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Hippocampus-centred Grey Matter Covariance Networks Predict the Development and Reversion of Mild Cognitive Impairment by Mingxi Dang; Caishui Yang; Kewei Chen; Peng Lu; He Li; Zhanjun Zhang is a Medicine article available to read on EtoBox.

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Abstract Background Mild cognitive impairment (MCI) has been thought of as the transitional stage between normal ageing and Alzheimer’s disease, involving substantial changes in brain grey matter structures. As most previous studies have focused on single regions (e.g. the hippocampus) and their changes during MCI development and reversion, the relationship between grey matter covariance among distributed brain regions and clinical development and reversion of MCI remains unclear. Methods With samples from two independent studies (155 from the Beijing Aging Brain Rejuvenation Initiative and 286 from the Alzheimer’s Disease Neuroimaging Initiative), grey matter covariance of default, frontoparietal, and hippocampal networks were identified by seed-based partial least square analyses, and random forest models were applied to predict the progression from normal cognition to MCI (N-t-M) and the reversion from MCI to normal cognition (M-t-N). Results With varying degrees, the grey matter covariance in the three networks could predict N-t-M progression (AUC = 0.692–0.792) and M-t-N reversion (AUC = 0.701–0.809). Further analyses indicated that the hippocampus has emerged as an important

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Author

Mingxi Dang; Caishui Yang; Kewei Chen; Peng Lu; He Li; Zhanjun Zhang

Publisher

Springer Science and Business Media LLC

Published

2023

Language

EN

Field

Medicine (Health Sciences)