MATERIALS & METHODS

Study population

We retrospectively reviewed the medical records of 159 independent patients diagnosed with WD at the National Taiwan University Hospital between January 2006 and December 2021. WD diagnosis was based on the Leipzig diagnostic criteria [13], including a combination of characteristic clinical symptoms; Kayser–Fleischer (K-F) rings; abnormal brain magnetic resonance imaging (MRI); and biochemical parameters, including low serum ceruloplasmin (< 0.2 g/L) and increased urinary copper excretion (> 100 μg/24 h). A subgroup of patients underwent liver biopsy or genetic analysis to confirm the diagnosis. Exclusion criteria were any unrelated medical or psychiatric illness that interfered with the completion of assessments. Of the 159 patients, 36 were excluded due to the absence of detailed medical records regarding their initial clinical presentations.

Ethical standard

All procedures performed in studies involving human participants were in accordance with the ethical standards of the Institutional Ethical Committee of the National Taiwan University Hospital (No. 201911087RINA) and with the 1975 Helsinki declaration and its later amendments or comparable ethical standards. Informed consent was obtained from all the patients included in the study.

Clinical analysis

Medical records were reviewed in detail. When necessary, some participants were interviewed to determine their presentation at the time of diagnosis according to the international consensus on the phenotypic classification of WD [13]. Patients who had initially presented with neurological or psychiatric symptoms were classified as having neuropsychiatric presentations (n = 49). Those lacking neuropsychiatric symptoms and exhibiting abnormal liver function were classified as having hepatic presentations (n = 74). If a patient had both abnormal liver function and neurological or psychiatric involvement at the first clinic visit, excluding common kinetic tremor, anxiety, or depression, we classified the patient into the neuropsychiatric group. The neurological subscale of Unified Wilson’s Disease Rating Scale (UWDRS) [14] was recorded as the neurological severity of patients with neuropsychiatric presentations.

Laboratory examinations at the time of diagnosis, including serum ceruloplasmin level, serum copper level, and 24-hour urinary copper level, were documented. The following patient clinical characteristics were recorded: age at onset; current age; sex; physical presentations, including the presence of K-F rings, abnormal liver function, and liver cirrhosis; neurological features; cognitive function; and psychiatric symptoms at the first and last visits. Cognitive function was measured based on the Mini-Mental State Examination (MMSE). We also recorded the latest medication profile for each participant. During follow-up, the final functional outcome was evaluated based on the modified Rankin’s scale (mRS), and major events were recorded, including intensive care unit (ICU) admission, liver transplantation, and death.

Brain image acquisition, preprocessing, and analysis

Of the 123 participants, 60 participants had brain MRI data available for analysis. Brain MRI was performed within 3 months of their first neurology clinic visit using a 3-Tesla scanner. High-resolution structural imaging data were acquired with a sagittal 3-dimensional gradient echo T1-weighted sequence (256 × 256 matrix; field of view = 17 cm; slice thickness = 1 mm). Imaging preprocessing and analysis were performed using a stable version (v.7.1.1) of FreeSurfer software (http://surfer.nmr.mgh.harvard.edu). The automatic recon-all command with the qcache option was used for preprocessing at a smoothing size of 10-mm full-width half-maximum kernels. Cortical thickness was calculated in the surface-based pipeline, which comprises several stages, including affine registration to the Montreal Neurological Institute atlas, correction of intensity inhomogeneity, skull stripping, voxel classification into white matter and nonwhite matter, tessellation of gray‒white matter boundaries, automatic topographic correction, surface reconstruction, and cortical thickness estimated by the distance between the white surface and pial surface [15]. Total brain volume was recorded as the percentage of estimated total intracranial volume (eTIV) [16]. For subcortical volume analysis, the volume-based stream was automatically processed for final segmentation and volumetric labeling [17]. We selected the volumetric measures of the caudate, putamen, globus pallidum, and thalamus provided in the FreeSurfer output files. The volumes of these regions in the bilateral hemispheres were averaged and further divided by the eTIV to adjust for differences in individual head sizes. A vertex-wise correlation map was created to test for significant correlations between the cortical brain volume of individual regions and age, and we used age and the eTIV as covariates to control their effects. Monte Carlo simulations were applied for cluster-wise correction for multiple comparisons, using a vertex-wise cluster threshold of p < 0.001, a cluster-wise p-threshold of 0.05, and correction for analyzing cortical and subcortical brain volume in both hemispheres.

Genetic analysis

Of the 123 participants, 59 patients had DNA samples available for analysis. Genomic DNA was extracted from 10 mL of venous blood using a QIAamp DNA Mini Kit (Qiagen, Hilden, Germany). Whole-exome sequencing, covering all 21 exons and exon–intron boundary junctions of ATP7B, was performed with the Illumina NovaSeq 6000 sequencer as previously described [18]. Briefly, from the paired-end reads, we trimmed off the sequencing adaptor sequences and low-quality bases (Q < 30, Phred scale). The sequences were then aligned to the human reference genome (GRCh37/hg19). We removed common variants in the population that had minor allele frequencies of > 1% in dbSNP version 151 or Taiwan BioBank [19]. For variants in the coding region, we used PROVEAN, SIFT, and PolyPhen-2 to predict the potential impacts on protein structure and function. Pathogenicity was classified using the American College of Medical Genetics and Genomics interpretation criteria [20].

In silico protein modeling

The cryo–electron microscopy (cryo-EM) structure of ATP7B from Xenopus tropicalis has been reported at 3.2 Å resolution [21]. The human ATP7B shares 68.89% sequence identity with the X. tropicalis ortholog. We used the available atomic-resolution structure of frog ATP7B (PDB code: 7SI3) as a template and generated the 3D model structure of human ATP7B using the Swiss Model server. The global and per-residue model quality was assessed using the QMEANDisCo scoring function. The scores, which are between 0 and 1, give an indication of models, and residue scores of 0.6 or below are expected to be of low quality. The average per-residue score of the 3D model structure for human ATP7B was -0.70 ± 0.05.

Statistical analysis

All continuous variables are presented as the mean and standard error of the mean, and nominal variables are presented as numbers and percentages. The continuous variables were compared by unpaired Student’s t test or the Mann‒Whitney U test, while the categorical data were examined using the chi-square test or Fisher’s exact test. Baseline characteristics were compared between different genotype groups using analysis of variance or the Kruskal‒Wallis test when appropriate. We used a multivariate Cox regression model to examine the association between the allelic number of ATP7B p.R778L and the occurrence of functional progression during follow-up (the outcome of interest). The multivariate model was adjusted for age at onset (continuous), sex (male or female), serum ceruloplasmin level (continuous), and the existence of K-F rings at diagnosis (yes or no). The proportional hazards assumption was tested using Schoenfeld residuals (phtest), revealing no statistically significant violation. The results are presented as adjusted hazard ratios with their 95% confidence intervals for the associations. For survival analysis, the date of disease diagnosis was used as time zero, and the end time-point was the date when a poor functional outcome occurred (mRS ≥ 3). For event-free patients, the follow-up period ended on the date of the last clinic visit, and survival curves were estimated using the Kaplan–Meier method. A log-rank test was used to compare differences in functional outcome between groups. For correlations between the subcortical volume of individual brain regions and the UWDRS neurological subscale, we first normalized the preadjusted general cortical volume and subcortical volume to eTIV to eliminate the effect of age [22,23]. We then used age-adjusted Pearson correlation analysis for the correlations between individual subcortical brain volumes and UWDRS scores. Statistical analyses were performed using Prism software version 9.3.1 (GraphPad Software, Inc., San Diego, CA, USA).

RESULTS

Clinical analysis

The present analysis included 123 patients with WD with a mean follow-up of 11.12 ± 7.41 years. Among these patients, 74 patients (60.2%) had abnormal liver function at presentation, and 49 patients (39.8%) had neurological or psychiatric features as their predominant initial symptoms. Table 1 shows a comparison of clinical characteristics between the hepatic and neuropsychiatric groups. The mean onset age was significantly younger in the hepatic group than in the neuropsychiatric group (15.3 ± 11.4 [3–45] vs. 24.2 ± 11.3 years [12–50], p < 0.01). Compared to the hepatic group, the neuropsychiatric group exhibited more K-F rings (77.6% vs. 41.9%, p < 0.01) and lower serum ceruloplasmin levels (4.9 ± 3.9 vs. 6.3 ± 3.9 mg/dL, p < 0.01). Notably, although patients in the hepatic group exhibited abnormal liver function at diagnosis, there was a statistically higher frequency of liver cirrhosis in the neuropsychiatric group than in the hepatic group (59.2% vs. 39.2%, p < 0.01) during follow-up, but the hepatic failure rate did not differ between groups. In terms of cognitive and psychiatric presentations, the neuropsychiatric group exhibited lower MMSE scores and higher frequencies of depression, psychotic symptoms, and seizure (Table 1). The neuropsychiatric group showed a higher rate of movement disorders than the hepatic group during the follow-up period (87.8% vs. 10.8%, p < 0.01). Among these diverse movement disorders, kinetic tremor was the most common (30.6% vs. 10.8%) followed by dystonia (24.5% vs. 0%), parkinsonism features (16.3% vs. 0%), and ataxia (16.3% vs. 0%), which were all more prevalent in the neuropsychiatric group than in the hepatic group (all p < 0.01) (Table 1).

During follow-up, the groups showed comparable mortality rates and frequencies of any ICU admission. The liver transplantation rate did not significantly differ between the two groups (8.1% vs. 6.1%, p = 0.48). Notably, compared to the hepatic group, the neuropsychiatric group exhibited worse functional outcomes that needed at least partial support in daily activities during follow-up (mRS ≥ 3) (38.8% vs. 6.8%, p < 0.01). Those who had worse functional outcomes defined as mRS ≥ 3 in our cohort had impaired cognitive function (mean MMSE was 22.1 ± 2.5, n = 20), ataxia (n = 15), parkinsonism features (n = 9), and limb dystonia (n = 18). Kaplan–Meier curves showed a faster decline in functional outcome (mRS ≥ 3) in the neuropsychiatric group than in the hepatic group (p = 0.0003 by log-rank test) (Figure 1A).

Brain image analysis

Of the 123 participants, 60 patients had raw data from brain MRI available for analysis. The clinical characteristics of these patients with brain MRI are shown in Supplementary Table 1 (in the online-only Data Supplement). The mean onset age was 16.9 ± 13.8 years old in patients with the hepatic form who received brain MRI, while the onset age was 24.5 ± 11.7 years old for the neuropsychiatric group. Patients with neuropsychiatric presentations all presented with T2-weighted hyperintensities in the basal ganglia, thalamus, and brainstem, which are characteristic of WD. After adjusting for age, a smaller total brain volume was observed in the neuropsychiatric group than in the hepatic group (p = 0.0014) (Table 2). Compared to the hepatic group, the neuropsychiatric group also exhibited significantly smaller subcortical structural volume, especially for the caudate nucleus, putamen, globus pallidum, and thalamus (all p-values < 0.01, Table 2). Notably, while the supratentorial brain volume markedly differed between groups, the infratentorial cerebellar volume (p = 0.05) and white matter volume (p = 0.08) were relatively comparable between groups. We further examined whether there is any correlation between the atrophy of subcortical brain regions and clinical symptom severity. However, after adjusting for age, the negative correlations between the subcortical brain volumes, including caudate, putamen, globus pallidus, and thalamus, and the UWDRS neurological subscale did not reach the significance level (Supplementary Table 2 in the online-only Data Supplement).

Genetic analysis

Of the 123 participants, 59 patients had DNA samples available for genetic analysis. Among these 59 patients, we identified 33 distinct variants, including 24 missense pathogenic or likely pathogenic variants, 2 nonsense mutations, 4 frameshifts, 2 splicing variations, and 1 duplication. None of these 33 mutations was detected among 1,514 exomes from healthy controls in the Taiwan biobank. Among these pathogenic variants, p.R778L at exon 8 was the most common mutation (with an allelic frequency of 22.03%) followed by p.P992L at exon 13 (allelic frequency of 11.86%) and p.T935M at exon 12 (allelic frequency of 9.32%) (Figure 1B). The allelic frequency of p.R778L was more prevalent in patients with the hepatic form than in those with the neuropsychiatric form (31.7% vs. 12.1%, p = 0.02) (Table 1), while the prevalence of other genetic variants was comparable between groups.

We further observed that patients (n = 22) harboring the most frequent mutation, p.R778L, had a younger age at onset than those with other genetic variants (n = 37) (p = 0.04) (Table 3). The mean onset age was 5.0 ± 1.2 years for patients with homozygous p.R778L (n = 4), 15.1 ± 2.9 years for those with a compound heterozygous p.R778L mutation (n = 18), and 17.6 ± 2.2 years for patients with other mutations in ATP7B (n = 37) (Figure 2A). All patients with the homozygous p.R778L variant presented with the hepatic form, and the p.R778L variant was more prevalent in patients who initially presented with abnormal liver function (p = 0.02) (Table 3). The frequency of K-F ring presence was lower among patients with at least one allele of the p. R778L variant (6/22; 27.3%) than patients with other genetic variants (19/37; 51.4%) (p = 0.04). Notably, p.R778L carriers had lower levels of ceruloplasmin (p = 0.003) and serum copper (p = 0.03) than patients with other genetic variants with the lowest levels observed in patients with the homozygous p.R778L mutation (Figure 2A). Compared to patients with other genetic mutations (7.04 ± 0.66 µg/dL), the mean serum ceruloplasmin level was 3.6 ± 0.78 µg/dL in the homozygous p.R778L group and 4.89 ± 1.18 µg/dL in the heterozygous p.R778L group.

During the mean follow-up period of 11.12 ± 7.41 years, 18 of 37 (48.6%) WD patients without the p.R778L variant exhibited functional deterioration to the dependent status that manifested as an mRS ≥ 3 point, while 4 of 22 (18.6%) WD patients with at least one allele of p.R778L substitution reached the functional dependence level during follow-up. Kaplan–Meier curves showed a faster decline in functional outcome (mRS ≥ 3) in those patients with homozygous or compound heterozygous p.R778L variant than in those without the p.R778L substitution (p = 0.0012 by log-rank test) (Figure 2B). The multivariate Cox regression model with adjustment for age at onset, sex, baseline levels of serum ceruloplasmin, the existence of the K-F ring at diagnosis, and the allelic number of p.R778L mutation revealed an older onset age and a lower serum ceruloplasmin level. Moreover, harboring genetic variants other than the p.R778L mutation was associated with a higher risk of poor functional outcome (Table 4), suggesting that carriers with the p.R778L variant have a better functional outcome than other genetic variants. For other genetic variants, including p.P992L and p.T935M, the clinical presentations and long-term outcomes during follow-up were comparable between carriers and noncarriers (data not shown). Consistently, we observed that patients who had follow-up for more than 10 years had a younger onset age (p = 0.04), a lower percentage of neuropsychiatric forms (p = 0.02), a larger volume of the putamen (p = 0.04) on the initial brain MRI, a larger volume of the caudate nucleus (p = 0.02) on the initial brain MRI, and a higher allelic number of the p.R778L variant (p = 0.03) compared to those with follow-up less than 10 years (Table 5). Together, these findings suggested that clinical, radiological, and genetic features may be associated with the progression of the disease.

To predict the potential pathogenicity of these three common mutations, we next examined the structural changes induced by these three common genetic substitutions using the structural model of the human ATP7B protein (Figure 2C-F). Notably, the substitution of hydrophobic leucine for p.R778 disrupted polar contacts with nearby residues, including salt bridges or hydrogen bonds formed by the side-chain guanidium of p.R778 with the side-chain carboxyl groups of residues p.D730, p.E781, and p.D981, respectively (Figure 2D). The p.T935 residue engaged residues p.M931 and p.S932 with its side-chain hydroxyl group and backbone amide, respectively. Due to the high hydrophobicity of methionine, the p.T935M substitution had dramatic effects on the structure of ATP7B (Figure 2E). Moreover, the existence of P992 introduced a kink into the alpha helices, and P992L substitution resulted in the loss of proline from a kinked helix, thus giving rise to the loss of a kink or reduction in its kink angle (Figure 2F). Helix kinks are important because they are flexible and/or carry out crucial functional roles. Therefore, these three substitutions may lead to destabilization of the ATP7B protein structure, which may potentially influence copper transport activity.

DISCUSSION

In the present study, we compiled data from 123 patients with WD. The present results showed that compared to patients with hepatic features, patients with neuropsychiatric presentation exhibited a higher frequency of K-F rings, lower serum ceruloplasmin levels, smaller brain volumes (especially in the deep nucleus regions), and worse functional outcomes during follow-up. The ATP7B p.R778L variant was the most prevalent mutation in our cohort. Patients with the p.R778L substitution had a younger onset age, lower ceruloplasmin levels, lower serum copper levels, higher percentage of hepatic presentation, and a lower risk of functional dependence during follow-up compared to WD patients with other genetic variants.

Among the enrolled patients, 60.2% had predominant hepatic presentation, and 39.8% had predominant neurological or psychiatric features. These percentages were consistent with previous studies in which 40%–60% of WD patients initially present with liver disease and 18%–68% of WD patients initially present with neurological symptoms [24,25]. In accordance with previous evidence [26,27], the patients in our cohort with hepatic presentation had a significantly younger mean onset age (15.3 years) than those with neuropsychiatric presentation (24.2 years). Although abnormal liver function is the main feature of patients in the hepatic group, we paradoxically observed that liver cirrhosis was more common in the neuropsychiatric group, but the risk of liver failure was comparable between groups. Higher frequencies of liver cirrhosis in patients with neuropsychiatric presentations than in those with hepatic presentations have been observed in several previous studies [28,29]. This observation may correlate with the present finding of lower serum ceruloplasmin levels in the neuropsychiatric group than in the hepatic group. Lower serum ceruloplasmin levels suggest greater copper deposition in other organ systems, including the brain [30]. Accordingly, K-F rings were more common among patients with neuropsychiatric presentation compared to patients with hepatic presentation. However, the K-F ring frequency was only 77.1% in the neuropsychiatric group, which was lower than the > 90% K-F ring frequencies in WD patients described in previous reports conducted in western populations [27,31-33]. One study has reported an 84% frequency of K-F rings among Chinese patients with WD [34], while another study has reported a 73.3% frequency in Korean WD patients [35]. These observations suggest that the absence of the K-F ring may be more common in Asian WD patients with neuropsychiatric involvement, probably with less copper involvement in the corneas.

K-F ring-negative patients should be closely followed for the late appearance of K-F rings or other ocular manifestations, such as cataracts. Together, these features further reinforce that the clinical presentation of WD may vary among different ethnic groups.

In the present study, the majority of neurological presentations included a variety of movement disorders associated with other features, such as cognitive decline. In accordance with previous reports [24,25,27], the most common movement disorder feature was kinetic tremor followed by parkinsonism, dystonia, and ataxia, which could occur in combination. The mechanism for neurological involvement in WD is primarily driven by the effects of excess copper in the brain [36]. Neuropathological changes, including demyelination, reactive astrogliosis, central pontine myelinolysis, cavitation, and heavy metal depositions (such as copper and iron), have been described in both the gray matter and white matter of the brain [37]. Advances in neuroimaging have improved the detection of central nervous system involvement in WD. Among WD patients assessed using semiquantitative measures in specific regions of interest, the characteristic “face of giant panda’’ sign, created by hyperintensities in the brainstem and basal ganglia on T2-weighted images, is a pathognomonic imaging marker of WD. Although some studies have demonstrated an association between the overall lesion load and neurological severity, T2-weighted hyperintensity lesions may persist or progress despite clinical improvement after the initiation of chelation therapy in some patients [38]. Quantitative analyses of brain lesions using other imaging modalities or features are needed to depict neurological severity or progression in patients with WD. A recent whole-brain imaging study applying a combination of different imaging modalities in 40 WD patients has reported smaller gray matter volumes in the basal ganglia, thalamus, brainstem, cerebellum, and orbitofrontal cortex in patients with neurological presentations compared to those with hepatic presentations [16]. Furthermore, the severity of neurological deficits is correlated with gray matter volumes in these subcortical brain regions but not with the white matter hyperintensity volume [16]. Similarly, the present results revealed a significantly reduced volume of subcortical gray matter structures in patients with neuropsychiatric presentation compared to that in patients with hepatic presentation. In contrast, the cortical gray matter volume and white matter volume were comparable between groups. These imaging findings may explain the prevalent neurological symptoms of movement disorders in patients with WD. Notably, the present findings indicated worse functional outcomes among patients with initial neuropsychological presentations versus those with hepatic presentations. These observations reinforce the importance of early diagnosis, including establishing quantitative imaging markers for copper deposition in the brain and early management of WD.

Among the WD patients in the present population, the p. R778L mutation was the most prevalent pathogenic variant with an allelic frequency of 22%. The p.R778L mutation is common among East Asians with frequencies of 37.9% in Korea [6], 20%–30% in China [12], and 16.7% in Japan [39], but it is rare in other geographic regions, including India and Saudi Arabia [11]. Consistent with the present observations, patients harboring the p.R778L mutation have been reported to show an earlier onset, lower serum ceruloplasmin level, predominantly hepatic presentation, and less worsening function deterioration compared to patients with other genetic variants [12]. In contrast, the p.H1069Q mutation has an allelic frequency of 30%–70% among Caucasians but is rare among Asians [11]. Carriers of the p.H1069Q mutation exhibit a predominantly neurological phenotype [12]. These different presentations may be related to various features of WD, including the subcellular localization and transport activity of copper, associated with the ATP7B variant. Normal ATP7B protein is localized in the trans Golgi network and endoplasmic reticulum (ER) of hepatocytes. The missense p.R778L variant is predominantly located in the ER, and the p.H1069Q variant is associated with defective adenosine triphosphate-binding ability and reduced copper transport activity [40]. There remains a need for further functional studies of the p.R778L mutation in terms of copper transport within hepatic or neuronal cells to explain the phenotypic differences with this variant compared to other genetic variants.

The present study had several limitations. First, it was a retrospective study based on a review of patients’ medical records. The inevitable occurrence of missing data may cause some bias. Second, some patients received evaluation and treatment in only a single department. Because WD usually has multisystem involvement, a team-based approach, including a gastrointestinalist, neurologist, psychiatrist, and ophthalmologist, is needed to depict the comprehensive clinical spectrum of WD patients. Third, we assessed cognitive function using only the MMSE, a simple measurement for global cognitive function. Future studies should include detailed neuropsychological tests evaluating individual cognitive domains to further assess the correlation between brain MRI findings using quantitative susceptibility mapping analysis and individual cognitive domain decline in patients with WD. Finally, because next-generation sequencing in clinical practice has only been available in recent years, some patients lacked genetic information regarding ATP7B, leading to a limited sample size for the present genetic analysis. Furthermore, the number of patients with the homozygous p.R778L variant was too small to draw a definite conclusion. A future prospective study with comprehensive genetic analysis of ATP7B is needed to delineate the long-term outcome and treatment responses of patients with different genotypes, especially the p.R778L variant, in our population.

In conclusion, we evaluated a cohort of Asian WD patients with follow-up information. Patients with neuropsychiatric symptoms at initial presentation had worse functional outcomes than those with initial hepatic presentation. Because WD patients can have long overall survival with adequate treatment, there is a need for regular detailed neurological evaluations combined with quantitative brain image analysis to improve quality of life and treatment response in these patients. The distinct clinical characteristics of patients carrying the ATP7B p.R778L mutation support the ethnic differences of both the mutational spectrum and clinical presentations of WD.

Supplementary Material

Notes

Data Availability Statemen

The datasets generated and/or analyzed during the present study are available from the corresponding author upon reasonable request.

Conflicts of Interest

The authors have no financial conflicts of interest.

Funding Statement

This work was supported by grants from the National Taiwan University Hospital (110-A154).

Author contributions

Conceptualization: Sung-Pin Fan, Chin-Hsien Lin, Yen-Hsuan Ni. Data curation: all authors. Formal analysis: Sung-Pin Fan. Funding acquisition: Chin-Hsien Lin, Yen-Hsuan Ni. Investigation: Sung-Pin Fan, Chin-Hsien Lin, Yen-Hsuan Ni. Methodology: all authors. Project administration: Chin-Hsien Lin, Yen-Hsuan Ni. Resources: Chin-Hsien Lin, Yen-Hsuan Ni. Software: Sung-Pin Fan. Supervision: Chin-Hsien Lin, Yen-Hsuan Ni. Validation: Sung-Pin Fan, Chin-Hsien Lin, Yen-Hsuan Ni. Visualization: Sung-Pin Fan, Chin-Hsien Lin, Yen-Hsuan Ni. Writing—original draft: Sung-Pin Fan. Writing—review & editing: Chin-Hsien Lin, Yen-Hsuan Ni.

Acknowledgments

We thank all of the participants who participated in this study.

Figure 1.

Survival curve and distribution of ATP7B gene mutations among patients with Wilson’s disease. A: Kaplan–Meier survival curves for final poor functional status (modified Rankin scale ≥ 3) according to two clinical presentation groups (p = 0.0003, log-rank test). B: Frequency of mutations found in the present study given per exon as a percentage of the total mutant alleles.

Figure 2.

Clinical features, long-term outcome, in silico protein model, and ATP7B mutations. A: Distinct clinical and laboratory features of patients harboring p.R778L and other genetic variants. B: Kaplan–Meier survival curves for final poor functional status (modified Rankin scale ≥ 3) according to the genotype (p = 0.0012, log-rank test). C: Predicted protein structural model of the human ATP7B protein. Wildtype residues are marked in blue, and mutant residues are marked in purple. D–F: Relationships of p.R778 (D), p.M935 (E), and p.992 (F) residues with their surrounding residues. ^*p < 0.05; ^**p < 0.01. ns, not significant.

REFERENCES

• 1. Sandahl TD, Laursen TL, Munk DE, Vilstrup H, Weiss KH, Ott P. The prevalence of Wilson’s disease: an update. Hepatology 2020;71:722–732.ArticlePubMedPDF
• 2. Coffey AJ, Durkie M, Hague S, McLay K, Emmerson J, Lo C, et al. A genetic study of Wilson’s disease in the United Kingdom. Brain 2013;136(Pt 5):1476–1487.ArticlePubMedPMC
• 3. Taly AB, Prashanth LK, Sinha S. Wilson’s disease: An Indian perspective. Neurol India 2009;57:528–540.ArticlePubMed
• 4. Xie JJ, Wu ZY. Wilson’s disease in China. Neurosci Bull 2017;33:323–330.ArticlePubMedPMCPDF
• 5. Cheng N, Wang K, Hu W, Sun D, Wang X, Hu J, et al. Wilson disease in the South Chinese han population. Can J Neurol Sci 2014;41:363–367.ArticlePubMed
• 6. Choe EJ, Choi JW, Kang M, Lee YK, Jeon HH, Park BK, et al. A population-based epidemiology of Wilson’s disease in South Korea between 2010 and 2016. Sci Rep 2020;10:14041.ArticlePubMedPMCPDF
• 7. Tanzi RE, Petrukhin K, Chernov I, Pellequer JL, Wasco W, Ross B, et al. The Wilson disease gene is a copper transporting ATPase with homology to the Menkes disease gene. Nat Genet 1993;5:344–350.ArticlePubMedPDF
• 8. Cheung KS, Seto WK, Fung J, Mak LY, Lai CL, Yuen MF. Epidemiology and natural history of Wilson’s disease in the Chinese: a territory-based study in Hong Kong between 2000 and 2016. World J Gastroenterol 2017;23:7716–7726.ArticlePubMedPMC
• 9. Chu NS, Hung TP. Geographic variations in Wilson’s disease. J Neurol Sci 1993;117(1-2):1–7.ArticlePubMed
• 10. Gomes A, Dedoussis GV. Geographic distribution of ATP7B mutations in Wilson disease. Ann Hum Biol 2016;43:1–8.ArticlePubMed
• 11. Espinós C, Ferenci P. Are the new genetic tools for diagnosis of Wilson disease helpful in clinical practice? JHEP Rep 2020;2:100114.ArticlePubMedPMC
• 12. Dong Y, Ni W, Chen WJ, Wan B, Zhao GX, Shi ZQ, et al. Spectrum and classification of ATP7B variants in a large cohort of Chinese patients with Wilson’s disease guides genetic diagnosis. Theranostics 2016;6:638–649.ArticlePubMedPMC
• 13. Ferenci P, Caca K, Loudianos G, Mieli-Vergani G, Tanner S, Sternlieb I, et al. Diagnosis and phenotypic classification of Wilson disease. Liver Int 2003;23:139–142.PubMed
• 14. Volpert HM, Pfeiffenberger J, Gröner JB, Stremmel W, Gotthardt DN, Schäfer M, et al. Comparative assessment of clinical rating scales in Wilson’s disease. BMC Neurol 2017;17:140.ArticlePubMedPMCPDF
• 15. Fischl B, Dale AM. Measuring the thickness of the human cerebral cortex from magnetic resonance images. Proc Natl Acad Sci U S A 2000;97:11050–11055.ArticlePubMedPMC
• 16. Shribman S, Bocchetta M, Sudre CH, Acosta-Cabronero J, Burrows M, Cook P, et al. Neuroimaging correlates of brain injury in Wilson’s disease: a multimodal, whole-brain MRI study. Brain 2022;145:263–275.ArticlePubMedPMCPDF
• 17. Fischl B, Salat DH, Busa E, Albert M, Dieterich M, Haselgrove C, et al. Whole brain segmentation: automated labeling of neuroanatomical structures in the human brain. Neuron 2002;33:341–355.ArticlePubMed
• 18. Fan SP, Lee NC, Lin CH. Novel phenotype of 6p25 deletion syndrome presenting juvenile Parkinsonism and brain calcification. Mov Disord 2020;35:1457–1462.ArticlePubMedPDF
• 19. Lin JC, Fan CT, Liao CC, Chen YS. Taiwan Biobank: making cross-database convergence possible in the Big Data era. Gigascience 2018;7:1–4.ArticlePubMedPMC
• 20. Richards S, Aziz N, Bale S, Bick D, Das S, Gastier-Foster J, et al. Standards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology. Genet Med 2015;17:405–424.ArticlePubMedPMCPDF
• 21. Bitter RM, Oh S, Deng Z, Rahman S, Hite RK, Yuan P. Structure of the Wilson disease copper transporter ATP7B. Sci Adv 2022;8:eabl5508. ArticlePubMedPMC
• 22. Whitwell JL, Crum WR, Watt HC, Fox NC. Normalization of cerebral volumes by use of intracranial volume: implications for longitudinal quantitative MR imaging. AJNR Am J Neuroradiol 2001;22:1483–1489.PubMedPMC
• 23. O’Brien LM, Ziegler DA, Deutsch CK, Frazier JA, Herbert MR, Locascio JJ. Statistical adjustments for brain size in volumetric neuroimaging studies: some practical implications in methods. Psychiatry Res 2011;193:113–122.ArticlePubMedPMC
• 24. Bandmann O, Weiss KH, Kaler SG. Wilson’s disease and other neurological copper disorders. Lancet Neurol 2015;14:103–113.ArticlePubMedPMC
• 25. Członkowska A, Litwin T, Dusek P, Ferenci P, Lutsenko S, Medici V, et al. Wilson disease. Nat Rev Dis Primers 2018;4:21.ArticlePubMedPMCPDF
• 26. Pfeiffer RF. Wilson’s disease. Semin Neurol 2007;27:123–132.ArticlePubMed
• 27. Shribman S, Warner TT, Dooley JS. Clinical presentations of Wilson disease. Ann Transl Med 2019;7(Suppl 2):S60.ArticlePubMedPMC
• 28. Harris S, Naina HV, Siddique S. Wilson’s disease. Lancet 2007;369:902–903.Article
• 29. Przybyłkowski A, Gromadzka G, Chabik G, Wierzchowska A, Litwin T, Członkowska A. Liver cirrhosis in patients newly diagnosed with neurological phenotype of Wilson’s disease. Funct Neurol 2014;29:23–29.PubMedPMC
• 30. Manto M. Abnormal copper homeostasis: mechanisms and roles in neurodegeneration. Toxics 2014;2:327–345.Article
• 31. European Association for Study of Liver. EASL Clinical Practice Guidelines: Wilson’s disease. J Hepatol 2012;56:671–685.ArticlePubMed
• 32. Merle U, Schaefer M, Ferenci P, Stremmel W. Clinical presentation, diagnosis and long-term outcome of Wilson’s disease: a cohort study. Gut 2007;56:115–120.ArticlePubMedPMC
• 33. Bem RS, Muzzillo DA, Deguti MM, Barbosa ER, Werneck LC, Teive HA. Wilson’s disease in southern Brazil: a 40-year follow-up study. Clinics (Sao Paulo) 2011;66:411–416.ArticlePubMedPMC
• 34. Li XH, Lu Y, Ling Y, Fu QC, Xu J, Zang GQ, et al. Clinical and molecular characterization of Wilson’s disease in China: identification of 14 novel mutations. BMC Med Genet 2011;12:6.ArticlePubMedPMCPDF
• 35. Youn J, Kim JS, Kim HT, Lee JY, Lee PH, Ki CS, et al. Characteristics of neurological Wilson’s disease without Kayser-Fleischer ring. J Neurol Sci 2012;323(1-2):183–186.ArticlePubMed
• 36. Litwin T, Gromadzka G, Szpak GM, Jabłonka-Salach K, Bulska E, Członkowska A. Brain metal accumulation in Wilson’s disease. J Neurol Sci 2013;329(1-2):55–58.ArticlePubMed
• 37. Meenakshi-Sundaram S, Mahadevan A, Taly AB, Arunodaya GR, Swamy HS, Shankar SK. Wilson’s disease: a clinico-neuropathological autopsy study. J Clin Neurosci 2008;15:409–417.ArticlePubMed
• 38. Kim TJ, Kim IO, Kim WS, Cheon JE, Moon SG, Kwon JW, et al. MR imaging of the brain in Wilson disease of childhood: findings before and after treatment with clinical correlation. AJNR Am J Neuroradiol 2006;27:1373–1378.PubMedPMC
• 39. Okada T, Shiono Y, Hayashi H, Satoh H, Sawada T, Suzuki A, et al. Mutational analysis of ATP7B and genotype-phenotype correlation in Japanese with Wilson’s disease. Hum Mutat 2000;15:454–462.ArticlePubMed
• 40. Huster D, Kühne A, Bhattacharjee A, Raines L, Jantsch V, Noe J, et al. Diverse functional properties of Wilson disease ATP7B variants. Gastroenterology 2012;142:947–956.e5.ArticlePubMed

Figure & Data

References

Citations

Citations to this article as recorded by  

• Topographical metal burden correlates with brain atrophy and clinical severity in Wilson's disease
  Sung-Pin Fan, Ya-Fang Chen, Cheng-Hsuan Li, Yih-Chih Kuo, Ni-Chung Lee, Yin-Hsiu Chien, Wuh-Liang Hwu, Tai-Chung Tseng, Tung-Hung Su, Chien-Ting Hsu, Huey-Ling Chen, Chin-Hsien Lin, Yen-Hsuan Ni
  NeuroImage.2024; 299: 120829.     CrossRef
• ATP7B Gene Variant Profile İdentified by NGS in Wilson’s Disease
  Orhan Gorukmez, Taner Özgür, Ozlem Gorukmez, Ali Topak
  Fetal and Pediatric Pathology.2023; 42(6): 891.     CrossRef

Comments on this article