Executive Summary of 2023 International Conference of the Korean Dementia Association (IC-KDA 2023): A Report From the Academic Committee of the Korean Dementia Association.

The Korean Dementia Association (KDA) has been organizing biennial international academic conferences since 2019, with the International Conference of the KDA (IC-KDA) 2023 held in Busan under the theme 'Beyond Boundaries: Advancing Global Dementia Solutions.' The conference comprised 6 scientific sessions, 3 plenary lectures, and 4 luncheon symposiums, drawing 804 participants from 35 countries. Notably, a Korea-Taiwan Joint Symposium addressed insights into Alzheimer's disease (AD). Plenary lectures by renowned scholars explored topics such as microbiome-related AD pathogenesis, social cognition in neurodegenerative diseases, and genetic frontotemporal dementia (FTD). On the first day, specific presentations covered subjects like the gut-brain axis and neuroinflammation in dementia, blood-based biomarkers in AD, and updates in AD therapeutics. The second day's presentations addressed recent issues in clinical neuropsychology, FTD cohort studies, and the pathogenesis of non-AD dementia. The Academic Committee of the KDA compiles lecture summaries to provide comprehensive understanding of the advanced dementia knowledge presented at IC-KDA 2023.

Alterations in Gut Microbiota and Their Correlation with Brain Beta-Amyloid Burden Measured by 18F-Florbetaben PET in Mild Cognitive Impairment Due to Alzheimer's Disease.

(1) Background: This study investigated changes in the gut microbial composition of individuals with mild cognitive impairment (MCI) due to Alzheimer's disease (AD) and their relationship with positron emission tomography (PET) amyloid accumulation. (2) Methods: In total, 17 cognitively normal individuals without amyloid-beta (Aß) accumulation (Aß-NC) and 24 with Aß-positive mild cognitive impairment (Aß+MCI) who underwent 18F-florbetaben PET and fecal bacterial 16S ribosomal RNA gene sequencing were enrolled. The taxonomic compositions of the Aß-NC and Aß+MCI groups were compared. The abundance of taxa was correlated with the standardized uptake value ratio (SUVR), using generalized linear models. (3) Results: There were significant differences in microbiome richness (ACE, p = 0.034 and Chao1, p = 0.024), alpha diversity (Shannon, p = 0.039), and beta diversity (Bray-Curtis, p = 0.018 and Generalized UniFrac, p = 0.034) between the Aß-NC and Aß+MCI groups. The global SUVR was positively correlated with the genus Intestinibacter (q = 0.006) and negatively correlated with the genera Roseburia (q = 0.008) and Agathobaculum (q = 0.029). (4) Conclusions: In this study, we identified significant changes in the gut microbiota composition that occur in individuals with MCI due to AD. In particular, the correlation analysis results between PET amyloid burden and gut microbial abundance showed that amyloid deposition is associated with a reduction in specific taxa involved in butyrate production.

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.

Geriatric depression and anxiety screening via deep learning using activity tracking and sleep data.

BACKGROUND: Geriatric depression and anxiety have been identified as mood disorders commonly associated with the onset of dementia. Currently, the diagnosis of geriatric depression and anxiety relies on self-reported assessments for primary screening purposes, which is uncomfortable for older adults and can be prone to misreporting. When a more precise diagnosis is needed, additional methods such as in-depth interviews or functional magnetic resonance imaging are used. However, these methods can not only be time-consuming and costly but also require systematic and cost-effective approaches. OBJECTIVE: The main objective of this study was to investigate the feasibility of training an end-to-end deep learning (DL) model by directly inputting time-series activity tracking and sleep data obtained from consumer-grade wrist-worn activity trackers to identify comorbid depression and anxiety. METHODS: To enhance accuracy, the input of the DL model consisted of step counts and sleep stages as time series data, along with minimal depression and anxiety assessment scores as non-time-series data. The basic structure of the DL model was designed to process mixed-input data and perform multi-label-based classification for depression and anxiety. Various DL models, including the convolutional neural network (CNN) and long short-term memory (LSTM), were applied to process the time-series data, and model selection was conducted by comparing the performances of the hyperparameters. RESULTS: This study achieved significant results in the multi-label classification of depression and anxiety, with a Hamming loss score of 0.0946 in the Residual Network (ResNet), by applying a mixed-input DL model based on activity tracking data. The comparison of hyper-parameter performance and the development of various DL models, such as CNN, LSTM, and ResNet contributed to the optimization of time series data processing and achievement of meaningful results. CONCLUSIONS: This study can be considered as the first to develop a mixed-input DL model based on activity tracking data for the multi-label identification of late-life depression and anxiety. The findings of the study demonstrate the feasibility and potential of using consumer-grade wrist-worn activity trackers in conjunction with DL models to improve the identification of comorbid mental health conditions in older adults. The study also established a multi-label classification framework for identifying the complex symptoms of depression and anxiety.

Discourse-based verbal working memory training and transfer effects for individuals with an amnestic type of mild cognitive impairment.

PURPOSE: The purpose of the study was to investigate the treatment efficacy of a discourse-based working memory (WM) protocol for individuals with the amnestic type of mild cognitive impairment (MCI). METHOD: The current study employed a randomised, single-blind design. Fourteen individuals with MCI participated in the study (n = 7 treatment group and n = 7 control group). The treatment protocol consisted of 10 sessions two times per week, and treatment was individually administered only to the treatment group. A Wilcoxon signed-rank test was performed to verify pre-post comparisons within each group. Mann-Whitney nonparametric tests were conducted to confirm the differences between the treatment and control groups for the post-treatment scores. RESULT: The treatment group demonstrated a significant increase in story-retelling outcomes for both the treated stories and untreated novel stories compared to the control group. Furthermore, the treatment group presented transfer effects for WM span measures and controlled word association tasks. CONCLUSION: The results indicated that a discourse-based WM treatment protocol is efficacious for the amnestic type of mild cognitive impairment with the effects transferred to frontal lobe functions, as measured by WM tasks and semantic word fluency measures. Further studies are needed to track the trajectory of performance across sessions.

Effects of the multidomain intervention with nutritional supplements on cognition and gut microbiome in early symptomatic Alzheimer's disease: a randomized controlled trial.

Background: The SoUth Korean study to PrEvent cognitive impaiRment and protect BRAIN health through lifestyle intervention in at-risk elderly people (SUPERBRAIN) is a part of the World-Wide Finnish Geriatric Intervention Study to Prevent Cognitive Impairment and Disability (WW-FINGERS) network. This study aimed to demonstrate the effects of the SUPERBRAIN-based multidomain intervention with nutritional supplements in amyloid positive emission tomography (PET) proven early symptomatic Alzheimer's disease patients. Methods: Forty-six participants who were diagnosed with mild cognitive impairment or mild dementia and were positive in the amyloid PET study randomized into three groups: group A, the multidomain intervention with nutritional supplements; group B, nutritional supplements only; and a control group. The primary outcome was a change in the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) total scale index score after an 8-week intervention. Secondary outcomes, including gut microbiome data, were also analyzed. Results: The RBANS total scale index score improved significantly in group A compared with group B (p < 0.032) and compared with the control group (p < 0.001). After intervention, beta diversity of the gut microbiome between group A and the control group increased, and patients in group A were more enriched with Bifidobacterium. Conclusion: SUPERBRAIN-based multidomain intervention with nutritional supplements improves cognition and gut microbiota in patients with early symptomatic Alzheimer's disease who were amyloid-positive by PET.

Sex differences in the structural rich-club connectivity in patients with Alzheimer's disease.

Background and objectives: Alzheimer's disease (AD) is more prevalent in women than in men; however, there is a discrepancy in research on sex differences in AD. The human brain is a large-scale network with hub regions forming a central core, the rich-club, which is vital to cognitive functions. However, it is unknown whether alterations in the rich-clubs in AD differ between men and women. We aimed to investigate sex differences in the rich-club organization in the brains of patients with AD. Methods: In total, 260 cognitively unimpaired individuals with negative amyloid positron emission tomography (PET) scans, 281 with prodromal AD (mild cognitive impairment due to AD) and 285 with AD dementia who confirmed with positive amyloid PET scans participated in the study. We obtained high-resolution T1-weighted and diffusion tensor images and performed network analysis. Results: We observed sex differences in the rich-club and feeder connections in patients with AD, suggesting lower structural connectivity strength in women than in men. We observed a significant group-by-sex interaction in the feeder connections, particularly in the thalamus. In addition, the connectivity strength of the thalamus in the feeder connections was significantly correlated with general cognitive function in only men with prodromal AD and women with AD dementia. Conclusion: Our findings provide important evidence for sex-specific alterations in the structural brain network related to AD.

Identifying the acute toxicity of contaminated sediments using machine learning models.

Ecological risk assessment of contaminated sediment has become a fundamental component of water quality management programs, supporting decision-making for management actions or prompting additional investigations. In this study, we proposed a machine learning (ML)-based approach to assess the ecological risk of contaminated sediment as an alternative to existing index-based methods and costly toxicity testing. The performance of three widely used index-based methods (the pollution load index, potential ecological risk index, and mean probable effect concentration) and three ML algorithms (random forest, support vector machine, and extreme gradient boosting [XGB]) were compared in their prediction of sediment toxicity using 327 nationwide data sets from Korea consisting of 14 sediment quality parameters and sediment toxicity testing data. We also compared the performances of classifiers and regressors in predicting the toxicity for each of RF, SVM, and XGB algorithms. For all algorithms, the classifiers poorly classified toxic and non-toxic samples due to limited information on the sediment composition and the small training dataset. The regressors with a given classification threshold provided better classification, with the XGB regressor outperforming the other models in the classification. A permutation feature importance analysis revealed that Cr, Cu, Pb, and Zn were major contributors to toxicity prediction. The ML-based approach has the potential to be even more useful in the future with the expected increase in available sediment data.

Predictive Scale for Amyloid PET Positivity Based on Clinical and MRI Variables in Patients with Amnestic Mild Cognitive Impairment.

The presence of amyloid-ß (Aß) deposition is considered important in patients with amnestic mild cognitive impairment (aMCI), since they can progress to Alzheimer's disease dementia. Amyloid positron emission tomography (PET) has been used for detecting Aß deposition, but its high cost is a significant barrier for clinical usage. Therefore, we aimed to develop a new predictive scale for amyloid PET positivity using easily accessible tools. Overall, 161 aMCI patients were recruited from six memory clinics and underwent neuropsychological tests, brain magnetic resonance imaging (MRI), apolipoprotein E (APOE) genotype testing, and amyloid PET. Among the potential predictors, verbal and visual memory tests, medial temporal lobe atrophy, APOE genotype, and age showed significant differences between the Aß-positive and Aß-negative groups and were combined to make a model for predicting amyloid PET positivity with the area under the curve (AUC) of 0.856. Based on the best model, we developed the new predictive scale comprising integers, which had an optimal cutoff score ≥ 3. The new predictive scale was validated in another cohort of 98 participants and showed a good performance with AUC of 0.835. This new predictive scale with accessible variables may be useful for predicting Aß positivity in aMCI patients in clinical practice.

Executive Summary of the 2021 International Conference of Korean Dementia Association: A Report From the Academic Committee of the Korean Dementia Association.

Recently, aducanumab, a beta amyloid targeted immunotherapy, has been approved by the US Food and Drug Administration for the treatment of Alzheimer's dementia (AD). Although many questions need to be answered, this approval provides a promising hope for the development of AD drugs that could be supported by new biomarkers such as blood-based ones and composite neuropsychological tests that can confirm pathologic changes in early stages of AD. It is important to elucidate the complexity of AD which is known to be associated with other factors such as vascular etiologies and neuro-inflammation. Through the second international conference of the Korean Dementia Association (KDA), researchers from all over the world have participated in the exchange of opinions with KDA members on the most up-to-date topics. The Academic Committee of the KDA summarizes lectures to provide the depth of the conference as well as discussions. This will be an important milestone to widen the latest knowledge in the research of AD's diagnosis, therapeutics, pathogenesis that can lead to the establishment of future directions.

Association Between Body Mass Index and Cognitive Function in Mild Cognitive Impairment Regardless of APOE ε4 Status.

BACKGROUND AND PURPOSE: In this study we aimed to find the association between neuropsychological performance and body mass index (BMI) in patients with mild cognitive impairment (MCI). In addition, we investigated the effects of the apolipoprotein E (APOE) genotype in the relationship between the BMI and cognition in MCI. METHODS: We enrolled a cohort of 3,038 subjects with MCI aged 65-90 from the Clinical Research Center for Dementia of South Korea and a dementia cohort of the Ewha Womans University Mokdong Hospital. MCI patients were classified into three subgroups according to the Asian standard of BMI. We compared cognitive performances between groups by one-way analysis of variance. To investigate the effects of the APOE genotype, we used multivariate linear regression models after adjusting for possible confounders. RESULTS: Even though normal BMI groups were younger, had more females, and had less comorbidities, the higher BMI groups had better cognitive functions. Among subjects with APOE ε4 carriers, there was a positive relationship between the BMI and the memory task alone. CONCLUSIONS: Our findings suggested that higher BMI in patients with MCI were associated with better cognitive performance. The effects of the APOE ε4 genotype in the associations between BMI and cognition were distinguishing. Therefore, according to physical status, APOE ε4 genotype-specific strategies in the assessments and treatments may be necessary in elderly patients with MCI.

Predicting superagers by machine learning classification based on the functional brain connectome using resting-state functional magnetic resonance imaging.

Superagers are defined as older adults who have youthful memory performance comparable to that of middle-aged adults. Classifying superagers based on the brain connectome using machine learning modeling can provide important insights on the physiology underlying successful aging. We aimed to investigate the unique patterns of functional brain connectome of superagers and develop predictive models to differentiate superagers from typical agers based on machine learning methods. We obtained resting-state functional magnetic resonance imaging (rsfMRI) data and cognitive measures from 32 superagers and 58 typical agers. The accuracies of three machine learning methods including the linear support vector machine classifier (SV), the random forest classifier (RF), and the logistic regression classifier (LR) in predicting superagers were comparable (SV = 0.944, RF = 0.944, LR = 0.944); however, RF achieved the highest area under the curve (AUC; 0.979). An ensemble learning method combining the three classifiers achieved the highest AUC (0.986). The most discriminative nodes for predicting superagers encompassed areas in the precuneus; posterior cingulate gyrus; insular cortex; and superior, middle, and inferior frontal gyrus, which were located in default, salient, and multiple-demand networks. Thus, rsfMRI data can provide high accuracy for predicting superagers, thereby capturing and describing the unique characteristics of their functional brain connectome.

The Moderating Role of Sleep Quality on the Association between Neuroticism and Frontal Executive Function in Older Adults.

OBJECTIVE/BACKGROUND: Personality traits are regarded as risk factors for cognitive impairment in older adults, while sleep disturbance and physical inactivity are also considered as modifiable risk factors. Therefore, it could be beneficial to investigate the effects of those modifiable risk factors on the relationship between personality traits and cognitive functions, to prepare appropriate strategies for mitigating cognitive impairment. PARTICIPANTS: A total of 155 cognitively unimpaired older adults were included. METHODS: All participants underwent cognitive function tests using the Seoul Neuropsychological Screening Battery and examinations for personality traits using the Big Five Inventory. Individual physical activity and sleep quality were assessed using the International Physical Activity Questionnaire and Pittsburgh Sleep Quality Index, respectively. A hierarchical linear multiple regression analysis was performed to demonstrate the direct association between personality traits and cognitive functions, and the multiple moderator analysis was used to analyze the moderating effects of lifestyle factors on this association. RESULTS: Among the five personality traits, only neuroticism was negatively associated with the frontal executive and visuospatial functions after controlling age, sex, and years of education. Interestingly, the negative relationship between neuroticism and frontal executive function was alleviated in older adults with higher sleep quality. CONCLUSIONS: Our findings demonstrated that higher sleep quality has significant moderating effects on the negative association between neuroticism and frontal executive functions in older adults, which suggests intervention for improving sleep quality such as cognitive behavioral therapy can be considered in older adults who have personality traits associated with a high risk of cognitive impairment.

Older adults' experiences and perceptions of living with Bomy, an assistive dailycare robot: a qualitative study.

An aging global population and preference for aging-in-place pose the opportunity for home-based robots to assist older adults with their daily routines. However, there is limited research into the experiences of older adults using robots in their own homes. In this descriptive qualitative feasibility study, older self-supporting and community-dwelling adults with various age-related health needs used Bomy, a dailycare robot in their homes for up to one week. The study explored the usefulness of the robot and participants' perceptions and experiences of using it. Bomy reminded them of daily activities and delivered cognitive stimulation games. Semi-structured in-person interviews were conducted, and data were analyzed thematically. Findings revealed an acceptance toward robots and the value of assistive dailycare robots. Participants perceived Bomy as a companion and made suggestions for improvement, including resolving technical issues associated with long-term use. Future functions should be personalizable, to accommodate each user's health needs and could also include smoke detection and reading aloud functions. Dailycare robots show promising potential in elderly care, especially in providing reminders for medication, health and wellbeing. This study highlights the importance of co-design and testing robotics in the environments for which they have been developed. Widespread implementation of Bomy might be feasible in the future, with some further adjustments.

A Comparison of the Performance between the 60- and 120-Second Conditions of the Korean-Color Word Stroop Test: Color Reading (K-CWST: CR).

BACKGROUND AND PURPOSE: The Korean-Color Word Stroop Test: Color Reading (K-CWST: CR) included in the Seoul Neuropsychological Screening Battery, 2nd Edition (SNSB-II) examines inhibitory control deficit. It provides normative data for both 60- and 120-second conditions, but the validity of the 60-second condition has not yet been proven. This study examined the validity of the 60-second condition by observing concordance between the performances in cognitively normal, MCI, and mild dementia groups. METHODS: There were 1,336 patients performed the SNSB-II, including the K-CWST: CR. Based on the cognitive test results, activities of daily living, and clinical interview, the patients were assigned to normal cognition (n=104), MCI (n=884), or mild dementia (n=348) groups. Abnormal performance on the K-CWST: CR was operationally defined as 1SD below the normative mean. The receiver operating characteristic curve analyses were conducted to compare the discriminability between the 60- and 120-second conditions. RESULTS: The percentages of abnormal performance in the MCI group were 41.5% and 42.3%, and those in the mild dementia group were 82.7% and 82.4% for the 60- and 120-second conditions, respectively. The areas under the curve for the 60- and 120-seconds were as follows; 0.80 and 0.81 in differentiating normal from MCI; 0.95 and 0.96 in normal from mild dementia; and 0.77 and 0.77 in MCI from mild dementia. CONCLUSIONS: The 60-second condition of the K-CWST showed very similar results, not statistically different from the 120-second condition. Therefore, the 60-second condition could be used interchangeably with the 120-second condition in a clinical setting.

Aberrantly higher functional connectivity in the salience network is associated with transient global amnesia.

Triple intrinsic brain networks including the salience network (SN), default mode network (DMN), and central executive network (CEN), are known to be important in human cognition. Therefore, investigating those intrinsic brain networks in transient global amnesia (TGA) may offer novel insight useful for the pathophysiology of TGA. Fifty TGA patients underwent the resting state functional magnetic resonance imaging (rsfMRI) within 24 h, at 72 h, and 3 months after TGA onset. Twenty-five age, gender matched controls also underwent rsfMRI. Within 24 h of TGA onset, TGA patients showed greater functional connectivity in the SN and lower functional connectivity in the DMN, while relatively preserved functional connectivity was observed in the CEN. Interestingly, TGA patients continued to show decreased connectivity in the DMN, while no alterations were shown in the SN 72 h after illness onset. Three months after TGA onset, alterations of functional connectivity in the SN or the DMN were normalized. Our findings suggest that TGA is associated with transient greater functional connectivity in the SN and lower connectivity in the DMN.

Dual-phase 18F-florbetaben PET provides cerebral perfusion proxy along with beta-amyloid burden in Alzheimer's disease.

BACKGROUND: This study investigated changes in brain perfusion and Aß burden according to the progression of Alzheimer's disease (AD) by using a dual-phase 18F-florbetaben (FBB) PET protocol. METHODS: Sixty subjects, including 12 with Aß-negative normal cognition (Aß-NC), 32 with Aß-positive mild cognitive impairment (Aß+MCI), and 16 with Aß-positive AD (Aß+AD), were enrolled. A dynamic PET scan was obtained in the early phase (0-10 min, eFBB) and delayed phase (90-110 min, dFBB), which were then averaged into a single frame, respectively. In addition to the averaged eFBB, an R1 parametric map was calculated from the eFBB scan based on a simplified reference tissue model (SRTM). Between-group regional and voxel-wise analyses of the images were performed. The associations between cognitive profiles and PET-derived parameters were investigated. RESULTS: Both the R1 and eFBB perfusion reductions in the cortical regions were not significantly different between the Aß-NC and Aß+MCI groups, while they were significantly reduced from the Aß+MCI to Aß+AD groups in regional and voxel-wise analyses. However, cortical Aß depositions on dFBB were not significantly different between the Aß+MCI and Aß+AD groups. There were strong positive correlations between the R1 and eFBB images in regional and voxel-wise analyses. Both perfusion components showed significant correlations with general and specific cognitive profiles. CONCLUSION: The results of this study demonstrated the feasibility of dual-phase 18F-FBB PET to evaluate different trajectories of dual biomarkers for neurodegeneration and Aß burden over the course of AD. In addition, both eFBB and SRTM-based R1 can provide robust indices of brain perfusion.

Microbiota dysbiosis and functional outcome in acute ischemic stroke patients.

Currently, few studies are reported on the composition of microbiota in stroke patients and the association with stroke prognosis. This study investigated the differing microbiota composition in stroke patients and confirmed the association of microbiota composition with poor functional outcome. Between January of 2018 and December of 2019, 198 patients with acute cerebral infarction were included in this study. For the case-control study, age and sex-matched normal healthy subjects (n = 200) were included when receiving their health screening examinations. We isolated bacterial extracellular membrane vesicles and extracted DNA from blood samples. Taxonomic assignments were performed by using the sequence reads of 16S rRNA genes following blood microbiota analysis. Statistical analysis was conducted appropriately by using Statistical Analysis System software. The mean age of the stroke patients were 63.7 ± 12.5 years, and the male sex was 58.5%. Of the total enrolled patients, poor functional outcome (modified Rankin Score ≥ 3) was noted in 19.7%. The principal component analysis of microbiota composition revealed significant differences between healthy control subjects and stroke patients. At the genus level, Aerococcaceae(f), ZB2(c), TM7-1(c), and Flavobacterium were significantly increased in stroke patients compared to the healthy controls, whereas Mucispirillum, rc4-4, Akkermansia, Clostridiales(o), Lactobacillus, and Stenotrophomonas were decreased considerably. For the functional outcome after ischemic stroke, Anaerococcus, Blautia, Dialister, Aerococcaceae(f), Propionibacterium, Microbacteriaceae(f), and Rothia were enriched in the group with good outcomes, whereas Ruminococcaceae(f) and Prevotella were enriched in the group with poor outcome. There was apparent dysbiosis of blood microbiota in patients with acute ischemic stroke compared to healthy people. Ruminococcaceae(f) and Prevotella were elevated in stroke patients with poor functional outcome.

Asymmetric Amyloid Deposition as an Early Sign of Progression in Mild Cognitive Impairment Due to Alzheimer Disease.

PURPOSE: In typical Alzheimer disease with dementia (ADD), amyloid pathologies affect both cerebral hemispheres symmetrically. However, the spatial distribution of amyloid-ß (Aß) in the early stage of ADD or over the course of disease has not been investigated. Therefore, we explored asymmetric pattern of Aß deposition in both hemispheres according to the ADD continuum using 18F-florbetaben PET. METHODS: Sixty-eight subjects, including 15 Aß-negative normal controls, 28 Aß-positive mild cognitive impairment (Aß+ MCI), and 25 Aß-positive ADD (Aß+ ADD) subjects, were enrolled. Differences in the asymmetry index and SUV ratio in each of the 6 target regions (4 cortical lobes, cingulate, precuneus) plus composite region between groups were explored. RESULTS: The composite and target regional asymmetry indices were significantly different between groups and was highest in Aß+ MCI (composite, occipital, and temporal, P < 0.001; frontal, P = 0.004). The composite and target regional SUV ratios were significantly different according to 3 groups with gradual increase and were highest in Aß+ ADD (composite and all target regions, P < 0.001). CONCLUSIONS: The asymmetric pattern of amyloid deposition was distinct between Aß-negative normal controls and Aß+ MCI. This pattern disappeared as the disease progressed. These data indicate that asymmetric amyloid deposition may be an early sign of MCI over the course of ADD.