Discriminative Power of Seoul Cognitive Status Test in Differentiating Subjective Cognitive Decline, Amnestic Mild Cognitive Impairment, and Dementia Based on CERAD-K Standards.

Background and Purpose: We developed a new digital cognitive assessment called Seoul Cognitive Status Test (SCST), formerly called Inbrain Cognitive Screening Test. The purpose of this study was to validate the clinical utility of the SCST by comparing its scores of those with subjective cognitive decline (SCD), amnestic mild cognitive impairment (aMCI), and dementia diagnosed by the Korean version of the Consortium to Establish a Registry for Alzheimer's Disease Assessment Packet (CERAD-K). Methods: All participants (n=296) who completed the CERAD-K, SCST, and Instrumental Activities of Daily Living tests were included in this study. Total score, cognitive domain scores, and subtest scores of the SCST were compared among the 3 groups (SCD, aMCI, and dementia). Additionally, correlations between SCST and CERAD-K subtests were examined. Results: Cognitive domain scores and total score of the SCST showed significant differences among the three groups, with scores being the highest in the order of SCD, aMCI, and dementia (p<0.001). Most subtests of the SCST also showed higher scores in the order of SCD, aMCI, and dementia (p<0.001). However, SCD and aMCI groups showed no significant differences in scores of the Phonemic Word Fluency Test (p=0.083) or Korean Trail Making Test-Elderly version Part A (p=0.434). Additionally, there was no significant difference in the score of Place Recognition (p=0.274) of the Word-Place Association Test between aMCI and dementia groups. Conclusions: In conclusion, differences in total score, cognitive domain scores, and subtest scores of the SCST among the 3 groups of participants diagnosed using CERAD-K confirm the clinical utility of the SCST for cognitive assessment.

Air pollution and acute kidney injury with comorbid disease: A nationwide case-crossover study in South Korea.

Emerging evidence suggests that air pollution is a significant contributor to the global burden of kidney disease. Although acute kidney injury (AKI) is a common secondary event in ill patients, evidence regarding the association between air pollution and AKI accompanied by specific comorbidities is limited. This study aimed to estimate the association between short-term exposure to air pollution (fine particulate matter ≤2.5 µm [PM2.5] and ozone [O3]) and incident AKI by comorbid diseases using the Korea National Health Information Database (NHID). Total of 160,390 incident AKI cases, defined as an emergency department (ED) visit due to AKI, were observed within the period 2015-2021 in inland South Korea. A time-stratified case-crossover design was applied for PM2.5 and O3 individually, using a conditional logistic regression model within each case and its own control (three or four days of the same day of the week in the same month) to estimate the association between short-term air pollution exposure and ED visits due to AKI. Short-term exposure to PM2.5 and O3 was associated with ED visits due to AKI with ORs of 1.008 (95% confidence interval [CI]: 0.999, 1.017) and 1.019 (95% CI: 1.005, 1.033) for an interquartile range (IQR) increase in lag 0-1 day PM2.5 and O3 respectively, although OR for PM2.5 was marginally significant. The odds of incident AKI associated with PM2.5 was evident in conjunction with ischemic heart disease, cerebrovascular disease, gastrointestinal bleeding, and pneumonia. For O3, the estimated odds was prominent for AKI with ischemic heart disease. In addition, the comorbid disease-specific odds of AKI attributed to air pollution varied by sex and age. Our findings provide epidemiological evidence of a plausible mechanism between air pollution and incident AKI and suggest the need for personalized AKI prevention strategies attributed to air pollution.

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.

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.

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.

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.

Distinct spatiotemporal patterns of cortical thinning in Alzheimer's disease-type cognitive impairment and subcortical vascular cognitive impairment.

Previous studies on Alzheimer's disease-type cognitive impairment (ADCI) and subcortical vascular cognitive impairment (SVCI) has rarely explored spatiotemporal heterogeneity. This study aims to identify distinct spatiotemporal cortical atrophy patterns in ADCI and SVCI. 1,338 participants (713 ADCI, 208 SVCI, and 417 cognitively unimpaired elders) underwent brain magnetic resonance imaging (MRI), amyloid positron emission tomography, and neuropsychological tests. Using MRI, this study measures cortical thickness in five brain regions (medial temporal, inferior temporal, posterior medial parietal, lateral parietal, and frontal areas) and utilizes the Subtype and Stage Inference (SuStaIn) model to predict the most probable subtype and stage for each participant. SuStaIn identifies two distinct cortical thinning patterns in ADCI (medial temporal: 65.8%, diffuse: 34.2%) and SVCI (frontotemporal: 47.1%, parietal: 52.9%) patients. The medial temporal subtype of ADCI shows a faster decline in attention, visuospatial, visual memory, and frontal/executive domains than the diffuse subtype (p-value < 0.01). However, there are no significant differences in longitudinal cognitive outcomes between the two subtypes of SVCI. Our study provides valuable insights into the distinct spatiotemporal patterns of cortical thinning in patients with ADCI and SVCI, suggesting the potential for individualized therapeutic and preventive strategies to improve clinical outcomes.

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).

Shared genetic architectures of educational attainment in East Asian and European populations.

Educational attainment (EduYears), a heritable trait often used as a proxy for cognitive ability, is associated with various health and social outcomes. Previous genome-wide association studies (GWASs) on EduYears have been focused on samples of European (EUR) genetic ancestries. Here we present the first large-scale GWAS of EduYears in people of East Asian (EAS) ancestry (n = 176,400) and conduct a cross-ancestry meta-analysis with EduYears GWAS in people of EUR ancestry (n = 766,345). EduYears showed a high genetic correlation and power-adjusted transferability ratio between EAS and EUR. We also found similar functional enrichment, gene expression enrichment and cross-trait genetic correlations between two populations. Cross-ancestry fine-mapping identified refined credible sets with a higher posterior inclusion probability than single population fine-mapping. Polygenic prediction analysis in four independent EAS and EUR cohorts demonstrated transferability between populations. Our study supports the need for further research on diverse ancestries to increase our understanding of the genetic basis of educational attainment.

Association between long-term PM2.5 exposure and risk of Kawasaki disease in children: A nationwide longitudinal cohort study.

BACKGROUND: Based on previous studies suggesting air pollution as a potential risk factor for Kawasaki Disease (KD), we examined the association of long-term exposure to childhood fine particulate matter (PM2.5) with the risk of KD. METHODS: We used National Health Insurance Service-National Sample Cohort data from 2002 to 2019, which included beneficiaries aged 0 years at enrollment and followed-up until the onset of KD or age 5 years. The onset of KD was defined as the first hospital visit record with a primary diagnostic code of M30.3, based on the 10th revision of the International Classification of Diseases, and with an intravenous immunoglobulin (IVIG) prescription. We assigned PM2.5 concentrations to 226 districts, based on mean annual predictions from a machine learning-based ensemble prediction model. We performed Cox proportional-hazards modeling with time-varying exposures and confounders. RESULTS: We identified 134,634 individuals aged five or less at enrollment and, of these, 1220 individuals who had a KD onset and an IVIG prescription during study period. The average annual concentration of PM2.5 exposed to the entire cohort was 28.2 µg/m³ (Standard Deviation 2.9). For each 5 µg/m³ increase in annual PM2.5 concentration, the hazard ratio of KD was 1.21 (95% CI 1.05-1.39). CONCLUSIONS: In this nationwide, population-based, cohort study, long-term childhood exposure to PM2.5 was associated with an increased incidence of KD in children. The study highlights plausible mechanisms for the association between PM2.5 and KD, but further studies are needed to confirm our findings.

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.

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.