Frontoparietal atrophy trajectories in cognitively unimpaired elderly individuals using longitudinal Bayesian clustering

被引：1
作者：
Lorenzon, G. [1 ]
Poulakis, K. [1 ]
Mohanty, R. [1 ]
Kivipelto, M. [1 ,2 ,3 ,4 ,5 ]
Eriksdotter, M. [1 ]
Ferreira, D. [1 ,6 ]
Westman, E. [1 ,7 ]
机构：
[1] Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Neo 7th floor, Huddinge
[2] Theme Inflammation and Aging, Karolinska University Hospital, Huddinge
[3] Institute of Public Health and Clinical Nutrition, University of Eastern Finland, P.O. Box 1627, Kuopio
[4] Ageing Epidemiology Research Unit, School of Public Health, Room 10L05
[5] Imperial College London, Charing Cross Hospital, St Dunstan's Road, London
[6] Department of Radiology, Mayo Clinic, Mayo Building West, 2nd Floor, 200 First St. SW, Rochester, 55905, MN
[7] Department of Neuroimaging, Centre for Neuroimaging Sciences, Institute of Psychiatry, Psychology and Neuroscience: King's College London, De Crespigny Park, London
来源：
Computers in Biology and Medicine | 2024年 / 182卷
基金：
美国国家卫生研究院;
关键词：
Aging; Atrophy; Clustering; Heterogeneity; Longitudinal; MRI;
D O I：
10.1016/j.compbiomed.2024.109190
中图分类号：
学科分类号：
摘要：
Introduction: Frontal and/or parietal atrophy has been reported during aging. To disentangle the heterogeneity previously observed, this study aimed to uncover different clusters of grey matter profiles and trajectories within cognitively unimpaired individuals. Methods: Structural magnetic resonance imaging (MRI) data of 307 Aβ-negative cognitively unimpaired individuals were modelled between ages 60–85 from three cohorts worldwide. We applied unsupervised clustering using a novel longitudinal Bayesian approach and characterized the clusters' cerebrovascular and cognitive profiles. Results: Four clusters were identified with different grey matter profiles and atrophy trajectories. Differences were mainly observed in frontal and parietal brain regions. These distinct frontoparietal grey matter profiles and longitudinal trajectories were differently associated with cerebrovascular burden and cognitive decline. Discussion: Our findings suggest a conciliation of the frontal and parietal theories of aging, uncovering coexisting frontoparietal GM patterns. This could have important future implications for better stratification and identification of at-risk individuals. © 2024 The Authors
引用
收藏
相关论文
共 79 条
  • [1] Peters R., Ageing and the brain, Postgrad. Med., 82, 964, pp. 84-88, (2006)
  • [2] Gur R.C., Gunning-Dixon F.M., Turetsky B.I., Bilker W.B., Gur R.E., Brain region and sex differences in age association with brain volume: a quantitative MRI study of healthy young adults, Am. J. Geriatr. Psychiatr., 10, 1, pp. 72-80, (2002)
  • [3] Hedman A.M., van Haren N.E.M., Schnack H.G., Kahn R.S., Hulshoff Pol H.E., Human brain changes across the life span: a review of 56 longitudinal magnetic resonance imaging studies, Hum. Brain Mapp., 33, 8, pp. 1987-2002, (2012)
  • [4] West R.L., An application of prefrontal cortex function theory to cognitive aging, Psychol. Bull., 120, 2, pp. 272-292, (1996)
  • [5] Greenwood P.M., The frontal aging hypothesis evaluated, J. Int. Neuropsychol. Soc., 6, 6, pp. 705-726, (2000)
  • [6] Good C.D., Johnsrude I.S., Ashburner J., Henson R.N.A., Friston K.J., Frackowiak R.S.J., A voxel-based morphometric study of ageing in 465 normal adult human brains, Neuroimage, 14, 1, pp. 21-36, (2001)
  • [7] Resnick S.M., Pham D.L., Kraut M.A., Zonderman A.B., Davatzikos C., Longitudinal magnetic resonance imaging studies of older adults: a shrinking brain, J. Neurosci.: The Official Journal of the Society for Neuroscience, 23, 8, pp. 3295-3301, (2003)
  • [8] Bennett I.J., Madden D.J., Vaidya C.J., Howard D.V., Howard J.H., Age-related differences in multiple measures of white matter integrity: a diffusion tensor imaging study of healthy aging, Hum. Brain Mapp., 31, 3, pp. 378-390, (2010)
  • [9] Jernigan T.L., Archibald S.L., Berhow M.T., Sowell E.R., Foster D.S., Hesselink J.R., Cerebral structure on MRI, Part I: localization of age-related changes, Biol. Psychiatr., 29, 1, pp. 55-67, (1991)
  • [10] MacDonald M.E., Pike G.B., MRI of healthy brain aging: a review, NMR Biomed., 34, 9, (2021)
12345678