ABSTRACT
Background@#and PurposeWe aimed to determine the effect of demographic factors on cortical thickness and brain glucose metabolism in healthy aging subjects. @*Methods@#The following tests were performed on 71 subjects with normal cognition: neurological examination, 3-tesla magnetic resonance imaging, 18F-fluorodeoxyglucose positron-emission tomography, and neuropsychological tests. Cortical thickness and brain metabolism were measured using vertex- and voxelwise analyses, respectively. General linear models (GLMs) were used to determine the effects of age, sex, and education on cortical thickness and brain glucose metabolism. The effects of mean lobar cortical thickness and mean lobar metabolism on neuropsychological test scores were evaluated using GLMs after controlling for age, sex, and education. The intracranial volume (ICV) was further included as a predictor or covariate for the cortical thickness analyses. @*Results@#Age was negatively correlated with the mean cortical thickness in all lobes (frontal and parietal lobes, p=0.001; temporal and occipital lobes, p<0.001) and with the mean temporal metabolism (p=0.005). Education was not associated with cortical thickness or brain metabolism in any lobe. Male subjects had a lower mean parietal metabolism than did female subjects (p<0.001), while their mean cortical thicknesses were comparable. ICV was positively correlated with mean cortical thickness in the frontal (p=0.016), temporal (p=0.009), and occipital (p=0.007) lobes. The mean lobar cortical thickness was not associated with cognition scores, while the mean temporal metabolism was positively correlated with verbal memory test scores. @*Conclusions@#Age and sex affect cortical thickness and brain glucose metabolism in different ways. Demographic factors must therefore be considered in analyses of cortical thickness and brain metabolism.
ABSTRACT
Because of repeated failures of clinical trials, the concept of Alzheimer's disease (AD) has been changing rapidly in recent years. As suggested by the National Institute on Aging and the Alzheimer's Association Research Framework, the diagnosis and classification of AD is now based on biomarkers rather than on symptoms, allowing more accurate identification of proper candidates for clinical trials by pathogenesis and disease stage. Recent development in neuroimaging has provided a way to reveal the complex dynamics of amyloid and tau in the brain in vivo, and studies of blood biomarkers are taking another leap forward in diagnosis and treatment of AD. In the field of basic and translational research, the development of animal models and a deeper understanding of the role of neuroinflammation are taking a step closer to clarifying the pathogenesis of AD. Development of big data and the Internet of Things is also incorporating dementia care and research into other aspects. Largescale genetic research has identified genetic abnormalities that can provide a foundation for precision medicine along with the aforementioned digital technologies. Through the first international conference of the Korean Dementia Association, experts from all over the world gathered to exchange opinions with association members on these topics. The Academic Committee of the Korean Dementia Association briefly summarizes the contents of the lectures to convey the depth of the conference and discussions. This will be an important milestone in understanding the latest trends in AD's pathogenesis, diagnostic and therapeutic research and in establishing a future direction.
ABSTRACT
BACKGROUND AND PURPOSE: Evaluating instrumental activities of daily living (IADL) is an important part of procedure to diagnose dementia. The Korean-Instrumental Activities of Daily Living (K-IADL) has been used extensively in Korea. However, its cut-off score has not been reformulated since 2002. The purpose of this study was to yield a new optimal cut-off score for the K-IADL and confirm the validity of this new cut-off score with various dementia groups. METHODS: We retrospectively collected a total of 2,347 patients' K-IADL data from 6 general hospitals in Korea. These patients had mild cognitive impairment (MCI) or dementia with various etiologies for cognitive impairment. We also recruited a normal control group (n=254) from the community. Korean-Mini Mental State Examination, Short version of the Geriatric Depression Scale, Clinical Dementia Rating, and Global Deterioration Scale were administered to all participants. Caregivers completed K-IADL and Barthel Index. RESULTS: K-IADL scores were significantly different among dementia subgroups, but not significantly different among MCI subgroups. Based on internal consistency, correlations with other scales, and factor analysis, K-IADL showed excellent reliability and validity. The new optimal cut-off score to diagnose dementia was 0.40, which gave a sensitivity of 0.901 and a specificity of 0.916. Positive predictive value for dementia using the new cut-off score was 94.2% for Alzheimer's disease, 100% for vascular dementia, and 84% for Parkinson's disease. CONCLUSIONS: Our results illustrate that the new K-IADL cut-off score of 0.40 is reliable and valid for screening impairments of daily functioning resulting from various etiologies.