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Background <p>As a major chronic liver condition, metabolic dysfunction-associated steatotic liver disease (MASLD) is linked to numerous extrahepatic manifestations, including cognitive and emotional dysfunction. However, its neuroanatomical and functional brain correlates remain unclear. This study investigates cerebral alterations in MASLD by examining structural differences via voxel-based morphometry (VBM), along with functional features using resting-state functional connectivity (FC).</p> Methods and patients <p>Seventy-four MASLD patients and sixty-two demographically matched healthy controls (HC) underwent structural MRI and resting-state fMRI. Group differences in gray matter volume (GMV) and FC were analyzed using VBM and seed-based FC methods. Correlations and mediation analyses were further used to assess the relationships among abnormal GMV, altered resting-state FC and clinical indicators in MASLD individuals.</p> Results <p>Patients with MASLD exhibited reduced GMV in the bilateral hippocampus, left parahippocampal gyrus, left middle temporal gyrus, right fusiform gyrus, right supplementary motor area (SMA), and right cerebellum. Importantly, liver fat content fully mediated the effects of hippocampal atrophy on cognitive-emotional symptoms. Seed-based FC analysis further revealed decreased connectivity between the right hippocampus and the right orbitofrontal cortex. This reduction in connectivity was also associated with worse cognitive function and a higher waist-to-hip ratio.</p> Conclusion <p>MASLD-related brain atrophy and functional disruption are linked to visceral adiposity and neuropsychiatric deficits. The mediating role of liver fat highlights the importance of dual-pathway interventions that target both metabolic health and neural protection, potentially reducing long-term neurocognitive disability burdens and enabling accessible risk stratification in practice.</p>

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Liver fat mediates hippocampal-orbitofrontal reward circuit disruption and cognitive-emotional impairments in MASLD

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年9月19日

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  • Liqiang Wu,
  • Ruoyu Tang,
  • Yidan Liang,
  • Yihan Jin,
  • Kuanghui Xu,
  • Xiaofei Chen,
  • Junping Shi,
  • Jie Li

摘要

Background

As a major chronic liver condition, metabolic dysfunction-associated steatotic liver disease (MASLD) is linked to numerous extrahepatic manifestations, including cognitive and emotional dysfunction. However, its neuroanatomical and functional brain correlates remain unclear. This study investigates cerebral alterations in MASLD by examining structural differences via voxel-based morphometry (VBM), along with functional features using resting-state functional connectivity (FC).

Methods and patients

Seventy-four MASLD patients and sixty-two demographically matched healthy controls (HC) underwent structural MRI and resting-state fMRI. Group differences in gray matter volume (GMV) and FC were analyzed using VBM and seed-based FC methods. Correlations and mediation analyses were further used to assess the relationships among abnormal GMV, altered resting-state FC and clinical indicators in MASLD individuals.

Results

Patients with MASLD exhibited reduced GMV in the bilateral hippocampus, left parahippocampal gyrus, left middle temporal gyrus, right fusiform gyrus, right supplementary motor area (SMA), and right cerebellum. Importantly, liver fat content fully mediated the effects of hippocampal atrophy on cognitive-emotional symptoms. Seed-based FC analysis further revealed decreased connectivity between the right hippocampus and the right orbitofrontal cortex. This reduction in connectivity was also associated with worse cognitive function and a higher waist-to-hip ratio.

Conclusion

MASLD-related brain atrophy and functional disruption are linked to visceral adiposity and neuropsychiatric deficits. The mediating role of liver fat highlights the importance of dual-pathway interventions that target both metabolic health and neural protection, potentially reducing long-term neurocognitive disability burdens and enabling accessible risk stratification in practice.