The Usefulness of 18F-FDG PET to Differentiate Subtypes of Dementia: The Systematic Review and Meta-Analysis.

Background and Purpose: Dementia subtypes, including Alzheimer's dementia (AD), dementia with Lewy bodies (DLB), and frontotemporal dementia (FTD), pose diagnostic challenges. This review examines the effectiveness of 18F-Fluorodeoxyglucose Positron Emission Tomography (18F-FDG PET) in differentiating these subtypes for precise treatment and management. Methods: A systematic review following Preferred Reporting Items for Systematic reviews and Meta-Analyses guidelines was conducted using databases like PubMed and Embase to identify studies on the diagnostic utility of 18F-FDG PET in dementia. The search included studies up to November 16, 2022, focusing on peer-reviewed journals and applying the gold-standard clinical diagnosis for dementia subtypes. Results: From 12,815 articles, 14 were selected for final analysis. For AD versus FTD, the sensitivity was 0.96 (95% confidence interval [CI], 0.88-0.98) and specificity was 0.84 (95% CI, 0.70-0.92). In the case of AD versus DLB, 18F-FDG PET showed a sensitivity of 0.93 (95% CI 0.88-0.98) and specificity of 0.92 (95% CI, 0.70-0.92). Lastly, when differentiating AD from non-AD dementias, the sensitivity was 0.86 (95% CI, 0.80-0.91) and the specificity was 0.88 (95% CI, 0.80-0.91). The studies mostly used case-control designs with visual and quantitative assessments. Conclusions: 18F-FDG PET exhibits high sensitivity and specificity in differentiating dementia subtypes, particularly AD, FTD, and DLB. This method, while not a standalone diagnostic tool, significantly enhances diagnostic accuracy in uncertain cases, complementing clinical assessments and structural imaging.

Enrichment of infection-associated bacteria in the low biomass brain bacteriota of Alzheimer's disease patients.

Alzheimer's disease (AD) is a neurodegenerative disease accompanied by neuroimmune inflammation in the frontal cortex and hippocampus. Recently, the presence of bacteria in AD-affected brains has been documented, prompting speculation about their potential role in AD-associated neuroinflammation. However, the characterization of bacteriota in human brains affected by AD remains inconclusive. This study aimed to investigate potential associations between specific bacteria and AD pathology by examining brain tissues from AD-associated neurodegenerative regions (frontal cortex and hippocampus) and the non-AD-associated hypothalamus. Employing 16S rRNA gene sequencing, 30 postmortem brain tissue samples from four individuals with normal brain histology (N) and four AD patients were analyzed, along with three blank controls. A remarkably low biomass characterized the brain bacteriota, with their overall structures delineated primarily by brain regions rather than the presence of AD. While most analyzed parameters exhibited no significant distinction in the brain bacteriota between the N and AD groups, the unique detection of Cloacibacterium normanense in the AD-associated neurodegenerative regions stood out. Additionally, infection-associated bacteria, as opposed to periodontal pathogens, were notably enriched in AD brains. This study's findings provide valuable insights into potential link between bacterial infection and neuroinflammation in AD.

Lower-Body Fractures and the Risk of Dementia: A Nationwide Population-Based Study.

BACKGROUND AND PURPOSE: The association between physical activity and dementia has been shown in various observational studies. We aimed to determine the risk of dementia in the elderly with lower-body fractures. METHODS: We reconstructed a population-based matched cohort from the National Health Insurance Service-Senior Cohort data set that covers 511,953 recipients of medical insurance in South Korea. RESULTS: Overall 53,776 subjects with lower-body fractures were identified during 2006-2012, and triplicate control groups were matched randomly by sex, age, and years from the index date for each subject with a fracture. There were 3,573 subjects (6.6%) with and 7,987 subjects (4.9%) without lower-body fractures who developed dementia from 2008 up to 2015. Lower-body fractures were independently associated with a subsequent dementia diagnosis with a higher adjusted hazard ratio (aHR) (1.55, 95% confidence interval [CI]=1.49-1.62) compared with upper-body fractures (aHR=1.19, 95% CI=1.14-1.23). CONCLUSIONS: These results support the protective role of physical activity against dementia and highlight the importance of promoting fracture prevention in the elderly.

Influence of Sensory Impairments on Incidence of Dementia in the Korean Population.

OBJECTIVE: Previous studies have shown the influence of visual and auditory sensory impairment on dementia incidence. In this study, we tested the hypothesis that the incidence of dementia will increase with visual and auditory impairments than with visual or auditory impairment. METHODS: Data from the Korea National Health Insurance Service database were used, including disease and medication codes from 2009 to 2018, and the 2011 national health check-up results. Participants were grouped based on their sensory abilities: normal, visual impairment, auditory impairment, and both visual and auditory impairments (dual sensory impairment). To compare the incidence of dementia, hazard ratios were calculated for each group, with reference to the normal sensory (NS) group. Sensitivity analyses were performed comparing dementia incidence from 2014 to 2018, excluding the onset of the disease in 2012 and 2013. RESULTS: We identified 8,289 cases of dementia during the seven-year follow-up. In the multiple Cox regression analysis, adjusted for sex, social economic status, age, comorbidities, smoking, alcohol consumption, and activity level, the auditory impairment (hazard ratio= 1.1908) and visual impairment (hazard ratio=1.3553) groups showed a significantly higher dementia incidence than the NS group. Dual sensory impairment (hazard ratio=1.5267) showed the highest incidence. The sensitivity analysis yielded similar results. CONCLUSION: Visual and auditory impairments are associated with an increased risk of dementia, particularly in individuals with dual sensory impairment. Hence, visual and auditory impairments might have increased the risk of dementia through independent pathological processes. Therefore, preventing and correcting sensory impairment is necessary to reduce the risk of dementia.

Dementia Incidence Rate Before and After Implementing the National Responsibility Policy for Dementia Care in Patients With Vascular Risk Factors in Korea.

Background and Purpose: The National Responsibility Policy for Dementia Care was implemented in September 2017 in Korea. This study aimed to compare dementia incidence in Seoul and Gangwon-do before and after the implementation of this policy. Methods: We extracted insurance claim data from the Korean Health Insurance Review and Assessment Service for people diagnosed with diabetes, hypertension, or dyslipidemia for the first time in Seoul and Gangwon-do, Korea. We defined two enrollment groups based on the policy implementation date: 1) January 1, 2015 to December 31, 2016 (Index 1, pre-implementation), and 2) January 1, 2017 to December 31, 2018 (Index 2, post-implementation). Each group was followed up for 1 year from the time of enrollment. Then, we calculated hazard ratios to compare the incidence of dementia between the two groups, and between Seoul and Gangwon-do. Results: In Seoul, the incidence of dementia was significantly lower in Index 2 than in Index 1 (hazard ratio [HR], 0.926; 95% confidence interval [CI], 0.875-0.979). However, the incidence rate did not differ between the 2 groups (HR, 1.113; 95% CI, 0.966-1.281) in Gangwon-do. In Index 1, the incidence of dementia did not differ between Seoul and Gangwon-do (HR, 1.043; 95% CI, 0.941-1.156), but in Index 2, was significantly higher in Gangwon-do than in Seoul (HR, 1.240; 95% CI, 1.109-1.386). Conclusions: After implementing the National Responsibility Policy for Dementia Care, the dementia incidence rate decreased significantly in Seoul, consistent with other studies, but not in Gangwon-do.

Deep learning application for the classification of Alzheimer's disease using 18F-flortaucipir (AV-1451) tau positron emission tomography.

The positron emission tomography (PET) with 18F-flortaucipir can distinguish individuals with mild cognitive impairment (MCI) and Alzheimer's disease (AD) from cognitively unimpaired (CU) individuals. This study aimed to evaluate the utility of 18F-flortaucipir-PET images and multimodal data integration in the differentiation of CU from MCI or AD through DL. We used cross-sectional data (18F-flortaucipir-PET images, demographic and neuropsychological score) from the ADNI. All data for subjects (138 CU, 75 MCI, 63 AD) were acquired at baseline. The 2D convolutional neural network (CNN)-long short-term memory (LSTM) and 3D CNN were conducted. Multimodal learning was conducted by adding the clinical data with imaging data. Transfer learning was performed for classification between CU and MCI. The AUC for AD classification from CU was 0.964 and 0.947 in 2D CNN-LSTM and multimodal learning. The AUC of 3D CNN showed 0.947, and 0.976 in multimodal learning. The AUC for MCI classification from CU had 0.840 and 0.923 in 2D CNN-LSTM and multimodal learning. The AUC of 3D CNN showed 0.845, and 0.850 in multimodal learning. The 18F-flortaucipir PET is effective for the classification of AD stage. Furthermore, the effect of combination images with clinical data increased the performance of AD classification.

Machine learning application for classification of Alzheimer's disease stages using 18F-flortaucipir positron emission tomography.

BACKGROUND: The progression of Alzheimer's dementia (AD) can be classified into three stages: cognitive unimpairment (CU), mild cognitive impairment (MCI), and AD. The purpose of this study was to implement a machine learning (ML) framework for AD stage classification using the standard uptake value ratio (SUVR) extracted from 18F-flortaucipir positron emission tomography (PET) images. We demonstrate the utility of tau SUVR for AD stage classification. We used clinical variables (age, sex, education, mini-mental state examination scores) and SUVR extracted from PET images scanned at baseline. Four types of ML frameworks, such as logistic regression, support vector machine (SVM), extreme gradient boosting, and multilayer perceptron (MLP), were used and explained by Shapley Additive Explanations (SHAP) to classify the AD stage. RESULTS: Of a total of 199 participants, 74, 69, and 56 patients were in the CU, MCI, and AD groups, respectively; their mean age was 71.5 years, and 106 (53.3%) were men. In the classification between CU and AD, the effect of clinical and tau SUVR was high in all classification tasks and all models had a mean area under the receiver operating characteristic curve (AUC) > 0.96. In the classification between MCI and AD, the independent effect of tau SUVR in SVM had an AUC of 0.88 (p < 0.05), which was the highest compared to other models. In the classification between MCI and CU, the AUC of each classification model was higher with tau SUVR variables than with clinical variables independently, which yielded an AUC of 0.75(p < 0.05) in MLP, which was the highest. As an explanation by SHAP for the classification between MCI and CU, and AD and CU, the amygdala and entorhinal cortex greatly affected the classification results. In the classification between MCI and AD, the para-hippocampal and temporal cortex affected model performance. Especially entorhinal cortex and amygdala showed a higher effect on model performance than all clinical variables in the classification between MCI and CU. CONCLUSIONS: The independent effect of tau deposition indicates that it is an effective biomarker in classifying CU and MCI into clinical stages using MLP. It is also very effective in classifying AD stages using SVM with clinical information that can be easily obtained at clinical screening.

Clinical outcomes of increased focal amyloid uptake in individuals with subthreshold global amyloid levels.

Background: Although the standardized uptake value ratio (SUVR) method is objective and simple, cut-off optimization using global SUVR values may not reflect focal increased uptake in the cerebrum. The present study investigated clinical and neuroimaging characteristics according to focally increased ß-amyloid (Aß) uptake and global Aß status. Methods: We recruited 968 participants with cognitive continuum. All participants underwent neuropsychological tests and 498 18F-florbetaben (FBB) amyloid positron emission tomography (PET) and 470 18F-flutemetamol (FMM) PET. Each PET scan was assessed in 10 regions (left and right frontal, lateral temporal, parietal, cingulate, and striatum) with focal-quantitative SUVR-based cutoff values for each region by using an iterative outlier approach. Results: A total of 62 (6.4%) subjects showed increased focal Aß uptake with subthreshold global Aß status [global (-) and focal (+) Aß group, G(-)F(+) group]. The G(-)F(+) group showed worse performance in memory impairment (p < 0.001), global cognition (p = 0.009), greater hippocampal atrophy (p = 0.045), compared to those in the G(-)F(-). Participants with widespread Aß involvement in the whole region [G(+)] showed worse neuropsychological (p < 0.001) and neuroimaging features (p < 0.001) than those with focal Aß involvement G(-)F(+). Conclusion: Our findings suggest that individuals show distinctive clinical outcomes according to focally increased Aß uptake and global Aß status. Thus, researchers and clinicians should pay more attention to focal increased Aß uptake in addition to global Aß status.

Transferability of Alzheimer Disease Polygenic Risk Score Across Populations and Its Association With Alzheimer Disease-Related Phenotypes.

Importance: Polygenic risk scores (PRSs), which aggregate the genetic effects of single-nucleotide variants identified in genome-wide association studies (GWASs), can help distinguish individuals at a high genetic risk for Alzheimer disease (AD). However, genetic studies have predominantly focused on populations of European ancestry. Objective: To evaluate the transferability of a PRS for AD in the Korean population using summary statistics from a prior GWAS of European populations. Design, Setting, and Participants: This cohort study developed a PRS based on the summary statistics of a large-scale GWAS of a European population (the International Genomics of Alzheimer Project; 21 982 AD cases and 41 944 controls). This PRS was tested for an association with AD dementia and its related phenotypes in 1634 Korean individuals, who were recruited from 2013 to 2019. The association of a PRS based on a GWAS of a Japanese population (the National Center for Geriatrics and Gerontology; 3962 AD cases and 4074 controls) and a transancestry meta-analysis of European and Japanese GWASs was also evaluated. Data were analyzed from December 2020 to June 2021. Main Outcomes and Measures: Risk of AD dementia, amnestic mild cognitive impairment (aMCI), earlier symptom onset, and amyloid ß deposition (Aß). Results: A total of 1634 Korean patients (969 women [59.3%]), including 716 individuals (43.6%) with AD dementia, 222 (13.6%) with aMCI, and 699 (42.8%) cognitively unimpaired controls, were analyzed in this study. The mean (SD) age of the participants was 71.6 (9.0) years. Higher PRS was associated with a higher risk of AD dementia independent of APOE ɛ4 status in the Korean population (OR, 1.95; 95% CI, 1.40-2.72; P < .001). Furthermore, PRS was associated with aMCI, earlier symptom onset, and Aß deposition independent of APOE ɛ4 status. The PRS based on a transancestry meta-analysis of data sets comprising 2 distinct ancestries showed a slightly improved accuracy. Conclusions and Relevance: In this cohort study, a PRS derived from a European GWAS identified individuals at a high risk for AD dementia in the Korean population. These findings emphasize the transancestry transferability and clinical value of PRSs and suggest the importance of enriching diversity in genetic studies of AD.

Improving Medication Adherence in Isolated Patients With Cognitive Impairment Using Automated Telephone Reminders.

Background and Purpose: Medication adherence is essential for effective medical treatment. However, it is challenging for cognitively impaired patients. We investigated whether an automated telephone reminder service improves medication adherence and reduces the decline of cognitive function in isolated patients with cognitive impairment. Methods: This was a single-center, randomized clinical trial. We enrolled mild cognitive impairment (MCI) or Alzheimer's disease (AD) patients who lived alone or with a cognitively impaired spouse. We provided an automated telephone reminder service for taking medication to the intervention group for 6 months. The control group was provided with general guidelines for taking the medication every month. The participants underwent neuropsychological assessment at the beginning and end of the study. Statistical significance was tested using nonparametric Wilcoxon rank sum and Wilcoxon matched-pairs signed-rank tests. Results: Thirty participants were allocated randomly to groups, and data for 29 participants were analyzed. The mean age was 79.6 (standard deviation, 6.0) years and 79.3% of the participants were female. There was no significant difference in medication adherence between the 2 groups. However, a subgroup analysis among participants with more than 70% response rates showed better medication adherence compared to the control group (intervention: 94.6%; control: 90.2%, p=0.0478). There was no significant difference in the change in cognitive function between the 2 groups. Conclusions: If a patient's compliance is good, telephone reminders might be effective in improving medication adherence. It is necessary to develop reminder tools that can improve compliance for cognitively impaired patients.

Predicting progression to dementia with "comprehensive visual rating scale" and machine learning algorithms.

Background and Objective: Identifying biomarkers for predicting progression to dementia in patients with mild cognitive impairment (MCI) is crucial. To this end, the comprehensive visual rating scale (CVRS), which is based on magnetic resonance imaging (MRI), was developed for the assessment of structural changes in the brains of patients with MCI. This study aimed to investigate the use of the CVRS score for predicting dementia in patients with MCI over a 2-year follow-up period using various machine learning (ML) algorithms. Methods: We included 197 patients with MCI who were followed up more than once. The data used for this study were obtained from the Japanese-Alzheimer's Disease Neuroimaging Initiative study. We assessed all the patients using their CVRS scores, cortical thickness data, and clinical data to determine their progression to dementia during a follow-up period of over 2 years. ML algorithms, such as logistic regression, random forest (RF), XGBoost, and LightGBM, were applied to the combination of the dataset. Further, feature importance that contributed to the progression from MCI to dementia was analyzed to confirm the risk predictors among the various variables evaluated. Results: Of the 197 patients, 108 (54.8%) showed progression from MCI to dementia. Tree-based classifiers, such as XGBoost, LightGBM, and RF, achieved relatively high performance. In addition, the prediction models showed better performance when clinical data and CVRS score (accuracy 0.701-0.711) were used than when clinical data and cortical thickness (accuracy 0.650-0.685) were used. The features related to CVRS helped predict progression to dementia using the tree-based models compared to logistic regression. Conclusions: Tree-based ML algorithms can predict progression from MCI to dementia using baseline CVRS scores combined with clinical data.

Machine learning-based automatic estimation of cortical atrophy using brain computed tomography images.

Cortical atrophy is measured clinically according to established visual rating scales based on magnetic resonance imaging (MRI). Although brain MRI is the primary imaging marker for neurodegeneration, computed tomography (CT) is also widely used for the early detection and diagnosis of dementia. However, they are seldom investigated. Therefore, we developed a machine learning algorithm for the automatic estimation of cortical atrophy on brain CT. Brain CT images (259 Alzheimer's dementia and 55 cognitively normal subjects) were visually rated by three neurologists and used for training. We constructed an algorithm by combining the convolutional neural network and regularized logistic regression (RLR). Model performance was then compared with that of neurologists, and feature importance was measured. RLR provided fast and reliable automatic estimations of frontal atrophy (75.2% accuracy, 93.6% sensitivity, 67.2% specificity, and 0.87 area under the curve [AUC]), posterior atrophy (79.6% accuracy, 87.2% sensitivity, 75.9% specificity, and 0.88 AUC), right medial temporal atrophy (81.2% accuracy, 84.7% sensitivity, 79.6% specificity, and 0.88 AUC), and left medial temporal atrophy (77.7% accuracy, 91.1% sensitivity, 72.3% specificity, and 0.90 AUC). We concluded that RLR-based automatic estimation of brain CT provided a comprehensive rating of atrophy that can potentially support physicians in real clinical settings.

Association between Baseline Cognitive Function and Longitudinal Functional Outcome Change after Ischemic Stroke.

INTRODUCTION: Ischemic stroke can cause impairment of daily function and cognitive function. Higher cognitive function is reported in many studies to be associated with better functional outcomes; however, evidence from longitudinal study is lacking. Therefore, in the present study, the association between cognitive function and longitudinal changes of functional outcome was investigated based on stroke severity. Furthermore, whether the effect of cognitive function remained consistent after controlling for depression was investigated. METHODS: The data of 423 stroke patients (292 minor strokes, 93 moderate strokes, and 38 severe strokes) were collected. Baseline Mini-Mental State Examination (MMSE) score was considered a predictor, and change of modified Rankin Scale (mRS) score during 12 months of follow-up was the outcome. First, the association between the baseline MMSE score and longitudinal change in the mRS score was analyzed using linear mixed-effects models. Fixed effects were MMSE score group, time, and MMSE score group × time interaction. Additional adjustment was made for the Geriatric Depression Scale (GDS) score. RESULTS: Among the 423 subjects, the mean age was 73.5 years, and 43.4% were female. In the minor stroke group, the high MMSE score group had a decreased mRS score, and the low MMSE score group had an increased mRS score (p < 0.001). This association remained after additional adjustment of the GDS score. Association was not observed between cognitive function and functional recovery in the moderate or severe stroke group. CONCLUSION: After ischemic stroke, higher baseline global cognitive function was a predictive factor for better functional recovery regardless of depression symptoms in the minor stroke group.

Analysis of treatment pattern of anti-dementia medications in newly diagnosed Alzheimer's dementia using OMOP CDM.

Anti-dementia medications are widely prescribed to patients with Alzheimer's dementia (AD) in South Korea. This study investigated the pattern of medical management in newly diagnosed patients with AD using a standardized data format-the Observational Medical Outcome Partnership Common Data Model from five hospitals. We examined the anti-dementia treatment patterns from datasets that comprise > 5 million patients during 2009-2019. The medication utility information was analyzed with respect to treatment trends and persistence across 11 years. Among the 8653 patients with newly diagnosed AD, donepezil was the most commonly prescribed anti-dementia medication (4218; 48.75%), followed by memantine (1565; 18.09%), rivastigmine (1777; 8.98%), and galantamine (494; 5.71%). The rising prescription trend during observation period was found only with donepezil. The treatment pathways for the three cholinesterase inhibitors combined with N-methyl-D-aspartate receptor antagonist were different according to the drugs (19.6%; donepezil; 28.1%; rivastigmine, and 17.2%; galantamine). A 12-month persistence analysis showed values of approximately 50% for donepezil and memantine and approximately 40% for rivastigmine and galantamine. There were differences in the prescribing pattern and persistence among anti-dementia medications from database using the Observational Medical Outcome Partnership Common Data Model on the Federated E-health Big Data for Evidence Renovation Network platform in Korea.

Distinctive Mediating Effects of Subcortical Structure Changes on the Relationships Between Amyloid or Vascular Changes and Cognitive Decline.

Objective: We investigated the mediation effects of subcortical volume change in the relationship of amyloid beta (Aß) and lacune with cognitive function in patients with mild cognitive impairment (MCI). Methods: We prospectively recruited 101 patients with MCI who were followed up with neuropsychological tests, MRI, or Pittsburgh compound B (PiB) PET for 3 years. The mediation effect of subcortical structure on the association of PiB or lacunes with cognitive function was analyzed using mixed effects models. Results: Volume changes in the amygdala and hippocampus partially mediated the effect of PiB changes on memory function (direct effect = -0.168/-0.175, indirect effect = -0.081/-0.077 for amygdala/hippocampus) and completely mediated the effect of PiB changes on clinical dementia rating scale sum of the box (CDR-SOB) (indirect effect = 0.082/0.116 for amygdala/hippocampus). Volume changes in the thalamus completely mediated the effect of lacune on memory, frontal executive functions, and CDR-SOB (indirect effect = -0.037, -0.056, and 0.047, respectively). Conclusions: Our findings provide a better understanding of the distinct role of subcortical structures in the mediation of the relationships of amyloid or vascular changes with a decline in specific cognitive domains.

Effect of education on functional network edge efficiency in Alzheimer's disease.

We investigated the effect of education on the edge efficiency in resting state functional networks (RSFNs) in amnestic mild cognitive impairment (aMCI) and Alzheimer's disease dementia (ADD). We collected the data of 57 early aMCI, 141 late aMCI, 173 mild ADD, and 39 moderate-to-severe ADD patients. We used years of education as a proxy for cognitive reserve. We measured edge efficiency for each edge in RSFNs, and performed simple slope analyses to discover their associations with education level among the four groups. In the late aMCI, a sub-network that had hub nodes in the right middle frontal gyrus and the right posterior cingulate gyrus, showed a positive association between RSFN edge efficiency and education (threshold = 2.5, p = 0.0478). There was no negative effect of education on the RSFN edge efficiency. In the early aMCI, mild ADD, and moderate-to-severe ADD, there were no sub-networks showing positive or negative correlation between education and RSFN edge efficiency. There was a positive effect of higher education on RSFN edge efficiency in the late aMCI, but not in the early aMCI or ADD. This indicates that in late aMCI, those who have higher education level have greater ability to resist collapsed functional network.

The Impact of Amyloid-ß or Tau on Cognitive Change in the Presence of Severe Cerebrovascular Disease.

BACKGROUND: As Alzheimer's disease (AD) and cerebral small vessel disease (CSVD) commonly coexist, the interaction between two has been of the considerable interest. OBJECTIVE: We determined whether the association of Aß and tau with cognitive decline differs by the presence of significant CSVD. METHODS: We included 60 subcortical vascular cognitive impairment (SVCI) from Samsung Medical Center and 82 Alzheimer's disease-related cognitive impairment (ADCI) from ADNI, who underwent Aß (florbetaben or florbetapir) and tau (flortaucipir, FTP) PET imaging. They were retrospectively assessed for 5.0±3.9 and 5.6±1.9 years with Clinical Dementia Rating-sum of boxes (CDR-SB)/Mini-Mental State Examination (MMSE). Mixed effects models were used to investigate the interaction between Aß/tau and group on CDR-SB/MMSE changes. RESULTS: The frequency of Aß positivity (45% versus 54.9%, p = 0.556) and mean global FTP SUVR (1.17±0.21 versus 1.16±0.17, p = 0.702) were not different between the two groups. We found a significant interaction effect of Aß positivity and SVCI group on CDR-SB increase/MMSE decrease (p = 0.013/p < 0.001), and a significant interaction effect of global FTP uptake and SVCI group on CDR-SB increase/MMSE decrease (p < 0.001 and p = 0.030). Finally, the interaction effects of regional tau and group were prominent in the Braak III/IV (p = 0.001) and V/VI (p = 0.003) not in Braak I/II region (p = 0.398). CONCLUSION: The association between Aß/tau and cognitive decline is stronger in SVCI than in ADCI. Therefore, our findings suggested that Aß positivity or tau burden (particularly in the Braak III/IV or V/VI regions) and CSVD might synergistically affect cognitive decline.

Disease progression modeling of Alzheimer's disease according to education level.

To develop a disease progression model of Alzheimer's disease (AD) that shows cognitive decline from subjective cognitive impairments (SCI) to the end stage of AD dementia (ADD) and to investigate the effect of education level on the whole disease spectrum, we enrolled 565 patients who were followed up more than three times and had a clinical dementia rating sum of boxes (CDR-SB). Three cohorts, SCI (n = 85), amnestic mild cognitive impairment (AMCI, n = 240), and ADD (n = 240), were overlapped in two consecutive cohorts (SCI and AMCI, AMCI and ADD) to construct a model of disease course, and a model with multiple single-cohorts was estimated using a mixed-effect model. To examine the effect of education level on disease progression, the disease progression model was developed with data from lower (≤ 12) and higher (> 12) education groups. Disease progression takes 274.3 months (22.9 years) to advance from 0 to 18 points using the CDR-SB. Based on our predictive equation, it takes 116.5 months to progress from SCI to AMCI and 56.2 months to progress from AMCI to ADD. The rate of CDR-SB progression was different according to education level. The lower-education group showed faster CDR-SB progression from SCI to AMCI compared to the higher-education group, and this trend disappeared from AMCI to ADD. In the present study, we developed a disease progression model of AD spectrum from SCI to the end stage of ADD. Our disease modeling provides us with more understanding of the effect of education on cognitive trajectories.

Depressive symptoms are associated with worse cognitive prognosis in patients with newly diagnosed idiopathic Parkinson disease.

BACKGROUND: Although depression is very common in patients with Parkinson disease (PD), only a few studies have investigated the longitudinal effects of initial depression on cognitive decline in these patients. The purpose of this study was to investigate the effect of depression on cognitive functions in patients with PD. METHODS: We used data from the Parkinson Progression Markers Initiative (PPMI) to investigate the relationship between depression and PD. Depressive symptoms were measured in patients with PD based on the Geriatric Depression Scale (GDS) or Neuropsychiatric Inventory-Questionnaire (NPI-Q) scores obtained at baseline. We evaluated cognitive decline as whether a patient with PD progressed to PD with mild cognitive impairment (MCI) during a 4-year follow-up period. Multivariate Cox regression analysis was done to know whether depression can predict the conversion to MCI. In addition, a voxel-based morphometric analysis using volumetric brain magnetic resonance imaging was used to compare structural changes related to future cognitive decline as well as to reveal longitudinal effect of baseline depression on cortical atrophy. RESULTS: Data from 263 patients with cognitively normal de novo PD who were available for longitudinal cognitive testing were analysed. The multivariate Cox regression analysis revealed that the depressive symptoms were independent risk factors for conversion to MCI in patients with de novo PD after adjusting for covariates (hazards ratio (95% CI)) of depression defined by the GDS (1.753 (1.084-2.835)) and the NPI (1.815 (1.083-3.042)) scores, respectively. The significant structural changes in PD with MCI as well as longitudinal effect of baseline depression on subsequent cortical atrophy were found in multiple areas on the voxel-based morphometric analysis (P < 0.001, family-wise error rate corrected). CONCLUSIONS: Our study indicates that the presence of depressive symptoms in patients with early PD is associated with a higher risk of progression to MCI and early depression may reflect subsequent cortical atrophy.

Small vessel disease more than Alzheimer's disease determines diffusion MRI alterations in memory clinic patients.

INTRODUCTION: Microstructural alterations as assessed by diffusion tensor imaging (DTI) are key findings in both Alzheimer's disease (AD) and small vessel disease (SVD). We determined the contribution of each of these conditions to diffusion alterations. METHODS: We studied six samples (N = 365 participants) covering the spectrum of AD and SVD, including genetically defined samples. We calculated diffusion measures from DTI and free water imaging. Simple linear, multivariable random forest, and voxel-based regressions were used to evaluate associations between AD biomarkers (amyloid beta, tau), SVD imaging markers, and diffusion measures. RESULTS: SVD markers were strongly associated with diffusion measures and showed a higher contribution than AD biomarkers in multivariable analysis across all memory clinic samples. Voxel-wise analyses between tau and diffusion measures were not significant. DISCUSSION: In memory clinic patients, the effect of SVD on diffusion alterations largely exceeds the effect of AD, supporting the value of diffusion measures as markers of SVD.