Functional Network-Based Statistics Reveal Abnormal Resting-State Functional Connectivity in Minimal Hepatic...

Area of Science:

• Neuroscience
• Medical Imaging
• Systems Biology

Background:

• Hepatic encephalopathy (HE) is a complex neurological complication of liver disease.
• Minimal hepatic encephalopathy (MHE) represents the earliest, often subclinical, stage of HE.
• Understanding the brain mechanisms of MHE is crucial for early diagnosis and intervention.

Purpose of the Study:

• To identify specific brain subnetworks with altered functional connectivity in patients with MHE.
• To investigate the relationship between functional connectivity changes and cognitive performance in MHE.

Main Methods:

• Resting-state functional magnetic resonance imaging (fMRI) was used to assess whole-brain functional connectivity.
• Network-based statistical analysis was applied to compare functional connectomes between MHE patients and controls.
• Cognitive function was evaluated using the Psychometric Hepatic Encephalopathy Score (PHES).

Main Results:

• MHE patients exhibited reduced positive functional connectivity within the default-mode network (DMN).
• Significant reductions in negative functional connectivity were observed between DMN regions and somatosensory/language networks in MHE patients.
• Alterations in DMN functional connectivity correlated with cognitive scores (PHES).

Conclusions:

• Default-mode network dysfunction is a key feature in the pathophysiology of MHE.
• MHE is characterized by intrinsic disruptions in brain network organization.
• Functional network analysis provides valuable insights into the neurological underpinnings of HE.