Cognitive reserve moderates the functional connectivity changes in resting-state
Creators: name: Ersoezlue, Ersin
name: Boris-Stephan Rauchmann
name: Peters, Oliver
name: J Priller
name: Schneider, Anja
name: Ramirez, Alfredo
name: Wiltfang, Jens
name: Jessen, Frank
name: Buerger, Katharina
name: Teipel, Stefan
name: Laske, Christoph
name: Spottke, Annika
name: Wagner, Michael
name: Blanco, Arturo Cardenas
name: Duezel, Emrah
name: Perneczky, Robert
Publisher: name: F1000 Research Limited
Year: 2021

description: <b>Background: </b>Cognitive reserve (CR) refers to the adaptability of cognitive processes that can explain the individual differences in cognition relative to brain aging or neurodegenerative changes. Recently, various studies tried to quantify a marker that represents CR. Among others, the residual approach suggested being relatively reliable as it has been studied not only with cross-sectional but also with longitudinal observations. However, it is unknown how and which changes in functional network structures in the resting-state are related to cognitive reserve.<br> <b>Methods: </b>In the present study we defined a CR Marker based on residuals calculated through a multimodal (multi-linear) regression model adapted from a recent study using magnetic resonance imaging (MRI) derived cortical thickness of vulnerable regions related to the pathology of Alzheimer’s Disease (AD) and hippocampal volume, genetic and sociodemographic information as predictors (<b>Fig. 1</b>). The data of 818 participants including healthy controls and with subjective cognitive decline (SCD), patients with mild cognitive impairment (MCI), and AD from the German multicentric DELCODE cohort was assessed (<b>Table 1</b>). To examine neural substrates of defined CR marker, we constructed a weighted undirected partial correlation matrix using the brain connectivity toolbox implemented in the CONN and analyzed graph-theoretical metrics in GraphVar toolbox following the removal of negative weights in global and nodal topography with various cut-off threshold values. False discovery rate (FDR) are conducted in the analysis on the nodal level.<br> We examined the possible associations between CR and alterations in functional connectivity. The following list of metrics has been calculated at a global level: (1) <i>global transitivity</i>, (2) <i>global efficiency</i>, (3) <i>modularity</i> under the Louvain method. Then on the local level: (1) <i>local efficiency</i>, (2) normalized <i>clustering coefficient</i>, (3) <i>betweenness centrality</i>, and (4) <i>degree</i>. The analyses were conducted both in the whole network and within the default-mode network (DMN) by separating the belonging nodes according to resting-state networks defined in Brainnetome-Atlas<sup> </sup>(BN-Atlas).<br> <br> <b>Results: </b>CR Marker was positively correlated (r=0.35, p&lt;0.001) with higher years of formal education, adjusting for age, gender, and APOE e4 allele-status. In the graph-theory based analysis of connectivity changes in resting-state-functional-MRI using a region of interest (ROI) based approach utilizing parcellations of the BN-Atlas, we demonstrated that CR marker is significantly interacting with the diagnosis in a general linear model with the graph measures of <i>global efficiency (p&lt;0.05)</i> and <i>modularity (p&lt;0.05) of DMN </i>(<b>Table 2, Fig. 2</b>).<br> We adjusted the models for age, gender, imaging site, and APOE e4 allele status.<br> On the local level, however, nodes that belong particularly to DMN and cognitive task-related networks such as salience, frontoparietal, and dorsal attention networks show a significant interaction (false discovery rate-corrected alpha level &lt;0.05) that are summarized in <b>Table 3</b>. In a further analysis on the nodal level within DMN, the latent CR-marker and diagnosis interact in terms of <i>degree </i>and <i>local efficiency in </i>frontal regions and in terms of betweenness centrality in the temporal lobe.<br> These results indicating that CR moderates the effect of the disease stage on network features evaluated by using graph theory both on global and local topographies within DMN. Moreover, the interaction is observable also in nodes belong to other resting-state networks in various measures.<br> <br> <b>Discussion:</b> It was suggested that CR is associated with a higher ability of the brain to form more efficient functional networks by optimizing the balance between integration and segregation. Our analysis focused on changes in AD by examining the participants in the spectrum of AD with individually obtained latent CR Marker and we revealed comparable results on the local level with previous studies that examined effects of CR on graph theoretical measures. However, we found interaction on global topography only within DMN in measures of both integrity i.e. <i>efficiency,</i> and segregation i.e. <i>modularity</i>. Considering previous findings, we assume that the moderation of CR is associated with more efficient network structures which are more prominent in DMN. These findings can foster understanding of the functional network alterations in AD and will be useful to help identify individuals with vulnerability or resistance to AD pathology and characterize patients for intervention or drug trials.