当前位置: 首页 > 详情页

Glucose metabolism patterns: A potential index to characterize brain ageing and predict high conversion risk into cognitive impairment.

文献详情

资源类型:
WOS体系:
Pubmed体系:

收录情况: ◇ SCIE

机构: [1]Institute of Biomedical Engineering, School of Information and Communication Engineering, Shanghai University, Shanghai 200444, China [2]Department of Neurology, Xuanwu Hospital of Capital Medical University, Beijing 100053, China [3]School of Biomedical Engineering, Hainan University, Haikou 570228, China [4]German Centre for Neurodegenerative Disease, Clinical Research Group, Venusberg Campus 1, 53121 Bonn, Germany [5]Centre of Alzheimer’s Disease, Beijing Institute for Brain Disorders, Beijing 100053, China [6]National Clinical Research Centre for Geriatric Disorders, Beijing 100053, China
出处:
ISSN:

关键词: Pattern Brain ageing Positron emission tomography Glucose metabolism

摘要:
Exploring individual hallmarks of brain ageing is important. Here, we propose the age-related glucose metabolism pattern (ARGMP) as a potential index to characterize brain ageing in cognitively normal (CN) elderly people. We collected 18F-fluorodeoxyglucose (18F-FDG) PET brain images from two independent cohorts: the Alzheimer's Disease Neuroimaging Initiative (ADNI, N = 127) and the Xuanwu Hospital of Capital Medical University, Beijing, China (N = 84). During follow-up (mean 80.60 months), 23 participants in the ADNI cohort converted to cognitive impairment. ARGMPs were identified using the scaled subprofile model/principal component analysis method, and cross-validations were conducted in both independent cohorts. A survival analysis was further conducted to calculate the predictive effect of conversion risk by using ARGMPs. The results showed that ARGMPs were characterized by hypometabolism with increasing age primarily in the bilateral medial superior frontal gyrus, anterior cingulate and paracingulate gyri, caudate nucleus, and left supplementary motor area and hypermetabolism in part of the left inferior cerebellum. The expression network scores of ARGMPs were significantly associated with chronological age (R = 0.808, p < 0.001), which was validated in both the ADNI and Xuanwu cohorts. Individuals with higher network scores exhibited a better predictive effect (HR: 0.30, 95% CI: 0.1340 ~ 0.6904, p = 0.0068). These findings indicate that ARGMPs derived from CN participants may represent a novel index for characterizing brain ageing and predicting high conversion risk into cognitive impairment.© 2022. The Author(s), under exclusive licence to American Aging Association.

基金:
语种:
被引次数:
WOS:
PubmedID:
中科院(CAS)分区:
出版当年[2021]版:
大类 | 2 区 医学
小类 | 2 区 老年医学
最新[2025]版:
大类 | 2 区 医学
小类 | 2 区 老年医学
JCR分区:
出版当年[2020]版:
Q1 GERIATRICS & GERONTOLOGY
最新[2023]版:
Q1 GERIATRICS & GERONTOLOGY

影响因子: 最新[2023版] 最新五年平均 出版当年[2020版] 出版当年五年平均 出版前一年[2019版] 出版后一年[2021版]

第一作者:
第一作者机构: [1]Institute of Biomedical Engineering, School of Information and Communication Engineering, Shanghai University, Shanghai 200444, China
共同第一作者:
通讯作者:
通讯机构: [2]Department of Neurology, Xuanwu Hospital of Capital Medical University, Beijing 100053, China [3]School of Biomedical Engineering, Hainan University, Haikou 570228, China [5]Centre of Alzheimer’s Disease, Beijing Institute for Brain Disorders, Beijing 100053, China [6]National Clinical Research Centre for Geriatric Disorders, Beijing 100053, China
推荐引用方式(GB/T 7714):
APA:
MLA:

资源点击量:17010 今日访问量:0 总访问量:909 更新日期:2025-04-01 建议使用谷歌、火狐浏览器 常见问题

版权所有©2020 首都医科大学宣武医院 技术支持:重庆聚合科技有限公司 地址:北京市西城区长椿街45号宣武医院