based on two MRIs (n = 95) compared to HC (FU>24months, p = 0.020). Linear regression models showed that baseline atrophy of WB, GM, CGM, and increased CSF volumes predicted cognitive impairment.

Conclusion:

WB and GM volumes extracted by MSmetrix could be used to define the clinical spectrum of AD accurately and along with CGM, they are able to predict cognitive impairment based on (decline in) MMSE scores. Therefore, MSmetrix can support clinicians in their diagnostic decisions, is able to detect clinical disease progression, and is of help to stratify populations for clinical trials.

Apolipoprotein E Homozygous ε4 Allele Status: A Deteriorating Effect on Visuospatial Working Memory and Global Brain Structure

Theoretical background: The Apolipoprotein E (APOE) ε4 genotype is known to be one of the strongest single-gene predictors for Alzheimer disease, which is characterized by widespread brain structural degeneration progressing along with cognitive impairment. The ε4 allele status has been associated with brain structural alterations and lower cognitive ability in non-demented subjects. However, it remains unclear to what extent the visuospatial cognitive domain is affected, from what age onward changes are detectable and if alterations may interact with cognitive deficits in major depressive disorder (MDD). The current work investigated the effect of APOE ε4 homozygosity on visuospatial working memory (vWM) capacity, and on hippocampal morphometry. Furthermore, potential moderating roles of age and MDD were assessed.

Methods: A sample of n = 31 homozygous ε4 carriers was contrasted with n = 31 non-ε4 carriers in a cross-sectional design. The sample consisted of non-demented, young to mid-age participants (mean age = 34.47; SD = 13.48; 51.6% female). Among them were n = 12 homozygous ε4 carriers and n = 12 non-ε4 carriers suffering from MDD (39%). VWM was assessed using the Corsi block-tapping task. Region of interest analyses of hippocampal gray matter density and volume were conducted using voxel-based morphometry (CAT12), and Freesurfer, respectively.

Results: Homozygous ε4 carriers showed significantly lower Corsi span capacity than non-ε4 carriers did, and Corsi span capacity was associated with higher gray matter density of the hippocampus. APOE group differences in hippocampal volume could be detected but were no longer present when controlling for total intracranial volume. Hippocampal gray matter density did not differ between APOE groups. We did not find any interaction effects of age and MDD diagnosis on hippocampal morphometry.

Conclusion: Our results point toward a negative association of homozygous ε4 allele status with vWM capacity already during mid-adulthood, which emerges independently of MDD diagnosis and age. APOE genotype seems to be associated with global brain structural rather than hippocampus specific alterations in young- to mid-age participants.

Microglial activation in early Alzheimer trajectory is associated with higher gray matter volume

Objective

To investigate the influence of microglial activation in the early stages of Alzheimer's disease trajectory, we assessed the relationship between microglial activation and gray matter volume and hippocampal volume in patients with mild cognitive impairment (MCI).

Methods

In this study, 55 participants (37 with early stages of MCI and 18 controls) underwent [¹¹C]PBR28 PET, a marker of microglial activation; volumetric MRI to evaluate gray matter and hippocampal volumes as well as clinical and neuropsychometric evaluation. [¹¹C]PBR28 V_T (volume of distribution) was calculated using arterial input function and Logan graphical analysis. Gray matter volume and hippocampal volumes were calculated from MRI for each participant. Statistical parametric mapping software was used to perform voxel-wise correlations and biological parametric mapping analysis. Amyloid status was assessed using [¹⁸F]flutemetamol PET.

Results

Higher [¹¹C]PBR28 V_T in different cortical areas correlated with higher gray matter volume in both amyloid-positive and -negative MCI. In addition, higher hippocampal volume correlated with higher cortical [¹¹C]PBR28 Logan V_T.

Conclusions

In this in vivo study, we have demonstrated that microglial activation quantified using [¹¹C]PBR28 PET was associated with higher gray matter volume and higher hippocampal volume in patients with MCI. This might suggest that microglial activation may not always be associated with neuronal damage, and indeed it may have a beneficial effect in the early stages of the Alzheimer trajectory. While further longitudinal studies are necessary, these findings have significant implications on therapeutic strategies targeting microglial activation.

Relationship between Cortical Thickness and Neuropsychological Performance in Normal Older Adults and Those with Mild Cognitive Impairment

Mild cognitive impairment (MCI) has been extensively investigated in recent decades to identify groups with a high risk of dementia and to establish effective prevention methods during this period. Neuropsychological performance and cortical thickness are two important biomarkers used to predict progression from MCI to dementia. This study compares the cortical thickness and neuropsychological performance in people with MCI and cognitively healthy older adults. We further focus on the relationship between cortical thickness and neuropsychological performance in these two groups. Forty-nine participants with MCI and 40 cognitively healthy older adults were recruited. Cortical thickness was analysed with semiautomatic software, Freesurfer. The analysis reveals that the cortical thickness in the left caudal anterior cingulate (p=0.041), lateral occipital (p=0.009) and right superior temporal (p=0.047) areas were significantly thinner in the MCI group after adjustment for age and education. Almost all neuropsychological test results (with the exception of forward digit span) were significantly correlated to cortical thickness in the MCI group after adjustment for age, gender and education. In contrast, only the score on the Category Verbal Fluency Test and the forward digit span were found to have significant inverse correlations to cortical thickness in the control group of cognitively healthy older adults. The study results suggest that cortical thinning in the temporal region reflects the global change in cognition in subjects with MCI and may be useful to predict progression of MCI to Alzheimer’s disease. The different pattern in the correlation of cortical thickness to the neuropsychological performance of patients with MCI from the healthy control subjects may be explained by the hypothesis of MCI as a disconnection syndrome.

Effects of exercise on brain activity during walking in older adults: a randomized controlled trial

BACKGROUND

Physical activity may preserve neuronal plasticity, increase synapse formation, and cause the release of hormonal factors that promote neurogenesis and neuronal function. Previous studies have reported enhanced neurocognitive function following exercise training. However, the specific cortical regions activated during exercise training remain largely undefined. In this study, we quantitatively and objectively evaluated the effects of exercise on brain activity during walking in healthy older adults.

METHODS

A total of 24 elderly women (75-83 years old) were randomly allocated to either an intervention group or a control group. Those in the intervention group attended 3 months of biweekly 90-min sessions focused on aerobic exercise, strength training, and physical therapy. We monitored changes in regional cerebral glucose metabolism during walking in both groups using positron emission tomography (PET) and [¹⁸F]fluorodeoxyglucose (FDG).

RESULTS

All subjects completed the 3-month experiment and the adherence to the exercise program was 100%. Compared with the control group, the intervention group showed a significantly greater step length in the right foot after 3 months of physical activity. The FDG-PET assessment revealed a significant post-intervention increase in regional glucose metabolism in the left posterior entorhinal cortex, left superior temporal gyrus, and right superior temporopolar area in the intervention group. Interestingly, the control group showed a relative increase in regional glucose metabolism in the left premotor and supplemental motor areas, left and right somatosensory association cortex, and right primary visual cortex after the 3-month period. We found no significant differences in FDG uptake between the intervention and control groups before vs. after the intervention.

CONCLUSION

Exercise training increased activity in specific brain regions, such as the precuneus and entorhinal cortices, which play an important role in episodic and spatial memory. Further investigation is required to confirm whether alterations in glucose metabolism within these regions during walking directly promote physical and cognitive performance.

TRIAL REGISTRATION

UMIN-CTR ( UMIN000021829 ). Retrospectively registered 10 April 2016.

Impact of Resveratrol on Glucose Control, Hippocampal Structure and Connectivity, and Memory Performance in Patients with Mild Cognitive Impairment

In healthy older adults, resveratrol supplementation has been shown to improve long-term glucose control, resting-state functional connectivity (RSFC) of the hippocampus, and memory function. Here, we aimed to investigate if these beneficial effects extend to individuals at high-risk for dementia, i.e., patients with mild cognitive impairment (MCI). In a randomized, double-blind interventional study, 40 well-characterized patients with MCI (21 females; 50-80 years) completed 26 weeks of resveratrol (200 mg/d; n = 18) or placebo (1,015 mg/d olive oil; n = 22) intake. Serum levels of glucose, glycated hemoglobin A1c and insulin were determined before and after intervention. Moreover, cerebral magnetic resonance imaging (MRI) (3T) (n = 14 vs. 16) was conducted to analyze hippocampus volume, microstructure and RSFC, and neuropsychological testing was conducted to assess learning and memory (primary endpoint) at both time points. In comparison to the control group, resveratrol supplementation resulted in lower glycated hemoglobin A1c concentration with a moderate effect size (ANOVA_RMp = 0.059, Cohen's d = 0.66), higher RSFC between right anterior hippocampus and right angular cortex (p < 0.001), and led to a moderate preservation of left anterior hippocampus volume (ANOVA_RMp = 0.061, Cohen's d = 0.68). No significant differences in memory performance emerged between groups. This proof-of-concept study indicates for the first-time that resveratrol intake may reduce glycated hemoglobin A1c, preserves hippocampus volume, and improves hippocampus RSFC in at-risk patients for dementia. Larger trials with longer intervention time should now determine if these benefits can be validated and extended to cognitive function.

Are Dietary Supplements and Nutraceuticals Effective for Musculoskeletal Health and Cognitive Function? A Scoping Review

OBJECTIVE

The aim of our scoping review was to summarize the state of the art regarding micronutrients in order to identify which of them might effectively improve health status in the areas typically impaired in older people: bone, skeletal muscle, and cognitive function.

DESIGN

Scoping review.

METHODS

The Italian Study Group on Healthy Aging by Nutraceuticals and Dietary Supplements (HANDS) performed this scoping review, based on the following steps: doing a list of micronutrients related with musculoskeletal or cognitive functions, included in dietary supplements and nutraceuticals commercialized in Italy; planning a research on PubMed, according to an evidence-based approach, in order to the most relevant positive study for each micronutrient into each of the three areas involved (bone, skeletal muscle and cognitive function); identifying the micronutrients effective in maintaining or achieving an adequate health status in older people, specifying the effective and safe daily doses, according to the selected studies.

RESULTS

In literature we found 12 relevant positive studies (1 international society guidelines/recommendations, 1 systematic review, 7 randomized controlled trials, and 3 prospective cohort studies). We showed that only 16 micronutrients resulted to have appropriate scientific evidences in terms of improving musculoskeletal health and/or cognitive function in older people: beta-alanine, calcium, creatine, fluorides, leucine, magnesium, omega-3 fatty acids, potassium, vitamin B6, vitamin B9, vitamin B12, vitamin C, vitamin D, vitamin E, vitamin K2, and zinc.

CONCLUSION

This scoping review showed that selected micronutrients in adequate doses might have an ancillary role in musculoskeletal health and cognitive functions in older people.

Successful Scene Encoding in Presymptomatic Early-Onset Alzheimer's Disease

BACKGROUND

Brain regions critical to episodic memory are altered during the preclinical stages of Alzheimer's disease (AD). However, reliable means of identifying cognitively-normal individuals at higher risk to develop AD have not been established.

OBJECTIVE

To examine whether functional MRI can detect early functional changes associated with scene encoding in a group of presymptomatic presenilin-1 (PSEN1) E280A mutation carriers.

METHODS

Participants were 39 young, cognitively-normal individuals from an autosomal dominant early-onset AD kindred, located in Antioquia, Colombia. Participants performed a functional MRI scene encoding task and a post-scan subsequent memory test.

RESULTS

PSEN1 mutation carriers exhibited hyperactivation within medial temporal lobe regions (hippocampus,parahippocampal formation) during successful scene encoding compared to age-matched non-carriers.

CONCLUSION

Hyperactivation in medial temporal lobe regions during scene encoding is seen in individuals genetically-determined to develop AD years before their clinical onset. Our findings will guide future research with the ultimate goal of using functional neuroimaging in the early detection of preclinical AD.

Reduced prefrontal oxygenation in mild cognitive impairment during memory retrieval

BACKGROUND

Memory impairment is considered a hallmark of amnestic mild cognitive impairment (aMCI) and dementia. Emerging evidence suggests that the prefrontal lobe is required to maintain memory functions. The purpose of this study was to clarify whether older adults with aMCI have decreased prefrontal oxygenation during memory encoding and retrieval compared with age-matched healthy older adults, using multi-channel near-infrared spectroscopy.

METHODS

We examined 64 older adults with aMCI (mean 71.8 years) and 66 cognitively healthy control subjects comparable in age and gender (mean 71.7 years). The concentration of oxy-hemoglobin, which is a reliable biomarker of changes in regional cerebral blood flow, was measured in the prefrontal cortex during encoding and delayed retrieval of a list of 10 target words. Task performance was evaluated as average number of correct answers in the retrieval task.

RESULTS

Subjects with aMCI showed reduced activation in the bilateral dorsolateral cortex (approximately Brodmann area 9) and provided fewer correct answers in the retrieval period than control subjects. There were no significant differences during encoding.

CONCLUSIONS

Reduced activation in the dorsolateral cortex during retrieval may cause deficits in memory performance, which may be used as a marker of aMCI. Further studies are required to examine the predictive validity of this decreased activation pattern for the incidence of Alzheimer's disease.

Hippocampal volume and hippocampal angle (a more practical marker) in mild cognitive impairment: A case-control magnetic resonance imaging study

Background:

Mild cognitive impairment (MCI) accompanies brain atrophy in neuroimaging investigations. The aim of this study was to compare MCI patients with the normal population for hippocampal volume (HV) and hippocampal angle (HA), and to assess the correlation between HV and HA.

Materials and Methods:

In a case-control study on 2014, in Kashani Hospital (Isfahan, Iran), 20 MCI patients were compared with 20 normal controls for HV and HA. Subjects were diagnosed with MCI or normal control, based on neuropsychiatry interview, which was confirmed by neuropsychiatry unit cognitive assessment tool (NUCOG). All magnetic resonance imaging scans were processed using the Free-Surfer software package for HV assessment. The HA was measured on the most rostral slice in which the uncal sulcus could be identified on a coronal plane. The data were analyzed using multiple analysis of co-variance and Pearson correlation.

Results:

The mean (standard deviation [SD]) score of NUCOG in control and case group were 91.05 (3.01) and 82.42 (3.57), respectively. Comparison of HV and HA scores in two groups, showed that mean (SD) HV and HA were not different between control and case groups, significantly, (P = 0.094 and P = 0.394, respectively). There was a negative correlation between the adjusted HV and the HA in case (r = −0.642, P = 0.004), and control groups (r = −0.654, P = 0.003).

Conclusion:

HV and HA were not different between MCI patients and normal controls; however, HA is correlated with HV negatively and may be used as an alternative factor because of more feasibility and availability in clinical settings in compared to HV.

Investigating Associative Learning Effects in Patients with Prodromal Alzheimer's Disease Using the Temporal Context Model

The purpose of this study was to investigate associative learning effects in patients with prodromal Alzheimer's disease (prAD) by referring to the Temporal Context Model (TCM; Howard, Jing, Rao, Provyn, & Datey, 2009), in an attempt to enhance the understanding of their associative memory impairment. TCM explains fundamental effects described in classical free-recall tasks and cued-recall tasks involving overlapping word pairs (e.g., A-B, B-C), namely (1) the contiguity effect, which is the tendency to successively recall nearby items in a list, and (2) the observation of backward (i.e., B-A) and transitive associations (i.e., A-C) between items. In TCM, these effects are hypothesized to rely on contextual representation, binding and retrieval processes, which supposedly depend on hippocampal and parahippocampal regions. As these regions are affected in prAD, the current study investigated whether prAD patients would show reduced proportions of backward and transitive associations in free and cued-recall, coupled to a reduced contiguity effect in free-recall. Seventeen older controls and 17 prAD patients performed a cued-recall task involving overlapping word pairs and a final free-recall task. Proportions of backward and transitive intrusions in cued-recall did not significantly differ between groups. However, in free-recall, prAD patients demonstrated a reduced contiguity effect as well as reduced proportions of backward and transitive associations compared to older controls. These findings are discussed within the hypothesis that the contextual representation, binding and/or retrieval processes are affected in prAD patients compared to healthy older individuals.

Medial temporal lobe high resolution magnetic resonance images for the early diagnosis of Alzheimer's disease

A challenging point in neuroimaging is the diagnosis of Alzheimer's disease (AD) during its asymptomatic phase. Among all the biomarkers proposed in the literature, a measure of the hippocampal atrophy via Magnetic Resonance Imaging (MRI) seems to be one of the most reliable. Refined image processing techniques were already proposed to automatically extract the hippocampal boxes from images acquired with the standard full brain acquisition protocol suggested by the Alzheimer's Disease Neuroimaging Initiative (ADNI). In order to enhance this approach, here we propose a high resolution (HR) MRI protocol focused on the medial temporal lobe (MTL) mainly conceived for 1.5T MRI device, hereafter referred as MTL-HR protocol. A preliminary characterization of its behavior when compared to the standard ADNI protocol is also presented.

The diagnosis and management of mild cognitive impairment: a clinical review

IMPORTANCE

Cognitive decline is a common and feared aspect of aging. Mild cognitive impairment (MCI) is defined as the symptomatic predementia stage on the continuum of cognitive decline, characterized by objective impairment in cognition that is not severe enough to require help with usual activities of daily living.

OBJECTIVE

To present evidence on the diagnosis, treatment, and prognosis of MCI and to provide physicians with an evidence-based framework for caring for older patients with MCI and their caregivers.

EVIDENCE ACQUISITION

We searched PubMed for English-language articles in peer-reviewed journals and the Cochrane Library database from inception through July 2014. Relevant references from retrieved articles were also evaluated.

FINDINGS

The prevalence of MCI in adults aged 65 years and older is 10% to 20%; risk increases with age and men appear to be at higher risk than women. In older patients with MCI, clinicians should consider depression, polypharmacy, and uncontrolled cardiovascular risk factors, all of which may increase risk for cognitive impairment and other negative outcomes. Currently, no medications have proven effective for MCI; treatments and interventions should be aimed at reducing cardiovascular risk factors and prevention of stroke. Aerobic exercise, mental activity, and social engagement may help decrease risk of further cognitive decline. Although patients with MCI are at greater risk for developing dementia compared with the general population, there is currently substantial variation in risk estimates (from <5% to 20% annual conversion rates), depending on the population studied. Current research targets improving early detection and treatment of MCI, particularly in patients at high risk for progression to dementia.

CONCLUSIONS AND RELEVANCE

Cognitive decline and MCI have important implications for patients and their families and will require that primary care clinicians be skilled in identifying and managing this common disorder as the number of older adults increases in coming decades. Current evidence supports aerobic exercise, mental activity, and cardiovascular risk factor control in patients with MCI.

The effects of healthy aging, amnestic mild cognitive impairment, and Alzheimer's disease on recollection and familiarity: a meta-analytic review

It is well established that healthy aging, amnestic Mild Cognitive Impairment (aMCI), and Alzheimer's Disease (AD) are associated with substantial declines in episodic memory. However, there is still debate as to how two forms of episodic memory - recollection and familiarity - are affected by healthy and pathological aging. To address this issue we conducted a meta-analytic review of the effect sizes reported in studies using remember/know (RK), receiver operating characteristic (ROC) and process dissociation (PD) methods to examine recollection and familiarity in healthy aging (25 published reports), aMCI (9 published reports), and AD (5 published reports). The results from the meta-analysis revealed that healthy aging is associated with moderate-to-large recollection impairments. Familiarity was not impaired in studies using ROC or PD methods but was impaired in studies that used the RK procedure. aMCI was associated with large decreases in recollection whereas familiarity only tended to show a decrease in studies with a patient sample comprised of both single-domain and multiple-domain aMCI patients. Lastly, AD was associated with large decreases in both recollection and familiarity. The results are consistent with neuroimaging evidence suggesting that the hippocampus is critical for recollection whereas familiarity is dependent on the integrity of the surrounding perirhinal cortex. Moreover, the results highlight the relevance of method selection when examining aging, and suggest that familiarity deficits might be a useful behavioral marker for identifying individuals that will develop dementia.

Coronary artery disease and plasma apolipoprotein E4 in mild cognitive impairment

BACKGROUND

Atherosclerosis and apolipoprotein E4 (APOE4) are known risks for Dementia. We sought to evaluate the relationship between coronary atherosclerosis and APOE4 with mild cognitive impairment (MCI).

METHODS

In a case-control study, subjects with age more than 60 years and recent coronary angiography were evaluated by mini-mental state examination and neuropsychiatry unit cognitive assessment tool (NUCOG) to find the patients with MCI (n = 40) and the controls with normal cognition (n = 40). Coronary angiography records were re-assessed to find the severity of coronary artery disease by the Gensini scores. Plasma levels of APOE4 were measured.

RESULTS

There were no-significant difference between the 2 groups regarding the plasma APOE4 levels (P = 0.706) and the Gensini scores (P = 0.236). Associations between the Gensini scores and the NUCOG scores in the MCI group (r = -0.196, P = 0.225) and the control group (r = 0.189, P = 0.243) were not significant. However, the interaction effect between the Gensini and the NUCOG scores based on allocation to the control or the patient groups showed statistically significant difference (F(1,67) = 4.84, P = 0.031).

CONCLUSION

Although atherosclerosis has been considered as known risk factor for dementia and MCI, this study could not reveal that coronary atherosclerosis-related to declining in cognitive functioning. There was no significant association between plasma APOE4 levels and MCI.

High-Dimensional Medial Lobe Morphometry: An Automated MRI Biomarker for the New AD Diagnostic Criteria

Introduction. Medial temporal lobe atrophy assessment via magnetic resonance imaging (MRI) has been proposed in recent criteria as an in vivo diagnostic biomarker of Alzheimer's disease (AD). However, practical application of these criteria in a clinical setting will require automated MRI analysis techniques. To this end, we wished to validate our automated, high-dimensional morphometry technique to the hypothetical prediction of future clinical status from baseline data in a cohort of subjects in a large, multicentric setting, compared to currently known clinical status for these subjects. Materials and Methods. The study group consisted of 214 controls, 371 mild cognitive impairment (147 having progressed to probable AD and 224 stable), and 181 probable AD from the Alzheimer's Disease Neuroimaging Initiative, with data acquired on 58 different 1.5 T scanners. We measured the sensitivity and specificity of our technique in a hierarchical fashion, first testing the effect of intensity standardization, then between different volumes of interest, and finally its generalizability for a large, multicentric cohort. Results. We obtained 73.2% prediction accuracy with 79.5% sensitivity for the prediction of MCI progression to clinically probable AD. The positive predictive value was 81.6% for MCI progressing on average within 1.5 (0.3 s.d.) year. Conclusion. With high accuracy, the technique's ability to identify discriminant medial temporal lobe atrophy has been demonstrated in a large, multicentric environment. It is suitable as an aid for clinical diagnostic of AD.

Neural Correlates of Unsuccessful Memory Performance in MCI

People with mild cognitive impairment (MCI) are at an elevated risk of developing Alzheimer’s disease or other forms of dementia. Although the neural correlates of successful memory performance in MCI have been widely investigated, the neural mechanisms involved in unsuccessful memory performance remain unknown. The current study examines the differences between patients suffering from stable amnestic MCI with multiple deficit syndromes and healthy elderly controls in relation to the neural correlates of both successful and unsuccessful encoding and recognition. Forty-six subjects (27 controls, 19 MCI) from the HelMA (Helmholtz Alliance for Mental Health in an Aging Society) completed a comprehensive neuropsychological test battery and participated in an fMRI experiment for associative face-name memory. In patients, the areas of frontal, parietal, and temporal cortices were less involved during unsuccessful encoding and recognition. A temporary dysfunction of the top-down control of frontal or parietal (or both) areas is likely to result in a non-selective propagation of task-related information to memory.

The relationship between regional brain volumes and the extent of coronary artery disease in mild cognitive impairment

BACKGROUND

There are conflicting reports regarding the association between coronary artery disease (CAD) and mild cognitive impairment (MCI). Volumetric Magnetic resonance imaging (MRI) investigations have been considered as an objective biomarker for MCI. In this study, we determined the relationship between the regional brain volumes and the extent of CAD in MCI patients and cognitively normal controls.

MATERIALS AND METHODS

In a case-control study a subset of MCI patients (n = 20) and cognitively normal controls (n = 20), aged 66.4 ± 4.6 and 65.3 ± 3.9 respectively, from subjects who were recently admitted to cardiac catheterization facilities in two general hospitals were selected. All subjects underwent a clinical interview, biochemical measures, neuropsychological testing and Neuropsychiatry Unit COGnitive assessment tool. Video records of coronary angiography were scored with the Gensini method. For volumetric evaluation of regions of interest, brain MRI scans was processed using the FreeSurfer software package the relationship between the regional brain volumes and the extent of CAD in MCI patients and cognitively normal controls were compared.

RESULTS

We have found that, there were significant differences between the two groups in volumes of left fusiform (P = 0.039), left pars triangularis (P = 0.003) and left superior temporal gyrus (P = 0.009), after controlling for intracranial volumes. Higher Gensini scores were associated with reduced volumes of total cortical volume (P = 0.047, R = -0.4), left precuneus (P = 0.022, R = -0.5), right inferior parietal lobule (P = 0.011, R = -0.5) and left supra marginal gyrus (P = 0.035, R = -0.04) in MCI.

CONCLUSION

In MCI, a greater degree of coronary stenosis correlates with greater loss of gray matter in specific brain regions relevant to cognitive function. This, however, was not the case for cognitively normal subjects.

A comprehensive assessment of resting state networks: bidirectional modification of functional integrity in cerebro-cerebellar networks in dementia

In resting state fMRI (rs-fMRI), only functional connectivity (FC) reductions in the default mode network (DMN) are normally reported as a biomarker for Alzheimer's disease (AD). In this investigation we have developed a comprehensive strategy to characterize the FC changes occurring in multiple networks and applied it in a pilot study of subjects with AD and Mild Cognitive Impairment (MCI), compared to healthy controls (HC). Resting state networks (RSNs) were studied in 14 AD (70 ± 6 years), 12 MCI (74 ± 6 years), and 16 HC (69 ± 5 years). RSN alterations were present in almost all the 15 recognized RSNs; overall, 474 voxels presented a reduced FC in MCI and 1244 in AD while 1627 voxels showed an increased FC in MCI and 1711 in AD. The RSNs were then ranked according to the magnitude and extension of FC changes (gFC), putting in evidence 6 RSNs with prominent changes: DMN, frontal cortical network (FCN), lateral visual network (LVN), basal ganglia network (BGN), cerebellar network (CBLN), and the anterior insula network (AIN). Nodes, or hubs, showing alterations common to more than one RSN were mostly localized within the prefrontal cortex and the mesial-temporal cortex. The cerebellum showed a unique behavior where voxels of decreased gFC were only found in AD while a significant gFC increase was only found in MCI. The gFC alterations showed strong correlations (p < 0.001) with psychological scores, in particular Mini-Mental State Examination (MMSE) and attention/memory tasks. In conclusion, this analysis revealed that the DMN was affected by remarkable FC increases, that FC alterations extended over several RSNs, that derangement of functional relationships between multiple areas occurred already in the early stages of dementia. These results warrant future work to verify whether these represent compensatory mechanisms that exploit a pre-existing neural reserve through plasticity, which evolve in a state of lack of connectivity between different networks with the worsening of the pathology.

Application of a MRI based index to longitudinal atrophy change in Alzheimer disease, mild cognitive impairment and healthy older individuals in the AddNeuroMed cohort

Cross sectional studies of patients at risk of developing Alzheimer disease (AD) have identified several brain regions known to be prone to degeneration suitable as biomarkers, including hippocampal, ventricular, and whole brain volume. The aim of this study was to longitudinally evaluate an index based on morphometric measures derived from MRI data that could be used for classification of AD and healthy control subjects, as well as prediction of conversion from mild cognitive impairment (MCI) to AD. Patients originated from the AddNeuroMed project at baseline (119 AD, 119 MCI, 110 controls (CTL)) and 1-year follow-up (62 AD, 73 MCI, 79 CTL). Data consisted of 3D T1-weighted MR images, demographics, MMSE, ADAS-Cog, CERAD and CDR scores, and APOE e4 status. We computed an index using a multivariate classification model (AD vs. CTL), using orthogonal partial least squares to latent structures (OPLS). Sensitivity, specificity and AUC were determined. Performance of the classifier (AD vs. CTL) was high at baseline (10-fold cross-validation, 84% sensitivity, 91% specificity, 0.93 AUC) and at 1-year follow-up (92% sensitivity, 74% specificity, 0.93 AUC). Predictions of conversion from MCI to AD were good at baseline (77% of MCI converters) and at follow-up (91% of MCI converters). MCI carriers of the APOE e4 allele manifested more atrophy and presented a faster cognitive decline when compared to non-carriers. The derived index demonstrated a steady increase in atrophy over time, yielding higher accuracy in prediction at the time of clinical conversion. Neuropsychological tests appeared less sensitive to changes over time. However, taking the average of the two time points yielded better correlation between the index and cognitive scores as opposed to using cross-sectional data only. Thus, multivariate classification seemed to detect patterns of AD changes before conversion from MCI to AD and including longitudinal information is of great importance.

Discerning mild cognitive impairment and Alzheimer Disease from normal aging: morphologic characterization based on univariate and multivariate models

RATIONALE AND OBJECTIVES

Differentiating mild cognitive impairment (MCI) and Alzheimer Disease (AD) from healthy aging remains challenging. This study aimed to explore the cerebral structural alterations of subjects with MCI or AD as compared to healthy elderly based on the individual and collective effects of cerebral morphologic indices using univariate and multivariate analyses.

MATERIALS AND METHODS

T1-weighted images (T1WIs) were retrieved from Alzheimer Disease Neuroimaging Initiative database for 116 subjects who were categorized into groups of healthy aging, MCI, and AD. Analysis of covariance (ANCOVA) and multivariate analysis of covariance (MANCOVA) were performed to explore the intergroup morphologic alterations indexed by surface area, curvature index, cortical thickness, and subjacent white matter volume with age and sex controlled as covariates, in 34 parcellated gyri regions of interest (ROIs) for both cerebral hemispheres based on the T1WI. Statistical parameters were mapped on the anatomic images to facilitate visual inspection.

RESULTS

Global rather than region-specific structural alterations were revealed in groups of MCI and AD relative to healthy elderly using MANCOVA. ANCOVA revealed that the cortical thickness decreased more prominently in entorhinal, temporal, and cingulate cortices and was positively correlated with patients' cognitive performance in AD group but not in MCI. The temporal lobe features marked atrophy of white matter during the disease dynamics. Significant intercorrelations were observed among the morphologic indices with univariate analysis for given ROIs.

CONCLUSIONS

Significant global structural alterations were identified in MCI and AD based on MANCOVA model with improved sensitivity. The intercorrelation among the morphologic indices may dampen the use of individual morphological parameter in featuring cerebral structural alterations. Decrease in cortical thickness is not reflective of the cognitive performance at the early stage of AD.

Impaired cortical oscillatory coupling in mild cognitive impairment: anatomical substrate and ApoE4 effects

Our current knowledge about the anatomical substrate of impaired resting-state cortical oscillatory coupling in mild cognitive impairment is still rudimentary. Here, we show that both resting-state oscillatory coupling and its anatomical correlates clearly distinguish healthy older (HO) adults from individuals with amnestic mild cognitive impairment (aMCI). aMCI showed failures in neural-phase coupling of resting-state electroencephalographic alpha activity mostly evident between fronto-temporal and parietal regions. As oligomers of amyloid-beta (Aβ) are linked to synaptic dysfunction in Alzheimer's disease (AD), we further investigated whether plasma concentrations of these oligomers (Aβ40 and Aβ42) accounted for impaired patterns of oscillatory coupling in aMCI. Results revealed that decreased plasma Aβ42 was associated with augmented coupling of parieto-temporal regions in HO subjects, but no relationship was found in aMCI. Oscillatory coupling of frontal regions was also significantly reduced in aMCI carriers of the ε4 allele of the Apolipoprotein E (ApoE) compared to ε4 noncarriers, although neither neuroanatomical nor plasma Aβ changes accounted for this difference. However, the abnormal pattern of oscillatory coupling in aMCI was negatively related to volume of the angular gyrus, and positively related to volume of the precuneus and the splenium of the corpus callosum. Previous evidence suggests that all these regions are neuropathological targets of AD. The current study takes that scenario one step further, suggesting that this anatomical damage could be responsible for disrupted cortical oscillatory coupling in aMCI. Together, these data shed light on how the MCI status modifies anatomo-functional relationships underlying coordination of large-scale cortical systems in the resting-state.

Olfactory identification and cognitive performance in community-dwelling older adults with mild cognitive impairment

Olfactory impairment constitutes one of the earliest signs of Alzheimer's disease in older adults with mild cognitive impairment. We investigated which aspects of neuropsychological measures are correlated with olfactory identification performance among older adults with mild cognitive impairment. Total of 220 participants with mild cognitive impairment (mean age 71.7 years) were examined. Odor identification was assessed using the Open Essence test. Participants underwent comprehensive neurocognitive evaluation, including measures of verbal memory, visual memory, working memory, attention/executive function, and processing speed. We examined associations between olfactory function and cognitive performance scores. Participants with severe hyposmia exhibited significantly poor verbal and visual memory performance, attention/executive function, and slower processing speed scores compared with those without severe hyposmia. In multivariable logistic regression models, better performance scores on verbal and visual memory were significantly associated with decreased likelihood of severe hyposmia after adjusting for age, sex, education, and other cognitive performance scores. These findings suggest that olfactory impairment might be more closely associated with memory loss compared with other aspects of cognitive functioning in mild cognitive impairment subjects.

Visual reproduction on the Wechsler Memory Scale-Revised as a predictor of Alzheimer's disease in Japanese patients with mild cognitive impairments

BACKGROUND

The Visual Reproduction (VR) test is used to assess mild cognitive impairment (MCI), but the characteristics of visual memory in Japanese MCI patients remain unclear.

METHODS

VR scores of 27 MCI patients were evaluated using the Wechsler Memory Scale-Revised. Scores of MCI, no-dementia, and Alzheimer's disease (AD) groups were then compared.

RESULTS

The annual conversion rate of MCI to AD was 18.8%. Mean VR-I and VR-II baseline scores for MCI patients were 33.3 ± 5.6 and 20.5 ± 14.0, respectively. Mean VR-II scores for converted and nonconverted MCI patients were 7.2 ± 8.7 and 29.8 ± 9.3, respectively.

CONCLUSIONS

It is likely that VR-II and VR-II/I scores are more sensitive for predicting conversion to AD in Japanese than in American MCI patients. Our results indicate that VR is a sensitive and useful measure for predicting the conversion of Japanese MCI patients to AD within 2 years.