ORIGINAL RESEARCH published: 13 December 2018 doi: 10.3389/fnagi.2018.00404 Alterations in Brain Network Topology and Structural-Functional Connectome Coupling Relate to Cognitive Impairment Juan Wang 1†, Reza Khosrowabadi 1,2†, Kwun Kei Ng 1†, Zhaoping Hong 1, Joanna Su Xian Chong 1, Yijun Wang 1, Chun-Yin Chen 1, Saima Hilal 3, Narayanaswamy Venketasubramanian 4, Tien Yin Wong 5,6, Christopher Li-Hsian Chen 3‡, Mohammad Kamran Ikram 3,5,6,7‡ and Juan Zhou 1,8*‡ 1 Center for Cognitive Neuroscience, Neuroscience and Behavioral Disorders Program, Duke-National University of Singapore Medical School, Singapore, Singapore, 2 Institute for Cognitive and Brain Sciences, Shahid Beheshti University, Tehran, Iran, Edited by: 3 Department of Pharmacology, National University of Singapore, Singapore, Singapore, 4 Neuroscience Clinic, Raffles Agustin Ibanez, Hospital, Singapore, Singapore, 5 Memory Aging & Cognition Centre, National University Health System, Singapore, Institute of Cognitive and Translational Singapore, 6 Singapore National Eye Centre, Singapore Eye Research Institute, Singapore, Singapore, 7 Department of Neuroscience (INCYT), Argentina Neurology, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, Netherlands, 8 Clinical Imaging Research Reviewed by: Centre, The Agency for Science, Technology and Research-National University of Singapore, Singapore, Singapore Yong Liu, Institute of Automation (CAS), China Pierpaolo Sorrentino, According to the network-based neurodegeneration hypothesis, neurodegenerative Università degli Studi di Napoli diseases target specific large-scale neural networks, such as the default mode network, Parthenope, Italy and may propagate along the structural and functional connections within and between *Correspondence: these brain networks. Cognitive impairment no dementia (CIND) represents an early Juan Zhou [email protected] prodromal stage but few studies have examined brain topological changes within and between brain structural and functional networks. To this end, we studied the structural †These authors have contributed equally to this work networks [diffusion magnetic resonance imaging (MRI)] and functional networks (task-free ‡share senior authorship functional MRI) in CIND (61 mild, 56 moderate) and healthy older adults (97 controls). Structurally, compared with controls, moderate CIND had lower global efficiency, and Received: 09 May 2018 lower nodal centrality and nodal efficiency in the thalamus, somatomotor network, and Accepted: 23 November 2018 Published: 13 December 2018 higher-order cognitive networks. Mild CIND only had higher nodal degree centrality in Citation: dorsal parietal regions. Functional differences were more subtle, with both CIND groups Wang J, Khosrowabadi R, Ng KK, showing lower nodal centrality and efficiency in temporal and somatomotor regions. Hong Z, Chong JSX, Wang Y, Importantly, CIND generally had higher structural-functional connectome correlation Chen C-Y, Hilal S, Venketasubramanian N, Wong TY, than controls. The higher structural-functional topological similarity was undesirable as Chen C-H, Ikram MK and Zhou J higher correlation was associated with poorer verbal memory, executive function, and (2018) Alterations in Brain Network Topology and Structural-Functional visuoconstruction. Our findings highlighted the distinct and progressive changes in brain Connectome Coupling Relate to structural-functional networks at the prodromal stage of neurodegenerative diseases. Cognitive Impairment. Front. Aging Neurosci. 10:404. Keywords: cognitive impairment no dementia, functional connectome, structural connectome, doi: 10.3389/fnagi.2018.00404 structural-functional coupling, task-free fMRI, diffusion tensor imaging (DTI) Frontiers in Aging Neuroscience | www.frontiersin.org 1 December 2018 | Volume 10 | Article 404 Wang et al. Brain Connectome in Cognitive Impairment INTRODUCTION to lose their hub-like character in AD and MCI compared to healthy controls (Buckner et al., 2009; Brier et al., 2014) and Neurodegenerative diseases target large-scale neural networks was associated with cognitive deficits (Reijmer et al., 2013; Dicks (Braak and Braak, 1991; Seeley et al., 2009; Zhou et al., 2012; et al., 2018). Nevertheless, few studies have compared structural Wang et al., 2015b). Networks, such as the default mode and functional network patterns at different stages of MCI or network, dorsal attention network, and the salience network have CIND (Wang et al., 2011, 2012). A recent study in MCI patients been shown to be “epicenters” of different dementia subtypes, revealed that the intra- and inter-network functional connectivity with the differential involvement of these networks closely tied disruptions were more profound in late MCI compared to the with the symptomatic differences across subtypes, and can be early MCI patients (Zhan et al., 2016). Similar to the MCI contrasted with normal age-related brain network degradation classification, work on the topological changes in both structural (Zhou and Seeley, 2014; Chong et al., 2017; Chhatwal et al., and functional connectome underlying CIND cognitive decline 2018). These observations have served as the solid foundation remains largely unknown (Zhu et al., 2014). of the network-based selective vulnerability hypothesis (Seeley Recent work has found that structural connectivity could et al., 2009; Greicius and Kimmel, 2012). Transneuronal spread shape and impose constraints on the pattern of functional model is one possible mechanism in which disease agents, such connectivity in health (Hagmann et al., 2010; Goni et al., 2014). as tau and amyloid would transmit through neural pathways Both human and animal studies have shown that the functional characterized by functional and/or structural relationship instead connectome (FC) at the unconscious state is more similar to of spatial proximity between brain regions (Greicius and SC (Barttfeld et al., 2015) and time spent in the more SC-like Kimmel, 2012; Raj et al., 2012; Zhou et al., 2012). Human state is associated with poorer vigilance task performance (Wang brain neural networks have been directly probed by structural et al., 2016). On the other hand, FC patterns can also in turn connectivity derived from diffusion tensor imaging (DTI) and reflect underlying structural architecture in health and disease functional connectivity derived from task-free or resting-state (Greicius et al., 2009; Wang F. et al., 2009; Zhang et al., 2014; functional magnetic resonance imaging (fMRI) (Wang et al., Vecchio et al., 2015). More importantly, the structural-functional 2015b; Teipel et al., 2016; Zhou et al., 2017). Converging relationships of large-scale brain networks may be disrupted in neuroimaging evidence from our group and others have shown disease (Hagmann et al., 2010; Wang et al., 2015a) and the two syndrome-specific structural and functional network disruptions might interact to relate to cognitive deficits (Qiu et al., 2016). in Alzheimer’s disease (AD) and other types of neurodegenerative Yet, brain network SC-FC coupling changes at the system-level disorders (Greicius et al., 2004; He et al., 2009; Zhou et al., in mild and moderate CIND individuals needs to be established. 2010; Zhou and Seeley, 2014), highlighting the valuable To this end, we compared the brain SC and FC in individuals insights of understanding these disorders with a network-based with mild CIND (two or fewer domain deficits), moderate CIND approach. Applied on both whole-brain structural and functional (multi-domain deficits), and no cognitive impairment (NCI) connectivity data (connectomes), graph theoretical measures using graph theoretical approach (Rubinov and Sporns, 2010). characterize complex brain neural network topology and quantify We hypothesized that moderate CIND rather than mild CIND network integration, modularity, or efficient communications would exhibit greater deterioration in SC and FC, such as using both nodal and global indices (Bullmore and Sporns, 2009; reduced global and nodal efficiency, compared to NCI. Moreover, Rubinov and Sporns, 2010), and has been an exellent tool for given previous findings on the close association of high SC-FC probing brain structural and functional networks perturbed by similarity with reduced consciousness and lower vigilance, we neurodegnerative disorders (Stam, 2014). expected that CIND (moderate rather than mild) would have Considerable effort has been devoted to better understand higher SC-FC coupling than NCI and such changes would be the changes in neural network topology and its associations associated with cognitive impairment. with symptoms manifestation in prodromal stages of dementia, such as participants with mild cognitive impairment (MCI) MATERIALS AND METHODS and cognitive impairment no dementia (CIND) (Hughes et al., 2011; Karantzoulis and Galvin, 2011). In prodromal and clinical Participants AD, the structural connectome (SC) exhibits altered topological Participants were drawn from the ongoing Epidemiology of network metrics, such as increased shortest path lengths and Dementia in Singapore study (Hilal et al., 2013), which is part decreased local and global efficiency (Lo et al., 2010; Bai of the Singapore Epidemiology of Eye Disease study (Huang et al., 2012b; Shao et al., 2012). In parallel, similar functional et al., 2015). The present analysis was restricted to the Chinese connectomic disruptions have been reported in prodromal AD component of the Epidemiology of Dementia in Singapore study, (Greicius et al., 2004;