Cognitive, genetic, and brain perfusion factors associated with four year incidence of Alzheimer's disease from mild cognitive impairment

Brain perfusion SPECT in dementia: what radiologists should know

The findings of brain perfusion single-photon emission computed tomography (SPECT), which detects abnormalities often before changes manifest in morphological imaging, mainly reflect neurodegeneration and contribute to dementia evaluation. A major shift is about to occur in dementia practice to the approach of diagnosing based on biomarkers and treating with disease-modifying drugs. Accordingly, brain perfusion SPECT will be required to serve as a biomarker of neurodegeneration. Hypoperfusion in Alzheimer's disease (AD) is typically seen in the posterior cingulate cortex and precuneus early in the disease, followed by the temporoparietal cortices. On the other hand, atypical presentations of AD such as the posterior variant, logopenic variant, frontal variant, and corticobasal syndrome exhibit hypoperfusion in areas related to symptoms. Additionally, hypoperfusion especially in the precuneus and parietal association cortex can serve as a predictor of progression from mild cognitive impairment to AD. In dementia with Lewy bodies (DLB), the differentiating feature is the presence of hypoperfusion in the occipital lobes in addition to that observed in AD. Hypoperfusion of the occipital lobe is not a remarkable finding, as it is assumed to reflect functional loss due to impairment of the cholinergic and dopaminergic systems rather than degeneration per se. Moreover, the cingulate island sign reflects the degree of AD pathology comorbid in DLB. Frontotemporal dementia is characterized by regional hypoperfusion according to the three clinical types, and the background pathology is diverse. Idiopathic normal pressure hydrocephalus shows apparent hypoperfusion around the Sylvian fissure and corpus callosum and apparent hyperperfusion in high-convexity areas. The cortex or striatum with diffusion restriction on magnetic resonance imaging in prion diseases reflects spongiform degeneration and brain perfusion SPECT reveals hypoperfusion in the same areas. Brain perfusion SPECT findings in dementia should be carefully interpreted considering background pathology.

Sex differences in functional connectivity and the predictive role of the connectome-based predictive model in Alzheimer's disease

Alzheimer's disease (AD) is a neurodegenerative disease characterized by cognitive decline. Sex differences in the progression of AD exist, but the neural mechanisms are not well understood. The purpose of the current study was to explore sex differences in brain functional connectivity (FC) at different stages of AD and their predictive ability on Montreal Cognitive Assessment (MoCA) scores using connectome-based predictive modeling (CPM). Resting-state functional magnetic resonance imaging was collected from 81 AD patients (44 females), 78 amnestic mild cognitive impairment patients (44 females), and 92 healthy controls (50 females). The FC analysis was conducted and the interaction effect between sex and group was investigated using two-factor variance analysis. The CPM was used to predict MoCA scores. There were sex-by-group interaction effects on FC between the left dorsolateral superior frontal gyrus and left middle temporal gyrus, left precuneus and right calcarine fissure surrounding cortex, left precuneus and left middle occipital gyrus, left middle temporal gyrus and left precentral gyrus, and between the left middle temporal gyrus and right cuneus. In the CPM, the positive network predictive model significantly predicted MoCA scores in both males and females. There were significant sex-by-group interaction effects on FC between the left precuneus and left middle occipital gyrus, and between the left middle temporal gyrus and right cuneus could predict MoCA scores in female patients. Our results suggest that there are sex differences in FC at different stages of AD. The sex-specific FC can further predict MoCA scores at individual level.

Amyloid Pathology Modulates the Associations of Neuropsychiatric Symptoms with Cognitive Impairments and Neurodegeneration in Non-Demented Elderly

BACKGROUND

The associations between neuropsychiatric symptoms (NPSs) and Alzheimer's disease (AD) have been well-studied, yet gaps remain.

OBJECTIVE

We aimed to examine the associations of four subsyndromes (hyperactivity, psychosis, affective symptoms, and apathy) of NPSs with cognition, neurodegeneration, and AD pathologies.

METHODS

Totally 1,040 non-demented elderly (48.07% males) from the Alzheimer's Disease Neuroimaging Initiative (ADNI) were included. We assessed the relationships between NPSs and AD neuropathologies, cognition, neurodegeneration, and clinical correlates in cross-sectional and longitudinal via multiple linear regression, linear mixed effects, and Cox proportional hazard models. Causal mediation analyses were conducted to explore the mediation effects of AD pathologies on cognition and neurodegeneration.

RESULTS

We found that individuals with hyperactivity, psychosis, affective symptoms, or apathy displayed a poorer cognitive status, a lower CSF amyloid-β (Aβ) level and a higher risk of clinical conversion (p < 0.05). Hyperactivity and affective symptoms were associated with increasing cerebral Aβ deposition (p < 0.05). Except psychosis, the other three subsyndromes accompanied with faster atrophy of hippocampal volume (p < 0.05). Specific NPSs were predominantly associated with different cognitive domains decline through an 8-year follow-up (p < 0.05). Moreover, the relationships between NPSs and cognitive decline, neurodegeneration might be associated with Aβ, the mediation percentage varied from 6.05% to 17.51% (p < 0.05).

CONCLUSIONS

NPSs could be strongly associated with AD. The influences of NPSs on cognitive impairments, neurodegeneration might be partially associated with Aβ.

Evaluation of glymphatic system activity by diffusion tensor image analysis along the perivascular space (DTI-ALPS) in dementia patients

OBJECTIVES

Dementia is a clinical syndrome caused by multiple etiologies, usually manifests with progressive and diffuse brain dysfunction. The activity of the human glymphatic system was evaluated in cases of dementia by the diffusion tensor image analysis along the perivascular space (DTI-ALPS).

METHODS

We recruited 28 healthy subjects and 77 patients, including 38 with Alzheimer's disease (AD),18 with mild cognitive impairment (MCI), 28 with normal controls (NC) and 21 with vascular cognitive impairment (VCI). All participants underwent DTI scanning. Diffusivities in the X, Y and Z axes were obtained in the lateral ventricle body plane of all subjects. We assessed the diffusivity along the perivascular spaces, as well as projection fibers and association fibers, respectively, in order to acquire an DTI-ALPS-index and correlated them with mini mental state examination (MMSE) and montreal cognitive assessment (MOCA) scores using partial correlation which the influence of age was controlled.

RESULTS

The AD, MCI, and VCI patients showed significantly lower DTI-ALPS-index (p < 0.001) compared to the NC. Besides, the VCI group had significantly higher DTI-ALPS-index than the AD group (p = 0.007). There was a significant positive correlation between DTI-ALPS-index and MMSE and MOCA scores (the effect of age was controlled), showing that lower water diffusivity along the perivascular spaces associated with dementia.The higher Dzassoc led to the reduced DTI-ALPS-index in VCI, while lower Dxassoc contributed to the decrease of DTI-ALPS-index in AD.

CONCLUSION

The evaluation of DTI-ALPS demonstrates impairment of the glymphatic system in dementia patients by decreased DTI-ALPS-index. Different from AD, the VCI patients show glymphatic drainage disorder rather than glymphatic system impairment.

ADVANCES IN KNOWLEDGE

This article comprehensively covers several types of dementia and performs the comparison of VCI, AD and MCI in glymphatic system dysfunction.

Positive Effect of Cognitive Training in Older Adults with Different APOE Genotypes and COVID-19 History: A 1-Year Follow-Up Cohort Study

(1) Background: Older people suffer from cognitive decline; several risk factors contribute to greater cognitive decline. We used acquired (COVID-19 infection) and non-modifiable (presence of APOE rs429358 and rs7412 polymorphisms) factors to study the progression of subjective cognitive impairment while observing patients for one year. Cognitive training was used as a protective factor. (2) Methods: Two groups of subjects over the age of 65 participated in the study: group with subjective cognitive decline receiving cognitive training and individuals who did not complain of cognitive decline without receiving cognitive training (comparison group). On the first visit, the concentration of antibodies to COVID-19 and APOE genotype was measured. At the first and last point (1 year later) the Mini-Mental State Examination scale and the Hospital Anxiety and Depression Scale were performed. (3) Results: COVID-19 infection did not affect cognitive function. A significant role of cognitive training in improving cognitive functions was revealed. Older adults with APOE-ε4 genotype showed no positive effect of cognitive training. (4) Conclusions: Future research should focus on cognitive dysfunction after COVID-19 in long-term follow-up. Attention to the factors discussed in our article, but not limited to them, are useful for a personalized approach to maintaining the cognitive health of older adults.

Prediction of conversion to dementia using interpretable machine learning in patients with amnestic mild cognitive impairment

Purpose

Amnestic mild cognitive impairment (aMCI) is a transitional state between normal aging and Alzheimer’s disease (AD). However, not all aMCI patients are observed to convert to AD dementia. Therefore, developing a predictive algorithm for the conversion of aMCI to AD dementia is important. Parametric methods, such as logistic regression, have been developed; however, it is difficult to reflect complex patterns, such as non-linear relationships and interactions between variables. Therefore, this study aimed to improve the predictive power of aMCI patients’ conversion to dementia by using an interpretable machine learning (IML) algorithm and to identify the factors that increase the risk of individual conversion to dementia in each patient.

Methods

We prospectively recruited 705 patients with aMCI who had been followed-up for at least 3 years after undergoing baseline neuropsychological tests at the Samsung Medical Center between 2007 and 2019. We used neuropsychological tests and apolipoprotein E (APOE) genotype data to develop a predictive algorithm. The model-building and validation datasets were composed of data of 565 and 140 patients, respectively. For global interpretation, four algorithms (logistic regression, random forest, support vector machine, and extreme gradient boosting) were compared. For local interpretation, individual conditional expectations (ICE) and SHapley Additive exPlanations (SHAP) were used to analyze individual patients.

Results

Among the four algorithms, the extreme gradient boost model showed the best performance, with an area under the receiver operating characteristic curve of 0.852 and an accuracy of 0.807. Variables, such as age, education, the scores of visuospatial and memory domains, the sum of boxes of the Clinical Dementia Rating scale, Mini-Mental State Examination, and APOE genotype were important features for creating the algorithm. Through ICE and SHAP analyses, it was also possible to interpret which variables acted as strong factors for each patient.

Conclusion

We were able to propose a predictive algorithm for each aMCI individual’s conversion to dementia using the IML technique. This algorithm is expected to be useful in clinical practice and the research field, as it can suggest conversion with high accuracy and identify the degree of influence of risk factors for each patient.

From Face-to-Face to Home-to-Home: Validity of a Teleneuropsychological Battery

Background:

Over the last decade, teleneuropsychology has increased substantially. There is a need for valid neuropsychological batteries to be administered home-to-home. Since 2006, the neuropsychological battery of Fundació ACE (NBACE) has been administered face-to-face in our clinical settings. Recently, we adapted the NBACE for teleneuropsychology use to be administered home-to-home (NBACEtn).

Objective:

The aims of the present study are: 1) to determine the home-to-home NBACE equivalence compared to its original face-to-face version; and 2) to examine home-to-home NBACE discriminant capacity by differentiating among cognitively healthy, mild cognitive impairment, or mild dementia subjects and comparing it with the face-to-face version.

Methods:

Data from 338 individuals assessed home-to-home (NBACEtn) were contrasted with 7,990 participants assessed with its face-to-face version (NBACE). Exploratory and confirmatory factorial structure, and invariance analysis of the two versions of the battery were performed.

Results:

Exploratory and confirmatory factor analysis supported the four-factor model (attention, memory, executive, and visuospatial/constructional functions). Configural, metric, and scalar measurement invariance was found between home-to-home and face-to-face NBACE versions. Significant differences in most of the neuropsychological variables assessed were observed between the three clinical groups in both versions of administration. No differences were found between the technological devices used by participants (computer or tablet and mobile devices).

Conclusion:

For the first time, invariance analysis findings were addressed by determining a teleneuropsychological battery’s equivalence in comparison with its face-to-face version. This study amplifies the neuropsychological assessment’s applicability using a home-to-home format, maintaining the original measure’s structure, interpretability, and discriminant capacity.

Characteristics of Regional Cerebral Blood Flow in Alzheimer Disease and Amnestic Mild Cognitive Impairment by Single-Photon Emission Computerized Tomography: A Cross-Sectional Study

Introduction

The regional cerebral blood flow (rCBF) distribution can affect brain functioning, leading to amnestic mild cognitive impairment (aMCI) and mild Alzheimer disease (AD). This study aimed to clarify the detailed characteristics of rCBF distribution in patients with mild AD and aMCI.

Methods

This cross-sectional study from April 2015 to March 2018 included 103 older adults (mean age 78.9 years; 60% females), out of a total of 302 adults, and categorized them into 3 groups according to cognitive symptoms. The normal control (NC), aMCI, and mild AD groups included 20, 50, and 33 participants, respectively. The primary outcome was rCBF, which was compared among the 3 groups using a 2-sample t test without correction for multiple comparisons.

Results

In the aMCI group, the rCBF decreased in the bilateral parietal and left frontal association cortex and the bilateral premotor cortex (p < 0.01) but increased in the bilateral cerebellum (p < 0.01). In the mild AD group, the rCBF decreased in the bilateral parietal and occipital association cortex, the bilateral premotor cortex, the left temporal and frontal association cortex, and the left limbic lobe (p < 0.01). Conversely, the rCBF increased in some parts of the cerebellum, the bilateral frontal and temporal association cortex, the left occipital association cortex, and the right premotor cortex (p < 0.01).

Conclusion

Based on the analysis of the values obtained, it was inferred that the rCBF undergoes reduction and elevation in aMCI and AD patients.

Association of dyslipidaemia with Alzheimer's disease in a cohort of postmenopausal women

Objective

To evaluate the association between dyslipidaemia and Alzheimer’s disease (AD) in a cohort of postmenopausal women.

Methods

This retrospective study analysed data from postmenopausal women with early AD (group AD) and a cohort of healthy age- and sex-matched control subjects (group NC) that were considered to be within standard limits according to a neuropsychological assessment between March 2010 and March 2019. The primary endpoints were body mass index and lipid-related laboratory parameters, including leptin, high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), total cholesterol, adiponectin, triglycerides, apolipoprotein A1, apolipoprotein B and apolipoprotein E4, which were evaluated using multivariate binary logistic analysis.

Results

The study enrolled 200 postmenopausal women with early AD (mean ± SD age 69.34 ± 6.25 years) and 180 control subjects (mean ± SD age 67.48 ± 7.42 years). Lower HDL-C and higher LDL-C were risk factors for AD. A multivariate binary logistic regression model demonstrated that lower HDL-C and higher LDL-C were the only variables associated with the development of AD (odds ratio [OR] 21.14, 95% confidence interval [CI] 2.47, 4.13; OR 36.35, 95% CI 1.24, 3.38; respectively).

Conclusion

Both low HDL-C and high LDL-C were associated with the occurrence of AD in a cohort of postmenopausal women.

Comparative Cognitive Effects of Choreographed Exercise and Multimodal Physical Therapy in Older Adults with Amnestic Mild Cognitive Impairment: Randomized Clinical Trial

Background:

Recent research on mild cognitive impairment (MCI) has primarily focused on searching for measures to prevent or delay the progression of MCI to dementia. Physical exercise has shown to be effective in the prevention of age-related cognitive decline in elderly adults with MCI. However, the most effective type and dose of exercise for the improvement of cognition are yet to be determined.

Objective:

To compare the cognitive effects of choreographed exercise (Choreography group) with a multimodal physical therapy program (Physical Therapy group) in elderly adults with amnestic MCI, a population with an increased risk of developing dementia.

Methods:

We conducted a randomized clinical trial with two parallel groups under allocation concealment and assessor blinding. Participants were allocated into Choreography or Physical Therapy group and performed exercises twice per week in 60-minute sessions during 12 weeks.

Results:

Thirty-six participants with amnestic MCI, ages 65 to 85, were assessed at baseline and after 12 weeks of intervention, by comprehensive validated neuropsychological and physical assessments. A Repeated measures General Lineal Model showed statistically significant differences in cognitive and physical outcomes. Both groups significantly improved in visual delayed recall. The Choreography group exhibited significantly more benefits on verbal recognition memory than the Physical Therapy group.

Conclusion:

Greater cognitive benefits were achieved in the choreographic intervention than in the multimodal physical therapy, mainly in those functions more related to the risk of conversion to dementia. Additional studies are needed to confirm whether the observed effects are related to delayed onset of Alzheimer’s disease in elderly adults with amnestic MCI.

HMPAO-SPECT Can Discriminate between Patients with Subjective Cognitive Complaints with and without Cognitive Deficits and those with Mild Cognitive Impairment

BACKGROUND

Growing evidence suggests that pathological processes leading to Alzheimer's disease occurs gradually and begins to develop decades before the earliest clinical symptoms occur. The use of biomarkers has been proposed to detect evidence of preclinical Alzheimer's pathologic change in asymptomatic subjects. Subjective cognitive complaints (SCC) i.e. self-reported cognitive decline with normal cognition have been reported as an indicator of future cognitive decline, however, this condition is unspecific.

OBJECTIVE

In the present study we used the regional brain perfusion measured by HMPAO-SPECT as Biomarker of neurodegeneration to compare the regional brain perfusion of patient with subjective cognitive complaints with and without minimal cognitive dysfunction (SCC+ and SCC- respectively) in respect to patients with mild cognitive impairment (MCI).

METHODS

We retrospectively examined 736 Patients who referred to our Memory Clinic because of suspected cognitive dysfunction. After exclusion of patients with overt dementia, automated, quantitatively assessed relative cerebral blood flow of 10 forebrain regions (thalamus, parietotemporal, medial temporal, posterior temporal, posterior cingulate gyrus, each region left hemispheric and right hemispheric) and neuropsychological assessment of 64 SCC (32 SCC+; 32 SCC-) and 28 MCI subjects were analysed.

RESULTS

.The most relevant differences between groups in cognitive performance concerned verbal memory. Left hemispheric medial temporal region could significantly discriminate between all three groups, with a progressive decrease n perfusion from SCC towards MCI. Area under the curve of left medial temporal region showed a sensitivity of 0,61 and a specificity of 0,78 for discriminating MCI from SCC.

CONCLUSION

Automated analysis of HMPAO-SPECT data of MCI and SCC+ patients showed significant perfusion differences in medial temporal region and impaired verbal memory, both of which are known features of Alzheimer's disease. Perfusion patterns and verbal memory performance in SCC+ are more similar to MCI than SCC-. Thus, SPECT analysis could distinguish those subjects whose perfusion pattern resembles that of an MCI from those who do not. In our opinion, this could identify two populations with a different risk of progression to AD, with SCC+ subjects needing further diagnostic examination and repeated follow-up.

Semantic Relations in a Categorical Verbal Fluency Test: An Exploratory Investigation in Mild Cognitive Impairment

Categorical verbal fluency tests (CFT) are commonly used to assess the integrity of semantic memory in individuals with brain damage. Persons with Dementia of the Alzheimer's Type display a reduced output on CFT, and a similar pattern has been reported in persons with amnesic Mild Cognitive Impairment (aMCI). The aims of the present study were to assess whether the semantic relations between lexical entries produced on a categorical fluency test were different between healthy persons and those with aMCI, and whether this difference was more pronounced in individuals who converted to dementia during a 3-year follow-up period.

Methods

We recruited 34 individuals with aMCI and 29 matched healthy persons. During the follow-up period, 10 individuals converted to Dementia (aMCI-conv). Two measures assessing semantic relations between consecutively produced word pairs (Path length and Extended Gloss Overlap) were obtained from the Wordnet database.

Results

The number of word pairs analyzed among the healthy participants (HP) and persons with aMCI were 498 (birds: 262; pieces of furniture: 236) and 395 (birds: 174; pieces of furniture: 221), respectively. Path length was lower in aMCI-conv than in HP (p = 0.035), but no differences were found between stable aMCI and HP, and between aMCI-stable and aMCI-conv. The ANOVA for lexical entries belonging to the "birds" category showed a significant effect of group (F = 5.630; p = 0.004); the post hoc analysis showed a significant difference between HP and aMCI-conv (p = 0.003). The "pieces of furniture" category was significantly affected by group (F = 4.107; p = 0.017); the post hoc test showed significant differences between aMCI-conv and healthy individuals (p = 0.049), and between aMCI-conv and stable aMCI (p = 0.001).

Discussion

Individuals with aMCI who convert to dementia show a deterioration in the semantic relations between lexical entries, produced on a CFT. This phenomenon may be interpreted as a marker of a very early disruption of semantic memory.

The Vascular Hypothesis of Alzheimer's Disease: A Key to Preclinical Prediction of Dementia Using Neuroimaging

The vascular hypothesis of Alzheimer's disease (VHAD) was proposed 24 years ago from observations made in our laboratory using aging rats subjected to chronic brain hypoperfusion. In recent years, VHAD has become a mother-lode to numerous neuroimaging studies targeting cerebral hemodynamic changes, particularly brain hypoperfusion in elderly patients at risk of developing Alzheimer's disease (AD). There is a growing consensus among neuroradiologists that brain hypoperfusion is likely involved in the pathogenesis of AD and that disturbed cerebral blood flow (CBF) can serve as a key biomarker for predicting conversion of mild cognitive impairment to AD. The use of cerebral hypoperfusion as a preclinical predictor of AD is becoming decisive in stratifying low and high risk patients that may develop cognitive decline and for assessing the effectiveness of therapeutic interventions. There is currently an international research drive from neuroimaging groups to seek new perspectives that can broaden our understanding of AD and improve lifestyle. Diverse neuroimaging methods are currently being used to monitor normal and dyscognitive brain activity. Some techniques are very powerful and can detect, diagnose, quantify, prognose, and predict cognitive decline before AD onset, even from a healthy cognitive state. Multimodal imaging offers new insights in the treatment and prevention of cognitive decline during advanced aging and better understanding of the functional and structural organization of the human brain. This review discusses the impact the VHAD and CBF are having on the neuroimaging technology that can usher practical strategies to help prevent AD.

Association of Apathy With Risk of Incident Dementia: A Systematic Review and Meta-analysis

IMPORTANCE

Fear of dementia is pervasive in older people with cognitive concerns. Much research is devoted to finding prognostic markers for dementia risk. Studies suggest apathy in older people may be prodromal to dementia and could be a relevant, easily measurable predictor of increased dementia risk. However, evidence is fragmented and methods vary greatly between studies.

OBJECTIVE

To systematically review and quantitatively synthesize the evidence for an association between apathy in dementia-free older individuals and incident dementia.

DATA SOURCES

Two reviewers conducted a systematic search of Medline, Embase, and PsychINFO databases.

STUDY SELECTION

Inclusion criteria were (1) prospective cohort studies, (2) in general populations or memory clinic patients without dementia, (3) with clear definitions of apathy and dementia, and (4) reporting on the association between apathy and incident dementia.

DATA EXTRACTION AND SYNTHESIS

PRISMA and MOOSE guidelines were followed. Data were extracted by 1 reviewer and checked by a second.

MAIN OUTCOMES AND MEASURES

Main outcomes were pooled crude risk ratios, maximally adjusted reported hazard ratios (HR), and odds ratios (OR) using DerSimonian-Laird random effects models.

RESULTS

The mean age of the study populations ranged from 69.2 to 81.9 years (median, 71.6 years) and the percentage of women ranged from 35% to 70% (median, 53%). After screening 2031 titles and abstracts, 16 studies comprising 7365 participants were included. Apathy status was available for 7299 participants. Studies included populations with subjective cognitive concerns (n = 2), mild cognitive impairment (n = 11), cognitive impairment no dementia (n = 1), or mixed cognitive and no cognitive impairment (n = 2). Apathy was present in 1470 of 7299 participants (20.1%). Follow-up ranged from 1.2 to 5.4 years. In studies using validated apathy definitions (n = 12), the combined risk ratio of dementia for patients with apathy was 1.81 (95% CI, 1.32-2.50; I2 = 76%; n = 12), the hazard ratio was 2.39 (95% CI, 1.27-4.51; I2 = 90%; n = 7), and the odds ratio was 17.14 (95% CI, 1.91-154.0; I2 = 60%; n = 2). Subgroup analyses, meta-regression, and individual study results suggested the association between apathy and dementia weakened with increasing follow-up time, age, and cognitive impairment. Meta-regression adjusting for apathy definition and follow-up time explained 95% of heterogeneity in mild cognitive impairment.

CONCLUSIONS AND RELEVANCE

Apathy was associated with an approximately 2-fold increased risk of dementia in memory clinic patients. Moderate publication bias may have inflated some of these estimates. Apathy deserves more attention as a relevant, cheap, noninvasive, and easily measureable marker of increased risk of incident dementia with high clinical relevance, particularly because these vulnerable patients may forgo health care.

Validation of the Delayed Matching-to-Sample Task 48 (DMS48) in Elderly Chinese

BACKGROUND

Delayed Matching-to-Sample Task 48 (DMS48), a brief tool measuring visual recognition memory, is valid to identify the early stage of Alzheimer's disease (AD) in Caucasians. However, little data is available in Chinese.

OBJECTIVE

To develop norms and optimal cutoff points for the DMS48 in Chinese elders.

METHODS

A cross-sectional study was conducted in seven memory clinics from five cities across China. DMS48 was applied to 369 Chinese aged 50 or older (138 cognitively normal [CN], 112 mild cognitive impairment due to AD (MCI-A), and 119 mild AD dementia). The demographic factors which influence DMS48 scores were investigated and the norms were established considering those factors. Receiver operating characteristic (ROC) analysis was used to determine the optimal cutoff points.

RESULTS

Age was shown to influence DMS48 scores (r = -0.36, p < 0.05), and we presented the age-stratified normative data for the DMS48. The optimal cutoff point is 42/43 for identifying cognitive impairment (MCI-A and AD dementia) against CN (sensitivity 97.80% and specificity 89.13%) and MCI-A against CN (sensitivity 86.60% and specificity 94.20%). A cutoff of 39/40 obtained good sensitivity (100.00%) and specificity (94.90%) in discriminating AD dementia from CN. The age-stratified optimal cutoff points for identifying MCI-A were 43/44 for individuals aged 50 to 59 years old, 42/43 for 60 to 69 years old, 41/42 for 70 to 79 years old, and 40/41 for 80 or older, respectively (sensitivity 84.80% and specificity 95.70%).

CONCLUSION

This study proved that DMS48 is of good validation in screening MCI-A in elderly Chinese.

Patient Engagement: The Fundació ACE Framework for Improving Recruitment and Retention in Alzheimer's Disease Research

Alzheimer's disease (AD) research is at a critical time. The global society is increasingly aware of the frightening rate of growth of the human and financial burden caused by this condition and of the urgent need to halt its progression. Consequently, the scientific community holds great responsibility to quickly put in place and optimize the machinery necessary for testing new treatments or interventions. In this context demand for participants for AD research is at an all-time high. In this review, we will focus on a methodological factor that is increasingly recognized as a key factor that shapes trial populations and affects validity of results in clinical trials: patient engagement, recruitment, and retention. We outline specific problems relevant to patient engagement in AD including recruiting enough participants, difficulties in participant retention, ensuring the recruited sample is representative of the general AD population, the burden of screening failures, and new challenges related to recruiting in preclinical disease. To address the urgent need for more research studying the applicability and cost-effectiveness of different recruitment strategies across different settings and nationalities, we describe the Models of Patient Engagement for Alzheimer's Disease (MOPEAD) project, a public-private partnership promoted by the Innovative Medicine Initiative (IMI), which will provide a large multinational quantitative analysis comparing different innovative recruitment models. We also discuss strategies that address each problem and draw on the experience of Fundació ACE to argue that focusing resources on comprehensive AD centers that offer coordinated clinical and social care and participate in basic and clinical research, is an effective and efficient way of implementing many of the discussed strategies.

Advancing Alzheimer's research: A review of big data promises

OBJECTIVE

To review the current state of science using big data to advance Alzheimer's disease (AD) research and practice. In particular, we analyzed the types of research foci addressed, corresponding methods employed and study findings reported using big data in AD.

METHOD

Systematic review was conducted for articles published in PubMed from January 1, 2010 through December 31, 2015. Keywords with AD and big data analytics were used for literature retrieval. Articles were reviewed and included if they met the eligibility criteria.

RESULTS

Thirty-eight articles were included in this review. They can be categorized into seven research foci: diagnosing AD or mild cognitive impairment (MCI) (n=10), predicting MCI to AD conversion (n=13), stratifying risks for AD (n=5), mining the literature for knowledge discovery (n=4), predicting AD progression (n=2), describing clinical care for persons with AD (n=3), and understanding the relationship between cognition and AD (n=3). The most commonly used datasets are AD Neuroimaging Initiative (ADNI) (n=16), electronic health records (EHR) (n=11), MEDLINE (n=3), and other research datasets (n=8). Logistic regression (n=9) and support vector machine (n=8) are the most used methods for data analysis.

CONCLUSION

Big data are increasingly used to address AD-related research questions. While existing research datasets are frequently used, other datasets such as EHR data provide a unique, yet under-utilized opportunity for advancing AD research.

Abnormal global functional network connectivity and its relationship to medial temporal atrophy in patients with amnestic mild cognitive impairment

Background

Amnestic mild cognitive impairment (aMCI), which is recently considered as a high risk status for developing Alzheimer’s disease (AD), manifests with gray matter atrophy and increased focal functional activity in the medial temporal lobe (MTL). However, the abnormalities of whole-brain functional network connectivity in aMCI and its relationship to medial temporal atrophy (MTA) remain unknown.

Methods

In this study, thirty-six aMCI patients and thirty-five healthy controls (HCs) were recruited. Neuropsychological assessments and MTA visual rating scaling were carried out on all participants. Furthermore, whole brain functional network was constructed at voxel level, and functional connectivity strength (FCS) was computed as the sum of the connections for each node to capture its global integrity. General linear model was used to analyze the FCS values differences between aMCI and HCs. Then, the regions showing significant FCS differences were adopted as the imaging markers for discriminative analysis. Finally, the relationship between FCS values and clinical cognitive scores was correlated in patients with aMCI.

Results

Comparing to HCs, aMCI exhibited significant atrophy in the MTL, while higher FCS values within the bilateral MTL regions and orbitofrontal cortices. Notably, the right hippocampus had the highest classification power, with the area under receiver operating characteristics (ROC) curve (AUC) of 0.790 (confidence interval: 0.678, 0.901). Moreover, FCS values of the right hippocampus and the left temporal pole were positively correlated with the cognitive performance in aMCI.

Conclusion

This study demonstrated significantly structural atrophy and raised global functional integrity in the MTL, suggesting simultaneous disruption and compensation in prodromal AD. Increased intrinsic functional connectivity in the MTL may have the potential to discriminate subjects with tendency to develop AD.

A Nonparametric Approach for Mild Cognitive Impairment to AD Conversion Prediction: Results on Longitudinal Data

The goal of this study is to introduce a nonparametric technique for predicting conversion from Mild Cognitive impairment (MCI)-to-Alzheimer's disease (AD). Progression of a slowly progressing disease such as AD benefits from the use of longitudinal data; however, research till now is limited due to the insufficient patient data and short follow-up time. A small dataset size invalidates the estimation of underlying disease progression model; hence, a supervised nonparametric method is proposed. While depicting a real-world setting, longitudinal data of three years are employed for training, whereas only the baseline visit's data is used for validation. The train set is preprocessed for extraction of two dense clusters representing the subjects who remain stable at MCI or progress to AD after three years of the baseline visit. Similarity between these clusters and the test point is calculated in Euclidean space. Multiple features from two modalities of biomarkers, i.e., neuropsychological measures (NM) and structural magnetic resonance imaging (MRI) morphometry are also analyzed. Due to the limited MCI dataset size (NM: 145, MRI: 52, NM+MRI: 29), leave-one-out cross validation setup is employed for performance evaluation. The algorithm performance is noted for both unimodal case and bimodal cases. Superior performance (accuracy: 89.66%, sensitivity: 87.50%, specificity: 92.31%, precision: 93.33%) is delivered by multivariate predictors. Three notable conclusions of this study are: 1) Longitudinal data are more powerful than the temporal data, 2) MRI is a better predictor of MCI-to-AD conversion than NM, and 3) multivariate predictors outperform single predictor models.

Prediction of Cognitive and Functional Decline Using the Telephone-Administered Minnesota Cognitive Acuity Screen

OBJECTIVES

To examine whether a telephone-based cognitive assessment-the Minnesota Cognitive Acuity Screen (MCAS)-is effective in predicting cognitive and functional decline in older adults with mild cognitive impairment (MCI) and conversion to dementia.

DESIGN

Longitudinal.

SETTING

Academic medical center.

PARTICIPANTS

Individuals aged 60 to 84 with MCI (N = 61).

MEASUREMENTS

An initial office visit consisting of a neurological examination, Clinical Dementia Rating Scale (CDR), and neuropsychological testing using the Dementia Rating Scale-2 (DRS-2), followed by the MCAS within 1 month. Participants completed up to three follow-up in-office neuropsychological assessments, originally scheduled 1 year apart. A multidisciplinary consensus group determined diagnosis (MCI, dementia) at each assessment.

RESULTS

Higher baseline MCAS total scores emerged as a significant predictor of slower functional decline (P = .002) and dementia conversion (P = .02). An increase in score from 43 to 50 points (1st to 3rd quartile) was associated with a 0.59-point (95% confidence interval (CI) = 0.23-0.95) lower CDR score at follow-up, and a 71% (95% CI = 1.11-2.63) increase in median time to dementia conversion from 2 years to 3.5 years. Of the MCAS subscales, delayed word recall predicted functional decline alone (P < .001), whereas computation was nominally associated with cognitive (P = .01) and functional (P = .01) decline.

CONCLUSION

The brief telephone-administered MCAS provides valuable information about future cognitive and functional decline in older adults with MCI and predicted conversion from MCI to dementia. These findings provide additional support for use of MCAS in clinical and research settings. The instrument may be particularly valuable in settings in which an office visit is difficult.

Clinical Evaluation of Brain Perfusion SPECT with Brodmann Areas Mapping in Early Diagnosis of Alzheimer's Disease

Early diagnosis of Alzheimer's disease (AD) based on clinical criteria alone may be problematic, while current and future treatments should be administered earlier in order to be more effective. Thus, various disease biomarkers could be used for early detection of AD. We evaluated brain perfusion with 99mTc-HMPAO single photon emission computed tomography (SPECT) and Brodmann areas (BAs) mapping in mild AD using an automated software (NeuroGam) for the semi-quantitative evaluation of perfusion in BAs and the comparison with the software's normal database. We studied 34 consecutive patients with mild AD: 9 men, 25 women, mean age 70.9 ± 8.1 years, mean Mini-Mental State Examination 22.6 ± 2.5. BAs 25L, 25R, 38L, 38R, 28L, 28R, 36L, and 36R had the lower mean perfusion values, while BAs 31L, 31R, 19R, 18L, 18R, 17L, and 17R had the higher mean values. Compared with healthy subjects of the same age, perfusion values in BAs 25L, 25R, 28R, 28L, 36L, and 36R had the greatest deviations from the healthy sample, while the lowest deviations were found in BAs 32L, 32R, 19R, 24L, 17L, 17R, 18L, and 18R. A percentage of ≥94% of patients had perfusion values more than -2SDs below the mean of healthy subjects in BAs 38R, 38L, 36L, 36R, 23L, 23R, 22L, 44L, 28L, 28R, 25L, and 25R. The corresponding proportion was less than 38% for BAs 11L, 19R, 32L, 32R, 18L, 18R, 24L, and 17R. In conclusion, brain SPECT studies with automated perfusion mapping could be useful as an ancillary tool in daily practice, revealing perfusion impairments in early AD.

Clinical features of incidental mild cognitive impairment and dementia in a population-based study

AIM

The number of people with dementia is rapidly increasing as populations around the world age. It is important to grasp the characteristic features of mild cognitive impairment (MCI) for early detection and prevention of dementia.

METHODS

We examined 408 individuals recruited from a health checkup for metabolic syndrome, which comprised three groups: normal (n = 325), MCI (n = 55) and apparent cognitive decline (ACD; n = 28). We compared cognitive/affective functions and exercise/hobby habits with assessments of vascular risk factors and results from computerized touch-panel tests.

RESULTS

Among the 408 individuals, 93.1% showed normal scores on the Mini-Mental State Examination, and 6.9% had ACD. Among the normal Mini-Mental State Examination participants, 14.5% had MCI (13.5% of all participants). The three groups of participants showed significant differences in age, education, systolic blood pressure, glycosylated hemoglobin and high-density lipoprotein cholesterol level. Even within the normal range, those in the MCI group showed significantly lower cognitive function than those in the normal group. Scores on the Geriatric Depression Scale were greater in the MCI group, and "day-night reversal" was worse in the ACD group. Scores on touch-panel screening tests were significantly worse in the MCI and ACD groups than in the normal group. Participants showed better cognitive and affective function if they exercised regularly or had hobbies.

CONCLUSIONS

Incidental MCI and ACD had prevalences of 13.5% and 6.9%, respectively, in the population-based study. Participants with these conditions showed cognitive/affective decline and impairment on computerized touch-panel tests in relation to vascular risk factors and exercise/hobbies. Geriatr Gerontol Int 2017; 17: 722-729.

APOE-ɛ4 Carrier Status and Donepezil Response in Patients with Alzheimer's Disease

BACKGROUND

Previous studies have investigated associations between apolipoprotein E (APOE)-ɛ4 allele status and acetylcholinesterase inhibitor treatment response in patients with Alzheimer's disease. The ability to draw definitive conclusions regarding the effect of APOE-ɛ4 genotype on treatment response has been hindered by inconsistent results among studies and methodological limitations that restrict interpretation of study findings.

OBJECTIVE

To determine whether APOE-ɛ4 carrier status influences the magnitude of change in 13-item Alzheimer's Disease Assessment Scale-Cognitive Subscale (ADAS-cog) score associated with acetylcholinesterase inhibitor treatment (i.e., donepezil).

METHODS

Analyses were performed using pooled data from the donepezil and placebo treatment arms of three consecutive, similarly designed, 12-week, multi-national, randomized clinical studies that enrolled patients with mild-to-moderate Alzheimer's disease. Correlations between APOE-ɛ4 carrier status and ADAS-cog scores were evaluated using analysis of covariance.

RESULTS

No appreciable interaction between donepezil response and APOE-ɛ4 carrier status or copy number was detected. Both carriers and non-carriers of APOE-ɛ4 who received donepezil experienced significant improvements from baseline in ADAS-cog score versus placebo (p <  0.05). Change from baseline to final observation in the donepezil treatment group was - 2.95 for APOE-ɛ4 carriers and - 4.09 for non-carriers (p = 0.23). In contrast, non-carriers of APOE-ɛ4 in the placebo treatment group exhibited a greater improvement from baseline versus carriers (-2.38 versus - 0.60, p = 0.05).

CONCLUSION

Within this population, APOE genotype had no statistically significant effect on cognitive response to donepezil treatment; however, APOE-ɛ4 allele status was associated with a difference in the magnitude of the change in ADAS-cog of placebo-treated patients.