Seok Woo Moon

A nationwide survey on the prevalence of dementia and mild cognitive impairment in South Korea.

We investigated the prevalence of dementia and mild cognitive impairment (MCI) and the factors associate with risk of dementia from a representative nationwide sample of Korean elders. 8,199 randomly-sampled Koreans aged 65 years or older were invited to participate in the Phase I screening assessment using Mini-Mental State Examination by door-to-door home visit, and 6,141 subjects (response rate = 74.9%) responded. Among them, 2,336 subjects were invited to participate in the Phase II diagnostic assessment for dementia and MCI, and 1,673 subjects responded (response rate = 71.6%). Diagnostic assessments were administered using the Korean version of the Consortium to Establish a Registry for Alzheimers Disease Assessment Packet (CERAD-K) Clinical Assessment Battery. The CERAD-K Neuropsychological Assessment Battery was used for diagnosing MCI. Age-, gender-, education-, and urbanicity-standardized prevalence of dementia was estimated to be 8.1% (95% CI = 6.9-9.2) for overall dementia and 24.1% (95% CI = 21.0-27.2) for MCI. Alzheimers disease (AD) was the most prevalent type (5.7%) followed by vascular dementia (2.0%). Amnestic subtype (20.1%) was much more prevalent than nonamnestic subtype in MCI (4.0%). Older age, being male, lower education level, illiteracy, smoking, and histories of head trauma or depression were associated with increased dementia risk, and alcohol use and moderately intense exercise were associated with decreased dementia risk. We expect numbers of dementia patients to double every 20 years until 2050 in Korea and expect AD to account for progressively more dementia cases in the future.

A nationwide survey on the prevalence and risk factors of late life depression in South Korea

OBJECTIVE This study aimed to estimate prevalence rates and risk factors of LLD among a large nationwide sample of Korean elders in South Korea. METHOD Of 8199 randomly sampled Koreans aged 65 years or more, 6018 participated (response rate=73.4%). Using the Korean version of the short form Geriatric Depression Scale (SGDS-K), we classified individual scoring 8 or 9 as having possible depression and those scoring ≥ 10 as having probable depression. RESULTS The age-, gender-, education-, and urbanicity-standardized prevalences were 10.1% (95% CI=9.3-10.8) for possible depression, 17.8% (95% CI=16.8-8.7) for probable depression, and 27.8% (95% CI=26.7-29.0) for overall depression. Poverty, living alone, low education, illiteracy, smoking, history of head trauma, and low Mini Mental Status Examination score were associated with greater risk of depression, while mild alcohol use and moderate to heavy exercise were associated with lower risk of depression. However gender difference in the risk of depression was not found. CONCLUSION LLD is decidedly common in South Korea. It was associated with various sociodemographic and clinical factors, some of which are amendable through policy actions. This study was limited by use of the SGDS-K rather than a standardized clinical interview.

Validity of the telephone interview for cognitive status (TICS) and modified TICS (TICSm) for mild cognitive imparment (MCI) and dementia screening

This study aimed to validate the TICS and modified TICS (TICSm) in Korean elderly population and to compare MCI and dementia screening ability between TICS and TICSm. TICS and TICSm were administered to 70 cognitively normal (CN), 75 MCI, and 85 dementia subjects, with mini-mental state examination (MMSE) and other cognitive and functional measures. TICS and TICSm scores were highly correlated with other global cognitive and functional scores. The CN vs. dementia discrimination ability of both instruments was as excellent as that of MMSE (sensitivity/specificity at optimal cutoff: 87.1/90.1 for TICS; 88.2/90.0 for TICSm). Although their CN vs. MCI discrimination performances were comparable to that of MMSE, they were far from perfect (sensitivity/specificity: 69.3/68.6 for TICS; 73.3/67.1 for TICSm). There was no significant difference in dementia or MCI screening accuracy between TICS and TICSm. Both of them also showed high test-retest reliability. Our findings indicate that TICS and TICSm are reliable and as valid as MMSE in regard of screening cognitively impaired elderly. In terms of the comparison between TICSm and TICS, however, TICSm has little advantage over TICS for screening dementia and even MCI, in spite of longer administration time and more efforts required.

High-throughput neuroimaging-genetics computational infrastructure.

Many contemporary neuroscientific investigations face significant challenges in terms of data management, computational processing, data mining, and results interpretation. These four pillars define the core infrastructure necessary to plan, organize, orchestrate, validate, and disseminate novel scientific methods, computational resources, and translational healthcare findings. Data management includes protocols for data acquisition, archival, query, transfer, retrieval, and aggregation. Computational processing involves the necessary software, hardware, and networking infrastructure required to handle large amounts of heterogeneous neuroimaging, genetics, clinical, and phenotypic data and meta-data. Data mining refers to the process of automatically extracting data features, characteristics and associations, which are not readily visible by human exploration of the raw dataset. Result interpretation includes scientific visualization, community validation of findings and reproducible findings. In this manuscript we describe the novel high-throughput neuroimaging-genetics computational infrastructure available at the Institute for Neuroimaging and Informatics (INI) and the Laboratory of Neuro Imaging (LONI) at University of Southern California (USC). INI and LONI include ultra-high-field and standard-field MRI brain scanners along with an imaging-genetics database for storing the complete provenance of the raw and derived data and meta-data. In addition, the institute provides a large number of software tools for image and shape analysis, mathematical modeling, genomic sequence processing, and scientific visualization. A unique feature of this architecture is the Pipeline environment, which integrates the data management, processing, transfer, and visualization. Through its client-server architecture, the Pipeline environment provides a graphical user interface for designing, executing, monitoring validating, and disseminating of complex protocols that utilize diverse suites of software tools and web-services. These pipeline workflows are represented as portable XML objects which transfer the execution instructions and user specifications from the client user machine to remote pipeline servers for distributed computing. Using Alzheimers and Parkinsons data, we provide several examples of translational applications using this infrastructure1.

The perfect neuroimaging-genetics-computation storm: collision of petabytes of data, millions of hardware devices and thousands of software tools

The volume, diversity and velocity of biomedical data are exponentially increasing providing petabytes of new neuroimaging and genetics data every year. At the same time, tens-of-thousands of computational algorithms are developed and reported in the literature along with thousands of software tools and services. Users demand intuitive, quick and platform-agnostic access to data, software tools, and infrastructure from millions of hardware devices. This explosion of information, scientific techniques, computational models, and technological advances leads to enormous challenges in data analysis, evidence-based biomedical inference and reproducibility of findings. The Pipeline workflow environment provides a crowd-based distributed solution for consistent management of these heterogeneous resources. The Pipeline allows multiple (local) clients and (remote) servers to connect, exchange protocols, control the execution, monitor the states of different tools or hardware, and share complete protocols as portable XML workflows. In this paper, we demonstrate several advanced computational neuroimaging and genetics case-studies, and end-to-end pipeline solutions. These are implemented as graphical workflow protocols in the context of analyzing imaging (sMRI, fMRI, DTI), phenotypic (demographic, clinical), and genetic (SNP) data.

Structural Neuroimaging Genetics Interactions in Alzheimer’s Disease

This article investigates late-onset cognitive impairment using neuroimaging and genetics biomarkers for Alzheimers Disease Neuroimaging Initiative (ADNI) participants. Eight-hundred and eight ADNI subjects were identified and divided into three groups: 200 subjects with Alzheimers disease (AD), 383 subjects with mild cognitive impairment (MCI), and 225 asymptomatic normal controls (NC). Their structural magnetic resonance imaging (MRI) data were parcellated using BrainParser, and the 80 most important neuroimaging biomarkers were extracted using the global shape analysis Pipeline workflow. Using Plink via the Pipeline environment, we obtained 80 SNPs highly-associated with the imaging biomarkers. In the AD cohort, rs2137962 was significantly associated bilaterally with changes in the hippocampi and the parahippocampal gyri, and rs1498853, rs288503, and rs288496 were associated with the left and right hippocampi, the right parahippocampal gyrus, and the left inferior temporal gyrus. In the MCI cohort, rs17028008 and rs17027976 were significantly associated with the right caudate and right fusiform gyrus, rs2075650 (TOMM40) was associated with the right caudate, and rs1334496 and rs4829605 were significantly associated with the right inferior temporal gyrus. In the NC cohort, Chromosome 15 [rs734854 (STOML1), rs11072463 (PML), rs4886844 (PML), and rs1052242 (PML)] was significantly associated with both hippocampi and both insular cortices, and rs4899412 (RGS6) was significantly associated with the caudate. We observed significant correlations between genetic and neuroimaging phenotypes in the 808 ADNI subjects. These results suggest that differences between AD, MCI, and NC cohorts may be examined by using powerful joint models of morphometric, imaging and genotypic data.

Structural Brain Changes in Early-Onset Alzheimer's Disease Subjects Using the LONI Pipeline Environment.

This study investigates 36 subjects aged 55‐65 from the Alzheimers Disease Neuroimaging Initiative (ADNI) database to expand our knowledge of early‐onset (EO) Alzheimers Disease (EO‐AD) using neuroimaging biomarkers.

Prevalence Rates of Dementia and Mild Cognitive Impairment Are Affected by the Diagnostic Parameter Changes for Neurocognitive Disorders in the DSM-5 in a Korean Population

Aim: To examine the impact of the revised diagnostic criteria for neurocognitive disorders (NCDs) in the Diagnostic and Statistical Manual of Mental Disorders, 5th edition (DSM-5) on the prevalence of dementia and mild cognitive impairment (MCI). Methods: A total of 755 participants aged 65 years or older in the Nationwide Survey on Dementia Epidemiology in Korea 2012 were rediagnosed according to the DSM-5 criteria. Results: The estimated age-, gender-, education-, and urbanicity-standardized prevalence rates of major and mild NCDs were 8.35 and 11.10%, respectively, and those of dementia and MCI were 8.74 and 31.85%, respectively. Cohens κ for dementia and major NCD was 0.988, and that for MCI and mild NCD was 0.273. Conclusion: Diagnostic discrepancies between major/mild NCDs and dementia/MCI might depend on the operationalization of neuropsychological performance criteria.

Gene Interactions and Structural Brain Change in Early-Onset Alzheimer's Disease Subjects Using the Pipeline Environment

Objective This article investigates subjects aged 55 to 65 from the Alzheimers Disease Neuroimaging Initiative (ADNI) database to broaden our understanding of early-onset (EO) cognitive impairment using neuroimaging and genetics biomarkers. Methods Nine of the subjects had EO-AD (Alzheimers disease) and 27 had EO-MCI (mild cognitive impairment). The 15 most important neuroimaging markers were extracted with the Global Shape Analysis (GSA) Pipeline workflow. The 20 most significant single nucleotide polymorphisms (SNPs) were chosen and were associated with specific neuroimaging biomarkers. Results We identified associations between the neuroimaging phenotypes and genotypes for a total of 36 subjects. Our results for all the subjects taken together showed the most significant associations between rs7718456 and L_hippocampus (volume), and between rs7718456 and R_hippocampus (volume). For the 27 MCI subjects, we found the most significant associations between rs6446443 and R_superior_frontal_gyrus (volume), and between rs17029131 and L_Precuneus (volume). For the nine AD subjects, we found the most significant associations between rs16964473 and L_rectus gyrus (surface area), and between rs12972537 and L_rectus_gyrus (surface area). Conclusion We observed significant correlations between the SNPs and the neuroimaging phenotypes in the 36 EO subjects in terms of neuroimaging genetics. However, larger sample sizes are needed to ensure that the effects will be detectable for a reasonable false-positive error rate using the GSA and Plink Pipeline workflows.

The Effect of Choline Acetyltransferase Genotype on Donepezil Treatment Response in Patients with Alzheimer’s Disease

Objective We examined the difference in responses to donepezil between carriers and non-carriers of the A allele at the +4 position of the choline acetyltransferase (ChAT) gene in Koreans. Methods Patients who met the criteria for probable Alzheimer’s disease (AD) (n=199) were recruited. Among these, 145 completed the 12-week follow-up evaluation and 135 completed the 26-week scheduled course. Differences and changes in the Korean version of the mini-mental state examination (MMSE-KC) score, Korean version of the Consortium to Establish a Registry for Alzheimer’s Disease Neuropsychological Assessment Battery (CERAD-K[N]) wordlist subtest score (WSS), CERAD-K(N) total score (TS), and the Korean version of geriatric depression scale (GDS-K) score between baseline and 12 weeks or 26 weeks were assessed by the Student’s t-test. Results At 12 weeks, the changes in the MMSE-KC score, CERAD-K(N) WSS, and CERAD-K(N) TS from baseline were not significant between ChAT A allele carriers and non-carriers; however, at 26 weeks, these changes were significantly larger in ChAT A allele carriers than in non-carriers (p=0.02 for MMSE-KC and p=0.03 for CERAD-K(N) WSS respectively). Conclusion Our findings in this study suggested that presence of the A allele at the +4 position of ChAT might positively influence the treatment effect of donepezil in the early stages of AD in Koreans.