AUTHOR=Xiao Yaqiong , Gao Lei , Hu Yubin ,  The Alzheimer’s Disease Neuroimaging Initiative 

TITLE=Disrupted single-subject gray matter networks are associated with cognitive decline and cortical atrophy in Alzheimer’s disease

JOURNAL=Frontiers in Neuroscience

VOLUME=Volume 18 - 2024

YEAR=2024

URL=https://www.frontiersin.org/journals/neuroscience/articles/10.3389/fnins.2024.1366761

DOI=10.3389/fnins.2024.1366761

ISSN=1662-453X

ABSTRACT=Background: Research has shown disrupted structural network measures related to cognitive decline and future cortical atrophy during the progression of Alzheimer’s disease (AD). However, evidence is still sparse regarding the individual variability of grey matter network measures and the associations with concurrent cognitive decline and cortical atrophy related to AD. 
Objective: To investigate whether alterations in single-subject grey matter networks are related to concurrent cognitive decline and cortical grey matter atrophy during AD progression.
Methods: We analyzed structural MRI data from 185 cognitively normal (CN), 150 MCI, and 153 AD participants, and calculated the global network metrics of grey matter networks for each participant. We examined the alterations of single-subject grey matter networks in mild cognitive impairment (MCI) and AD patients, and examined the associations of network metrics with concurrent cognitive decline and cortical grey matter atrophy. 
Results: The small-world properties including gamma, lambda, and sigma had lower values in the MCI and AD groups than the CN group. AD patients had reduced degree, connectivity density, clustering coefficient, and path length than the CN and MCI (except for connectivity density) groups. We observed significant associations of cognitive ability with degree in the CN group, with gamma and sigma in the MCI group, and with degree, connectivity density, clustering coefficient, and path length in the AD group. There were significant correlation patterns between sigma values and cortical grey matter volume in the CN, MCI, and AD groups. 
Conclusion: These findings suggest the individual variability of grey matter network metrics may be valuable to track concurrent cognitive decline and cortical atrophy during AD progression, which may contribute to a better understanding of cognitive decline and brain morphological alterations related to AD.