Dynamic brain states and molecular signatures in primary angle-closure glaucoma

Area of Science:

• Neuroscience
• Ophthalmology
• Systems Biology

Background:

• Primary angle-closure glaucoma (PACG) is increasingly recognized as involving the central nervous system, not just the eye.
• Previous studies focused on static brain abnormalities, leaving dynamic network properties and molecular links in PACG unclear.

Purpose of the Study:

• To investigate dynamic large-scale brain network properties in PACG using neuroimaging.
• To explore the molecular and cellular correlates of observed brain network alterations in PACG.

Main Methods:

• Resting-state functional MRI and Leading Eigenvector Dynamics Analysis were used on 44 PACG patients and 57 controls.
• Machine learning models evaluated state-specific metrics, and partial least squares regression linked imaging data to cortical gene expression.
• Pathway, cell-type, and neurotransmitter receptor/transporter enrichment analyses explored biological associations.

Main Results:

• PACG patients exhibited prolonged dwell time in a dynamic brain state, indicating reduced network flexibility.
• Machine learning models identified default mode network regions as key discriminators.
• Transcriptomic analysis revealed enrichment in synaptic signaling, ion channels, and neurotransmitter transport genes, implicating neurons and astrocytes.

Conclusions:

• PACG is associated with altered large-scale brain dynamics, particularly default mode network instability.
• Observed neuroimaging abnormalities in PACG correlate with molecular, cellular, and neurotransmitter signatures, supporting broader CNS involvement.