Topographical Heterogeneity of Alzheimer’s Disease Based on MR Imaging, Tau PET, and Amyloid PET

Frontiers in Aging Neuroscience

Young Noh¹  Yeong-Bae Lee²  Kee Hyung Park²  Sang-Yoon Lee⁴  Seongho Seo⁴  Jae Myeong Kang⁵  Byeong Kil Yeon⁵  Nobuyuki Okamura⁶  Alan C. Evans⁷  Thomas Funck⁷  Seun Jeon⁷  Duk L. Na⁸  Hye Jin Jeong⁹  Tatsuo Ido⁹ 

[1] Department of Health Science and Technology, GAIHST, Gachon University, Incheon, South Korea;Department of Neurology, Gil Medical Center, Gachon University College of Medicine, Incheon, South Korea;Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea;Department of Neuroscience, Gachon University College of Medicine, Incheon, South Korea;Department of Psychiatry, Gil Medical Center, Gachon University College of Medicine, Incheon, South Korea;Division of Pharmacology, Faculty of Medicine, Tohoku Medical and Pharmaceutical University, Sendai, Japan;McGill Centre for Integrative Neuroscience, Montreal Neurological Institute, McGill University, Montreal, QC, Canada;Neuroscience Center, Samsung Medical Center, Seoul, South Korea;Neuroscience Research Institute, Gachon University, Incheon, South Korea;

关键词: Alzheimer’s disease;    cluster analysis;    tau;    amyloid;    cortical thickness;    positron emission tomography;   

DOI  :  10.3389/fnagi.2019.00211

来源: DOAJ

【 摘 要 】

Alzheimer’s disease (AD) patients are known to have heterogeneous clinical presentation and pathologic patterns. We hypothesize that AD dementia can be categorized into subtypes based on multimodal imaging biomarkers such as magnetic resonance imaging (MRI), tau positron emission tomography (PET), and amyloid PET. We collected 3T MRI, 18F-THK5351 PET, and 18F-flutemetamol (FLUTE) PET data from 83 patients with AD dementia [Clinical Dementia Rating (CDR) ≤1] and 60 normal controls (NC), and applied surface-based analyses to measure cortical thickness, THK5351 standardized uptake value ratio (SUVR) and FLUTE SUVR for each participant. For the patient group, we performed an agglomerative hierarchical clustering analysis using the three multimodal imaging features on the vertices (n = 3 × 79,950). The identified AD subtypes were compared to NC using general linear models adjusting for age, sex, and years of education. We mapped the effect size within significant cortical regions reaching a corrected p-vertex <0.05 (random field theory). Our surface-based multimodal framework has revealed three distinct subtypes among AD patients: medial temporal-dominant subtype (MT, n = 44), parietal-dominant subtype (P, n = 19), and diffuse atrophy subtype (D, n = 20). The topography of cortical atrophy and THK5351 retention differentiates between the three subtypes. In the case of FLUTE, three subtypes did not show distinct topographical differences, although cortical composite retention was significantly higher in the P type than in the MT type. These three subtypes also differed in demographic and clinical features. In conclusion, AD patients may be clustered into three subtypes with distinct topographical features of cortical atrophy and tau deposition, although amyloid deposition may not differ across the subtypes in terms of topography.

【 授权许可】

Unknown