Identification of Heterogeneous Subtypes of Mild Cognitive Impairment Using Cluster Analyses Based on PET Imaging of Tau and Astrogliosis

Frontiers in Aging Neuroscience

卷:12

Duk L. Na¹  Joon-Kyung Seong³  Young Noh⁴  Yeong-Bae Lee⁵  Kee Hyung Park⁵  Sang-Yoon Lee⁷  Seongho Seo⁷  Kwang-Pil Ko⁸  Jae Myeong Kang⁹  Byeong Kil Yeon⁹  Nobuyuki Okamura¹⁰  Hyun Jeong Lee¹¹  Woo-Ram Kim¹²  Ha-Eun Seo¹²  Eun-Chong Lee¹³ 

[1] 0Neuroscience Center, Samsung Medical Center, Seoul, South Korea;

[2] 1Department of Artificial Intelligence, Korea University, Seoul, South Korea;

[3] 2Interdisciplinary Program in Precision Public Health, Korea University, Seoul, South Korea;

[4] 3Department of Health Science and Technology, GAIHST, Gachon University, Incheon, South Korea;

[5] Department of Neurology, Gil Medical Center, Gachon University College of Medicine, Incheon, South Korea;

[6] Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea;

[7] Department of Neuroscience, College of Medicine, Gachon University, Incheon, South Korea;

[8] Department of Preventive Medicine, Gachon University College of Medicine, Incheon, South Korea;

[9] Department of Psychiatry, Gil Medical Center, Gachon University College of Medicine, Incheon, South Korea;

[10] Division of Pharmacology, Faculty of Medicine, Tohoku Medical and Pharmaceutical University, Sendai, Japan;

[11] Gil Medical Center, Gachon University College of Medicine, Incheon, South Korea;

[12] Neuroscience Research Institute, Gachon University, Incheon, South Korea;

[13] School of Biomedical Engineering, Korea University, Seoul, South Korea;

关键词: mild cognitive impairment;    tau;    THK;    cluster analysis;    positron emission tomography;   

DOI  :  10.3389/fnagi.2020.615467

来源: DOAJ

【 摘 要 】

Background: Mild cognitive impairment (MCI) is a condition with diverse causes and clinical outcomes that can be categorized into subtypes. [18F]THK5351 has been known to detect reactive astrogliosis as well as tau which is accompanied by neurodegenerative changes. Here, we identified heterogeneous groups of MCI patients using THK retention patterns and a graph theory approach, allowing for the comparison of risk of progression to dementia in these MCI subgroups.Methods: Ninety-seven participants including 60 MCI patients and individuals with normal cognition (NC, n = 37) were included and undertook 3T MRI, [18F]THK5351 PET, and detailed neuropsychological tests. [18F]Flutemetamol PET was also performed in 62 participants. We calculated similarities between MCI patients using their regional standardized uptake value ratio of THK retention in 75 ROIs, and clustered subjects with similar retention patterns using the Louvain method based on the modularity of the graph. The clusters of patients identified were compared with an age-matched control group using a general linear model. Dementia conversion was evaluated after a median follow-up duration of 34.6 months.Results: MCI patients were categorized into four groups according to their THK retention patterns: (1) limbic type; (2) diffuse type; (3) sparse type; and (4) AD type (retention pattern as in AD). Subjects of the limbic type were characterized by older age, small hippocampal volumes, and reduced verbal memory and frontal/executive functions. Patients of the diffuse type had relatively large vascular burden, reduced memory capacity and some frontal/executive functions. Co-morbidity and mortality were more frequent in this subgroup. Subjects of the sparse type were younger and declined only in terms of visual memory and attention. No individuals in this subgroup converted to dementia. Patients in the AD type group exhibited the poorest cognitive function. They also had the smallest hippocampal volumes and the highest risk of progression to dementia (90.9%).Conclusion: Using cluster analyses with [18F]THK5351 retention patterns, it is possible to identify clinically-distinct subgroups of MCI patients and those at greater risk of progression to dementia.

【 授权许可】

Unknown