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Updated: Sep 17, 2025
Abbiategrasso Brain Bank Protocol for Collecting, Processing and Characterizing Aging Brains
Published on: June 3, 2020
Atrophy related neuroimaging biomarkers for neurological and cognitive function in Wilson disease
Ann Carolin Hausmann1, Christian Rubbert2, Silja K Querbach1
1Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty and University Hospital Düsseldorf, Heinrich-Heine-University Düsseldorf, Düsseldorf, Germany.
Background:
Although brain atrophy is a prevalent finding in Wilson disease (WD), its role as a contributing factor to clinical symptoms, especially cognitive decline, remains unclear. The objective of this study was to investigate different neuroimaging biomarkers related to grey matter atrophy and their relationship with neurological and cognitive impairment in WD.
Methods:
In this study, 30 WD patients and 30 age- and sex-matched healthy controls were enrolled prospectively and underwent structural magnetic resonance imaging (MRI). Regional atrophy was evaluated using established linear radiological measurements and the automated workflow volumetric estimation of gross atrophy and brain age longitudinally (veganbagel) for age- and sex-specific estimations of regional brain volume changes. Brain Age Gap Estimate (BrainAGE), defined as the discrepancy between machine learning predicted brain age from structural MRI and chronological age, was assessed using an established model. Atrophy markers and clinical scores were compared between 19 WD patients with a neurological phenotype (neuro-WD), 11 WD patients with a hepatic phenotype (hep-WD), and a healthy control group using Welch's ANOVA or Kruskal-Wallis test. Correlations between atrophy markers and neurological and neuropsychological scores were investigated using Spearman's correlation coefficients.
Results:
Patients with neuro-WD demonstrated increased third ventricle width and bicaudate index, along with significant striatal-thalamic atrophy patterns that correlated with global cognitive function, mental processing speed, and verbal memory. Median BrainAGE was significantly higher in patients with neuro-WD (8.97 years, interquartile range [IQR] = 5.62-15.73) compared to those with hep-WD (4.72 years, IQR = 0.00-5.48) and healthy controls (0.46 years, IQR = - 4.11-4.24). Striatal-thalamic atrophy and BrainAGE were significantly correlated with neurological symptom severity.
Conclusions:
Our findings indicate advanced predicted brain age and substantial striatal-thalamic atrophy patterns in patients with neuro-WD, which serve as promising neuroimaging biomarkers for neurological and cognitive functions in treated, chronic WD.
