1
|
Villeda S, Brown-Borg H, Anderson R. Neurobiology of Aging: New Insights From Across the Research Spectrum. J Gerontol A Biol Sci Med Sci 2023; 78:869-871. [PMID: 37264524 PMCID: PMC10465077 DOI: 10.1093/gerona/glad110] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/03/2023] Open
Affiliation(s)
- Saul Villeda
- Department of Anatomy, University of California San Francisco, San Francisco, California, USA
- Bakar Aging Research Institute, San Francisco, California, USA
| | - Holly Brown-Borg
- Department of Biomedical Sciences, University of North Dakota, Grand Forks, North Dakota, USA
| | - Rozalyn Anderson
- Department of Medicine, SMPH, University of Wisconsin-Madison, Madison, Wisconsin, USA
- GRECC William S Middleton Memorial Veterans Hospital, Madison, Wisconsin, USA
| |
Collapse
|
2
|
Casanova R, Anderson AM, Barnard RT, Justice JN, Kucharska-Newton A, Windham BG, Palta P, Gottesman RF, Mosley TH, Hughes TM, Wagenknecht LE, Kritchevsky SB. Is an MRI-derived anatomical measure of dementia risk also a measure of brain aging? GeroScience 2023; 45:439-450. [PMID: 36050589 PMCID: PMC9886771 DOI: 10.1007/s11357-022-00650-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2022] [Accepted: 08/22/2022] [Indexed: 02/03/2023] Open
Abstract
Machine learning methods have been applied to estimate measures of brain aging from neuroimages. However, only rarely have these measures been examined in the context of biologic age. Here, we investigated associations of an MRI-based measure of dementia risk, the Alzheimer's disease pattern similarity (AD-PS) scores, with measures used to calculate biological age. Participants were those from visit 5 of the Atherosclerosis Risk in Communities Study with cognitive status adjudication, proteomic data, and AD-PS scores available. The AD-PS score estimation is based on previously reported machine learning methods. We evaluated associations of the AD-PS score with all-cause mortality. Sensitivity analyses using only cognitively normal (CN) individuals were performed treating CNS-related causes of death as competing risk. AD-PS score was examined in association with 32 proteins measured, using a Somalogic platform, previously reported to be associated with age. Finally, associations with a deficit accumulation index (DAI) based on a count of 38 health conditions were investigated. All analyses were adjusted for age, race, sex, education, smoking, hypertension, and diabetes. The AD-PS score was significantly associated with all-cause mortality and with levels of 9 of the 32 proteins. Growth/differentiation factor 15 (GDF-15) and pleiotrophin remained significant after accounting for multiple-testing and when restricting the analysis to CN participants. A linear regression model showed a significant association between DAI and AD-PS scores overall. While the AD-PS scores were created as a measure of dementia risk, our analyses suggest that they could also be capturing brain aging.
Collapse
Affiliation(s)
- Ramon Casanova
- Department of Biostatistics and Data Science, Wake Forest School of Medicine, Winston-Salem, NC, USA.
| | - Andrea M Anderson
- Department of Biostatistics and Data Science, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Ryan T Barnard
- Department of Biostatistics and Data Science, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Jamie N Justice
- Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | | | | | - Priya Palta
- School of Public Health, Columbia University, New York, NY, USA
| | | | | | - Timothy M Hughes
- Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Lynne E Wagenknecht
- Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Stephen B Kritchevsky
- Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, NC, USA
| |
Collapse
|