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Popov M, Molsberry SA, Lecci F, Junker B, Kingsley LA, Levine A, Martin E, Miller E, Munro CA, Ragin A, Seaberg E, Sacktor N, Becker JT. Brain structural correlates of trajectories to cognitive impairment in men with and without HIV disease. Brain Imaging Behav 2020; 14:821-829. [PMID: 30623289 PMCID: PMC6616021 DOI: 10.1007/s11682-018-0026-7] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
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.
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Affiliation(s)
- Mikhail Popov
- Department of Psychiatry, University of Pittsburgh, Suite 830, 3501 Forbes Avenue, Pittsburgh, PA, 15213, USA
- Wikimedia Foundation, San Francisco, CA, USA
| | - Samantha A Molsberry
- Department of Psychiatry, University of Pittsburgh, Suite 830, 3501 Forbes Avenue, Pittsburgh, PA, 15213, USA
- Population Health Sciences, Harvard University, Cambridge, MA, USA
| | - Fabrizio Lecci
- Department of Statistics, Carnegie Mellon University, Pittsburgh, PA, USA
- Uber, New York, NY, USA
| | - Brian Junker
- Department of Statistics, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Lawrence A Kingsley
- Department of Infectious Diseases and Microbiology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Andrew Levine
- Department of Neurology, University of California Los Angeles, Los Angeles, CA, USA
| | - Eileen Martin
- Department of Psychiatry, Rush Medical School, Chicago, IL, USA
| | - Eric Miller
- Department of Psychiatry, University of California Los Angeles, Los Angeles, CA, USA
| | - Cynthia A Munro
- Department of Psychiatry, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Neurology, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Ann Ragin
- Department of Radiology, Northwestern University, Evanston, IL, USA
| | - Eric Seaberg
- Department of Epidemiology, The Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Ned Sacktor
- Department of Neurology, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - James T Becker
- Department of Psychiatry, University of Pittsburgh, Suite 830, 3501 Forbes Avenue, Pittsburgh, PA, 15213, USA.
- Department of Neurology, University of Pittsburgh, Pittsburgh, PA, USA.
- Department of Psychology, University of Pittsburgh, Pittsburgh, PA, USA.
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