| Literature DB >> 30623289 |
Mikhail Popov1,2, Samantha A Molsberry1,3, Fabrizio Lecci4,5, Brian Junker4, Lawrence A Kingsley6, Andrew Levine7, Eileen Martin8, Eric Miller9, Cynthia A Munro10,11, Ann Ragin12, Eric Seaberg13, Ned Sacktor11, James T Becker14,15,16.
Abstract
There are distinct trajectories to cognitive impairment among participants in the Multicenter AIDS Cohort Study (MACS). Here we analyzed the relationship between regional brain volumes and the individual trajectories to impairment in a subsample (n = 302) of the cohort. 302 (167 HIV-infected; mean age = 55.7 yrs.; mean education: 16.2 yrs.) of the men enrolled in the MACS MRI study contributed data to this analysis. We used voxel-based morphometry (VBM) to segment the brain images to analyze gray and white matter volume at the voxel-level. A Mixed Membership Trajectory Model had previously identified three distinct profiles, and each study participant had a membership weight for each of these three trajectories. We estimated VBM model parameters for 100 imputations, manually performed the post-hoc contrasts, and pooled the results. We examined the associations between brain volume at the voxel level and the MMTM membership weights for two profiles: one considered "unhealthy" and the other considered "Premature aging." The unhealthy profile was linked to the volume of the posterior cingulate gyrus/precuneus, the inferior frontal cortex, and the insula, whereas the premature aging profile was independently associated with the integrity of a portion of the precuneus. Trajectories to cognitive impairment are the result, in part, of atrophy in cortical regions linked to normal and pathological aging. These data suggest the possibility of predicting cognitive morbidity based on patterns of CNS atrophy.Entities:
Keywords: Brain structure; Dementia; HIV; Mixed membership trajectory; Multiple imputation
Mesh:
Year: 2020 PMID: 30623289 PMCID: PMC6616021 DOI: 10.1007/s11682-018-0026-7
Source DB: PubMed Journal: Brain Imaging Behav ISSN: 1931-7557 Impact factor: 3.978