GREY MATTER CONNECTIVITY TRAJECTORIES ACROSS THE ALZHEIMER’S DISEASE CONTINUUM AND ASSOCIATIONS WITH COGNITIVE DECLINE

Abstract

not available. SATURDAY, JULY 13, 2019 ALZHEIMER’S IMAGING CONSORTIUM PODIUM PRESENTATIONS IC-02 LONGITUDINAL IMAGING IC-02-01 GREY MATTER CONNECTIVITY TRAJECTORIES ACROSS THE ALZHEIMER’S DISEASE CONTINUUM AND ASSOCIATIONS WITH COGNITIVE DECLINE Ellen Dicks, Wiesje M. van der Flier, Frederik Barkhof, Philip Scheltens, Betty M. Tijms, Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, Netherlands; Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, Netherlands; Institutes of Neurology and Healthcare Engineering, UCL, London, United Kingdom; Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, Netherlands. Contact e-mail: [email protected] Background: For the development of therapies measures are needed to monitor disease progression in Alzheimer’s disease (AD). Grey matter connectivity is disrupted in AD, manifesting already in preclinical stages due to aggregating amyloid, and is related to disease progression in predementia AD. It remains unclear, how these disruptions evolve over time and whether they translate to cognitive decline within individuals across the disease continuum. Methods: We included 150 amyloid negative, cognitively normal participants as controls (CN-) and 462 individuals with abnormal amyloid PET/CSF (75 preclinical AD, 272 prodromal AD, 115 AD dementia) who had repeatedMRI available (total MRIs: 3253; median [IQR]; 5[4-6] MRIs per subject over 2.1[2-4] years) (Table 1) from ADNI. Grey matter networks were extracted from all 3D-T1 structural MRIs and connectivity density, clustering, path length and normalized clustering (gamma) were calculated. Measures were standardized to baseline values of the CNgroup. We investigated with linear mixed models how network measures changed over time and whether these changes were related to decline on the MMSE. Analyses were adjusted for age, gender, education and intracranial volume and stratified by disease stage. Results: Over time, all individuals worsened on the MMSE (Table 2). All network measures declined over time in all groups, with steepest decline in gamma (Table 2, Figure 1). Decline in network measures tended to accelerate with increasing disease severity, although this difference was only significant for clustering (p<0.05) and gamma (p<0.001) in prodromal AD compared to preclinical AD. In all disease stages, we observed that decline in path length was associated with decline on the MMSE, and this association became stronger for more advanced disease stages (Table 3). In prodromal AD and AD dementia all network measures were associated with cognitive decline, with strongest effects for gamma (Table 3). Conclusions: Network measures declined over time across the AD continuum, and decline accelerated for more advanced disease stages. Within individuals, decline in path length was correlated with decline on MMSE across the AD clinical spectrum, suggesting that changes in grey matter connectivity may track a broad span in cognition from normal to dementia, and might have use for disease progression monitoring.