ObjectiveTo investigate the association between β-amyloid (Aβ) load and postmortem structural network topology in decedents without dementia.MethodsFourteen decedents (mean age at death 72.6 ± 7.2 years) without known clinical diagnosis of neurodegenerative disease and meeting pathology criteria only for no or low Alzheimer disease (AD) pathologic change were selected from the Normal Aging Brain Collection Amsterdam database. In situ brain MRI included 3D T1-weighted images for anatomical registration and diffusion tensor imaging for probabilistic tractography with subsequent structural network construction. Network topologic measures of centrality (degree), integration (global efficiency), and segregation (clustering and local efficiency) were calculated. Tissue sections from 12 cortical regions were sampled and immunostained for Aβ and hyperphosphorylated tau (p-tau), and histopathologic burden was determined. Linear mixed effect models were used to assess the relationship between Aβ and p-tau load and network topologic measures.ResultsAβ was present in 79% of cases and predominantly consisted of diffuse plaques; p-tau was sparsely present. Linear mixed effect models showed independent negative associations between Aβ load and global efficiency (β = −0.83 × 10−3, p = 0.014), degree (β = −0.47, p = 0.034), and clustering (β = −0.55 × 10−2, p = 0.043). A positive association was present between Aβ load and local efficiency (β = 3.16 × 10−3, p = 0.035). Regionally, these results were significant in the posterior cingulate cortex (PCC) for degree (β = −2.22, p < 0.001) and local efficiency (β = 1.01 × 10−2, p = 0.014) and precuneus for clustering (β = −0.91 × 10−2, p = 0.017). There was no relationship between p-tau and network topology.ConclusionThis study in deceased adults with AD-related pathologic change provides evidence for a relationship among early Aβ accumulation, predominantly of the diffuse type, and structural network topology, specifically of the PCC and precuneus.
Non-concave penalization in linear mixed-effect models and regularized selection of fixed effects
