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Transcriptomic profiles link heterogeneous brain structural deviation to neurological subtypes in Wilson's disease.

Kun Xia1, Shijing Wang1, Tong Wu1

  • 1Institute of Neurology, Anhui University of Chinese Medicine, Hefei, China.

Neurobiology of Disease
|June 19, 2026
PubMed
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This study reveals distinct brain structure patterns in Wilson's disease (WD) subtypes, linking brain age differences to neurological decline and identifying subtype-specific genetic risks for better understanding WD heterogeneity.

Area of Science:

  • Neuroscience
  • Genetics
  • Medical Imaging

Background:

  • Wilson's disease (WD) presents significant variation in disease progression and clinical presentation.
  • Understanding the underlying pathological and biological processes driving this heterogeneity, particularly in the brain, remains a challenge.

Purpose of the Study:

  • To develop and apply a gray matter volume (GMV)-based brain age model to quantify brain structure deviation (BSD) in WD subtypes.
  • To investigate the relationship between brain-predicted age difference (brainPAD), clinical severity, and subtype-specific pathology in WD.
  • To explore transcriptomic signatures associated with BSD patterns in cortical and subcortical regions across WD subtypes.

Main Methods:

  • Utilized a large dataset (N=1749) to develop a GMV-based brain age model, calculating brainPAD and BSD.
Keywords:
Biological processBrain structural deviationGray matter volumeSupport vector machineTranscriptomic signaturesWilson's disease

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  • Employed support vector machine (SVM) analysis to differentiate between neurological WD subtypes (parkinsonism - PWD, dystonia - DWD) based on BSD patterns.
  • Conducted transcriptomic analysis of cortical and subcortical regions to identify molecular differences associated with BSD and WD subtypes.

    • Main Results:

    • BrainPAD correlated with clinical severity and GMV, showing heterogeneous BSD patterns across neurological WD subtypes.
    • SVM analysis successfully discriminated PWD from DWD using GMV-based BSD patterns, with SVM-derived fingerprints linked to brainPAD.
    • Cortical transcriptomic analysis revealed subtype-specific signatures related to synaptic plasticity and neuronal development, while subcortical regions showed shared signatures reflecting disease-level pathology.
    • Genes associated with BSD were enriched for risks in multiple neurological disorders, suggesting complex underlying pathologies.

    Conclusions:

    • Heterogeneous brain structure deviation (BSD) patterns, particularly in cortical regions, are linked to subtype-specific pathology and clinical manifestations in neurological WD.
    • Convergent subcortical and divergent cortical transcriptomic signatures provide novel insights into the neurodegenerative mechanisms underlying WD heterogeneity.
    • The brain age model and BSD analysis offer a valuable tool for understanding WD pathophysiology and potentially guiding future therapeutic strategies.