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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
Summary
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.
- 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.
