Exploring Alzheimer's disease: a comprehensive brain connectome-based survey

Abstract

Dementia is an escalating global health challenge, with Alzheimer's disease (AD) at its forefront. Substantial evidence highlights the accumulation of AD-related pathological proteins in specific brain regions and their subsequent dissemination throughout the broader area along the brain network, leading to disruptions in both individual brain regions and their interconnections. Although a comprehensive understanding of the neurodegeneration-brain network link is lacking, it is undeniable that brain networks play a pivotal role in the development and progression of AD. To thoroughly elucidate the intricate network of elements and connections constituting the human brain, the concept of the brain connectome was introduced. Research based on the connectome holds immense potential for revealing the mechanisms underlying disease development, and it has become a prominent topic that has attracted the attention of numerous researchers. In this review, we aim to systematically summarize studies on brain networks within the context of AD, critically analyze the strengths and weaknesses of existing methodologies, and offer novel perspectives and insights, intending to serve as inspiration for future research.

Keywords

Alzheimer's disease / brain-connectome / graph theory / deep graph neural networks

Author contributions

Lu Zhang conceptualized and designed the structure of the review, conducted the literature search and data collection, drafted the initial manuscript, and managed the submission process. Junqi Qu, Haotian Ma, and Tong Chen conducted the literature search and edited the formulas. Tianming Liu and Dajiang Zhu reviewed and synthesized the primary findings, provided expert opinions on specific topics, and contributed to the overall coherence of the manuscript.

Conflict of interests

One of the authors, Tianming Liu, is also the editor board member of Psychoradiology. He was blinded from reviewing or making decisions on the manuscript.

Acknowledgement

This work was supported by National Institutes of Health (R01AG075582, RF1NS128534).

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