Ethnic differences in the effects of apolipoprotein E ɛ4 and vascular risk factors on accelerated brain aging.

The frequency of the apolipoprotein E ɛ4 allele and vascular risk factors differs among ethnic groups. We aimed to assess the combined effects of apolipoprotein E ɛ4 and vascular risk factors on brain age in Korean and UK cognitively unimpaired populations. We also aimed to determine the differences in the combined effects between the two populations. We enrolled 2314 cognitively unimpaired individuals aged ≥45 years from Korea and 6942 cognitively unimpaired individuals from the UK, who were matched using propensity scores. Brain age was defined using the brain age index. The apolipoprotein E genotype (ɛ4 carriers, ɛ2 carriers and ɛ3/ɛ3 homozygotes) and vascular risk factors (age, hypertension and diabetes) were considered predictors. Apolipoprotein E ɛ4 carriers in the Korean (ß = 0.511, P = 0.012) and UK (ß = 0.302, P = 0.006) groups had higher brain age index values. The adverse effects of the apolipoprotein E genotype on brain age index values increased with age in the Korean group alone (ɛ2 carriers × age, ß = 0.085, P = 0.009; ɛ4 carriers × age, ß = 0.100, P < 0.001). The apolipoprotein E genotype, age and ethnicity showed a three-way interaction with the brain age index (ɛ2 carriers × age × ethnicity, ß = 0.091, P = 0.022; ɛ4 carriers × age × ethnicity, ß = 0.093, P = 0.003). The effects of apolipoprotein E on the brain age index values were more pronounced in individuals with hypertension in the Korean group alone (ɛ4 carriers × hypertension, ß = 0.777, P = 0.038). The apolipoprotein E genotype, age and ethnicity showed a three-way interaction with the brain age index (ɛ4 carriers × hypertension × ethnicity, ß=1.091, P = 0.014). We highlight the ethnic differences in the combined effects of the apolipoprotein E ɛ4 genotype and vascular risk factors on accelerated brain age. These findings emphasize the need for ethnicity-specific strategies to mitigate apolipoprotein E ɛ4-related brain aging in cognitively unimpaired individuals.

Distinct effects of blood pressure parameters on Alzheimer's and vascular markers in 1,952 Asian individuals without dementia.

BACKGROUND: Risk factors for cardiovascular disease, including elevated blood pressure, are known to increase risk of Alzheimer's disease. There has been increasing awareness of the relationship between long-term blood pressure (BP) patterns and their effects on the brain. We aimed to investigate the association of repeated BP measurements with Alzheimer's and vascular disease markers. METHODS: We recruited 1,952 participants without dementia between August 2015 and February 2022. During serial clinic visits, we assessed both systolic BP (SBP) and diastolic BP (DBP), and visit-to-visit BP variability (BPV) was quantified from repeated measurements. In order to investigate the relationship of mean SBP (or DBP) with Alzheimer's and vascular markers and cognition, we performed multiple linear and logistic regression analyses after controlling for potential confounders (Model 1). Next, we investigated the relationship of with variation of SBP (or DBP) with the aforementioned variables by adding it into Model 1 (Model 2). In addition, mediation analyses were conducted to determine mediation effects of Alzheimer's and vascular makers on the relationship between BP parameters and cognitive impairment. RESULTS: High Aß uptake was associated with greater mean SBP (ß = 1.049, 95% confidence interval 1.016-1.083). High vascular burden was positively associated with mean SBP (odds ratio = 1.293, 95% CI 1.015-1.647) and mean DBP (1.390, 1.098-1.757). High tau uptake was related to greater systolic BPV (0.094, 0.001-0.187) and diastolic BPV (0.096, 0.007-0.184). High Aß uptake partially mediated the relationship between mean SBP and the Mini-Mental State Examination (MMSE) scores. Hippocampal atrophy mediated the relationship between diastolic BPV and MMSE scores. CONCLUSIONS: Each BP parameter affects Alzheimer's and vascular disease markers differently, which in turn leads to cognitive impairment. Therefore, it is necessary to appropriately control specific BP parameters to prevent the development of dementia. Furthermore, a better understanding of pathways from specific BP parameters to cognitive impairments might enable us to select the managements targeting the specific BP parameters to prevent dementia effectively.

A Two-Year Observational Study to Evaluate Conversion Rates from High- and Low-Risk Patients with Amnestic Mild Cognitive Impairment to Probable Alzheimer's Disease in a Real-World Setting.

Background: Predicting conversion to probable Alzheimer&s disease (AD) from amnestic mild cognitive impairment (aMCI) is difficult but important. A nomogram was developed previously for determining the risk of 3-year probable AD conversion in aMCI. Objective: To compare the probable AD conversion rates with cognitive and neurodegenerative changes for 2 years from high- and low risk aMCI groups classified using the nomogram. Methods: This prospective, multicenter, observational study was conducted in Korea. A total of patients were classified as high- or low-risk aMCI according to the nomogram and followed-up for 2 years to compare the annual conversion rate to probable AD and brain structure changes between the two groups. Results: In total, 176 (high-risk, 85; low-risk, 91) and 160 (high-risk, 77; low-risk, 83) patients completed the 1-year and 2-year follow-up, respectively. The probable AD conversion rate was significantly higher in the high-risk (Year 1, 28.9%; Year 2, 46.1%) versus low-risk group (Year 1, 0.0%; Year 2, 4.9%, both p < 0.0001). Mean changes from baseline in Seoul Neuropsychological Screening Battery-Dementia Version, Clinical Dementia Rating-Sum of Box, and Korean version of the Instrumental Activities of Daily Living scores and cortical atrophy index at Years 1 and 2 were significantly greater in the high-risk group (p < 0.0001). Conclusions: The high-risk aMCI group, as determined by the nomogram, had a higher conversion rate to probable AD and faster cognitive decline and neurodegeneration change than the low-risk group. These real-world results have clinical implications that help clinicians in accurately predicting patient outcomes and facilitating early decision-making.Trial Registration: ClinicalTrials.gov (NCT03448445).

Effectiveness of Personalized Hippocampal Network-Targeted Stimulation in Alzheimer Disease: A Randomized Clinical Trial.

Importance: Repetitive transcranial magnetic stimulation (rTMS) has emerged as a safe and promising intervention for Alzheimer disease (AD). Objective: To investigate the effect of a 4-week personalized hippocampal network-targeted rTMS on cognitive and functional performance, as well as functional connectivity in AD. Design, Setting, and Participants: This randomized clinical trial, which was sham-controlled and masked to participants and evaluators, was conducted between May 2020 and April 2022 at a single Korean memory clinic. Eligible participants were between ages 55 and 90 years and had confirmed early AD with evidence of an amyloid biomarker. Participants who met the inclusion criteria were randomly assigned to receive hippocampal network-targeted rTMS or sham stimulation. Participants received 4-week rTMS treatment, with assessment conducted at weeks 4 and 8. Data were analyzed between April 2022 and January 2024. Interventions: Each patient received 20 sessions of personalized rTMS targeting the left parietal area, functionally connected to the hippocampus, based on fMRI connectivity analysis over 4 weeks. The sham group underwent the same procedure, excluding actual magnetic stimulation. A personalized 3-dimensional printed frame to fix the TMS coil to the optimal target site was produced. Main Outcomes and Measures: The primary outcome was the change in the AD Assessment Scale-Cognitive Subscale test (ADAS-Cog) after 8 weeks from baseline. Secondary outcomes included changes in the Clinical Dementia Rating-Sum of Boxes (CDR-SOB) and Seoul-Instrumental Activity Daily Living (S-IADL) scales, as well as resting-state fMRI connectivity between the hippocampus and cortical areas. Results: Among 30 participants (18 in the rTMS group; 12 in the sham group) who completed the 8-week trial, the mean (SD) age was 69.8 (9.1) years; 18 (60%) were female. As the primary outcome, the change in ADAS-Cog at the eighth week was significantly different between the rTMS and sham groups (coefficient [SE], -5.2 [1.6]; P = .002). The change in CDR-SOB (-4.5 [1.4]; P = .007) and S-IADL (1.7 [0.7]; P = .004) were significantly different between the groups favoring rTMS groups. The fMRI connectivity analysis revealed that rTMS increased the functional connectivity between the hippocampus and precuneus, with its changes associated with improvements in ADAS-Cog (r = -0.57; P = .005). Conclusions and Relevance: This randomized clinical trial demonstrated the positive effects of rTMS on cognitive and functional performance, and the plastic changes in the hippocampal-cortical network. Our results support the consideration of rTMS as a potential treatment for AD. Trial Registration: ClinicalTrials.gov Identifier: NCT04260724.

Deep learning model for individualized trajectory prediction of clinical outcomes in mild cognitive impairment.

Objectives: Accurately predicting when patients with mild cognitive impairment (MCI) will progress to dementia is a formidable challenge. This work aims to develop a predictive deep learning model to accurately predict future cognitive decline and magnetic resonance imaging (MRI) marker changes over time at the individual level for patients with MCI. Methods: We recruited 657 amnestic patients with MCI from the Samsung Medical Center who underwent cognitive tests, brain MRI scans, and amyloid-ß (Aß) positron emission tomography (PET) scans. We devised a novel deep learning architecture by leveraging an attention mechanism in a recurrent neural network. We trained a predictive model by inputting age, gender, education, apolipoprotein E genotype, neuropsychological test scores, and brain MRI and amyloid PET features. Cognitive outcomes and MRI features of an MCI subject were predicted using the proposed network. Results: The proposed predictive model demonstrated good prediction performance (AUC = 0.814 ± 0.035) in five-fold cross-validation, along with reliable prediction in cognitive decline and MRI markers over time. Faster cognitive decline and brain atrophy in larger regions were forecasted in patients with Aß (+) than with Aß (-). Conclusion: The proposed method provides effective and accurate means for predicting the progression of individuals within a specific period. This model could assist clinicians in identifying subjects at a higher risk of rapid cognitive decline by predicting future cognitive decline and MRI marker changes over time for patients with MCI. Future studies should validate and refine the proposed predictive model further to improve clinical decision-making.

Prediction of Amyloid Positivity in Patients with Subcortical Vascular Cognitive Impairment.

Background: Amyloid-ß (Aß) commonly coexists and impacts prognosis in subcortical vascular cognitive impairment (SVCI). Objective: This study aimed to examine the differences in clinical and neuroimaging variables between Aß-positive and Aß-negative SVCI and to propose a prediction model for Aß positivity in clinically diagnosed SVCI patients. Methods: A total of 130 patients with SVCI were included in model development, and a separate cohort of 70 SVCI patients was used in external validation. The variables for the prediction model were selected by comparing the characteristics of the Aß-negative and Aß-positive SVCI groups. The final model was determined using a stepwise method. The model performance was evaluated using the receiver operating characteristic (ROC) curve and a calibration curve. A nomogram was used for visualization. Results: Among 130 SVCI patients, 70 (53.8%) were Aß-positive. The Aß-positive SVCI group was characterized by older age, tendency to be in the dementia stage, a higher prevalence of APOEɛ4, a lower prevalence of lacune, and more severe medial temporal atrophy (MTA). The final prediction model, which excluded MTA grade following the stepwise method for variable selection, demonstrated good accuracy in distinguishing between Aß-positive and Aß-negative SVCI, with an area under the curve (AUC) of 0.80. The external validation demonstrated an AUC of 0.71. Conclusions: The findings suggest that older age, dementia stage, APOEɛ4 carrier, and absence of lacunes may be predictive of Aß positivity in clinically diagnosed SVCI patients.

Effects of risk factors on the development and mortality of early- and late-onset dementia: an 11-year longitudinal nationwide population-based cohort study in South Korea.

BACKGROUND: Early-onset dementia (EOD, onset age < 65) and late-onset dementia (LOD, onset age ≥ 65) exhibit distinct features. Understanding the risk factors for dementia development and mortality in EOD and LOD respectively is crucial for personalized care. While risk factors are known for LOD development and mortality, their impact on EOD remains unclear. We aimed to investigate how hypertension, diabetes mellitus, hyperlipidemia, atrial fibrillation, and osteoporosis influence the development and mortality of EOD and LOD, respectively. METHODS: Using the Korean National Health Insurance Service (NHIS) database, we collected 546,709 dementia-free individuals and followed up for 11 years. In the two study groups, the Younger group (< 65 years old) and the Older group (≥ 65 years old), we applied Cox proportional hazard models to assess risk factors for development of EOD and LOD, respectively. Then, we assessed risk factors for mortality among EOD and LOD. RESULTS: Diabetes mellitus and osteoporosis increased the risk of EOD and LOD development. Hypertension increased the risk of EOD, while atrial fibrillation increased the risk of LOD. Conversely, hyperlipidemia exhibited a protective effect against LOD development. Additionally, diabetes mellitus increased mortality in EOD and LOD. Hypertension and atrial fibrillation increased mortality in LOD, while hyperlipidemia decreased mortality in EOD and LOD. CONCLUSIONS: Risk factors influencing dementia development and mortality differed in EOD and LOD. Targeted public health interventions addressing age-related risk factors may reduce dementia incidence and mortality.

Alterations of Structural Network Efficiency in Early-Onset and Late-Onset Alzheimer's Disease.

BACKGROUND AND PURPOSE: Early- and late-onset Alzheimer's disease (EOAD and LOAD, respectively) share the same neuropathological hallmarks of amyloid and neurofibrillary tangles but have distinct cognitive features. We compared structural brain connectivity between the EOAD and LOAD groups using structural network efficiency and evaluated the association of structural network efficiency with the cognitive profile and pathological markers of Alzheimer's disease (AD). METHODS: The structural brain connectivity networks of 80 AD patients (47 with EOAD and 33 with LOAD) and 57 healthy controls were reconstructed using diffusion-tensor imaging. Graph-theoretic indices were calculated and intergroup differences were evaluated. Correlations between network parameters and neuropsychological test results were analyzed. The correlations of the amyloid and tau burdens with network parameters were evaluated for the patients and controls. RESULTS: Compared with the age-matched control group, the EOAD patients had increased global path length and decreased global efficiency, averaged local efficiency, and averaged clustering coefficient. In contrast, no significant differences were found in the LOAD patients. Locally, the EOAD patients showed decreases in local efficiency and the clustering coefficient over a wide area compared with the control group, whereas LOAD patients showed such decreases only within a limited area. Changes in network parameters were significantly correlated with multiple cognitive domains in EOAD patients, but only with Clinical Dementia Rating Sum-of-Boxes scores in LOAD patients. Finally, the tau burden was correlated with changes in network parameters in AD signature areas in both patient groups, while there was no correlation with the amyloid burden. CONCLUSIONS: The impairment of structural network efficiency and its effects on cognition may differ between EOAD and LOAD.

Association of Glycemic Variability With Imaging Markers of Vascular Burden, ß-Amyloid, Brain Atrophy, and Cognitive Impairment.

BACKGROUND AND OBJECTIVE: We aimed to investigate the association between glycemic variability (GV) and neuroimaging markers of white matter hyperintensities (WMH), beta-amyloid (Aß), brain atrophy, and cognitive impairment. METHODS: This was a retrospective cohort study that included participants without dementia from a memory clinic. They all had Aß PET, brain MRI, and standardized neuropsychological tests and had fasting glucose (FG) levels tested more than twice during the study period. We defined GV as the intraindividual visit-to-visit variability in FG levels. Multivariable linear regression and logistic regression were used to identify whether GV was associated with the presence of severe WMH and Aß uptake with DM, mean FG levels, age, sex, hypertension, and presence of APOE4 allele as covariates. Mediation analyses were used to investigate the mediating effect of WMH and Aß uptake on the relationship between GV and brain atrophy and cognition. RESULTS: Among the 688 participants, the mean age was 72.2 years, and the proportion of female participants was 51.9%. Increase in GV was predictive of the presence of severe WMH (coefficient [95% CI] 1.032 [1.012-1.054]; p = 0.002) and increased Aß uptake (1.005 [1.001-1.008]; p = 0.007). Both WMH and increased Aß uptake partially mediated the relationship between GV and frontal-executive dysfunction (GV → WMH → frontal-executive; direct effect, -0.319 [-0.557 to -0.080]; indirect effect, -0.050 [-0.091 to -0.008]) and memory dysfunction (GV → Aß â†’ memory; direct effect, -0.182 [-0.338 to -0.026]; indirect effect, -0.067 [-0.119 to -0.015]), respectively. In addition, increased Aß uptake completely mediated the relationship between GV and hippocampal volume (indirect effect, -1.091 [-2.078 to -0.103]) and partially mediated the relationship between GV and parietal thickness (direct effect, -0.00101 [-0.00185 to -0.00016]; indirect effect, -0.00016 [-0.00032 to -0.000002]). DISCUSSION: Our findings suggest that increased GV is related to vascular and Alzheimer risk factors and neurodegenerative markers, which in turn leads to subsequent cognitive impairment. Furthermore, GV can be considered a potentially modifiable risk factor for dementia prevention.

Enhancing foveal avascular zone analysis for Alzheimer's diagnosis with AI segmentation and machine learning using multiple radiomic features.

We propose a hybrid technique that employs artificial intelligence (AI)-based segmentation and machine learning classification using multiple features extracted from the foveal avascular zone (FAZ)-a retinal biomarker for Alzheimer's disease-to improve the disease diagnostic performance. Imaging data of optical coherence tomography angiography from 37 patients with Alzheimer's disease and 48 healthy controls were investigated. The presence or absence of brain amyloids was confirmed using amyloid positron emission tomography. In the superficial capillary plexus of the angiography scans, the FAZ was automatically segmented using an AI method to extract multiple biomarkers (area, solidity, compactness, roundness, and eccentricity), which were paired with clinical data (age and sex) as common correction variables. We used a light-gradient boosting machine (a light-gradient boosting machine is a machine learning algorithm based on trees utilizing gradient boosting) to diagnose Alzheimer's disease by integrating the corresponding multiple radiomic biomarkers. Fivefold cross-validation was applied for analysis, and the diagnostic performance for Alzheimer's disease was determined by the area under the curve. The proposed hybrid technique achieved an area under the curve of [Formula: see text]%, outperforming the existing single-feature (area) criteria by over 13%. Furthermore, in the holdout test set, the proposed technique exhibited a 14% improvement compared to single features, achieving an area under the curve of 72.0± 4.8%. Based on these facts, we have demonstrated the effectiveness of our technology in achieving significant performance improvements in FAZ-based Alzheimer's diagnosis research through the use of multiple radiomic biomarkers (area, solidity, compactness, roundness, and eccentricity).

Effects of workbook training using editorials and newspaper articles in adults with preclinical stage of dementia.

Early detection and intervention in individuals in the pre-clinical stage of dementia are crucial. This study aimed to examine whether there are significant differences in (1) word retrieval, (2) subjective communication ability, (3) intervention satisfaction through the 'Fill-in-the-blanks in editorial and newspaper articles' training in patients with subjective cognitive decline and mild cognitive impairment corresponding to the pre-clinical stage of dementia. Ninety-nine patients (50 in the intervention group and 49 in the control group) aged 50-84 years were administered pre- and post-test after 6 weeks of intervention (30 sessions). Regarding word retrieval, there were significant intervention effects on confrontation naming, semantic fluency, and phonemic fluency. The majority of participants in the intervention group were highly satisfied with the training. In terms of intervention satisfaction, the majority of the participants in the intervention group showed high satisfaction with all the questions. This result confirmed the improvement of word retrieval ability through mass communication content-based 'Fill-in-the-blanks' training, and ultimately helps to provide a clinical basis for applying this intervention to prevent dementia.

Clinical and Pathological Validation of CT-Based Regional Harmonization Methods of Amyloid PET.

PURPOSE: The CT-based regional direct comparison Centiloid (dcCL) method was developed to harmonize and quantify regional ß-amyloid (Aß) burden. In the present study, we aimed to investigate correlations between the CT-based regional dcCL scales and Aß pathological burdens and to validate the clinical utility using thresholds derived from pathological assessment. PATIENTS AND METHODS: We included a pathological cohort of 63 cases and a clinical cohort of 4062 participants, and obtained modified Consortium to Establish a Registry for Alzheimer's Disease criteria (mCERAD) scores by assessment of neuritic plaque burdens in multiple areas of each cortical region. PET and CT images were processed using the CT-based regional dcCL method to calculate scales in 6 distinct regions. RESULTS: The CT-based regional dcCL scales were correlated with neuritic plaque burdens represented by mCERAD scores, globally and regionally ( r = 0.56~0.76). In addition, striatum dcCL scales reflected Aß involvement in the striatum ( P < 0.001). The regional dcCL scales could predict significant Aß deposition in specific brain regions with high accuracy: area under the receiver operating characteristic curve of 0.81-0.97 with an mCERAD cutoff of 1.5 and area under the receiver operating characteristic curve of 0.88-0.93 with an mCERAD cutoff of 0.5. When applying the dcCL thresholds of 1.5 mCERAD scores, the G(-)R(+) group showed lower performances in memory and global cognitive functions and had less hippocampal volume compared with the G(-)R(-) group ( P < 0.001). However, when applying the dcCL thresholds of 0.5 mCERAD scores, there were no differences in the global cognitive functions between the 2 groups. CONCLUSIONS: The thresholds of regional dcCL scales derived from pathological assessments might provide clinicians with a better understanding of biomarker-guided diagnosis and distinguishable clinical phenotypes, which are particularly useful when harmonizing different PET ligands with only PET/CT.

Development and preliminary validation of a virtual reality memory test for assessing visuospatial memory.

Background: Visuospatial memory impairment is a common symptom of Alzheimer's disease; however, conventional visuospatial memory tests are insufficient to fully reflect visuospatial memory impairment in daily life. Methods: To address patients' difficulties in locating and recalling misplaced objects, we introduced a novel visuospatial memory test, the Hidden Objects Test (HOT), conducted in a virtual environment. We categorized HOT scores into prospective memory, item free-recall, place free-recall, item recognition, and place-item matching scores. To validate the VR memory test, we compared HOT scores among individuals with Alzheimer's disease (AD), amnestic mild cognitive impairment (aMCI), and normal controls (NC), and also compared these scores with those of conventional neuropsychological tests. We tracked the participants' movement paths in the virtual environment and assessed basic features, such as total distance, duration, and speed. Additionally, we performed walking trajectory pattern mining such as outlier and stay-point detection. Results: We designed and implemented the HOT to simulate a house's living room and assess participants' ability to locate hidden objects. Our preliminary results showed that the total HOT score differed among 17 patients with AD, 14 with aMCI, and 15 NC (p < 0.001). The total HOT score correlated positively with conventional memory test scores (p < 0.001). Walking trajectories showed that patients with AD and aMCI wandered rather than going straight to the hidden objects. In terms of basic features, the total duration was significantly greater in AD than in NC (p = 0.008). In terms of trajectory pattern mining, the number of outliers, which were over 95% of the estimated trajectory, was significantly higher in AD than in NC (p = 0.002). The number of stay points, an index in which participants stayed in the same position for more than 2 s, was significantly higher in patients with AD and aMCI compared with NC (AD vs. NC: p = 0.003, aMCI vs. NC: p = 0.019). Conclusion: The HOT simulating real life showed potential as an ecologically valid test for assessing visuospatial memory function in daily life. Walking trajectory analysis suggested that patients with AD and aMCI wandered rather than going straight toward the hidden objects.

Efficacy of smartphone application-based multi-domain cognitive training in older adults without dementia.

Background: As the population ages and the prevalence of dementia increases, there is a growing emphasis on the importance of cognitive training to prevent dementia. A smartphone application-based cognitive training software program, BeauBrain Trainer (BBT), has been developed to provide better access to cognitive training for older adults. Numerous studies have revealed the effectiveness of cognitive training using a cognitive assessment tool. However, relatively few studies have evaluated brain activation using brain imaging as a result of improved cognitive function. Methods: All participants were required to download the BBT, an Android-based application for cognitive training, onto their own smartphone or tablet computer and to engage in cognitive training at home. Older adults without dementia were enrolled in this study, including 51 participants in the intervention group and 50 participants in the control group. The BBT comprised a set of 12 cognitive tasks, including two tasks in each of the following six cognitive domains: attention, language, calculation, visuospatial function, memory, and frontal/executive function. Each cognitive task was divided into four blocks based on its level of difficulty. A 16-week cognitive training was designed to carry out cognitive tasks using a total of 48 blocks (12 tasks × 4 levels) for at least 1.5 h per day, 5 days per week. All participants in the intervention group were given BBT tasks that gradually increased in difficulty level, which they submitted through a smartphone application daily for 16 weeks. The researchers monitored the participants' task performance records on the website and encouraged participants to engage in cognitive training through regular contact. This study was conducted to investigate the improvement in cognitive function and the activation pattern of the frontal cortex in older adults participating in smartphone application-based cognitive training. The cognitive assessment tool was the BeauBrain cognitive screening test (CST), a tablet-based computerized cognitive screening test. The activation pattern of the frontal cortex was measured using functional near-infrared spectroscopy (fNIRS). Additionally, this study aimed to determine the positive effects of cognitive training on everyday functioning and psychological states using a questionnaire. Results: Of 101 participants, 85 older adults without dementia (84.1%) who completed the study protocol were included in the statistical analysis. There were 41 participants (80.3%) in the intervention group and 44 participants (88.0%) in the control group. A two-way repeated-measures analysis of variance (ANOVA) was used to compare the cognitive scores over a 16-week period between the intervention and control groups. According to the CST results, the intervention group exhibited a statistically significant increase in the language subtest scores, specifically the phonemic word fluency test, compared to those of the control group. The fNIRS results revealed greater activation in the dorsolateral prefrontal cortex during the STROOP incongruent task in the intervention group than did the control group. However, the effectiveness of cognitive training was not observed across a variety of rating scales, including everyday functioning, depression, self-efficacy, attention, and subjective memory complaints. Conclusion: This study revealed that a smartphone-based cognitive training application led to improvements in phonemic generative naming ability and activation of the prefrontal cortex in older adults without dementia. This study is meaningful because it confirmed that cognitive training is partially effective in enhancing frontal lobe function. It also provided information on the brain mechanisms related to the effects of cognitive training using fNIRS.

Distinct effects of cholesterol profile components on amyloid and vascular burdens.

BACKGROUND: Cholesterol plays important roles in ß-amyloid (Aß) metabolism and atherosclerosis. However, the relationships of plasma cholesterol levels with Aß and cerebral small vessel disease (CSVD) burdens are not fully understood in Asians. Herein, we investigated the relationships between plasma cholesterol profile components and Aß and CSVD burdens in a large, non-demented Korean cohort. METHODS: We enrolled 1,175 non-demented participants (456 with unimpaired cognition [CU] and 719 with mild cognitive impairment [MCI]) aged ≥ 45 years who underwent Aß PET at the Samsung Medical Center in Korea. We performed linear regression analyses with each cholesterol (low-density lipoprotein cholesterol [LDL-c], high-density lipoprotein cholesterol [HDL-c], and triglyceride) level as a predictor and each image marker (Aß uptake on PET, white matter hyperintensity [WMH] volume, and hippocampal volume) as an outcome after controlling for potential confounders. RESULTS: Increased LDL-c levels (ß = 0.014 to 0.115, p = 0.013) were associated with greater Aß uptake, independent of the APOE e4 allele genotype and lipid-lowering medication. Decreased HDL-c levels (ß = - 0.133 to - 0.006, p = 0.032) were predictive of higher WMH volumes. Increased LDL-c levels were also associated with decreased hippocampal volume (direct effect ß = - 0.053, p = 0.040), which was partially mediated by Aß uptake (indirect effect ß = - 0.018, p = 0.006). CONCLUSIONS: Our findings highlight that increased LDL-c and decreased HDL-c levels are important risk factors for Aß and CSVD burdens, respectively. Furthermore, considering that plasma cholesterol profile components are potentially modified by diet, exercise, and pharmacological agents, our results provide evidence that regulating LDL-c and HDL-c levels is a potential strategy to prevent dementia.

Sex-specific relationship between non-alcoholic fatty liver disease and amyloid-ß in cognitively unimpaired individuals.

Background: Non-alcoholic fatty liver disease (NAFLD) is known to be associated with a high risk of clinically diagnosed Alzheimer's disease (AD). Additionally, the prevalence of NAFLD and AD is higher in elderly females than in males. However, a sex-specific association between NAFLD and amyloid-beta (Aß) deposition remains unclear. Therefore, we investigated the sex-specific relationship between NAFLD and Aß deposition in a large-sized cohort of cognitively unimpaired (CU) individuals. Methods: We enrolled 673 (410 [60.9%] females and 263 [39.1%] males) CU individuals aged ≥45 years who underwent Aß positron emission tomography (PET). The presence of NAFLD, assessed using the hepatic steatosis index, and the severity of NAFLD, assessed using the Fibrosis-4 index, were considered predictors. Aß deposition on PET was considered as an outcome. Results: Females had a higher frequency of NAFLD than males (48 and 23.2%, p < 0.001). Among females, the presence of NAFLD (ß = 0.216, p < 0.001) was predictive of increased Aß deposition, whereas among males, the presence of NAFLD (ß = 0.191, p = 0.064) was not associated with Aß deposition. Among females, the presence of NAFLD with low (ß = 0.254, p = 0.039), intermediate (ß = 0.201, p = 0.006), and high fibrosis (ß = 0.257, p = 0.027) was predictive of increased Aß deposition. Aß deposition also increased as the severity of NAFLD increased in females (p for trend = 0.001). Conclusion: We highlight the marked influence of NAFLD and its severity on the risk of Aß deposition in relation to sex. Furthermore, our findings suggest that sex-specific strategies regarding the management of NAFLD are necessary for the prevention of Aß deposition.

Linguistic, visuospatial, and kinematic writing characteristics in cognitively impaired patients with beta-amyloid deposition.

Introduction: Beta-amyloid (Aß) deposition, a hallmark of Alzheimer's disease (AD), begins before dementia and is an important factor in mild cognitive impairment (MCI). Aß deposition is a recognized risk factor for various cognitive impairments and has been reported to affect motor performance as well. This study aimed to identify the linguistic, visuospatial, and kinematic characteristics evident in the writing performance of patients with cognitive impairment (CI) who exhibit Aß deposition. Methods: A total of 31 patients diagnosed with amnestic mild cognitive impairment (aMCI) with Aß deposition, 26 patients with Alzheimer's-type dementia, and 33 healthy control (HC) participants without deposition were administered tasks involving dictation of 60 regular words, irregular words, and non-words consisting of 1-4 syllables. Responses from all participants were collected and analyzed through digitized writing tests and analysis tools. Results: In terms of linguistic aspects, as cognitive decline progressed, performance in the dictation of irregular words decreased, with errors observed in substituting the target grapheme with other graphemes. The aMCI group frequently exhibited corrective aspects involving letter rewriting during the task. In terms of visuospatial aspects, the AD group displayed more errors in grapheme combination compared to the HC group. Lastly, in the kinematic aspects, both the aMCI group and the AD group exhibited slower writing speeds compared to the HC group. Discussion: The findings suggest that individuals in the CI group exhibited lower performance in word dictation tasks than those in the HC group, and these results possibly indicate complex cognitive-language-motor deficits resulting from temporal-parietal lobe damage, particularly affecting spelling processing. These results provide valuable clinical insights into understanding linguistic-visuospatial-kinematic aspects that contribute to the early diagnosis of CI with Aß deposition.

Emerging role of vascular burden in AT(N) classification in individuals with Alzheimer's and concomitant cerebrovascular burdens.

OBJECTIVES: Alzheimer's disease (AD) is characterised by amyloid-beta accumulation (A), tau aggregation (T) and neurodegeneration (N). Vascular (V) burden has been found concomitantly with AD pathology and has synergistic effects on cognitive decline with AD biomarkers. We determined whether cognitive trajectories of AT(N) categories differed according to vascular (V) burden. METHODS: We prospectively recruited 205 participants and classified them into groups based on the AT(N) system using neuroimaging markers. Abnormal V markers were identified based on the presence of severe white matter hyperintensities. RESULTS: In A+ category, compared with the frequency of Alzheimer's pathological change category (A+T-), the frequency of AD category (A+T+) was significantly lower in V+ group (31.8%) than in V- group (64.4%) (p=0.004). Each AT(N) biomarker was predictive of cognitive decline in the V+ group as well as in the V- group (p<0.001). Additionally, the V+ group showed more severe cognitive trajectories than the V- group in the non-Alzheimer's pathological changes (A-T+, A-N+; p=0.002) and Alzheimer's pathological changes (p<0.001) categories. CONCLUSION: The distribution and longitudinal outcomes of AT(N) system differed according to vascular burdens, suggesting the importance of incorporating a V biomarker into the AT(N) system.

Identification of potential biomarkers related to mesenchymal stem cell response in patients with Alzheimer's disease.

BACKGROUND: Preclinical studies showed that mesenchymal stem cells (MSCs) ameliorate tau phosphorylation, amyloid-beta accumulation, and inflammation in Alzheimer's disease (AD) mouse models via secretion of neurotrophic factors and cytokines. We aimed to identify CSF biomarkers that can be used to predict or monitor the response to MSCs in patients with AD. METHODS: AD patients were injected with human umbilical cord blood-MSCs (n = 22) or placebo (n = 12). The cerebrospinal fluid (CSF) samples were collected at baseline, one day after the first injection, and one day after the third injection. The patients injected with MSCs were classified into good responder (GR) or poor responder (PR) groups based on the rate of changes in the ratio of total-tau and phosphorylated-tau in the CSF. We selected three typical participants in each group, and their CSF protein levels were analyzed using liquid chromatography/tandem mass spectrometry (LC-MS/MS). RESULTS: In the LC-MS/MS analysis, 1,667 proteins were identified. Eleven proteins showed significant differences between the typical GR and PR at baseline. Based on their significance level and known functions, two proteins, reticulocalbin-3 (RCN3) and follistatin-related protein 3 (FSTL3), were selected as potential biomarkers to predict MSC response. A total of 173 proteins showed significant change one day after the third injection compared to the baseline in typical GR. We excluded 45 proteins that showed significant change after the third injection compared to the baseline in the typical PR. Based on their significance level and known function, four proteins, scrapie-responsive protein 1 (SCRG1), neural proliferation differentiation and control protein (NPDC1), apolipoprotein E (ApoE), and cystatin C (CysC), were selected as potential biomarker to monitor MSC response. Additionally, functional analysis revealed that the increased CSF proteins after the third injection compared to the baseline in the typical GR were associated with synaptogenesis. CONCLUSIONS: This study identified two proteins (RCN3 and FSTL3) that may be potential biomarkers for predicting MSC response and four proteins (SCRG1, NPDC1, ApoE, CysC) that may be potential biomarkers for monitoring MSC response in patients with AD. Further studies are needed to validate our results. Trial registration Clinical Trials.gov, NCT02054208. Registered on 4 February 2014. Samsung Medical Center IRB File No.2017-04-025. Registered on 20 June 2017.

Dementia incidence and population-attributable fraction for dementia risk factors in Republic of Korea: a 12-year longitudinal follow-up study of a national cohort.

Background: We aimed to investigate the incidence of dementia by age and year as well as the population-attributable fractions (PAFs) for known dementia risk factors in Republic of Korea. Methods: A 12-year, nationwide, population-based, retrospective cohort study was conducted. We used customized health information from the National Health Insurance Service (NHIS) data from 2002 to 2017. We analyzed age- and sex-adjusted incidence rates and PAF of dementia for each risk factor such as depression, diabetes, hemorrhagic stroke, ischemic stroke, hypertension, osteoporosis and physical inactivity using Levin's formula. Results: Of the 794,448 subjects in the dementia-free cohort, 49,524 (6.2%) developed dementia. Dementia incidence showed annual growth from 1.56 per 1,000 person-years in 2006 to 6.94 per 1,000 person-years in 2017. Of all dementia cases, 34,544 subjects (69.8%) were female and 2,479 subjects (5.0%) were early onset dementia. AD dementia accounted for 66.5% of the total dementia incidence. Considering relative risk and prevalence, physical inactivity attributed the greatest to dementia (PAF, 8.1%), followed by diabetes (PAF, 4.2%), and hypertension (PAF, 2.9%). Altogether, the significant risk factors increased the risk of dementia by 18.0% (overall PAF). Conclusion: We provided the incidence of dementia and PAFs for dementia risk factors in Republic of Korea using a 12-year, nationwide cohort. Encouraging lifestyle modifications and more aggressive control of risk factors may effectively prevent dementia.