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Characterising the structural brain connectome in Alzheimer's disease and its relation to cognitive intra-individual variability.

Research on Alzheimer's disease (AD) has shown white matter (WM) degeneration and structural connectome disruptions measured by diffusion tensor imaging (DTI) as well as increased reaction time intra-individual variability (RT IIV) on neurocognitive testing. However, the relationship between these c...

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Main Author: Lee, Shao-Hsuan Stephanie
Other Authors: Jankiewicz, Marcin
Format: Thesis
Language:English
Published: Department of Human Biology 2023
Subjects:
Biomedical Engineering
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access_status_str Open Access
author Lee, Shao-Hsuan Stephanie
author2 Jankiewicz, Marcin
author_browse Jankiewicz, Marcin
Lee, Shao-Hsuan Stephanie
author_facet Jankiewicz, Marcin
Lee, Shao-Hsuan Stephanie
author_sort Lee, Shao-Hsuan Stephanie
collection Thesis
description Research on Alzheimer's disease (AD) has shown white matter (WM) degeneration and structural connectome disruptions measured by diffusion tensor imaging (DTI) as well as increased reaction time intra-individual variability (RT IIV) on neurocognitive testing. However, the relationship between these changes measured on these different modalities remains unexplored. To explore possible relationships between these alterations, this study used tractography to identify WM changes, as indexed by fractional anisotropy (FA) and mean diffusivity (MD), followed by a graph theory-based analysis of the brain structural connectome, and investigated the relationship between these graph theory metrics and RT IIV in 16 AD patients and 20 healthy elderly controls. Within AD patients, we identified WM tracts with lower FA and higher MD mostly located in the cortical and subcortical temporal lobes, such as the hippocampus subregions, compared to healthy elderly controls. We also observed higher FA in the WM tracts within the thalamus as well as between the thalamus and brainstem in AD patients. In the structural brain connectome of these patients, there were regions with altered nodal strength, transitivity, and local efficiency relative to the controls' connectome. Conversely to many studies, we found increases in nodal efficiency across multiple regions and higher global efficiency in AD patients compared to healthy elderly controls. Finally, higher global efficiency was correlated with increased RT IIV on the CRT task in AD patients. In AD, a positive relationship between transitivity in the left cingulate cortex and RT IIV as well as between nodal efficiency in the left cortical temporal lobe and mean RT on the CRT task were observed. On the other hand, lower transitivity in the right thalamus and increased RT IIV, as well as lower transitivity and longer mean RT were found on both the SRT and CRT tasks in AD patients. Our results may show evidence of disruptions and compensatory mechanisms in WM tracts and network metrics in AD. Together, these results revealed WM changes, topological alterations of the brain structural connectome in AD and that these findings can be used in combination with IIV to predict cognitive decline or progression of AD.
format Thesis
id oai:open.uct.ac.za:11427/37468
institution University of Cape Town (South Africa)
language eng
last_indexed 2026-06-10T12:31:54.917Z
license_str Not specified — see source repository
provenance_str_mv Harvested via OAI-PMH from UCTD — University of Cape Town Open Access Repository
publishDate 2023
publishDateRange 2023
publishDateSort 2023
publisher Department of Human Biology
publisherStr Department of Human Biology
record_format dspace
source_str UCTD — University of Cape Town Open Access Repository
spelling oai:open.uct.ac.za:11427/37468 Characterising the structural brain connectome in Alzheimer's disease and its relation to cognitive intra-individual variability. Lee, Shao-Hsuan Stephanie Jankiewicz, Marcin Robertson, Frances Christ, Björn Biomedical Engineering Research on Alzheimer's disease (AD) has shown white matter (WM) degeneration and structural connectome disruptions measured by diffusion tensor imaging (DTI) as well as increased reaction time intra-individual variability (RT IIV) on neurocognitive testing. However, the relationship between these changes measured on these different modalities remains unexplored. To explore possible relationships between these alterations, this study used tractography to identify WM changes, as indexed by fractional anisotropy (FA) and mean diffusivity (MD), followed by a graph theory-based analysis of the brain structural connectome, and investigated the relationship between these graph theory metrics and RT IIV in 16 AD patients and 20 healthy elderly controls. Within AD patients, we identified WM tracts with lower FA and higher MD mostly located in the cortical and subcortical temporal lobes, such as the hippocampus subregions, compared to healthy elderly controls. We also observed higher FA in the WM tracts within the thalamus as well as between the thalamus and brainstem in AD patients. In the structural brain connectome of these patients, there were regions with altered nodal strength, transitivity, and local efficiency relative to the controls' connectome. Conversely to many studies, we found increases in nodal efficiency across multiple regions and higher global efficiency in AD patients compared to healthy elderly controls. Finally, higher global efficiency was correlated with increased RT IIV on the CRT task in AD patients. In AD, a positive relationship between transitivity in the left cingulate cortex and RT IIV as well as between nodal efficiency in the left cortical temporal lobe and mean RT on the CRT task were observed. On the other hand, lower transitivity in the right thalamus and increased RT IIV, as well as lower transitivity and longer mean RT were found on both the SRT and CRT tasks in AD patients. Our results may show evidence of disruptions and compensatory mechanisms in WM tracts and network metrics in AD. Together, these results revealed WM changes, topological alterations of the brain structural connectome in AD and that these findings can be used in combination with IIV to predict cognitive decline or progression of AD. 2023-03-16T11:08:38Z 2023-03-16T11:08:38Z 2022 2023-03-16T09:50:22Z Master Thesis Masters MSc http://hdl.handle.net/11427/37468 eng application/pdf Department of Human Biology Faculty of Health Sciences
spellingShingle Biomedical Engineering
Lee, Shao-Hsuan Stephanie
Characterising the structural brain connectome in Alzheimer's disease and its relation to cognitive intra-individual variability.
thesis_degree_str Master's
title Characterising the structural brain connectome in Alzheimer's disease and its relation to cognitive intra-individual variability.
title_full Characterising the structural brain connectome in Alzheimer's disease and its relation to cognitive intra-individual variability.
title_fullStr Characterising the structural brain connectome in Alzheimer's disease and its relation to cognitive intra-individual variability.
title_full_unstemmed Characterising the structural brain connectome in Alzheimer's disease and its relation to cognitive intra-individual variability.
title_short Characterising the structural brain connectome in Alzheimer's disease and its relation to cognitive intra-individual variability.
title_sort characterising the structural brain connectome in alzheimer s disease and its relation to cognitive intra individual variability
topic Biomedical Engineering
url http://hdl.handle.net/11427/37468
work_keys_str_mv AT leeshaohsuanstephanie characterisingthestructuralbrainconnectomeinalzheimersdiseaseanditsrelationtocognitiveintraindividualvariability

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