Regional covariance of white matter hyperintensity volume patterns associated with hippocampal volume in healthy aging
Hippocampal volume is particularly sensitive to the accumulation of total brain white matter hyperintensity volume (WMH) in aging, but how the regional distribution of WMH volume differentially impacts the hippocampus has been less studied. In a cohort of 194 healthy older adults ages 50–89, we used...
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| 语言: | English |
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Frontiers Media S.A.
2024-03-01
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| 丛编: | Frontiers in Aging Neuroscience |
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| 在线阅读: | https://www.frontiersin.org/articles/10.3389/fnagi.2024.1349449/full |
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| author | Emily J. Van Etten Emily J. Van Etten Pradyumna K. Bharadwaj Pradyumna K. Bharadwaj Matthew D. Grilli Matthew D. Grilli Matthew D. Grilli David A. Raichlen David A. Raichlen Georg A. Hishaw Matthew J. Huentelman Matthew J. Huentelman Matthew J. Huentelman Theodore P. Trouard Theodore P. Trouard Theodore P. Trouard Gene E. Alexander Gene E. Alexander Gene E. Alexander Gene E. Alexander Gene E. Alexander Gene E. Alexander |
| author_facet | Emily J. Van Etten Emily J. Van Etten Pradyumna K. Bharadwaj Pradyumna K. Bharadwaj Matthew D. Grilli Matthew D. Grilli Matthew D. Grilli David A. Raichlen David A. Raichlen Georg A. Hishaw Matthew J. Huentelman Matthew J. Huentelman Matthew J. Huentelman Theodore P. Trouard Theodore P. Trouard Theodore P. Trouard Gene E. Alexander Gene E. Alexander Gene E. Alexander Gene E. Alexander Gene E. Alexander Gene E. Alexander |
| author_sort | Emily J. Van Etten |
| collection | DOAJ |
| description | Hippocampal volume is particularly sensitive to the accumulation of total brain white matter hyperintensity volume (WMH) in aging, but how the regional distribution of WMH volume differentially impacts the hippocampus has been less studied. In a cohort of 194 healthy older adults ages 50–89, we used a multivariate statistical method, the Scaled Subprofile Model (SSM), to (1) identify patterns of regional WMH differences related to left and right hippocampal volumes, (2) examine associations between the multimodal neuroimaging covariance patterns and demographic characteristics, and (3) investigate the relation of the patterns to subjective and objective memory in healthy aging. We established network covariance patterns of regional WMH volume differences associated with greater left and right hippocampal volumes, which were characterized by reductions in left temporal and right parietal WMH volumes and relative increases in bilateral occipital WMH volumes. Additionally, we observed lower expression of these hippocampal-related regional WMH patterns were significantly associated with increasing age and greater subjective memory complaints, but not objective memory performance in this healthy older adult cohort. Our findings indicate that, in cognitively healthy older adults, left and right hippocampal volume reductions were associated with differences in the regional distribution of WMH volumes, which were exacerbated by advancing age and related to greater subjective memory complaints. Multivariate network analyses, like SSM, may help elucidate important early effects of regional WMH volume on brain and cognitive aging in healthy older adults. |
| first_indexed | 2024-04-25T01:42:05Z |
| format | Article |
| id | doaj.art-61d96f3f69ff49b89b51d46b436b5c3d |
| institution | Directory Open Access Journal |
| issn | 1663-4365 |
| language | English |
| last_indexed | 2024-04-25T01:42:05Z |
| publishDate | 2024-03-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Aging Neuroscience |
| spelling | doaj.art-61d96f3f69ff49b89b51d46b436b5c3d2024-03-08T04:23:11ZengFrontiers Media S.A.Frontiers in Aging Neuroscience1663-43652024-03-011610.3389/fnagi.2024.13494491349449Regional covariance of white matter hyperintensity volume patterns associated with hippocampal volume in healthy agingEmily J. Van Etten0Emily J. Van Etten1Pradyumna K. Bharadwaj2Pradyumna K. Bharadwaj3Matthew D. Grilli4Matthew D. Grilli5Matthew D. Grilli6David A. Raichlen7David A. Raichlen8Georg A. Hishaw9Matthew J. Huentelman10Matthew J. Huentelman11Matthew J. Huentelman12Theodore P. Trouard13Theodore P. Trouard14Theodore P. Trouard15Gene E. Alexander16Gene E. Alexander17Gene E. Alexander18Gene E. Alexander19Gene E. Alexander20Gene E. Alexander21Department of Psychology, University of Arizona, Tucson, AZ, United StatesEvelyn F. McKnight Brain Institute, University of Arizona, Tucson, AZ, United StatesDepartment of Psychology, University of Arizona, Tucson, AZ, United StatesEvelyn F. McKnight Brain Institute, University of Arizona, Tucson, AZ, United StatesDepartment of Psychology, University of Arizona, Tucson, AZ, United StatesEvelyn F. McKnight Brain Institute, University of Arizona, Tucson, AZ, United StatesDepartment of Neurology, University of Arizona, Tucson, AZ, United StatesHuman and Evolutionary Biology Section, Department of Biological Sciences, University of Southern California, Los Angeles, CA, United StatesDepartment of Anthropology, University of Southern California, Los Angeles, CA, United StatesDepartment of Neurology, University of Arizona, Tucson, AZ, United StatesEvelyn F. McKnight Brain Institute, University of Arizona, Tucson, AZ, United StatesNeurogenomics Division, The Translational Genomics Research Institute (TGen), Phoenix, AZ, United StatesArizona Alzheimer’s Consortium, Phoenix, AZ, United StatesEvelyn F. McKnight Brain Institute, University of Arizona, Tucson, AZ, United StatesArizona Alzheimer’s Consortium, Phoenix, AZ, United StatesDepartment of Biomedical Engineering, University of Arizona, Tucson, AZ, United StatesDepartment of Psychology, University of Arizona, Tucson, AZ, United StatesEvelyn F. McKnight Brain Institute, University of Arizona, Tucson, AZ, United StatesArizona Alzheimer’s Consortium, Phoenix, AZ, United StatesDepartment of Psychiatry, University of Arizona, Tucson, AZ, United States0Neuroscience Graduate Interdisciplinary Program, University of Arizona, Tucson, AZ, United States1Physiological Sciences Graduate Interdisciplinary Program, University of Arizona, Tucson, AZ, United StatesHippocampal volume is particularly sensitive to the accumulation of total brain white matter hyperintensity volume (WMH) in aging, but how the regional distribution of WMH volume differentially impacts the hippocampus has been less studied. In a cohort of 194 healthy older adults ages 50–89, we used a multivariate statistical method, the Scaled Subprofile Model (SSM), to (1) identify patterns of regional WMH differences related to left and right hippocampal volumes, (2) examine associations between the multimodal neuroimaging covariance patterns and demographic characteristics, and (3) investigate the relation of the patterns to subjective and objective memory in healthy aging. We established network covariance patterns of regional WMH volume differences associated with greater left and right hippocampal volumes, which were characterized by reductions in left temporal and right parietal WMH volumes and relative increases in bilateral occipital WMH volumes. Additionally, we observed lower expression of these hippocampal-related regional WMH patterns were significantly associated with increasing age and greater subjective memory complaints, but not objective memory performance in this healthy older adult cohort. Our findings indicate that, in cognitively healthy older adults, left and right hippocampal volume reductions were associated with differences in the regional distribution of WMH volumes, which were exacerbated by advancing age and related to greater subjective memory complaints. Multivariate network analyses, like SSM, may help elucidate important early effects of regional WMH volume on brain and cognitive aging in healthy older adults.https://www.frontiersin.org/articles/10.3389/fnagi.2024.1349449/fullregional white matter hyperintensity volumehippocampal volumebrain agingsubjective memory complaintsscaled subprofile modelmultivariate analyses |
| spellingShingle | Emily J. Van Etten Emily J. Van Etten Pradyumna K. Bharadwaj Pradyumna K. Bharadwaj Matthew D. Grilli Matthew D. Grilli Matthew D. Grilli David A. Raichlen David A. Raichlen Georg A. Hishaw Matthew J. Huentelman Matthew J. Huentelman Matthew J. Huentelman Theodore P. Trouard Theodore P. Trouard Theodore P. Trouard Gene E. Alexander Gene E. Alexander Gene E. Alexander Gene E. Alexander Gene E. Alexander Gene E. Alexander Regional covariance of white matter hyperintensity volume patterns associated with hippocampal volume in healthy aging Frontiers in Aging Neuroscience regional white matter hyperintensity volume hippocampal volume brain aging subjective memory complaints scaled subprofile model multivariate analyses |
| title | Regional covariance of white matter hyperintensity volume patterns associated with hippocampal volume in healthy aging |
| title_full | Regional covariance of white matter hyperintensity volume patterns associated with hippocampal volume in healthy aging |
| title_fullStr | Regional covariance of white matter hyperintensity volume patterns associated with hippocampal volume in healthy aging |
| title_full_unstemmed | Regional covariance of white matter hyperintensity volume patterns associated with hippocampal volume in healthy aging |
| title_short | Regional covariance of white matter hyperintensity volume patterns associated with hippocampal volume in healthy aging |
| title_sort | regional covariance of white matter hyperintensity volume patterns associated with hippocampal volume in healthy aging |
| topic | regional white matter hyperintensity volume hippocampal volume brain aging subjective memory complaints scaled subprofile model multivariate analyses |
| url | https://www.frontiersin.org/articles/10.3389/fnagi.2024.1349449/full |
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