Metabolic Asymmetry Relates to Clinical Characteristics and Brain Network Abnormalities in Alzheimer’s Disease

正电子发射断层摄影术 标准摄取值 内科学 疾病 不对称 阿尔茨海默病 医学 心理学 神经科学 心脏病学 物理 量子力学
作者
Huamei Lin,Tingting Pan,Min Wang,Jingjie Ge,Jiaying Lu,Zizhao Ju,Keliang Chen,Huiwei Zhang,Yihui Guan,Qianhua Zhao,Baoci Shan,Binbin Nie,Chuantao Zuo,Ping Wu
出处
期刊:Journal of Alzheimer's Disease [IOS Press]
卷期号:93 (4): 1395-1406 被引量:1
标识
DOI:10.3233/jad-221258
摘要

Background: Metabolic asymmetry has been observed in Alzheimer’s disease (AD), but different studies have inconsistent viewpoints. Objective: To analyze the asymmetry of cerebral glucose metabolism in AD and investigate its clinical significance and potential metabolic network abnormalities. Methods: Standardized uptake value ratios (SUVRs) were obtained from 18F-FDG positron emission tomography (PET) images of all participants, and the asymmetry indices (AIs) were calculated according to the SUVRs. AD group was divided into left/right-dominant or bilateral symmetric hypometabolism (AD-L/AD-R or AD-BI) when more than half of the AIs of the 20 regions of interest (ROIs) were < –2SD, >2SD, or between±1SD. Differences in clinical features among the three AD groups were compared, and the abnormal network characteristics underlying metabolic asymmetry were explored. Results: In AD group, the proportions of AD-L, AD-R, and AD-BI were 28.4%, 17.9%, and 18.5%, respectively. AD-L/AD-R groups had younger age of onset and faster rate of cognitive decline than AD-BI group (p < 0.05). The absolute values of AIs in half of the 20 ROIs became higher at follow-up than at baseline (p < 0.05). Compared with those in AD-BI group, metabolic connection strength of network, global efficiency, cluster coefficient, degree centrality and local efficiency were lower, but shortest path length was longer in AD-L and AD-R groups (p < 0.05). Conclusion: Asymmetric and symmetric hypometabolism may represent different clinical subtypes of AD, which may provide a clue for future studies on the heterogeneity of AD and help to optimize the design of clinical trials.
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