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

Area of Science:

• Neuroscience
• Medical Imaging
• Computational Biology

Background:

• HIV-associated neurocognitive disorders (HAND) present significant challenges for people living with HIV (PLWH).
• HAND is characterized by neural circuit vulnerability due to synaptic degeneration and abnormal pruning.
• Understanding the precise mechanisms of HAND is crucial for effective management.

Purpose of the Study:

• To review the application of connectomics in understanding HIV-associated neurocognitive disorders (HAND).
• To elucidate the role of connectomics in identifying neural circuit vulnerabilities in PLWH.
• To explore connectomics as a tool for early diagnosis, prognosis, and personalized treatment of HAND.

Main Methods:

• Utilizing multimodal neuroimaging techniques: diffusion tensor imaging (DTI), structural magnetic resonance imaging (sMRI), and resting-state functional magnetic resonance imaging (rs-fMRI).
• Applying graph theory methods to analyze macro connectome network changes.
• Reviewing current connectomics research in the context of HAND.

Main Results:

• Connectomics provides detailed insights into brain connectome network alterations in PLWH.
• Multimodal neuroimaging reveals specific patterns of HIV-associated neurodegeneration.
• Connectomics offers potential biomarkers for HAND diagnosis, prognosis, and treatment monitoring.

Conclusions:

• Connectomics is a powerful approach for understanding the neural underpinnings of HAND.
• This methodology facilitates the identification of specific disease patterns in HIV-associated neurodegeneration.
• Future research directions include leveraging connectomics for personalized cognitive status prediction and treatment strategies.