Disrupted functional hierarchy organization and faster tau accumulation in Alzheimer’s disease
Poster No:
151
Submission Type:
Abstract Submission
Authors:
Sunghun Kim1, Jong-eun Lee1, Hyunjin Park1, Bo-yong Park2
Institutions:
1Sungkyunkwan University, Suwon-si, Gyeonggi-do, 2Korea University, Seoul, Seoul
First Author:
Co-Author(s):
Introduction:
The brain's macroscale functional organization supports integrated cognition and behavior, enabling complex information processing through the coordinated interaction of distributed networks. This organization follows a hierarchical structure characterized by distinct gradients, particularly along the unimodal-to-transmodal axis. Within this hierarchy, functional organization facilitates efficient information flow from primary sensory areas to higher-order association cortices. However, neurodegenerative conditions like Alzheimer's disease (AD) can significantly disrupt this hierarchical structure, leading to a contraction of the unimodal-transmodal functional axis and reduced network segregation. Emerging evidence suggests that such disruptions in hierarchical organization are intimately linked to pathological processes, such as tau protein accumulation. In this study, we hypothesized that disruption of the brain's hierarchical organization is associated with accelerated tau accumulation, potentially compromising network integrity and cognitive function.
Methods:
We analyzed longitudinal resting-state functional magnetic resonance imaging and tau-positron emission tomography (PET) data from the ADNI database, including 82 participants with a total of 196 observations. Macroscale brain organization was characterized by computing the principal functional connectivity gradient (G1) using dimensionality reduction techniques. We then constructed normative brain organization patterns from a healthy control cohort (N=522) using a generalized additive model for location, scale, and shape. Each participant's deviation from the normative pattern was quantified using a functional hierarchy score, calculated as the cosine similarity between their G1 profile and the normative model. To assess whole-brain tau accumulation, we estimated individual change rates from serial tau-PET scans using linear regression. Finally, we examined the association between functional hierarchy scores and tau accumulation rates.
Results:
The aging curve of G1 revealed an overall compression pattern (Fig. 1A). Sensory regions showed increased gradient values, while transmodal regions exhibited decreased values, indicating reduced functional differentiation between unimodal and transmodal areas. Notably, cognitively impaired participants whose baseline G1 patterns showed greater deviation from normative values demonstrated significantly accelerated tau accumulation in longitudinal follow-up. A negative correlation was observed between functional hierarchy scores and tau accumulation rates (r=-0.31, p<0.01; Fig. 1B), suggesting that disruptions in normal macroscale functional hierarchy may be associated with accelerated pathological tau progression.
·Age-related changes in principal gradient organization and association with tau accumulation
Conclusions:
Our results demonstrate that deviations from the normative macroscale functional hierarchy are linked to faster tau accumulation. Maintaining hierarchical functional organization may be important for slowing tau progression, and further research is needed to elucidate the relationship between these disruptions and clinical outcomes, as well as to explore potential interventions aimed at preserving or restoring this functional hierarchy.
This study was supported by National Research Foundation (RS-2024-00408040), Institute for Basic Science (IBS-R015-D1), AI Graduate School Support Program (Sungkyunkwan University) (RS-2019-II190421), ICT Creative Consilience program (RS-2020-II201821), Artificial Intelligence Innovation Hub program (RS-2021-II212068), and the Institute for Information and Communications Technology Planning and Evaluation (IITP) funded by the Korea Government (MSIT) (No. 2022-0-00448/RS-2022-II220448, Deep Total Recall: Continual Learning for Human-Like Recall of Artificial Neural Networks).
This study was supported by National Research Foundation (RS-2024-00408040), Institute for Basic Science (IBS-R015-D1), AI Graduate School Support Program (Sungkyunkwan University) (RS-2019-II190421), ICT Creative Consilience program (RS-2020-II201821), Artificial Intelligence Innovation Hub program (RS-2021-II212068), and the Institute for Information and Communications Technology Planning and Evaluation (IITP) funded by the Korea Government (MSIT) (No. 2022-0-00448/RS-2022-II220448, Deep Total Recall: Continual Learning for Human-Like Recall of Artificial Neural Networks).
Disorders of the Nervous System:
Neurodegenerative/ Late Life (eg. Parkinson’s, Alzheimer’s) 1
Lifespan Development:
Aging
Novel Imaging Acquisition Methods:
BOLD fMRI 2
PET
Keywords:
Aging
Degenerative Disease
FUNCTIONAL MRI
Positron Emission Tomography (PET)
1|2Indicates the priority used for review
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