Potential neuroimaging biomarkers of pathologic brain changes in Mild Cognitive Impairment and Alzheimer's disease: a systematic review

Cross-disease drug discovery based on bioinformatics and virtual screening: Study of key genes in Alzheimer's disease and ovarian cancer

BACKGROUND

Alzheimer's disease (AD) and cancer, both age-related diseases, are characterized by abnormal cellular behavior. Epidemiological data indicate an inverse relationship between AD and various cancers. Accordingly, this study seeks to analyze the negatively correlated genes between AD and ovarian cancer and identify closely related compounds through virtual screening technology to explore potential therapeutic drugs.

METHODS

Microarray data were downloaded from the Gene Expression Omnibus database, and negatively correlated genes between AD and ovarian cancer were identified using bioinformatics analysis. Clinical prognostic and survival analyses were performed to identify genes most negatively associated with these diseases. The top ten compounds with the strongest binding to the target genes were screened from the ChemDiv database using virtual screening technology, considering the blood-brain barrier. Molecular dynamics simulations were used to identify potential sites for the binding of these compounds to the target protein MX1. Additionally, point mutation analysis of the target protein was performed. Finally, the binding site was verified in vitro.

RESULTS

The MX1 gene was most significantly negatively associated with AD and ovarian cancer. Molecular dynamics simulations revealed intersection sites at Glu-227 and Gly-188, where MX1 binds tightly to the head compound.

CONCLUSION

This study successfully identified MX1 as being negatively associated with AD and ovarian cancer and assessed the potential drug compounds that bind most closely to it. Our findings provide important rationale and candidate targets for the development of novel therapeutic strategies for AD and ovarian cancer.

Research on magnetic resonance imaging in diagnosis of Alzheimer's disease

As a common disease in the elderly, the diagnosis of Alzheimer's disease (AD) is of great significance to the treatment and prognosis of the patients. Studies have found that magnetic resonance imaging plays an important role in the early diagnosis of Alzheimer's disease. This article tries to review the application of magnetic resonance imaging in the diagnosis and differential diagnosis of Alzheimer's disease.

Optimizing detection of Alzheimer's disease in mild cognitive impairment: a 4-year biomarker study of mild behavioral impairment in ADNI and MEMENTO

BACKGROUND

Disease-modifying drug use necessitates better Alzheimer disease (AD) detection. Mild cognitive impairment (MCI) leverages cognitive decline to identify the risk group; similarly, mild behavioral impairment (MBI) leverages behavioral change. Adding MBI to MCI improves dementia prognostication over conventional approaches of incorporating neuropsychiatric symptoms (NPS). Here, to determine if adding MBI would better identify AD, we interrogated associations between MBI in MCI, and cerebrospinal fluid biomarkers [β-amyloid (Aβ), phosphorylated-tau (p-tau), and total-tau (tau)-ATN], cross-sectionally and longitudinally.

METHODS

Data were from two independent referral-based cohorts, ADNI (mean[SD] follow-up 3.14[1.07] years) and MEMENTO (4.25[1.40] years), collected 2003-2021. Exposure was based on three-group stratification: 1) NPS meeting MBI criteria; 2) conventionally measured NPS (NPSnotMBI); and 3) noNPS. Cohorts were analyzed separately for: 1) cross-sectional associations between NPS status and ATN biomarkers (linear regressions); 2) 4-year longitudinal repeated-measures associations of MBI and NPSnotMBI with ATN biomarkers (hierarchical linear mixed-effects models-LMEs); and 3) rates of incident dementia (Cox proportional hazards regressions).

RESULTS

Of 510 MCI participants, 352 were from ADNI (43.5% females; mean [SD] age, 71.68 [7.40] years), and 158 from MEMENTO (46.2% females; 68.98 [8.18] years). In ADNI, MBI was associated with lower Aβ42 (standardized β [95%CI], -5.52% [-10.48-(-0.29)%]; p = 0.039), and Aβ42/40 (p = 0.01); higher p-tau (9.67% [3.96-15.70%]; p = 0.001), t-tau (7.71% [2.70-12.97%]; p = 0.002), p-tau/Aβ42 (p < 0.001), and t-tau/Aβ42 (p = 0.001). NPSnotMBI was associated only with lower Aβ42/40 (p = 0.045). LMEs revealed a similar 4-year AD-specific biomarker profile for MBI, with NPSnotMBI associated only with higher t-tau. MBI had a greater rate of incident dementia (HR [95%CI], 3.50 [1.99-6.17; p < 0.001). NPSnotMBI did not differ from noNPS (HR 0.96 [0.49-1.89]; p = 0.916). In MEMENTO, MBI demonstrated a similar magnitude and direction of effect for all biomarkers, but with a greater reduction in Aβ40. HR for incident dementia was 3.93 (p = 0.004) in MBI, and 1.83 (p = 0.266) in NPSnotMBI. Of MBI progressors to dementia, 81% developed AD dementia.

CONCLUSIONS

These findings support a biological basis for NPS that meet MBI criteria, the continued inclusion of MBI in NIA-AA ATN clinical staging, and the utility of MBI criteria to improve identification of patients for enrollment in disease-modifying drug trials or for clinical care.

Illuminating neurodegeneration: a future perspective on near-infrared spectroscopy in dementia research

SIGNIFICANCE

Dementia presents a global healthcare crisis, and neuroimaging is the main method for developing effective diagnoses and treatments. Yet currently, there is a lack of sensitive, portable, and low-cost neuroimaging tools. As dementia is associated with vascular and metabolic dysfunction, near-infrared spectroscopy (NIRS) has the potential to fill this gap.

AIM

This future perspective aims to briefly review the use of NIRS in dementia to date and identify the challenges involved in realizing the full impact of NIRS for dementia research, including device development, study design, and data analysis approaches.

APPROACH

We briefly appraised the current literature to assess the challenges, giving a critical analysis of the methods used. To assess the sensitivity of different NIRS device configurations to the brain with atrophy (as is common in most forms of dementia), we performed an optical modeling analysis to compare their cortical sensitivity.

RESULTS

The first NIRS dementia study was published in 1996, and the number of studies has increased over time. In general, these studies identified diminished hemodynamic responses in the frontal lobe and altered functional connectivity in dementia. Our analysis showed that traditional (low-density) NIRS arrays are sensitive to the brain with atrophy (although we see a mean decrease of 22% in the relative brain sensitivity with respect to the healthy brain), but there is a significant improvement (a factor of 50 sensitivity increase) with high-density arrays.

CONCLUSIONS

NIRS has a bright future in dementia research. Advances in technology - high-density devices and intelligent data analysis-will allow new, naturalistic task designs that may have more clinical relevance and increased reproducibility for longitudinal studies. The portable and low-cost nature of NIRS provides the potential for use in clinical and screening tests.

The association of dietary and nutrient patterns on neurocognitive decline: A systematic review of MRI and PET studies

BACKGROUND

As the global population ages, there has been a growing incidence of neurodegenerative diseases such as Alzheimer's. More recently, studies exploring the relationship between dietary patterns and neuroimaging outcomes have received particular attention. This systematic literature review provides a structured overview of the association between dietary and nutrient patterns on neuroimaging outcomes and cognitive markers in middle-aged to older adults. A comprehensive literature search was conducted to find relevant articles published from 1999 to date using the following databases Ovid MEDLINE, Embase, PubMed, Scopus and Web of Science. The inclusion criteria for the articles comprised studies reporting on the association between dietary patterns and neuroimaging outcomes, which includes both specific pathological hallmarks of neurodegenerative diseases such as Aβ and tau and nonspecific markers such as structural MRI and glucose metabolism. The risk of bias was evaluated using the Quality Assessment tool from the National Heart, Lung, and Blood Institute of the National Institutes of Health. The results were then organized into a summary of results table, collated based on synthesis without meta-analysis. After conducting the search, 6050 records were extracted and screened for eligibility, with 107 eligible for full-text screening and 42 articles ultimately being included in this review. The results of the systematic review indicate that there is some evidence suggesting that healthy dietary and nutrient patterns were associated with neuroimaging measures, indicative of a protective influence on neurodegeneration and brain ageing. Conversely, unhealthy dietary and nutrient patterns showed evidence pointing to decreased brain volumes, poorer cognition and increased Aβ deposition. Future research should focus on sensitive neuroimaging acquisition and analysis methods, to study early neurodegenerative changes and identify critical periods for interventions and prevention.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO registration no, CRD42020194444).

A longitudinal observational study of home-based conversations for detecting early dementia: protocol for the CUBOId TV task

INTRODUCTION

Limitations in effective dementia therapies mean that early diagnosis and monitoring are critical for disease management, but current clinical tools are impractical and/or unreliable, and disregard short-term symptom variability. Behavioural biomarkers of cognitive decline, such as speech, sleep and activity patterns, can manifest prodromal pathological changes. They can be continuously measured at home with smart sensing technologies, and permit leveraging of interpersonal interactions for optimising diagnostic and prognostic performance. Here we describe the ContinUous behavioural Biomarkers Of cognitive Impairment (CUBOId) study, which explores the feasibility of multimodal data fusion for in-home monitoring of mild cognitive impairment (MCI) and early Alzheimer's disease (AD). The report focuses on a subset of CUBOId participants who perform a novel speech task, the 'TV task', designed to track changes in ecologically valid conversations with disease progression.

METHODS AND ANALYSIS

CUBOId is a longitudinal observational study. Participants have diagnoses of MCI or AD, and controls are their live-in partners with no such diagnosis. Multimodal activity data were passively acquired from wearables and in-home fixed sensors over timespans of 8-25 months. At two time points participants completed the TV task over 5 days by recording audio of their conversations as they watched a favourite TV programme, with further testing to be completed after removal of the sensor installations. Behavioural testing is supported by neuropsychological assessment for deriving ground truths on cognitive status. Deep learning will be used to generate fused multimodal activity-speech embeddings for optimisation of diagnostic and predictive performance from speech alone.

ETHICS AND DISSEMINATION

CUBOId was approved by an NHS Research Ethics Committee (Wales REC; ref: 18/WA/0158) and is sponsored by University of Bristol. It is supported by the National Institute for Health Research Clinical Research Network West of England. Results will be reported at conferences and in peer-reviewed scientific journals.

Effects of resistance training combined with balance training on physical function among older adults: a protocol for a randomised controlled trial

INTRODUCTION

The world's population is ageing. Age-related declines in physical function negatively affect the quality of life but may be ameliorated by certain types of exercise. The purpose of this study is to investigate the effects of combining resistance training (RT) with balance training on physical function in older community-dwelling adults to provide a reference for this type of exercise compared with other exercises and to provide a theoretical basis for optimising exercise plans to improve physical function among older adults.

METHODS

This single-blind randomised controlled trial will recruit 66 community dwelling adults 60-89 years of age with normal cognition. Participants will be randomly assigned to one of three groups: RT, RT combined with balance training or a control group with usual daily activities. Exercise interventions will be conducted in three 45 min sessions per week for 24 weeks. Primary physical function outcomes will be assessed using the timed up and go test, usual walking speed, maximal walking speed, 30 s chair stand and 30 s arm curl. Secondary assessments will be conducted using the 2 min step test, back scratch test and chair sit-and-reach test. All physical function assessments will be performed at baseline and after 12 and 24 weeks of exercise interventions. Exercise intensity will be monitored to maintain moderate intensity by heart rate, ratings of perceived exertion and OMNI-Resistance Exercise Scale. Data that conform to a normal distribution will be expressed as means±SD, otherwise as medians and interquartile intervals. Pretest, mid-test and post-test outcomes will be analysed for within-group and between-group comparisons using two-way repeated measures analyses of variance.

ETHICS AND DISSEMINATION

This proposal was reviewed and approved by the Shanghai University of Sport Research Ethics Committee (102772021RT067). The results will be disseminated to the trial participants and as a peer-reviewed publication.

TRIAL REGISTRATION NUMBER

ChiCTR2200056090.

Multiple Cognitive and Behavioral Factors Link Association Between Brain Structure and Functional Impairment of Daily Instrumental Activities in Older Adults

OBJECTIVE

Functional impairment in daily activity is a cornerstone in distinguishing the clinical progression of dementia. Multiple indicators based on neuroimaging and neuropsychological instruments are used to assess the levels of impairment and disease severity; however, it remains unclear how multivariate patterns of predictors uniquely predict the functional ability and how the relative importance of various predictors differs.

METHOD

In this study, 881 older adults with subjective cognitive complaints, mild cognitive impairment (MCI), and dementia with Alzheimer's type completed brain structural magnetic resonance imaging (MRI), neuropsychological assessment, and a survey of instrumental activities of daily living (IADL). We utilized the partial least square (PLS) method to identify latent components that are predictive of IADL.

RESULTS

The result showed distinct brain components (gray matter density of cerebellar, medial temporal, subcortical, limbic, and default network regions) and cognitive-behavioral components (general cognitive abilities, processing speed, and executive function, episodic memory, and neuropsychiatric symptoms) were predictive of IADL. Subsequent path analysis showed that the effect of brain structural components on IADL was largely mediated by cognitive and behavioral components. When comparing hierarchical regression models, the brain structural measures minimally added the explanatory power of cognitive and behavioral measures on IADL.

CONCLUSION

Our finding suggests that cerebellar structure and orbitofrontal cortex, alongside with medial temporal lobe, play an important role in the maintenance of functional status in older adults with or without dementia. Moreover, the significance of brain structural volume affects real-life functional activities via disruptions in multiple cognitive and behavioral functions.

Frailty assessment tools for use by surgeons when evaluating older adults prior to surgery: a scoping review protocol

INTRODUCTION

Despite growing evidence, uncertainty persists about which frailty assessment tools are best suited for routine perioperative care. We aim to understand which frailty assessment tools perform well and are feasible to implement.

METHODS AND ANALYSIS

Using a registered protocol following Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols (PRISMA), we will conduct a scoping review informed by the Joanna Briggs Institute Guide for Scoping Reviews and reported using PRISMA extension for Scoping Reviews recommendations. We will develop a comprehensive search strategy with information specialists using the Peer Review of Electronic Search Strategies checklist, and implement this across relevant databases from 2005 to 13 October 2021 and updated prior to final review publication. We will include all studies evaluating a frailty assessment tool preoperatively in patients 65 years or older undergoing intracavitary, non-cardiac surgery. We will exclude tools not assessed in clinical practice, or using laboratory or radiologic values alone. After pilot testing, two reviewers will independently assess information sources for eligibility first by titles and abstracts, then by full-text review. Two reviewers will independently chart data from included full texts using a piloted standardised electronic data charting. In this scoping review process, we will (1) index frailty assessment tools evaluated in the preoperative clinical setting; (2) describe the level of investigation supporting each tool; (3) describe useability of each tool and (4) describe direct comparisons between tools. The results will inform ready application of frailty assessment tools in routine clinical practice by surgeons and other perioperative clinicians.

ETHICS AND DISSEMINATION

Ethic approval is not required for this secondary data analysis. This scoping review will be published in a peer-review journal. Results will be used to inform an ongoing implementation study focused on geriatric surgery to overcome the current lack of uptake of older adult-oriented care recommendations and ensure broad impact of research findings.

Differential and subtype-specific neuroimaging abnormalities in amnestic and nonamnestic mild cognitive impairment: A systematic review and meta-analysis

While mild cognitive impairment (MCI) has been classified into amnestic MCI (aMCI) and nonamnestic MCI (naMCI), the neuropathological bases of these two subtypes remain elusive. Here, we performed a systematic review and meta-analysis to determine the subtype specificity of neuroimaging abnormalities in MCI and to identify neural features that may differ between aMCI and naMCI. We synthesized 50 studies that used common neuroimaging modalities, including magnetic resonance imaging and positron emission tomography, to compare brain atrophy, white matter abnormalities, cortical thinning, cerebral hypometabolism, amyloid/tau deposition, or other features among aMCI, naMCI, and normal cognition. Compared with normal cognition, aMCI shows diverse neuroimaging abnormalities of large effect sizes. In contrast, naMCI exhibits restricted abnormalities of small effect sizes. Some features, including medial temporal lobe atrophy and white matter abnormalities, are shared by the two MCI subtypes. Overall, brain abnormalities are worse, if not similar, in aMCI than in naMCI. The only neuroimaging abnormality specific to aMCI is increased amyloid burden; no feature specific to naMCI was found. Taken together, our findings have elucidated the neuropathological changes that occur in aMCI and naMCI. Clarifying the neuroimaging profiles of aMCI and naMCI can improve the early identification, differentiation, and intervention of prodromal dementia.

Process evaluation of the New Interventions for independence in Dementia Study (NIDUS) Family stream randomised controlled trial: protocol

INTRODUCTION

New Interventions for independence in Dementia Study (NIDUS)-Family is an Alzheimer's Society funded new manualised, multimodal psychosocial intervention to support people living with dementia (PLWD) to achieve goals that they and their family carers set, towards living as independently and as well as possible at home for longer. This process evaluation will be embedded within the NIDUS-Family Randomised Controlled Trial intervention-arm (n=199), testing how the intervention influences change, as measured by goal attainment. The evaluation will test, refine and develop the NIDUS-Family theoretical model, associated causal assumptions and logic model to identify key mechanisms of impact, implementation and contextual factors influencing the intervention's effectiveness. Findings will inform how the programme is implemented in practice.

METHODS AND ANALYSIS

The process evaluation will be theory driven and apply a convergent mixed-methods design. Dyads (PLWD and family carer) will be purposively sampled based on high or low Goal Attainment Scaling scores (trial primary outcome). Qualitative interviews with dyads (approx. n=30) and their respective facilitators post-trial will explore their experiences of receiving and delivering the intervention. Interviews will be iteratively thematically analysed. Matching observational quantitative data will be collected concurrently from videorecordings and/or audiorecordings of NIDUS-Family dyad trial sessions. Further quantitative data will be collected through an acceptability questionnaire for all intervention-arm dyads (n=199). Mixed-method integration will use an interactive analysis strategy, considering qualitative and quantitative findings through mixed-method matrix for dyadic level 'case studies', and a joint display for 'population' level analysis and interpretation.

ETHICS AND DISSEMINATION

Ethical approval was received from Camden & Kings Cross Research Ethics Committee (REC). Study reference: 19/LO/1667. IRAS project ID: 271 363. This work is carried out within the UCL Alzheimer's Society Centre of Excellence (grant 300) for Independence at home, NIDUS programme.Findings will be disseminated through publications and conferences, and as recommendations for the implementation study and strategy.

TRIAL REGISTRATION NUMBER

ISRCTN11425138.

Prefrontal Activation During Effortful Processing Differentiates Memory Abilities in Adults with Memory Complaints

Background: Identifying individuals at increased risks for developing Alzheimer’s disease (AD) is crucial for early intervention. Memory complaints are associated with brain abnormalities characteristic of AD in cognitively normal older people. However, the utility of memory complaints for predicting mild cognitive impairment (MCI) or AD onset remains controversial, likely due to the heterogeneous nature of this construct. Objective: We investigated whether prefrontal oxygenation changes measured by functional near-infrared spectroscopy (fNIRS) during an arduous cognitive task, previously shown to be associated with the AD syndrome, could differentiate memory abilities among individuals with memory complaints. Episodic memory performance was adopted as a proxy for MCI/AD risks since it has been shown to predict AD progression across stages. Methods: Thirty-six adults self-reporting memory complaints in the absence of memory impairment completed a verbal list learning test and underwent a digit n-back paradigm with an easy (0-back) and a difficult (2-back) condition. K-means clustering was applied to empirically derive memory complaint subgroups based on fNIRS-based prefrontal oxygenation changes during the effortful 2-back task. Results: Cluster analysis revealed two subgroups characterized by high (n = 12) and low (n = 24) bilateral prefrontal activation during the 2-back but not a 0-back task. The low activation group was significantly less accurate across the n-back task and recalled significantly fewer words on the verbal memory test compared to the high activation group. Conclusion: fNIRS may have the potential to differentiate verbal memory abilities in individuals with self-reported memory complaints.

FARGO-360: a multi-disciplinary survey of practice and perspectives on provision of care for patients with frailty presenting with gynecological cancers in the UK and Ireland

OBJECTIVES

Frailty has been associated with worse cancer-related outcomes for people with gynecological cancers. However, the lack of clear guidance on how to assess and modify frailty prior to instigating active treatments has the potential to lead to large variations in practice and outcomes. This study aimed to evaluate current practice and perspectives of healthcare practitioners on the provision of care for patients with frailty and a gynecological cancer.

METHODS

Data were collected via a questionnaire-based survey distributed by the Audit and Research in Gynecological Oncology (ARGO) collaborative to healthcare professionals who identified as working with patients with gynecological malignancies in the United Kingdom (UK) or Ireland. Study data were collected using REDCap software hosted at the University of Manchester. Responses were collected over a 16 week period between January and April 2021.

RESULTS

A total of 206 healthcare professionals (30 anesthetists (14.6%), 30 pre-operative nurses (14.6%), 51 surgeons (24.8%), 34 cancer specialist nurses (16.5%), 21 medical/clinical oncologists (10.2%), 25 physiotherapists/occupational therapists (12.1%) and 15 dieticians (7.3%)) completed the survey. The respondents worked at 19 hospital trusts across the UK and Ireland. Frailty scoring was not routinely performed in 63% of care settings, yet the majority of practitioners reported modifying their practice when providing and deciding on care for patients with frailty. Only 16% of organizations surveyed had a dedicated pathway for assessment and management of patients with frailty. A total of 37% of respondents reported access to prehabilitation services, 79% to enhanced recovery, and 27% to community rehabilitation teams.

CONCLUSION

Practitioners from all groups surveyed considered that appropriate training, dedicated pathways for optimization, frailty specific performance indicators and evidence that frailty scoring had an impact on clinical outcomes and patient experience could all help to improve care for frail patients.

AD Resemblance Atrophy Index of Brain Magnetic Resonance Imaging in Predicting the Progression of Mild Cognitive Impairment Carrying Apolipoprotein E-ε4 Allele

Background and Objective

Early identification is important for timely Alzheimer’s disease (AD) treatment. Apolipoprotein E ε4 allele (APOE-ε4) is an important genetic risk factor for sporadic AD. The AD-Resemblance Atrophy Index (RAI)—a structural magnetic resonance imaging-derived composite index—was found to predict the risk of progression from mild cognitive impairment (MCI) to AD. Therefore, we investigated whether the AD-RAI can predict cognitive decline and progression to AD in patients with MCI carrying APOE ε4.

Methods

We included 733 participants with MCI from the Alzheimer’s Disease Neuroimaging Initiative Database (ADNI). Their APOE genotypes, cognitive performance, and levels of AD-RAI were assessed at baseline and follow-up. Linear regression models were used to test the correlations between the AD-RAI and baseline cognitive measures, and linear mixed models with random intercepts and slopes were applied to investigate whether AD-RAI and APOE-ε4 can predict the level of cognitive decline. Cox proportional risk regression models were used to test the association of AD-RAI and APOE status with the progression from MCI to AD.

Results

The baseline AD-RAI was higher in the MCI converted to AD group than in the MCI stable group (P < 0.001). The AD-RAI was significantly correlated with cognition, and had a synergistic effect with APOE-ε4 to predict the rate of cognitive decline. The AD-RAI predicted the risk and timing of MCI progression to AD. Based on the MCI population carrying APOE-ε4, the median time to progression from MCI to AD was 24 months if the AD-RAI > 0.5, while the median time to progression from MCI to AD was 96 months for patients with an AD-RAI ≤ 0.5.

Conclusion

The AD-RAI can predict the risk of progression to AD in people with MCI carrying APOE ε4, is strongly correlated with cognition, and can predict cognitive decline.

Hippocampus and its involvement in Alzheimer's disease: a review

Hippocampus is the significant component of the limbic lobe, which is further subdivided into the dentate gyrus and parts of Cornu Ammonis. It is the crucial region for learning and memory; its sub-regions aid in the generation of episodic memory. However, the hippocampus is one of the brain areas affected by Alzheimer's (AD). In the early stages of AD, the hippocampus shows rapid loss of its tissue, which is associated with the functional disconnection with other parts of the brain. In the progression of AD, atrophy of medial temporal and hippocampal regions are the structural markers in magnetic resonance imaging (MRI). Lack of sirtuin (SIRT) expression in the hippocampal neurons will impair cognitive function, including recent memory and spatial learning. Proliferation, differentiation, and migrations are the steps involved in adult neurogenesis. The microglia in the hippocampal region are more immunologically active than the other regions of the brain. Intrinsic factors like hormones, glia, and vascular nourishment are instrumental in the neural stem cell (NSC) functions by maintaining the brain's microenvironment. Along with the intrinsic factors, many extrinsic factors like dietary intake and physical activity may also influence the NSCs. Hence, pro-neurogenic lifestyle could delay neurodegeneration.

New Frontiers in the Prevention, Diagnosis, and Treatment of Alzheimer's Disease

One of the major puzzles in medical research and public health systems worldwide is Alzheimer's disease (AD), reaching nowadays a prevalence near 50 million people. This is a multifactorial brain disorder characterized by progressive cognitive impairment, apathy, and mood and neuropsychiatric disorders. The main risk of AD is aging; a normal biological process associated with a continuum dynamic involving a gradual loss of people's physical capacities, but with a sound experienced view of life. Studies suggest that AD is a break from normal aging with changes in the powerful functional capacities of neurons as well as in the mechanisms of neuronal protection. In this context, an important path has been opened toward AD prevention considering that there are elements of nutrition, daily exercise, avoidance of toxic substances and drugs, an active social life, meditation, and control of stress, to achieve healthy aging. Here, we analyze the involvement of such factors and how to control environmental risk factors for a better quality of life. Prevention as well as innovative screening programs for early detection of the disease using reliable biomarkers are becoming critical to control the disease. In addition, the failure of traditional pharmacological treatments and search for new drugs has stimulated the emergence of nutraceutical compounds in the context of a "multitarget" therapy, as well as mindfulness approaches shown to be effective in the aging, and applied to the control of AD. An integrated approach involving all these preventive factors combined with novel pharmacological approaches should pave the way for the future control of the disease.

Association Between Gait, Cognition, and Gray Matter Volumes in Mild Cognitive Impairment and Healthy Controls

AIMS

To assess the correlation between cognitive functioning and 3 gait parameters (gait speed, cadence, and stride length) in persons with mild cognitive impairment (MCI) and cognitively healthy controls and investigate linear correlations between gait and gray matter volumes.

MATERIALS AND METHODS

Participants were recruited at IRCCS San Camillo Hospital, Venice, Italy (MCI=43; age-matched controls=43). Participants underwent comprehensive neuropsychological assessment. Gait speed, cadence, and stride length, were assessed with the BTS FREEMG 300 device. Three-dimensional (3D) T1-weighted MR images were acquired using a 1.5 T Philips Achieva MRI system with a Turbo Field Echo sequence.

RESULTS

In MCI there was a positive correlation between gait speed and memory tests (P<0.05). In controls all 3 gait parameters correlated with executive functioning (P<0.01). Temporal and limbic areas (ie, superior temporal gyrus, thalamus and parahippocampal gyrus) were associated with gait parameters in MCI whereas in controls the associations were with frontal areas (ie, middle, inferior, and superior frontal gyrus) and in the cerebellum (anterior and posterior lobe).

CONCLUSIONS

Our results highlight a distinct pattern of association between gray matter volume and gait parameters in MCI patients and controls (temporal areas in MCI and frontal areas in healthy elderly), suggesting a relationship between dementia-related pathology and gait dysfunction.

Neurofeedback and the Aging Brain: A Systematic Review of Training Protocols for Dementia and Mild Cognitive Impairment

Dementia describes a set of symptoms that occur in neurodegenerative disorders and that is characterized by gradual loss of cognitive and behavioral functions. Recently, non-invasive neurofeedback training has been explored as a potential complementary treatment for patients suffering from dementia or mild cognitive impairment. Here we systematically reviewed studies that explored neurofeedback training protocols based on electroencephalography or functional magnetic resonance imaging for these groups of patients. From a total of 1,912 screened studies, 10 were included in our final sample (N = 208 independent participants in experimental and N = 81 in the control groups completing the primary endpoint). We compared the clinical efficacy across studies, and evaluated their experimental designs and reporting quality. In most studies, patients showed improved scores in different cognitive tests. However, data from randomized controlled trials remains scarce, and clinical evidence based on standardized metrics is still inconclusive. In light of recent meta-research developments in the neurofeedback field and beyond, quality and reporting practices of individual studies are reviewed. We conclude with recommendations on best practices for future studies that investigate the effects of neurofeedback training in dementia and cognitive impairment.

Demographically Corrected Normative Z Scores on the Neuropsychological Test Battery in Cognitively Normal Older Chinese Adults

BACKGROUND

Subjective questionnaires used for the diagnosis of pre-mild cognitive impairment (pre-MCI) and conventional criteria for MCI might mainly result in false-positive diagnostic errors. The integrated criteria based on demographically adjusted total and process Z scores on neuropsychological tests have been validated to be sensitive for measuring pre-MCI, MCI, and MCI subtypes. However, the underrepresentativity of Chinese populations and the complexity in some tests limit the use of the established Z scores in the elderly Chinese population.

OBJECTIVE

The aim of this study was to develop a useful Z score calculator to assess individual cognitive performance after adjustment of the scores on each of the neuropsychological tests according to sex, age, and education and to establish preliminary norms for the objective assessment of cognition function in elderly Chinese individuals.

METHODS

The neuropsychological test battery consists of measures of performance on different cognitive domains, including episodic memory, language, executive function, processing speed, and attention. Data were obtained from 220 clinically cognitively normal Chinese volunteers aged 60 years or older from the cohort of the Shanghai study of health promotion among frail elderly individuals. Regression models were used to investigate the impact of age, education, and sex on test scores. Z scores were estimated for the different scores by subtracting the predicted mean from the raw score and dividing it by the root mean square error term for any given linear regression model.

RESULTS

Preliminary analyses indicated that age, sex, or level of education significantly affected test scores. A series of linear regression models was constructed for all instruments, i.e.: the Trail-Making Test A and B, to assess executive function or attention; the Boston Naming Test and animal list generation, to assess language; delayed free correct responses and the Hopkins Verbal Learning Test-Revised (HVLT-R) recognition, as well as three process scores, i.e., intrusion errors, learning slope, and retroactive interference, from the HVLT-R, to assess memory, by adjusting for the covariates of age, sex, and level of education concurrently. The Z scores on all neuropsychological tests were estimated based on the corresponding regression coefficients.

CONCLUSIONS

We constructed a multivariable regression-based normative Z score method for the measurement of cognition among older Chinese individuals in the community. The normative score will be useful for the accurate diagnosis of different subtypes of pre-MCI and MCI after preliminary rapid screening in the community.

White matter connectivity for early prediction of Alzheimer's disease

BACKGROUND

Early diagnosis of Alzheimer's disease (AD) remains challenging. It is speculated that structural atrophy in white matter tracts commences prior to the onset of AD symptoms.

OBJECTIVE

We hypothesize that disruptions in white matter tract connectivity precedes the onset of AD symptoms and these disruptions could be leveraged for early prediction of AD.

METHODS

Diffusion tensor images (DTI) from 52 subjects with mild cognitive impairment (MCI) were selected. Subjects were dichotomized into two age and gender matched groups; the MCI-AD group (22 subjects who progressed to develop AD) and the MCI-control group (who did not develop AD). DTI images were anatomically parcellated into 90 distinct regions ROIs followed by tractography methods to obtain different biophysical networks. Features extracted from these networks were used to train predictive algorithms with the objective of discriminating the MCI-AD and MCI-control groups. Model performance and best features are reported.

RESULTS

Up to 80% prediction accuracy was achieved using a combination of features from the 'right anterior cingulum' and 'right frontal superior medial'. Additionally, local network features were more useful than global in improving the model's performance.

CONCLUSION

Connectivity-based characterization of white matter tracts offers potential for early detection of MCI-AD and in the discovery of novel imaging biomarkers.

Brain tissue properties link cardio-vascular risk factors, mood and cognitive performance in the CoLaus|PsyCoLaus epidemiological cohort

Given the controversy about the impact of modifiable risk factors on mood and cognition in ageing, we sought to investigate the associations between cardio-vascular risk, mental health, cognitive performance and brain anatomy in mid- to old age. We analyzed a set of risk factors together with multi-parameter magnetic resonance imaging (MRI) in the CoLaus|PsyCoLaus cohort (n > 1200). Cardio-vascular risk was associated with differences in brain tissue properties - myelin, free tissue water, iron content - and regional brain volumes that we interpret in the context of micro-vascular hypoxic lesions and neurodegeneration. The interaction between clinical subtypes of major depressive disorder and cardio-vascular risk factors showed differential associations with brain structure depending on individuals' lifetime trajectory. There was a negative correlation between melancholic depression, anxiety and MRI markers of myelin and iron content in the hippocampus and anterior cingulate. Verbal memory and verbal fluency performance were positively correlated with left amygdala volumes. The concomitant analysis of brain morphometry and tissue properties allowed for a neuro-biological interpretation of the link between modifiable risk factors and brain health.

Obesity and Brain Vulnerability in Normal and Abnormal Aging: A Multimodal MRI Study

Background:

How the relationship between obesity and MRI-defined neural properties varies across distinct stages of cognitive impairment due to Alzheimer’s disease is unclear.

Objective:

We used multimodal neuroimaging to clarify this relationship.

Methods:

Scans were acquired from 47 patients clinically diagnosed with mild Alzheimer’s disease dementia, 68 patients with mild cognitive impairment, and 57 cognitively healthy individuals. Voxel-wise associations were run between maps of gray matter volume, white matter integrity, and cerebral blood flow, and global/visceral obesity.

Results:

Negative associations were found in cognitively healthy individuals between obesity and white matter integrity and cerebral blood flow of temporo-parietal regions. In mild cognitive impairment, negative associations emerged in frontal, temporal, and brainstem regions. In mild dementia, a positive association was found between obesity and gray matter volume around the right temporoparietal junction.

Conclusion:

Obesity might contribute toward neural tissue vulnerability in cognitively healthy individuals and mild cognitive impairment, while a healthy weight in mild Alzheimer’s disease dementia could help preserve brain structure in the presence of age and disease-related weight loss.

Deep learning-Based 3D inpainting of brain MR images

The detailed anatomical information of the brain provided by 3D magnetic resonance imaging (MRI) enables various neuroscience research. However, due to the long scan time for 3D MR images, 2D images are mainly obtained in clinical environments. The purpose of this study is to generate 3D images from a sparsely sampled 2D images using an inpainting deep neural network that has a U-net-like structure and DenseNet sub-blocks. To train the network, not only fidelity loss but also perceptual loss based on the VGG network were considered. Various methods were used to assess the overall similarity between the inpainted and original 3D data. In addition, morphological analyzes were performed to investigate whether the inpainted data produced local features similar to the original 3D data. The diagnostic ability using the inpainted data was also evaluated by investigating the pattern of morphological changes in disease groups. Brain anatomy details were efficiently recovered by the proposed neural network. In voxel-based analysis to assess gray matter volume and cortical thickness, differences between the inpainted data and the original 3D data were observed only in small clusters. The proposed method will be useful for utilizing advanced neuroimaging techniques with 2D MRI data.

Age-Related Structural and Functional Changes of the Hippocampus and the Relationship with Inhibitory Control

Aging is associated with structural and functional changes in the hippocampus, and hippocampal dysfunction represents a risk marker of Alzheimer’s disease. Previously, we demonstrated age-related changes in reactive and proactive control in the stop signal task, each quantified by the stop signal reaction time (SSRT) and sequential effect computed as the correlation between the estimated stop signal probability and go trial reaction time. Age was positively correlated with the SSRT, but not with the sequential effect. Here, we explored hippocampal gray matter volume (GMV) and activation to response inhibition and to p(Stop) in healthy adults 18 to 72 years of age. The results showed age-related reduction of right anterior hippocampal activation during stop success vs. go trials, and the hippocampal activities correlated negatively with the SSRT. In contrast, the right posterior hippocampus showed higher age-related responses to p(Stop), but the activities did not correlate with the sequential effect. Further, we observed diminished GMVs of the anterior and posterior hippocampus. However, the GMVs were not related to behavioral performance or regional activities. Together, these findings suggest that hippocampal GMVs and regional activities represent distinct neural markers of cognitive aging, and distinguish the roles of the anterior and posterior hippocampus in age-related changes in cognitive control.

The Netrin-1/DCC Guidance Cue Pathway as a Molecular Target in Depression: Translational Evidence

The Netrin-1/DCC guidance cue pathway plays a critical role in guiding growing axons toward the prefrontal cortex during adolescence and in the maturational organization and adult plasticity of prefrontal cortex connectivity. In this review, we put forward the idea that alterations in prefrontal cortex architecture and function, which are intrinsically linked to the development of major depressive disorder, originate in part from the dysregulation of the Netrin-1/DCC pathway by a mechanism that involves microRNA-218. We discuss evidence derived from mouse models of stress and from human postmortem brain and genome-wide association studies indicating an association between the Netrin-1/DCC pathway and major depressive disorder. We propose a potential role of circulating microRNA-218 as a biomarker of stress vulnerability and major depressive disorder.

Impact of dementia on informal care: a systematic review of family caregivers' perceptions

INTRODUCTION

Caregivers play a major role in providing all the support and care in daily activities for their relatives with dementia. To fully describe the influence of dementia caregiving on family caregivers' life, we conducted a systematic review including caregivers' perceptions about the positive and negative aspects of caring and the expressed factors.

MATERIALS AND METHODS

We conducted a systematic review including articles from January 1998 to July 2020. Qualitative studies reporting family caregivers' perceptions about their experiences and the effects/impact of dementia caregiving were eligible. Two authors extracted the data independently, and the analysis focused on the positive and negative aspects of dementia caregiving in caregivers' life.

RESULTS

Eighty-one studies with 3347 participants were included in this review. The positive aspects of caregiving in caregivers' life encompass personal accomplishment and strengthening relationships, which were enhanced by good medical counselling/formal care support and family/friends support. The negative aspects included emotional and social aspects experienced by caregivers. Other factors such as inappropriate medical/formal care support, illness progression and the costs of dementia contributed to negative appraisal.

DISCUSSION AND IMPLICATIONS

The findings provide insights into the holistic experience of caring for a person with dementia revelling the major positive and negative aspects underlying the caregiver role. The evidence emphasises the need 'to focus on positive aspects' and targeted interventions aimed at reducing the negative impact of caregiving, which has serious consequences on caregivers' quality of life. A multicomplex intervention for dementia informal caregiving should be developed, committing the society to promote mental health, address these community needs and improve the quality of life of the person with dementia and their family caregivers.

An Operational Definition of 'Abnormal Cognition' to Optimize the Prediction of Progression to Dementia: What Are Optimal Cut-Off Points for Univariate and Multivariate Normative Comparisons?

Background:

In neuropsychology and neurology, there is no consensus on the definition of abnormal cognition.

Objective:

To operationally define ‘abnormal cognition’ for optimally predicting progression to dementia in a memory clinic sample, and to test whether multivariate profile analysis of cognitive test results improves this prediction compared to standard clinical evaluation.

Methods:

We used longitudinal data from 835 non-demented patients of the Amsterdam Dementia Cohort. For 10 cognitive measures at baseline, we determined which number of abnormal tests and which magnitude of score deviations best predicted progression.

Results:

Predictive ability for progression to dementia of one, two, and three abnormal test scores out of 10 is highly similar (Cox hazard ratios: 3.7–4.1) provided cut-off values are adapted appropriately. Cut-offs have to be less stringent if the number of abnormal tests required increases: the optimal cut-off is z < –1.45 when one deviating score is required, z < –1.15 when two abnormal tests are required, and z < –0.70 when three abnormal tests are required. The profile analysis has similar predictive ability at the cut-off of p < 0.22 (hazard ratio 3.8). A likelihood ratio test showed that this analysis improves prediction of progression to dementia when added to standard clinical evaluation (p < 0.001).

Conclusion:

Abnormal cognition may be defined as one, two, or three abnormal test scores out of 10 if the magnitude of score deviations is adapted accordingly. An abnormal score profile predicts decline to dementia equally well, and improves the prediction when used complimentary to standard clinical evaluation.

The project for objective measures using computational psychiatry technology (PROMPT): Rationale, design, and methodology

INTRODUCTION

Depressive and neurocognitive disorders are debilitating conditions that account for the leading causes of years lived with disability worldwide. However, there are no biomarkers that are objective or easy-to-obtain in daily clinical practice, which leads to difficulties in assessing treatment response and developing new drugs. New technology allows quantification of features that clinicians perceive as reflective of disorder severity, such as facial expressions, phonic/speech information, body motion, daily activity, and sleep.

METHODS

Major depressive disorder, bipolar disorder, and major and minor neurocognitive disorders as well as healthy controls are recruited for the study. A psychiatrist/psychologist conducts conversational 10-min interviews with participants ≤10 times within up to five years of follow-up. Interviews are recorded using RGB and infrared cameras, and an array microphone. As an option, participants are asked to wear wrist-band type devices during the observational period. Various software is used to process the raw video, voice, infrared, and wearable device data. A machine learning approach is used to predict the presence of symptoms, severity, and the improvement/deterioration of symptoms.

DISCUSSION

The overall goal of this proposed study, the Project for Objective Measures Using Computational Psychiatry Technology (PROMPT), is to develop objective, noninvasive, and easy-to-use biomarkers for assessing the severity of depressive and neurocognitive disorders in the hopes of guiding decision-making in clinical settings as well as reducing the risk of clinical trial failure. Challenges may include the large variability of samples, which makes it difficult to extract the features that commonly reflect disorder severity.

TRIAL REGISTRATION

UMIN000021396, University Hospital Medical Information Network (UMIN).

Non-invasive Brain Stimulation in Alzheimer's Disease and Mild Cognitive Impairment-A State-of-the-Art Review on Methodological Characteristics and Stimulation Parameters

Background: Transcranial magnetic stimulation (TMS) and transcranial direct current stimulation (tDCS) have been proposed as a new therapeutic way to enhance the cognition of patients with dementia. However, serious methodological limitations appear to affect the estimates of their efficacy. We reviewed the stimulation parameters and methods of studies that used TMS or tDCS to alleviate the cognitive symptoms of patients with Alzheimer's disease (AD) and mild cognitive impairment (MCI). Moreover, we evaluated the risk of bias in these studies. Our aim was to highlight the current vulnerabilities of the field and to formulate recommendations on how to manage these issues when designing studies. Methods: Electronic databases and citation searching were used to identify studies administering TMS or tDCS on patients with AD or MCI to enhance cognitive function. Data were extracted by one review author into summary tables with the supervision of the authors. The risk of bias analysis of randomized-controlled trials was conducted by two independent assessors with version 2 of the Cochrane risk-of-bias tool for randomized trials. Results: Overall, 36 trials were identified of which 23 randomized-controlled trials underwent a risk of bias assessment. More than 75% of randomized-controlled trials involved some levels of bias in at least one domain. Stimulation parameters were highly variable with some ranges of effectiveness emerging. Studies with low risk of bias indicated TMS to be potentially effective for patients with AD or MCI while questioned the efficacy of tDCS. Conclusions: The presence and extent of methodical issues affecting TMS and tDCS research involving patients with AD and MCI were examined for the first time. The risk of bias frequently affected the domains of the randomization process and selection of the reported data while missing outcome was rare. Unclear reporting was present involving randomization, allocation concealment, and blinding. Methodological awareness can potentially reduce the high variability of the estimates regarding the effectiveness of TMS and tDCS. Studies with low risk of bias delineate a range within TMS parameters seem to be effective but question the efficacy of tDCS.

Evaluation of Brain Tortuosity Measurement for the Automatic Multimodal Classification of Subjects with Alzheimer's Disease

The 3D tortuosity determined in several brain areas is proposed as a new morphological biomarker (BM) to be considered in early detection of Alzheimer's disease (AD). It is measured using the sum of angles method and it has proven to be sensitive to anatomical changes that appear in gray and white matter and temporal and parietal lobes during mild cognitive impairment (MCI). Statistical analysis showed significant differences (p < 0.05) between tortuosity indices determined for healthy controls (HC) vs. MCI and HC vs. AD in most of the analyzed structures. Other clinically used BMs have also been incorporated in the analysis: beta-amyloid and tau protein CSF and plasma concentrations, as well as other image-extracted parameters. A classification strategy using random forest (RF) algorithms was implemented to discriminate between three samples of the studied populations, selected from the ADNI database. Classification rates considering only image-extracted parameters show an increase of 9.17%, when tortuosity is incorporated. An enhancement of 1.67% is obtained when BMs measured from several modalities are combined with tortuosity.

The potential of neurofilaments analysis using dry-blood and plasma spots

The lack of biomarkers for an early diagnosis of neurodegenerative disorders (NDs) has hampered the development of therapeutics whose effect would be enhanced by a timely intervention. Neurofilaments light chain (Nf-L), an integral part of the axonal structure, has emerged as a robust fluid biomarker for fatal neurodegenerative disorders like amyotrophic lateral sclerosis (ALS). To facilitate large-scale studies into early-stage neurodegeneration, reduce costs of samples collection/processing and cold-chain storage, we describe the measurement of Nf-L in blood fractions obtained from dry blood spots (DBS) and dry plasma spots (DPS), two filter paper-based remote blood collection tools. To test the feasibility of using this approach, Nf-L analysis in DBS/DPS is compared to that in plasma obtained from the same blood sample, looking at Nf-L discriminatory power in the clinical stratification of ALS compared to healthy controls. With the best pre-analytical treatment for total protein recovery and using highly sensitive immunoassays, we report the detection of different Nf-L levels in DBS elute compared to reference plasma and DPS from the same blood samples. However, Nf-L measurement in DBS elutes provides a very good discrimination of ALS from healthy controls which is comparable to that obtained using plasma Nf-L assays. With the available immunodetection methods, we show that Nf-L measurement based on DPS microsampling is similar to that in plasma. The filter-paper biophysical characteristics and the interference of high haemoglobin concentration released by erythrocyte lysis is likely to perturb Nf-L detection in DBS elute. Further studies into DBS-based Nf-L detection and its analytical optimization are needed to make this method suitable for routine Nf-L blood analyses in neurodegeneration.

Clinical dementia severity associated with ventricular size is differentially moderated by cognitive reserve in men and women

Background

Interindividual differences in cognitive reserve (CR) are associated with complex and dynamic clinical phenotypes observed in cognitive impairment and dementia. We tested whether (1) CR early in life (E-CR; measured by education and IQ), (2) CR later in life (L-CR; measured by occupation), and (3) CR panel (CR-P) with the additive effects of E-CR and L-CR, act as moderating factors between baseline ventricular size and clinical dementia severity at baseline and across 2 years. We further examined whether this moderation is differentially represented by sex.

Methods

We examined a longitudinal model using patients (N = 723; mean age = 70.8 ± 9.4 years; age range = 38–90 years; females = 374) from the Sunnybrook Dementia Study. The patients represented Alzheimer’s disease (n = 439), mild cognitive impairment (n = 77), vascular cognitive impairment (n = 52), Lewy body disease (n = 30), and frontotemporal dementia (n = 125). Statistical analyses included (1) latent growth modeling to determine how clinical dementia severity changes over 2 years (measured by performance on the Dementia Rating Scale), (2) confirmatory factor analysis to establish a baseline E-CR factor, and (3) path analysis to predict dementia severity. Baseline age (continuous) and Apolipoprotein E status (ɛ4−/ɛ4+) were included as covariates.

Results

The association between higher baseline ventricular size and dementia severity was moderated by (1) E-CR and L-CR and (2) CR-P. This association was differentially represented in men and women. Specifically, men in only the low CR-P had higher baseline clinical dementia severity with larger baseline ventricular size. However, women in the low CR-P showed the (1) highest baseline dementia severity and (2) fastest 2-year decline with larger baseline ventricular size.

Conclusions

Clinical dementia severity associated with ventricular size may be (1) selectively moderated by complex and additive CR networks and (2) differentially represented by sex.

Trials registration

ClinicalTrials.gov, NCT01800214. Registered on 27 February 2013.

Electronic supplementary material

The online version of this article (10.1186/s13195-018-0419-2) contains supplementary material, which is available to authorized users.

γ-Aminobutyric acid type A receptor binding affinity in the right inferior frontal gyrus at resting state predicts the performance of healthy elderly people in the visual sustained attention test

ABSTRACTBackground:Although recent studies have suggested that the γ-aminobutyric acid type A (GABAA) receptor binding affinity can be a more sensitive marker of age-related neuronal loss than regional gray matter (GM) volume, knowledge about the relationship between decreased GABAA receptor binding affinity and cognitive decline during normal aging is still limited.

METHODS

Thirty-seven healthy elderly individuals (aged 50-77 years (mean, 64.5 ± 7.3 years); 15 males and 22 females) were enrolled in this study. We investigated the association of the performance of the healthy elderly in the attentional function test with regional GM volume, regional cerebral bold flow (rCBF), and GABAA receptor binding affinity in the resting state by structural magnetic resonance imaging (MRI), arterial spin labeling (ASL), and 123I-iomazenil (IMZ) SPECT, with the analysis focusing on the bilateral inferior frontal gyri.

RESULTS

The score of the rapid visual information processing (RVP) test, which is used to assess visual sustained attention, showed a positive correlation with GABAA receptor binding affinity in the right inferior frontal gyrus. No significant correlation was found between RVP test score and regional GM volume or rCBF.

CONCLUSION

The findings of 123I-IMZ SPECT, but not those of structural MRI or ASL, suggest that a decreased GABAA receptor binding affinity can be a sensitive marker of cognitive impairment.

Focused Ultrasound-Induced Blood-Brain Barrier Opening Enhances GSK-3 Inhibitor Delivery for Amyloid-Beta Plaque Reduction

Alzheimer's disease (AD) is a neurodegenerative disease that is the leading cause of age-related dementia. Currently, therapeutic agent delivery to the CNS is a valued approach for AD therapy. Unfortunately, the CNS penetration is greatly hampered by the blood-brain barrier (BBB). Focused-ultrasound (FUS) has been demonstrated to temporally open the BBB, thus promoting therapeutic agent delivery to the CNS. Recently, the BBB opening procedure was further reported to clear the deposited Aβ plaque due to microglia activation. In this study, we aimed to evaluate whether the use of FUS-induced BBB opening to enhance GSK-3 inhibitor delivery, which would bring additive effect of Aβ plaque clearance by FUS with the reduction of Aβ plaque synthesis by GSK-3 inhibitor in an AD mice model. FUS-induced BBB opening on APPswe/PSEN1-dE9 transgenic mice was performed unilaterally, with the contralateral hemisphere serving as a reference. GSK-3 level was confirmed by immunohistochemistry (IHC) and autoradiography (ARG) was also conducted to quantitatively confirm the Aβ plaque reduction. Results from IHC showed GSK-3 inhibitor effectively reduced GSK-3 activity up to 61.3% with the addition of FUS-BBB opening and confirming the proposed therapeutic route. ARG also showed significant Aβ-plaque reduction up to 31.5%. This study reveals the therapeutic potentials of ultrasound to AD treatment, and may provide a useful strategy for neurodegenerative disease treatment.

A Network-Based Perspective in Alzheimer's Disease: Current State and an Integrative Framework

A major rise in the prevalence and impact of Alzheimer's disease (AD) is projected in the coming decades, resulting from increasing life expectancy, thus leading to substantially increased healthcare costs. While brain disfunctions at the time of diagnosis are irreversible, it is widely accepted that AD pathology develops decades before clinical symptoms onset. If incipient processes can be detected early in the disease progression, prospective intervention for preventing or slowing the disease can be designed. Currently, there is no noninvasive biomarker available to detect and monitor early stages of disease progression. The complex etiology of AD warrants a systems-based approach supporting the integration of multimodal and multilevel data, while network-based modeling provides the scaffolding for methods revealing complex systems-level disruptions initiated by the disease. In this work, we review current state-of-the-art, focusing on network-based biomarkers at molecular and brain functional connectivity levels. Particular emphasis is placed on outlining recent trends, which highlight the functional importance of modular substructures in molecular and connectivity networks and their potential biomarker value. Our perspective is rooted in network medicine and summarizes the pipelines for identifying network-based biomarkers, as well as the benefits of integrating genotype and brain phenotype information for a comprehensively noninvasive approach in the early diagnosis of AD. Finally, we propose a framework for integrating knowledge from molecular and brain connectivity levels, which has the potential to enable noninvasive diagnosis, provide support for monitoring therapies, and help understand heretofore unexamined deep level relations between genotype and brain phenotype.

Cholinergic Hypofunction in Presbycusis-Related Tinnitus With Cognitive Function Impairment: Emerging Hypotheses

Presbycusis (age-related hearing loss) is a potential risk factor for tinnitus and cognitive deterioration, which result in poor life quality. Presbycusis-related tinnitus with cognitive impairment is a common phenotype in the elderly population. In these individuals, the central auditory system shows similar pathophysiological alterations as those observed in Alzheimer's disease (AD), including cholinergic hypofunction, epileptiform-like network synchronization, chronic inflammation, and reduced GABAergic inhibition and neural plasticity. Observations from experimental rodent models indicate that recovery of cholinergic function can improve memory and other cognitive functions via acetylcholine-mediated GABAergic inhibition enhancement, nicotinic acetylcholine receptor (nAChR)-mediated anti-inflammation, glial activation inhibition and neurovascular protection. The loss of cholinergic innervation of various brain structures may provide a common link between tinnitus seen in presbycusis-related tinnitus and age-related cognitive impairment. We hypothesize a key component of the condition is the withdrawal of cholinergic input to a subtype of GABAergic inhibitory interneuron, neuropeptide Y (NPY) neurogliaform cells. Cholinergic denervation might not only cause the degeneration of NPY neurogliaform cells, but may also result in decreased AChR activation in GABAergic inhibitory interneurons. This, in turn, would lead to reduced GABA release and inhibitory regulation of neural networks. Reduced nAChR-mediated anti-inflammation due to the loss of nicotinic innervation might lead to the transformation of glial cells and release of inflammatory mediators, lowering the buffering of extracellular potassium and glutamate metabolism. Further research will provide evidence for the recovery of cholinergic function with the use of cholinergic input enhancement alone or in combination with other rehabilitative interventions to reestablish inhibitory regulation mechanisms of involved neural networks for presbycusis-related tinnitus with cognitive impairment.

Changing Landscapes in the Neuroimaging of Dementia

Neuroimaging in dementia has advanced several folds in the past decade. It has evolved from diagnosing secondary causes of dementia to the current use in identifying primary dementia and aid in clinically perplexing situations. There has been a leap in the imaging technology that can virtually dissect the brain with a high degree of radiopathological correlation. The neuroimaging in dementia is classified into structural, functional, and molecular imaging. Structural imaging includes voxel-based morphometry and diffusion tensor imaging. Functional imaging includes 18F-fluorodeoxy glucose positron emission tomography imaging, 99mTc hexamethylpropyleneamineoxime single photon emission computed tomography imaging, and functional magnetic resonance imaging studies. Molecular imaging includes amyloid imaging, tau imaging, and translocated protein imaging. These advancements have led to using neuroimaging as a biomarker in assessing the progression and also in deciphering prognosis of the disease. In this article, we discuss the current clinical relevance of these neurological advancements.

Observational Study of Clinical and Functional Progression Based on Initial Brain MRI Characteristics in Patients with Alzheimer's Disease

BACKGROUND

Magnetic resonance imaging (MRI) is a useful tool to predict the diagnosis and progression of Alzheimer's disease (AD), especially for primary physicians. However, the correlation between baseline MRI findings and AD progression has not been fully established.

OBJECTIVE

To investigate the correlation between hippocampal atrophy (HA) and white matter hyperintensities (WMH) on initial brain MRI images and the degree of cognitive decline and functional changes over 1 year.

METHODS

In this prospective, 12-month observational study, dementia outpatients were recruited from 29 centers across South Korea. Baseline assessments of HA and WMH on baseline brain MRI were derived as well as cognitive function, dementia severity, activities of daily living, and acetylcholinesterase inhibitor (AChEI) use. Follow-up assessments were conducted at 6 and 12 months.

RESULTS

Among 899 enrolled dementia patients, 748 were diagnosed with AD of whom 654 (87%) were taking AChEIs. Baseline WMH showed significant correlations with age, current alcohol consumption, and Clinical Dementia Rating score; baseline HA was correlated with age, family history, physical exercise, and the results of cognitive assessments. Among the AChEI group, changes in the Korean version of the Instrumental Activities of Daily Living (K-IADL) were correlated with the severity of HA on baseline brain MRI, but not with the baseline severity of WMH. In the no AChEI group, changes in K-IADL were correlated with the severity of WMH and HA at baseline.

CONCLUSION

Baseline MRI findings could be a useful tool for predicting future clinical outcomes by primary physicians, especially in relation to patients' functional status.

Selecting the most relevant brain regions to discriminate Alzheimer's disease patients from healthy controls using multiple kernel learning: A comparison across functional and structural imaging modalities and atlases

BACKGROUND

Machine learning techniques such as support vector machine (SVM) have been applied recently in order to accurately classify individuals with neuropsychiatric disorders such as Alzheimer's disease (AD) based on neuroimaging data. However, the multivariate nature of the SVM approach often precludes the identification of the brain regions that contribute most to classification accuracy. Multiple kernel learning (MKL) is a sparse machine learning method that allows the identification of the most relevant sources for the classification. By parcelating the brain into regions of interest (ROI) it is possible to use each ROI as a source to MKL (ROI-MKL).

METHODS

We applied MKL to multimodal neuroimaging data in order to: 1) compare the diagnostic performance of ROI-MKL and whole-brain SVM in discriminating patients with AD from demographically matched healthy controls and 2) identify the most relevant brain regions to the classification. We used two atlases (AAL and Brodmann's) to parcelate the brain into ROIs and applied ROI-MKL to structural (T1) MRI, 18F-FDG-PET and regional cerebral blood flow SPECT (rCBF-SPECT) data acquired from the same subjects (20 patients with early AD and 18 controls). In ROI-MKL, each ROI received a weight (ROI-weight) that indicated the region's relevance to the classification. For each ROI, we also calculated whether there was a predominance of voxels indicating decreased or increased regional activity (for 18F-FDG-PET and rCBF-SPECT) or volume (for T1-MRI) in AD patients.

RESULTS

Compared to whole-brain SVM, the ROI-MKL approach resulted in better accuracies (with either atlas) for classification using 18F-FDG-PET (92.5% accuracy for ROI-MKL versus 84% for whole-brain), but not when using rCBF-SPECT or T1-MRI. Although several cortical and subcortical regions contributed to discrimination, high ROI-weights and predominance of hypometabolism and atrophy were identified specially in medial parietal and temporo-limbic cortical regions. Also, the weight of discrimination due to a pattern of increased voxel-weight values in AD individuals was surprisingly high (ranging from approximately 20% to 40% depending on the imaging modality), located mainly in primary sensorimotor and visual cortices and subcortical nuclei.

CONCLUSION

The MKL-ROI approach highlights the high discriminative weight of a subset of brain regions of known relevance to AD, the selection of which contributes to increased classification accuracy when applied to 18F-FDG-PET data. Moreover, the MKL-ROI approach demonstrates that brain regions typically spared in mild stages of AD also contribute substantially in the individual discrimination of AD patients from controls.

Alzheimer's Disease: Biomarkers in the Genome, Blood, and Cerebrospinal Fluid

Alzheimer's disease (AD) is a progressive neurodegenerative disorder that slowly destroys memory and thinking skills, resulting in behavioral changes. It is estimated that nearly 36 million are affected globally with numbers reaching 115 million by 2050. AD can only be definitively diagnosed at autopsy since its manifestations of senile plaques and neurofibrillary tangles throughout the brain cannot yet be fully captured with current imaging technologies. Current AD therapeutics have also been suboptimal. Besides identifying markers that distinguish AD from controls, there has been a recent drive to identify better biomarkers that can predict the rates of cognitive decline and neocortical amyloid burden in those who exhibit preclinical, prodromal, or clinical AD. This review covers biomarkers of three main types: genes, cerebrospinal fluid-derived, and blood-derived biomarkers. Looking ahead, cutting-edge OMICs technologies, including proteomics and metabolomics, ought to be fully tapped in order to mine even better biomarkers for AD that are more predictive.

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

Structural brain changes underlying mild cognitive impairment (MCI) have been well-researched, but most previous studies required subjective cognitive complaints (SCC) as a diagnostic criterion, diagnosed MCI based on a single screening test or lacked analyses in relation to neuropsychological impairment. This longitudinal voxel-based morphometry study aimed to overcome these limitations: The relationship between regional gray matter (GM) atrophy and behavioral performance was investigated over the course of 3 years in individuals unaware of cognitive decline, identified as amnestic MCI based on an extensive neuropsychological test battery. Region of interest analyses revealed GM atrophy in the left amygdala, hippocampus, and parahippocampus in MCI individuals compared to normally aging participants, which was specifically related to verbal memory impairment and evident already at the first measurement point. These findings demonstrate that GM atrophy is detectable in individuals with amnestic MCI despite unawareness of beginning cognitive decline. Thus, individuals with GM atrophy in regions associated with verbal memory impairment do not necessarily need to experience SCC before meeting neuropsychological criteria for MCI. These results have important implications for future research and diagnostic procedures of MCI.

MR brain image analysis in dementia: From quantitative imaging biomarkers to ageing brain models and imaging genetics

MR brain image analysis has constantly been a hot topic research area in medical image analysis over the past two decades. In this article, it is discussed how the field developed from the construction of tools for automatic quantification of brain morphology, function, connectivity and pathology, to creating models of the ageing brain in normal ageing and disease, and tools for integrated analysis of imaging and genetic data. The current and future role of the field in improved understanding of the development of neurodegenerative disease is discussed, and its potential for aiding in early and differential diagnosis and prognosis of different types of dementia. For the latter, the use of reference imaging data and reference models derived from large clinical and population imaging studies, and the application of machine learning techniques on these reference data, are expected to play a key role.