Differences of Gradient Connectivity and Ventricle Volumes in Long-Term Sensorineural Hearing Loss Related Cognitive...

Long-term sensorineural hearing loss (SNHL) is a prevalent condition associated with an increased risk of cognitive impairment. This study aimed to investigate the relationship among gradient connectivity, ventricle volumes, and transcriptional signatures in individuals experiencing cognitive deficits related to long-term SNHL. This study enrolled 81 patients with long-term SNHL and 78 healthy controls (HCs). All participants underwent audiological tests, neuropsychological assessment, and MRI scanning. Connectome gradient analysis and ventricular volume measurements were performed. Additionally, regional gene expression and neurotransmitter receptor data were integrated. Correlation analysis was conducted to examine associations between neuroimaging metrics and cognitive performance. Patients with SNHL had significantly higher hearing thresholds and worse cognitive performance than HCs. The principal gradient was compressed in the SNHL group, with significant differences in the default mode network and dorsal attention network. Enlarged volumes of the choroid plexus and lateral ventricles were also observed in the SNHL group. Correlation analysis revealed significant associations among ventricle volumes, gradient connectivity, and cognitive performance. Transcriptomic analysis revealed 496 genes associated with regions showing an increased principal gradient and 321 genes linked to regions with a decreased gradient. Enrichment analyses indicated these genes were implicated in synaptic plasticity, neurotransmitter regulation, energy metabolism, and neurodegenerative pathways. This study provides new insights into the multifaceted nature of SNHL-related cognitive impairments, suggesting that gradient connectivity, ventricle volumes, and transcriptional signatures are interconnected and may serve as potential biomarkers for monitoring cognitive decline in individuals with long-term SNHL. Future research should focus on elucidating the causal pathways and underlying biological mechanisms connecting these multimodal factors.