Abstract
Cortical hubs that link functionally specialized neural systems are crucial for cognition. Evidence suggests that the location and organization of hubs are related to Alzheimer’s disease (AD). However, two issues remain unclear: (i) where and how hubs change in AD, and (ii) whether hubs could be a potential pre-diagnosis biomarker for mild cognitive impairment (MCI) - a prodromal phase of AD. Accordingly, we examined the functional connectivity density (FCD) in two cohorts of resting-state functional magnetic resonance imaging (fMRI) scans (26 AD, 27 controls; 33 AD, 21 controls) and revealed consistently vulnerable FCD hub regions in AD compared with controls: within the default mode network, short-range FCD decreases in the posterior cingulate cortex and increases in the medial prefrontal cortex; within the frontal lobe, long-range FCD increases in the medial prefrontal cortex, superior frontal gyrus and middle frontal gyrus. Furthermore, FCD correlates with cognitive score and could distinguish MCI from controls with high accuracy (71.08% in dataset 1, 81% in dataset 2). By reflecting a robust and reproducible global shift in brain functions, FCD provides an fMRI biomarker for the underlying mechanism in AD.
Keywords: Alzheimer’s disease, biomarker, classification, functional connectivity density, mild cognitive impairment, resting state functional MRI.
Current Alzheimer Research
Title:Functional Connectivity Hubs Could Serve as a Potential Biomarker in Alzheimer’s Disease: A Reproducible Study
Volume: 12 Issue: 10
Author(s): Xiuchao Sui, Maohu Zhu, Yue Cui, Chunshui Yu, Jing Sui, Xinqing Zhang, Jieqiong Liu, Yunyun Duan, Zengqiang Zhang, Luning Wang, Xi Zhang and Tianzi Jiang
Affiliation:
Keywords: Alzheimer’s disease, biomarker, classification, functional connectivity density, mild cognitive impairment, resting state functional MRI.
Abstract: Cortical hubs that link functionally specialized neural systems are crucial for cognition. Evidence suggests that the location and organization of hubs are related to Alzheimer’s disease (AD). However, two issues remain unclear: (i) where and how hubs change in AD, and (ii) whether hubs could be a potential pre-diagnosis biomarker for mild cognitive impairment (MCI) - a prodromal phase of AD. Accordingly, we examined the functional connectivity density (FCD) in two cohorts of resting-state functional magnetic resonance imaging (fMRI) scans (26 AD, 27 controls; 33 AD, 21 controls) and revealed consistently vulnerable FCD hub regions in AD compared with controls: within the default mode network, short-range FCD decreases in the posterior cingulate cortex and increases in the medial prefrontal cortex; within the frontal lobe, long-range FCD increases in the medial prefrontal cortex, superior frontal gyrus and middle frontal gyrus. Furthermore, FCD correlates with cognitive score and could distinguish MCI from controls with high accuracy (71.08% in dataset 1, 81% in dataset 2). By reflecting a robust and reproducible global shift in brain functions, FCD provides an fMRI biomarker for the underlying mechanism in AD.
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Cite this article as:
Sui Xiuchao, Zhu Maohu, Cui Yue, Yu Chunshui, Sui Jing, Zhang Xinqing, Liu Jieqiong, Duan Yunyun, Zhang Zengqiang, Wang Luning, Zhang Xi and Jiang Tianzi, Functional Connectivity Hubs Could Serve as a Potential Biomarker in Alzheimer’s Disease: A Reproducible Study, Current Alzheimer Research 2015; 12 (10) . https://dx.doi.org/10.2174/1567205012666150710111615
DOI https://dx.doi.org/10.2174/1567205012666150710111615 |
Print ISSN 1567-2050 |
Publisher Name Bentham Science Publisher |
Online ISSN 1875-5828 |
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Aims and Scope: Introduction: Alzheimer's disease (AD) poses a significant global health challenge, with an increasing prevalence that demands concerted efforts to advance our understanding and strategies for prevention, diagnosis, treatment, and rehabilitation. This thematic issue aims to bring together cutting-edge research and innovative approaches from multidisciplinary perspectives to address ...read more
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Alzheimer's disease (AD) poses a significant global health challenge, with an increasing number of individuals affected yearly. Deep learning, a subfield of artificial intelligence, has shown immense potential in various domains, including healthcare. This thematic issue of Current Alzheimer Research explores the application of deep learning techniques in advancing our ...read more
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