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An accelerated degeneration of white matter microstructure and networks in the nondemented old-old.
Zhao, Haichao; Wen, Wei; Cheng, Jian; Jiang, Jiyang; Kochan, Nicole; Niu, Haijun; Brodaty, Henry; Sachdev, Perminder; Liu, Tao.
Afiliación
  • Zhao H; Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science and Medical Engineering, Beihang University, Beijing, China.
  • Wen W; Centre for Healthy Brain Ageing, School of Psychiatry (CHeBA), University of New South Wales, Sydney, NSW, Australia.
  • Cheng J; Neuropsychiatric Institute, Prince of Wales Hospital, Sydney, NSW, Australia.
  • Jiang J; School of Computer Science and Engineering, Beihang University, Beijing, China.
  • Kochan N; Centre for Healthy Brain Ageing, School of Psychiatry (CHeBA), University of New South Wales, Sydney, NSW, Australia.
  • Niu H; Centre for Healthy Brain Ageing, School of Psychiatry (CHeBA), University of New South Wales, Sydney, NSW, Australia.
  • Brodaty H; Neuropsychiatric Institute, Prince of Wales Hospital, Sydney, NSW, Australia.
  • Sachdev P; Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science and Medical Engineering, Beihang University, Beijing, China.
  • Liu T; Centre for Healthy Brain Ageing, School of Psychiatry (CHeBA), University of New South Wales, Sydney, NSW, Australia.
Cereb Cortex ; 33(8): 4688-4698, 2023 04 04.
Article en En | MEDLINE | ID: mdl-36178117
ABSTRACT
The nondemented old-old over the age of 80 comprise a rapidly increasing population group; they can be regarded as exemplars of successful aging. However, our current understanding of successful aging in advanced age and its neural underpinnings is limited. In this study, we measured the microstructural and network-based topological properties of brain white matter using diffusion-weighted imaging scans of 419 community-dwelling nondemented older participants. The participants were further divided into 230 young-old (between 72 and 79, mean = 76.25 ± 2.00) and 219 old-old (between 80 and 92, mean = 83.98 ± 2.97). Results showed that white matter connectivity in microstructure and brain networks significantly declined with increased age and that the declined rates were faster in the old-old compared with young-old. Mediation models indicated that cognitive decline was in part through the age effect on the white matter connectivity in the old-old but not in the young-old. Machine learning predictive models further supported the crucial role of declines in white matter connectivity as a neural substrate of cognitive aging in the nondemented older population. Our findings shed new light on white matter connectivity in the nondemented aging brains and may contribute to uncovering the neural substrates of successful brain aging.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Sustancia Blanca Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Revista: Cereb Cortex Asunto de la revista: CEREBRO Año: 2023 Tipo del documento: Article País de afiliación: China

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Sustancia Blanca Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Revista: Cereb Cortex Asunto de la revista: CEREBRO Año: 2023 Tipo del documento: Article País de afiliación: China