Speculating the timing of iron deposition in the putamen in multiple system atrophy

The Irony of Iron: The Element with Diverse Influence on Neurodegenerative Diseases

Iron accumulation in the brain is a common feature of many neurodegenerative diseases. Its involvement spans across the main proteinopathies involving tau, amyloid-beta, alpha-synuclein, and TDP-43. Accumulating evidence supports the contribution of iron in disease pathologies, but the delineation of its pathogenic role is yet challenged by the complex involvement of iron in multiple neurotoxicity mechanisms and evidence supporting a reciprocal influence between accumulation of iron and protein pathology. Here, we review the major proteinopathy-specific observations supporting four distinct hypotheses: (1) iron deposition is a consequence of protein pathology; (2) iron promotes protein pathology; (3) iron protects from or hinders protein pathology; and (4) deposition of iron and protein pathology contribute parallelly to pathogenesis. Iron is an essential element for physiological brain function, requiring a fine balance of its levels. Understanding of disease-related iron accumulation at a more intricate and systemic level is critical for advancements in iron chelation therapies.

Quantitative susceptibility mapping and blood neurofilament light chain differentiate between parkinsonian disorders

Objectives

We employed quantitative susceptibility mapping (QSM) to assess iron deposition in parkinsonian disorders and explored whether combining QSM values and neurofilament light (NfL) chain levels can improve the accuracy of distinguishing Parkinson’s disease (PD) from multiple system atrophy (MSA) and progressive supranuclear palsy (PSP).

Materials and methods

Forty-seven patients with PD, 28 patients with MSA, 18 patients with PSP, and 28 healthy controls (HC) were enrolled, and QSM data were reconstructed. Susceptibility values in the bilateral globus pallidus (GP), putamen (PUT), caudate nucleus (CN), red nucleus (RN), substantia nigra (SN), and dentate nucleus (DN) were obtained. Plasma NfL levels of 47 PD, 18 MSA, and 14 PSP patients and 22 HC were measured by ultrasensitive Simoa technology.

Results

The highest diagnostic accuracy distinguishing MSA from PD patients was observed with increased susceptibility values in CN (AUC: 0.740). The susceptibility values in RN yielded the highest diagnostic performance for distinguishing PSP from PD patients (AUC: 0.829). Plasma NfL levels were significantly higher in the MSA and PSP groups than in PD and HC groups. Combining the susceptibility values in the RN and plasma NfL levels improved the diagnostic performance for PSP vs. PD (AUC: 0.904), whereas plasma NfL levels had higher diagnostic accuracy for MSA vs. PD (AUC: 0.877).

Conclusion

The exploratory study indicates different patterns of iron accumulation in deep gray matter nuclei in Parkinsonian disorders. Combining QSM values with NfL levels may be a promising biomarker for distinguishing PSP from PD, whereas plasma NfL may be a reliable biomarker for differentiating MSA from PD. QSM and NfL measures appeared to have low accuracy for separating PD from controls.

Semiautomated Algorithm for the Diagnosis of Multiple System Atrophy With Predominant Parkinsonism

Objective

Putaminal iron deposition is an important feature that helps differentiate multiple system atrophy with predominant parkinsonism (MSA-p) from Parkinson’s disease (PD). Most previous studies used visual inspection or quantitative methods with manual manipulation to perform this differentiation. We investigated the value of a new semiautomated diagnostic algorithm using 3T-MR susceptibility-weighted imaging for MSA-p.

Methods

This study included 26 MSA-p, 68 PD, and 41 normal control (NC) subjects. The algorithm was developed in 2 steps: 1) determine the image containing the remarkable putaminal margin and 2) calculate the phase-shift values, which reflect the iron concentration. The next step was to identify the best differentiating conditions among several combinations. The highest phase-shift value of each subject was used to assess the most effective diagnostic set.

Results

The raw phase-shift values were present along the lateral margin of the putamen in each group. It demonstrates an anterior-to-posterior gradient that was identified most frequently in MSA-p. The average of anterior 5 phase shift values were used for normalization. The highest area under the receiver operating characteristic curve (0.874, 80.8% sensitivity, and 86.7% specificity) of MSA-p versus PD was obtained under the combination of 3 or 4 vertical pixels and one dominant side when the normalization methods were applied. In the subanalysis for the MSA-p patients with a longer disease duration, the performance of the algorithm improved.

Conclusion

This algorithm detected the putaminal lateral margin well, provided insight into the iron distribution of the putaminal rim of MSA-p, and demonstrated good performance in differentiating MSA-p from PD.

Update on neuroimaging for categorization of Parkinson's disease and atypical parkinsonism

PURPOSE OF REVIEW

Differential diagnosis of Parkinsonism may be difficult. The objective of this review is to present the work of the last three years in the field of imaging for diagnostic categorization of parkinsonian syndromes focusing on progressive supranuclear palsy (PSP) and multiple system atrophy (MSA).

RECENT FINDINGS

Two main complementary approaches are being pursued. The first seeks to develop and validate manual qualitative or semi-quantitative imaging markers that can be easily used in clinical practice. The second is based on quantitative measurements of magnetic resonance imaging abnormalities integrated in a multimodal approach and in automatic categorization machine learning tools.

SUMMARY

These two complementary approaches obtained high diagnostic around 90% and above in the classical Richardson form of PSP and probable MSA. Future work will determine if these techniques can improve diagnosis in other PSP variants and early forms of the diseases when all clinical criteria are not fully met.

Insights into the pathogenesis of multiple system atrophy: focus on glial cytoplasmic inclusions

Multiple system atrophy (MSA) is a debilitating and fatal neurodegenerative disorder. The disease severity warrants urgent development of disease-modifying therapy, but the disease pathogenesis is still enigmatic. Neurodegeneration in MSA brains is preceded by the emergence of glial cytoplasmic inclusions (GCIs), which are insoluble α-synuclein accumulations within oligodendrocytes (OLGs). Thus, preventive strategies against GCI formation may suppress disease progression. However, although numerous studies have tried to elucidate the molecular pathogenesis of GCI formation, difficulty remains in understanding the pathological interaction between the two pivotal aspects of GCIs; α-synuclein and OLGs. The difficulty originates from several enigmas: 1) what triggers the initial generation and possible propagation of pathogenic α-synuclein species? 2) what contributes to OLG-specific accumulation of α-synuclein, which is abundantly expressed in neurons but not in OLGs? and 3) how are OLGs and other glial cells affected and contribute to neurodegeneration? The primary pathogenesis of GCIs may involve myelin dysfunction and dyshomeostasis of the oligodendroglial cellular environment such as autophagy and iron metabolism. We have previously reported that oligodendrocyte precursor cells are more prone to develop intracellular inclusions in the presence of extracellular fibrillary α-synuclein. This finding implies a possibility that the propagation of GCI pathology in MSA brains is mediated through the internalization of pathological α-synuclein into oligodendrocyte precursor cells. In this review, in order to discuss the pathogenesis of GCIs, we will focus on the composition of neuronal and oligodendroglial inclusions in synucleinopathies. Furthermore, we will introduce some hypotheses on how α-synuclein pathology spreads among OLGs in MSA brains, in the light of our data from the experiments with primary oligodendrocyte lineage cell culture. While various reports have focused on the mysterious source of α-synuclein in GCIs, insights into the mechanism which regulates the uptake of pathological α-synuclein into oligodendroglial cells may yield the development of the disease-modifying therapy for MSA. The interaction between glial cells and α-synuclein is also highlighted with previous studies of post-mortem human brains, cultured cells, and animal models, which provide comprehensive insight into GCIs and the MSA pathomechanisms.

The role of iron in Parkinson's disease monkeys assessed by susceptibility weighted imaging and inductively coupled plasma mass spectrometry

Mounting evidences indicated that elevated iron levels in the substantia nigra (SN) have been concerned as the underlying mechanisms of neurodegenerative diseases, including Parkinson's disease (PD). The present study used the 1-Methyl-4-phenyl-1, 2, 3, 6 -tetrahydropyridine (MPTP)-treated cynomolgus monkeys for PD to evaluate the usability of SWI for assessing iron deposition in the cerebral nuclei of PD. The results showed that susceptibility-weighted imaging (SWI) phase values of the ipsilateral (MPTP-lesion side) SN of MPTP-treated monkeys were lower than those in the contralateral SN of MPTP-treated monkeys and the same side of Control monkeys, suggesting that iron deposition were elevated in the affected side SN of MPTP-treated monkeys. Whereas MPTP has not effects on the SWI phase values in other detected brain regions of monkeys, including red nucleus (RN), putamen (PUT) and caudate nucleus (CA). Furthermore, ICP-MS results showed that MPTP increased the iron levels in MPTP injection side, but no in the ipsilateral striatum. Additionally, MPTP treatment did not affect the calcium and manganese levels in the detected brain regions of monkeys. However, Pearson correlation analysis results indicated that there were not relationship between SWI phase values in MPTP-lesion side of SN with the behavioral score, tyrosine hydroxylase (TH)-positive cells number and iron levels in the MPTP-lesion side of midbrain. Taken together, the results confirm the involvement of SN iron accumulations in the MPTP-treated monkey models for PD, and indirectly verify the usability of SWI for the measurement of iron deposition in the cerebral nuclei of PD.

Quantifying iron deposition in the cerebellar subtype of multiple system atrophy and spinocerebellar ataxia type 6 by quantitative susceptibility mapping

We used quantitative susceptibility mapping (QSM) to assess the brain iron deposition in 28 patients with the cerebellar subtype of multiple system atrophy (MSA-C), nine patients with spinocerebellar ataxia type 6 (SCA6), and 23 healthy controls. Two reviewers independently measured the mean QSM values in brain structures including the putamen, globus pallidus, caudate nucleus, red nucleus, substantia nigra, and cerebellar dentate nucleus. A receiver operating characteristics (ROC) analysis was performed to assess the diagnostic usefulness of the QSM measurements. The QSM values in the substantia nigra were significantly higher in the MSA-C group compared to the HC group (p = .007). The QSM values in the cerebellar dentate nucleus were significantly higher in MSA-C than those in the SCA6 and HC groups (p < .001), and significantly lower in the SCA6 patients compared to the HCs (p = .027). The QSM values in the cerebellar dentate nucleus were correlated with disease duration in MSA-C, but inversely correlated with disease duration in SCA6. In the ROC analysis, the QSM values in the cerebellar dentate nucleus showed excellent accuracy for differentiating MSA-C from SCA6 (area under curve [AUC], 0.925), and good accuracy for differentiating MSA-C from healthy controls (AUC 0.834). QSM can identify increased susceptibility of the substantia nigra and cerebellar dentate nucleus in MSA-C patients. These results suggest that an increase in iron accumulation in the cerebellar dentate nucleus may be secondary to the neurodegeneration associated with MSA-C.