Wilson’s disease: update on pathogenesis, biomarkers and treatments

Wilson’s disease is an autosomal–recessive disorder of copper metabolism caused by mutations in ATP7B and associated with neurological, psychiatric, ophthalmological and hepatic manifestations. Decoppering treatments are used to prevent disease progression and reduce symptoms, but neurological outcomes remain mixed. In this article, we review the current understanding of pathogenesis, biomarkers and treatments for Wilson’s disease from the neurological perspective, with a focus on recent advances. The genetic and molecular mechanisms associated with ATP7B dysfunction have been well characterised, but despite extensive efforts to identify genotype–phenotype correlations, the reason why only some patients develop neurological or psychiatric features remains unclear. We discuss pathological processes through which copper accumulation leads to neurodegeneration, such as mitochondrial dysfunction, the role of brain iron metabolism and the broader concept of selective neuronal vulnerability in Wilson’s disease. Delayed diagnoses continue to be a major problem for patients with neurological presentations. We highlight limitations in our current approach to making a diagnosis and novel diagnostic biomarkers, including the potential for newborn screening programmes. We describe recent progress in developing imaging and wet (fluid) biomarkers for neurological involvement, including findings from quantitative MRI and other neuroimaging studies, and the development of a semiquantitative scoring system for assessing radiological severity. Finally, we cover the use of established and novel chelating agents, paradoxical neurological worsening, and progress developing targeted molecular and gene therapy for Wilson’s disease, before discussing future directions for translational research.

Alteration of Iron Concentration in Alzheimer’s Disease as a Possible Diagnostic Biomarker Unveiling Ferroptosis

Proper functioning of all organs, including the brain, requires iron. It is present in different forms in biological fluids, and alterations in its distribution can induce oxidative stress and neurodegeneration. However, the clinical parameters normally used for monitoring iron concentration in biological fluids (i.e., serum and cerebrospinal fluid) can hardly detect the quantity of circulating iron, while indirect measurements, e.g., magnetic resonance imaging, require further validation. This review summarizes the mechanisms involved in brain iron metabolism, homeostasis, and iron imbalance caused by alterations detectable by standard and non-standard indicators of iron status. These indicators for iron transport, storage, and metabolism can help to understand which biomarkers can better detect iron imbalances responsible for neurodegenerative diseases.

Utility of Multi-Modal MRI for Differentiating of Parkinson's Disease and Progressive Supranuclear Palsy Using Machine Learning

Background: Patients with Parkinson's disease (PD) and progressive supranuclear palsy Richardson's syndrome (PSP-RS) often show overlapping clinical features, leading to misdiagnoses. The objective of this study was to investigate the feasibility and utility of using multi-modal MRI datasets for an automatic differentiation of PD patients, PSP-RS patients, and healthy control (HC) subjects.Material and Methods: T1-weighted, T2-weighted, and diffusion-tensor (DTI) MRI datasets from 45 PD patients, 20 PSP-RS patients, and 38 HC subjects were available for this study. Using an atlas-based approach, regional values of brain morphology (T1-weighted), brain iron metabolism (T2-weighted), and microstructural integrity (DTI) were measured and employed for feature selection and subsequent classification using combinations of various established machine learning methods.Results: The optimal machine learning model using regional morphology features only achieved a classification accuracy of 65% (67/103 correct classifications) differentiating PD patients, PSP-RS patients, and HC subjects. The optimal machine learning model using only quantitative T2 values performed slightly better and achieved an accuracy of 75.7% (78/103). The optimal classifier using DTI features alone performed considerably better with 95.1% accuracy (98/103). The optimal multi-modal classifier using all features also achieved an accuracy of 95.1% but required more features and achieved a slightly lower F1-score compared to the optimal model using DTI features alone.Conclusion: Machine learning models using multi-modal MRI perform significantly better than uni-modal machine learning models using morphological parameters based on T1-weighted MRI datasets alone or brain iron metabolism markers based on T2-weighted MRI datasets alone. However, machine learnig models using regional brain microstructural integrity metrics computed from DTI datasets perform similar to the optimal multi-modal machine learning model. Thus, given the results from this study cohort, it appears that morphology and brain iron metabolism markers may not provide additional value for classification compared to using DTI metrics alone.

Cryo-EM structures and functional characterization of homo- and heteropolymers of human ferritin variants

The role of abnormal brain iron metabolism in neurodegenerative diseases is still insufficiently understood. Here, we investigate the molecular basis of the neurodegenerative disease hereditary ferritinopathy (HF), in which dysregulation of brain iron homeostasis is the primary cause of neurodegeneration. We mutagenized ferritin’s three-fold pores (3FPs), i.e. the main entry route for iron, to investigate ferritin’s iron management when iron must traverse the protein shell through the disrupted four-fold pores (4FPs) generated by mutations in the ferritin light chain (FtL) gene in HF. We assessed the structure and properties of ferritins using cryo-electron microscopy and a range of functional analyses in vitro. Loss of 3FP function did not alter ferritin structure but led to a decrease in protein solubility and iron storage. Abnormal 4FPs acted as alternate routes for iron entry and exit in the absence of functional 3FPs, further reducing ferritin iron-storage capacity. Importantly, even a small number of MtFtL subunits significantly compromises ferritin solubility and function, providing a rationale for the presence of ferritin aggregates in cell types expressing different levels of FtLs in patients with HF. These findings led us to discuss whether modifying pores could be used as a pharmacological target in HF.

Hepcidin overexpression in astrocytes alters brain iron metabolism and protects against amyloid-β induced brain damage in mice

Progressive iron accumulation in the brain and iron-induced oxidative stress are considered to be one of the initial causes of Alzheimer’s disease (AD), and modulation of brain iron level shows promise for its treatment. Hepcidin expressed by astrocytes has been speculated to regulate iron transport across the blood–brain barrier (BBB) and control the whole brain iron load. Whether increasing the expression of astrocyte hepcidin can reduce brain iron level and relieve AD symptoms has yet to be studied. Here, we overexpressed hepcidin in astrocytes of the mouse brain and challenged the mice with amyloid-β25–35 (Aβ25–35) by intracerebroventricular injection. Our results revealed that hepcidin overexpression in astrocytes significantly ameliorated Aβ25–35-induced cell damage in both the cerebral cortex and hippocampus. This protective role was also attested by behavioral tests of the mice. Our data further demonstrated that astrocyte-overexpressed hepcidin could decrease brain iron level, possibly by acting on ferroportin 1 (FPN1) on the brain microvascular endothelial cells (BMVECs), which in turn reduced Aβ25–35-induced oxidative stress and apoptosis, and ultimately protected cells from damage. This study provided in vivo evidences of the important role of astrocyte hepcidin in the regulation of brain iron metabolism and protection against Aβ-induced cortical and hippocampal damages and implied its potential in the treatment of oxidative stress-related brain disorders.

Age-Related Changes and Sex-Related Differences in Brain Iron Metabolism

Iron is an essential element that participates in numerous cellular processes. Any disruption of iron homeostasis leads to either iron deficiency or iron overload, which can be detrimental for humans’ health, especially in elderly. Each of these changes contributes to the faster development of many neurological disorders or stimulates progression of already present diseases. Age-related cellular and molecular alterations in iron metabolism can also lead to iron dyshomeostasis and deposition. Iron deposits can contribute to the development of inflammation, abnormal protein aggregation, and degeneration in the central nervous system (CNS), leading to the progressive decline in cognitive processes, contributing to pathophysiology of stroke and dysfunctions of body metabolism. Besides, since iron plays an important role in both neuroprotection and neurodegeneration, dietary iron homeostasis should be considered with caution. Recently, there has been increased interest in sex-related differences in iron metabolism and iron homeostasis. These differences have not yet been fully elucidated. In this review we will discuss the latest discoveries in iron metabolism, age-related changes, along with the sex differences in iron content in serum and brain, within the healthy aging population and in neurological disorders such as multiple sclerosis, Parkinson’s disease, Alzheimer’s disease, and stroke.