Hippocampal Perfusion Affects Motor and Cognitive Functions in Parkinson Disease: An Early Phase 18 F-FP-CIT Positron Emission Tomography Study.

OBJECTIVE: We investigated whether hippocampal perfusion changes are associated with cognitive decline, motor deficits, and the risk of dementia conversion in patients with Parkinson disease (PD). METHODS: We recruited patients with newly diagnosed and nonmedicated PD and healthy participants who underwent dual phase 18 F-N-(3-fluoropropyl)-2ß-carboxymethoxy-3ß-(4-iodophenyl) nortropane positron emission tomography scans. Patients were classified into 3 groups according to hippocampal perfusion measured by standard uptake value ratios (SUVRs): (1) PD hippocampal hypoperfusion group (1 standard deviation [SD] below the mean hippocampal SUVR of healthy controls; PD-hippo-hypo), (2) PD hippocampal hyperperfusion group (1 SD above the mean; PD-hippo-hyper), and (3) the remaining patients (PD-hippo-normal). We compared the baseline cognitive performance, severity of motor deficits, hippocampal volume, striatal dopamine transporter (DAT) availability, and risk of dementia conversion among the groups. RESULTS: We included 235 patients (PD-hippo-hypo, n = 21; PD-hippo-normal, n = 157; PD-hippo-hyper, n = 57) and 48 healthy participants. Patients in the PD-hippo-hypo group were older and had smaller hippocampal volumes than those in the other PD groups. The PD-hippo-hypo group showed less severely decreased DAT availability in the putamen than the other groups despite similar severities of motor deficit. The PD-hippo-hypo group had a higher risk of dementia conversion compared to the PD-hippo-normal (hazard ratio = 2.59, p = 0.013) and PD-hippo-hyper (hazard ratio = 3.73, p = 0.006) groups, despite similar cognitive performance at initial assessment between groups. INTERPRETATION: Hippocampal hypoperfusion may indicate a reduced capacity to cope with neurodegenerative processes in terms of the development of motor deficits and cognitive decline in patients with PD. ANN NEUROL 2024;95:388-399.

Difference in trajectories according to early amyloid accumulation in cognitively unimpaired elderly.

BACKGROUND AND PURPOSE: Amyloid ß (Aß), a major biomarker of Alzheimer's disease, leads to tau accumulation, neurodegeneration and cognitive decline. Modelling the trajectory of Aß accumulation in cognitively unimpaired (CU) individuals is crucial, as treatments targeting Aß are anticipated. The evolution of Aß levels was investigated to determine whether it could lead to classification into different groups by studying longitudinal Aß changes in older CU individuals, and differences between the groups were compared. METHODS: A total of 297 CU participants were included from the Alzheimer's Disease Neuroimaging Initiative database, and these participants underwent apolipoprotein E (APOE) genotyping, neuropsychological testing, brain magnetic resonance imaging, and an average of 3.03 follow-up 18F-florbetapir positron emission tomography scans. Distinct Aß trajectory patterns were classified using latent class growth analysis, and longitudinal cognitive performances across these patterns were assessed with a linear mixed effects model. RESULTS: The optimal model consisted of three classes, with a high entropy value of 0.947. The classes were designated as follows: class 1, non-accumulation group (n = 197); class 2, late accumulation group (n = 70); and class 3, early accumulation group (n = 30). The late accumulation and early accumulation groups had more APOE ε4 carriers than the non-accumulation group. The longitudinal analysis of cognitive performance revealed that the early accumulation group showed the steepest decline (modified Preclinical Alzheimer's Cognitive Composite with digit symbol substitution [mPACCdigit], p < 0.001; modified Preclinical Alzheimer's Cognitive Composite with trails B [mPACCtrailsB], p < 0.001) and the late accumulation group showed a steeper decline (mPACCdigit, p = 0.014; mPACCtrailsB, p = 0.007) compared to the non-accumulation group. CONCLUSIONS: Our study showed the heterogeneity of Aß accumulation trajectories in CU older individuals. The prognoses for cognitive decline differ according to the Aß trajectory patterns.

Ethnic differences in the prevalence of amyloid positivity and cognitive trajectories.

INTRODUCTION: We investigated the prevalence of amyloid beta (Aß) positivity (+) and cognitive trajectories in Koreans and non-Hispanic Whites (NHWs). METHODS: We included 5121 Koreans from multiple centers across South Korea and 929 NHWs from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Participants underwent Aß positron emission tomography and were categorized into cognitively unimpaired (CU), mild cognitive impairment (MCI), and dementia stages. Age, sex, education, and apolipoprotein E. genotype were adjusted using multivariable logistic regression and stabilized inverse probability of treatment weights based on the propensity scores to mitigate imbalances in these variables. RESULTS: The prevalence of Aß+ was lower in CU Koreans than in CU NHWs (adjusted odds ratio 0.60). Aß+ Koreans showed a faster cognitive decline than Aß+ NHWs in the CU (B = -0.314, p = .004) and MCI stages (B = -0.385, p < .001). DISCUSSION: Ethnic characteristics of Aß biomarkers should be considered in research and clinical application of Aß-targeted therapies in diverse populations. HIGHLIGHTS: Koreans have a lower prevalence of Aß positivity compared to NHWs in the CU stage. The effects of Alzheimer's risk factors on Aß positivity differ between Koreans and NHWs. Aß-positive (Aß+) Koreans show faster cognitive decline than Aß+ NHWs in the CU and MCI stages.

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.

Single-molecule DNA visualization using AT-specific red and non-specific green DNA-binding fluorescent proteins.

The recent advances in the single cell genome analysis are generating a considerable amount of novel insights into complex biological systems. However, there are still technical challenges because each cell has a single copy of DNA to be amplified in most single cell genome analytical methods. In this paper, we present a novel approach to directly visualize a genomic map on a large DNA molecule instantly stained with red and green DNA-binding fluorescent proteins without DNA amplification. For this visualization, we constructed a few types of fluorescent protein-fused DNA-binding proteins: H-NS (histone-like nucleoid-structuring protein), DNA-binding domain of BRCA1 (breast cancer 1), high mobility group-1 (HMG), and lysine tryptophan (KW) repeat motif. Because H-NS and HMG preferentially bind A/T-rich regions, we combined A/T specific binder (H-NS-mCherry and HMG-mCherry as red color) and a non-specific complementary DNA binder (BRCA1-eGFP and 2(KW)2-eGFP repeat as green color) to produce a sequence-specific two-color DNA physical map for efficient optical identification of single DNA molecules.

Hypoperfusion in Alzheimer's Disease-Prone Regions and Dementia Conversion in Parkinson's Disease.

PURPOSE OF THE REPORT: Although early detection of individuals at risk of dementia conversion is important in patients with Parkinson's disease (PD), there is still no consensus on neuroimaging biomarkers for predicting future cognitive decline. We aimed to investigate whether cerebral perfusion patterns on early-phase 18 F-N-(3-fluoropropyl)-2ß-carboxymethoxy-3ß-(4-iodophenyl) nortropane ( 18 F-FP-CIT) PET have the potential to serve as a neuroimaging predictor for early dementia conversion in patients with PD. MATERIALS AND METHODS: In this retrospective analysis, we enrolled 187 patients with newly diagnosed PD who underwent dual-phase 18 F-FP-CIT PET at initial assessment and serial cognitive assessments during the follow-up period (>5 years). Patients with PD were classified into 2 groups: the PD with dementia (PDD)-high-risk (PDD-H; n = 47) and the PDD-low-risk (PDD-L; n = 140) groups according to dementia conversion within 5 years of PD diagnosis. We explored between-group differences in the regional uptake in the early-phase 18 F-FP-CIT PET images. We additionally performed a linear discriminant analysis to develop a prediction model for early PDD conversion. RESULTS: The PDD-H group exhibited hypoperfusion in Alzheimer's disease (AD)-prone regions (inferomedial temporal and posterior cingulate cortices, and insula) compared with the PDD-L group. A prediction model using regional uptake in the right entorhinal cortex, left amygdala, and left isthmus cingulate cortex could optimally distinguish the PDD-H group from the PDD-L group. CONCLUSIONS: Regional hypoperfusion in the AD-prone regions on early-phase 18 F-FP-CIT PET can be a useful biomarker for predicting early dementia conversion in patients with PD.

Clinical characteristics of seizure recurrence and epilepsy development in patients with alcohol-related seizures.

BACKGROUND: Alcohol withdrawal is widely recognized as a trigger for acute symptomatic seizures among individuals with chronic alcohol consumption. While most alcohol withdrawal seizures occur shortly after cessation, chronic alcohol consumption can be associated with the development of epilepsy, necessitating anti-epileptic drug (AED) therapy. This study aimed to investigate the clinical characteristics, seizure recurrence, and epilepsy development in patients with alcohol-related seizures and to identify prognostic factors for epilepsy. METHODS: In a retrospective analysis at Ewha Womans University Mokdong Hospital, 206 patients with alcohol-related seizures were examined and 15 were excluded due to preexisting epilepsy. Demographic and clinical data, including alcohol withdrawal duration, seizure recurrence, types, and comorbidities, were investigated. Logistic regression models were used to analyze the risk factors for seizure recurrence and epilepsy development. The performance of the final models was evaluated based on the area under the receiver operating characteristic curve (AUC) and validated using calibration plots and leave-one-out cross-validation. RESULTS: Of the 191 patients (146 males; mean age 48.3 ± 12.1 years) with alcohol-related seizures, 99 patients (51.8%) experienced seizure recurrence and 79 patients (41.4%) developed epilepsy. Factors associated with seizure recurrence included alcohol consumption levels, occurrence of focal impaired awareness seizure, anxiety, and headache. The number of recurrent seizures, semiology, status epilepticus, electroencephalogram findings, and brain imaging findings was associated with epilepsy development. The predictive models showed strong diagnostic performance, with AUCs of 0.833 for seizure recurrence and 0.939 for epilepsy development. CONCLUSION: High alcohol consumption and specific clinical and diagnostic features are significant predictors of seizure recurrence and the development of epilepsy among patients with alcohol-related seizures. These findings underscore the importance of early identification and intervention to prevent seizure recurrence and the onset of epilepsy, emphasizing the importance of AED treatment in managing these conditions.

Deep learning-based quantification of brain atrophy using 2D T1-weighted MRI for Alzheimer's disease classification.

Background: Determining brain atrophy is crucial for the diagnosis of neurodegenerative diseases. Despite detailed brain atrophy assessments using three-dimensional (3D) T1-weighted magnetic resonance imaging, their practical utility is limited by cost and time. This study introduces deep learning algorithms for quantifying brain atrophy using a more accessible two-dimensional (2D) T1, aiming to achieve cost-effective differentiation of dementia of the Alzheimer's type (DAT) from cognitively unimpaired (CU), while maintaining or exceeding the performance obtained with T1-3D individuals and to accurately predict AD-specific atrophy similarity and atrophic changes [W-scores and Brain Age Index (BAI)]. Methods: Involving 924 participants (478 CU and 446 DAT), our deep learning models were trained on cerebrospinal fluid (CSF) volumes from 2D T1 images and compared with 3D T1 images. The performance of the models in differentiating DAT from CU was assessed using receiver operating characteristic analysis. Pearson's correlation analyses were used to evaluate the relations between 3D T1 and 2D T1 measurements of cortical thickness and CSF volumes, AD-specific atrophy similarity, W-scores, and BAIs. Results: Our deep learning models demonstrated strong correlations between 2D and 3D T1-derived CSF volumes, with correlation coefficients r ranging from 0.805 to 0.971. The algorithms based on 2D T1 accurately distinguished DAT from CU with high accuracy (area under the curve values of 0.873), which were comparable to those of algorithms based on 3D T1. Algorithms based on 2D T1 image-derived CSF volumes showed high correlations in AD-specific atrophy similarity (r = 0.915), W-scores for brain atrophy (0.732 ≤ r ≤ 0.976), and BAIs (r = 0.821) compared with those based on 3D T1 images. Conclusion: Deep learning-based analysis of 2D T1 images is a feasible and accurate alternative for assessing brain atrophy, offering diagnostic precision comparable to that of 3D T1 imaging. This approach offers the advantage of the availability of T1-2D imaging, as well as reduced time and cost, while maintaining diagnostic precision comparable to T1-3D.

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.

Distinct Cognitive Trajectories According to Amyloid Positivity in Non-Alzheimer Disease Dementias.

BACKGROUND: The clinical effects of ß-amyloid positivity (Aß+) on copathologies in various dementias remain relatively underexamined. Thus, the present study was conducted to investigate the prevalence and clinical effects of Aß+ in subcortical vascular cognitive impairment (SVCI) and frontotemporal dementia (FTD). PATIENTS AND METHODS: We enrolled SVCI (n = 583), FTD (n = 152), and cognitively unimpaired (CU) participants (n = 1,249) who underwent Aß PET scans. The odds of having Aß+ were subsequently compared among the diagnostic groups (CU, SVCI, and FTD) according to age and apolipoprotein E genotype. Additionally, a linear mixed-effects model was used to investigate the effects of Aß+ on cognitive trajectories in SVCI and FTD. RESULTS: Compared with CU, the SVCI group had a higher prevalence of Aß+ in the 75 to 90 years age group (adjusted odds ratio, 1.97; 95% confidence interval, 1.36-2.85; P < 0.001), as well as within the apolipoprotein E ε3/ε3 group (adjusted odds ratio, 1.78; 95% confidence interval, 1.20-2.63; P = 0.001), whereas the FTD group showed no difference in Aß+ prevalence. Aß+ was associated with a worse cognitive trajectory in SVCI (adjusted ß-coefficient = -0.6424; P < 0.001), but not in FTD. CONCLUSIONS: These findings contribute to our understanding of Aß biomarker traits in various dementias in Korea.

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.

The effects of imaging markers on clinical trajectory in cerebral amyloid angiopathy: a longitudinal study in a memory clinic.

BACKGROUND: We investigated the relevance of various imaging markers for the clinical trajectory of cerebral amyloid angiopathy (CAA) patients in a memory clinic. METHODS: A total of 226 patients with probable CAA were included in this study with a mean follow-up period of 3.5 ± 2.7 years. Although all had more than one follow-up visit, 173 underwent follow-up Mini-Mental Status Examination (MMSE) and Clinical Dementia Rating Sum of Boxes (CDR-SB) ranging from 2 to 15 time points. Among 226, 122 patients underwent amyloid-ß (Aß) PET imaging. The prevalence of intracerebral hemorrhage (ICH) and its imaging predictors was investigated. The effects of CAA imaging markers and Aß PET positivity on longitudinal cognition based on the MMSE and CDR-SB were evaluated using mixed effects models. RESULTS: During the follow-up, 10 (4.4%) patients developed ICH: cortical superficial siderosis (cSS; hazard ratio [HR], 6.45) and previous lobar ICH (HR, 4.9), but lobar cerebral microbleeds (CMBs) were not predictors of ICH development. The presence of CMIs (p = 0.045) and Aß positivity (p = 0.002) were associated with worse MMSE trajectory in CAA patients. Regarding CDR-SB trajectory, only Aß positivity was marginally associated with worse longitudinal change (p = 0.050). CONCLUSION: The results of the present study indicated that various imaging markers in CAA patients have different clinical relevance and predictive values for further clinical courses.

Contribution of clinical information to the predictive performance of plasma ß-amyloid levels for amyloid positron emission tomography positivity.

Background: Early detection of ß-amyloid (Aß) accumulation, a major biomarker for Alzheimer's disease (AD), has become important. As fluid biomarkers, the accuracy of cerebrospinal fluid (CSF) Aß for predicting Aß deposition on positron emission tomography (PET) has been extensively studied, and the development of plasma Aß is beginning to receive increased attention recently. In the present study, we aimed to determine whether APOE genotypes, age, and cognitive status increase the predictive performance of plasma Aß and CSF Aß levels for Aß PET positivity. Methods: We recruited 488 participants who underwent both plasma Aß and Aß PET studies (Cohort 1) and 217 participants who underwent both cerebrospinal fluid (CSF) Aß and Aß PET studies (Cohort 2). Plasma and CSF samples were analyzed using ABtest-MS, an antibody-free liquid chromatography-differential mobility spectrometry-triple quadrupole mass spectrometry method and INNOTEST enzyme-linked immunosorbent assay kits, respectively. To evaluate the predictive performance of plasma Aß and CSF Aß, respectively, logistic regression and receiver operating characteristic analyses were performed. Results: When predicting Aß PET status, both plasma Aß42/40 ratio and CSF Aß42 showed high accuracy (plasma Aß area under the curve (AUC) 0.814; CSF Aß AUC 0.848). In the plasma Aß models, the AUC values were higher than plasma Aß alone model, when the models were combined with either cognitive stage (p < 0.001) or APOE genotype (p = 0.011). On the other hand, there was no difference between the CSF Aß models, when these variables were added. Conclusion: Plasma Aß might be a useful predictor of Aß deposition on PET status as much as CSF Aß, particularly when considered with clinical information such as APOE genotype and cognitive stage.

Case report: Cerebrotendinous xanthomatosis with a novel mutation in the CYP27A1 gene mimicking behavioral variant frontotemporal dementia.

Background: Cerebrotendinous xanthomatosis (CTX) is a rare autosomal recessive lipid storage disease caused by a mutation in the CYP27A1 gene. Due to the disruption of bile acid synthesis leading to cholesterol and cholestanol accumulation, CTX manifests as premature cataracts, chronic diarrhea, and intellectual disability in childhood and adolescence. This report presents a case of CTX with an unusual phenotype of behavioral variant frontotemporal dementia (bvFTD) in middle age. Case presentation: A 60-year-old woman presented with behavioral and personality changes. She showed disinhibition, such as hoarding and becoming aggressive over trifles; compulsive behavior, such as closing doors; apathy; and dietary change. The patient showed a progressive cognitive decline and relatively sparing memory and visuospatial function. She had hyperlipidemia but no family history of neurodegenerative disorders. Initial fluid-attenuated inversion recovery (FLAIR) images showed a high signal in the periventricular area, and brain spectroscopy showed hypoperfusion in the frontal and temporal lobes, mimicking bvFTD. However, on physical examination, xanthomas were found on both the dorsum of the hands and the Achilles tendons. Hyperactive deep tendon reflexes in the bilateral biceps, brachioradialis, and knee and positive Chaddock signs on both sides were observed. Four years later, FLAIR images showed symmetrical high signals in the bilateral dentate nuclei of the cerebellum. Her serum cholestanol (12.4 mg/L; normal value ≤6.0) and 7α,12α-dihydroxycholest-4-en-3-one (0.485 nmol/mL; normal value ≤0.100) levels were elevated. A novel likely pathogenic variant (c.1001T>A, p.Met334Lys) and a known pathogenic variant (c.1420C>T, p.Arg474Trp) of the CYP27A1 gene were found in trans-location. The patient was diagnosed with CTX and prescribed chenodeoxycholic acid (750 mg/day). Conclusions: This report discusses the case of a middle-aged CTX patient with an unusual phenotype of bvFTD. A novel likely pathogenic variant (c.1001T>A, p.Met334Lys) was identified in the CYP27A1 gene. Early diagnosis is important because supplying chenodeoxycholic acid can prevent CTX progression.

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.

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

Purpose: Amnestic mild cognitive impairment (aMCI) is a transitional state between normal aging and Alzheimer's disease (AD). However, not all aMCI patients are observed to convert to AD dementia. Therefore, developing a predictive algorithm for the conversion of aMCI to AD dementia is important. Parametric methods, such as logistic regression, have been developed; however, it is difficult to reflect complex patterns, such as non-linear relationships and interactions between variables. Therefore, this study aimed to improve the predictive power of aMCI patients' conversion to dementia by using an interpretable machine learning (IML) algorithm and to identify the factors that increase the risk of individual conversion to dementia in each patient. Methods: We prospectively recruited 705 patients with aMCI who had been followed-up for at least 3 years after undergoing baseline neuropsychological tests at the Samsung Medical Center between 2007 and 2019. We used neuropsychological tests and apolipoprotein E (APOE) genotype data to develop a predictive algorithm. The model-building and validation datasets were composed of data of 565 and 140 patients, respectively. For global interpretation, four algorithms (logistic regression, random forest, support vector machine, and extreme gradient boosting) were compared. For local interpretation, individual conditional expectations (ICE) and SHapley Additive exPlanations (SHAP) were used to analyze individual patients. Results: Among the four algorithms, the extreme gradient boost model showed the best performance, with an area under the receiver operating characteristic curve of 0.852 and an accuracy of 0.807. Variables, such as age, education, the scores of visuospatial and memory domains, the sum of boxes of the Clinical Dementia Rating scale, Mini-Mental State Examination, and APOE genotype were important features for creating the algorithm. Through ICE and SHAP analyses, it was also possible to interpret which variables acted as strong factors for each patient. Conclusion: We were able to propose a predictive algorithm for each aMCI individual's conversion to dementia using the IML technique. This algorithm is expected to be useful in clinical practice and the research field, as it can suggest conversion with high accuracy and identify the degree of influence of risk factors for each patient.

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.

Distinctive Temporal Trajectories of Alzheimer's Disease Biomarkers According to Sex and APOE Genotype: Importance of Striatal Amyloid.

PURPOSE: Previously, sex and apolipoprotein E (APOE) genotype had distinct effects on the cognitive trajectory across the Alzheimer's disease (AD) continuum. We therefore aimed to investigate whether these trajectory curves including ß-amyloid (Aß) accumulation in the cortex and striatum, and tau accumulation would differ according to sex and APOE genotype. METHODS: We obtained 534 subjects for 18F-florbetapir (AV45) PET analysis and 163 subjects for 18F-flortaucipir (AV1451) PET analysis from the Alzheimer's Disease Neuroimaging Initiative database. For cortical Aß, striatal Aß, and tau SUVR, we fitted penalized splines to model the slopes of SUVR value as a non-linear function of baseline SUVR value. By integrating the fitted splines, we obtained the predicted SUVR curves as a function of time. RESULTS: The time from initial SUVR to the cutoff values were 14.9 years for cortical Aß, 18.2 years for striatal Aß, and 22.7 years for tau. Although there was no difference in cortical Aß accumulation rate between women and men, striatal Aß accumulation was found to be faster in women than in men, and this temporal difference according to sex was more pronounced in tau accumulation. However, APOE ε4 carriers showed faster progression than non-carriers regardless of kinds of AD biomarkers' trajectories. CONCLUSION: Our temporal trajectory models illustrate that there is a distinct progression pattern of AD biomarkers depending on sex and APOE genotype. In this regard, our models will be able to contribute to designing personalized treatment and prevention strategies for AD in clinical practice.

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.

18F-THK5351 PET Positivity and Longitudinal Changes in Cognitive Function in ß-Amyloid-Negative Amnestic Mild Cognitive Impairment.

PURPOSE: Neuroinflammation is considered an important pathway associated with several diseases that result in cognitive decline. 18F-THK5351 positron emission tomography (PET) signals might indicate the presence of neuroinflammation, as well as Alzheimer's disease-type tau aggregates. ß-amyloid (Aß)-negative (Aß-) amnestic mild cognitive impairment (aMCI) may be associated with non-Alzheimer's disease pathophysiology. Accordingly, we investigated associations between 18F-THK5351 PET positivity and cognitive decline among Aß- aMCI patients. MATERIALS AND METHODS: The present study included 25 amyloid PET negative aMCI patients who underwent a minimum of two follow-up neuropsychological evaluations, including clinical dementia rating-sum of boxes (CDR-SOB). The patients were classified into two groups: 18F-THK5351-positive and -negative groups. The present study used a linear mixed effects model to estimate the effects of 18F-THK5351 PET positivity on cognitive prognosis among Aß- aMCI patients. RESULTS: Among the 25 Aß- aMCI patients, 10 (40.0%) were 18F-THK5351 positive. The patients in the 18F-THK5351-positive group were older than those in the 18F-THK5351-negative group (77.4±2.2 years vs. 70.0±5.5 years; p<0.001). There was no difference between the two groups with regard to the proportion of apolipoprotein E ε4 carriers. Interestingly, however, the CDR-SOB scores of the 18F-THK5351-positive group deteriorated at a faster rate than those of the 18F-THK5351-negative group (B=0.003, p=0.033). CONCLUSION: The results of the present study suggest that increased 18F-THK5351 uptake might be a useful predictor of poor prognosis among Aß- aMCI patients, which might be associated with increased neuroinflammation (ClinicalTrials.gov NCT02656498).