Decoding HIV-associated neurocognitive disorders: a new perspective from multimodal connectomics

Currently, HIV-associated neurocognitive disorders (HAND) remains one of the major challenges faced by people living with HIV (PLWH). HAND involves the vulnerability of neural circuits caused by synaptic degeneration and abnormal synaptic pruning. In recent years, connectomics has been gradually app...

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Main Authors: Zhongkai Zhou, Wei Wang, Hui Li, Ying Shi, Lingling Zhao, Yibo Lu, Xingchen Wei, Hongjun Li
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-01-01
Series:Frontiers in Neurology
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Online Access:https://www.frontiersin.org/articles/10.3389/fneur.2025.1467175/full
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Summary:Currently, HIV-associated neurocognitive disorders (HAND) remains one of the major challenges faced by people living with HIV (PLWH). HAND involves the vulnerability of neural circuits caused by synaptic degeneration and abnormal synaptic pruning. In recent years, connectomics has been gradually applied to HAND research as a cutting-edge method for describing the structural and functional connectivity patterns of the brain, to further elucidate the specific mechanisms underlying these neural circuit vulnerabilities. Using multimodal neuroimaging techniques such as diffusion tensor imaging (DTI), structural magnetic resonance imaging (sMRI), and resting-state functional magnetic resonance imaging (rs-fMRI), researchers can detail the connectome network changes in the brains of PLWH. These technologies offer potential biomarkers for the early diagnosis, prognosis, and treatment monitoring of HAND, while also providing new avenues for personalized prediction of cognitive status. Here, we start with the pathogenesis and risk factors of HAND, providing a comprehensive review of the basic concepts of unimodal and multimodal macro connectomics and related graph theory methods, and we review the latest progress in HAND connectomics research. We emphasize the use of connectomics to identify specific disease patterns of HIV-associated neurodegeneration and discuss the potential research directions and challenges in understanding these diseases from a connectomics perspective.
ISSN:1664-2295