Topological Changes Of Morphological Brain Networks Across Aging

INTRODUCTION: Previous studies have shown that both functional and structural brain networks exhibit dynamic topological reorganization across aging.Compared with functional and structural brain networks,accumulating evidence indicates that morphological brain networks possess unique topological organization,and thus are complementary to functional and structural brain networks to fully characterize organizational principles governing the brain.However,little is known regarding how morphological brain networks dynamically reorganize across aging.Here,we used a single-subject morphological brain network method to systematically investigate the aging trajectory of the topological organization of morphological brain networks based on a large adult cohort from the Cambridge Centre for Ageing and Neuroscience.METHODS: A total of 650 participants(aged from 18 to 88 years)were included in this study.Individual morphological brain networks were constructed by calculating the Jensen-Shannon distance-based connectivity,which measures interregional similarity between the distribution of regional morphological indices(fractal dimension,gyrification index,sulcus depth and cortical thickness in the current study).Graph-based global(clustering coefficient,shortest path length,local efficiency,global efficiency and modularity)and nodal(degree,efficiency and betweenness)network measures,hub disruption index,and average strength of different types of connections were then calculated,followed by multiple general linear models to infer their relationships with age.Finally,we explored the mediating role of brain measures in aging and decline of intelligence.RESULTS: Significant aging effects were found for all types of morphological brain networks,in particular cortical thickness-based networks,at all topological levels.Specifically,at the global level,we found that the clustering coefficient of the fractal dimension-,sulcus depth-and cortical thickness-based networks,the local efficiency of sulcus depth-and cortical thickness-based networks,and the modularity of fractal dimensionand gyrification index-based networks showed aging effects.Moreover,the aging trajectories were different among different types of networks.Notably,all global measures of cortical thickness-based networks exhibited significant aging effects.In addition,fractal dimension-,gyrification index-and cortical thickness-based networks exhibited hub reorganization across aging and the reorganization consistently showed cubic trajectory with 40,50 and 60 as three key turning points.To gain insights into the aging effects on global network organization,we further characterized aging effects on hub-related connectivity strength and nodal centrality.We found that non-hub-related connectivity strength decreased linearly with age in fractal dimension-based networks,and hub-related connectivity strength increased linearly in sulcus depth-based networks and decreased linearly in cortical thickness-based networks.At the nodal level,significant aging-related changes were consistently found in the anterior cingulate cortex,prefrontal cortex,superior temporal gyrus,superior frontal gyrus,precentral gyrus,postcentral gyrus and central sulcus for gyrification index-,sulcus depth-and cortical thickness-based networks.Finally,we found that nodal degree of right orbitofrontal cortex in fractal dimension-based networks and the reorganization of cortical thickness-based networks were positively correlated with intelligence after correcting for age.Conclusion: This study systematically characterizes aging-related topological reorganization in single-level morphological brain networks.The results show that the reorganization is salient in cortical thickness-based networks with a pattern of cubic aging effect.Moreover,this reorganization of cortical thickness-based networks plays an important role in aging-related decline in global cognitive function.