Modern Brainstem MRI Techniques for the Diagnosis of Parkinson's Disease and Parkinsonisms

Advanced Immunolabeling Method for Optical Volumetric Imaging Reveals Dystrophic Neurites of Dopaminergic Neurons in Alzheimer's Disease Mouse Brain

Optical brain clearing combined with immunolabeling is valuable for analyzing molecular tissue structures, including complex synaptic connectivity. However, the presence of aberrant lipid deposition due to aging and brain disorders poses a challenge for achieving antibody penetration throughout the entire brain volume. Herein, we present an efficient brain-wide immunolabeling method, the immuno-active clearing technique (iACT). The treatment of brain tissues with a zwitterionic detergent, specifically SB3-12, significantly enhanced tissue permeability by effectively mitigating lipid barriers. Notably, Quadrol treatment further refines the methodology by effectively eliminating residual detergents from cleared brain tissues, subsequently amplifying volumetric fluorescence signals. Employing iACT, we uncover disrupted axonal projections within the mesolimbic dopaminergic (DA) circuits in 5xFAD mice. Subsequent characterization of DA neural circuits in 5xFAD mice revealed proximal axonal swelling and misrouting of distal axonal compartments in proximity to amyloid-beta plaques. Importantly, these structural anomalies in DA axons correlate with a marked reduction in DA release within the nucleus accumbens. Collectively, our findings highlight the efficacy of optical volumetric imaging with iACT in resolving intricate structural alterations in deep brain neural circuits. Furthermore, we unveil the compromised integrity of DA pathways, contributing to the underlying neuropathology of Alzheimer's disease. The iACT technique thus holds significant promise as a valuable asset for advancing our understanding of complex neurodegenerative disorders and may pave the way for targeted therapeutic interventions.

Exploiting macro- and micro-structural brain changes for improved Parkinson's disease classification from MRI data

Parkinson's disease (PD) is the second most common neurodegenerative disease. Accurate PD diagnosis is crucial for effective treatment and prognosis but can be challenging, especially at early disease stages. This study aimed to develop and evaluate an explainable deep learning model for PD classification from multimodal neuroimaging data. The model was trained using one of the largest collections of T1-weighted and diffusion-tensor magnetic resonance imaging (MRI) datasets. A total of 1264 datasets from eight different studies were collected, including 611 PD patients and 653 healthy controls (HC). These datasets were pre-processed and non-linearly registered to the MNI PD25 atlas. Six imaging maps describing the macro- and micro-structural integrity of brain tissues complemented with age and sex parameters were used to train a convolutional neural network (CNN) to classify PD/HC subjects. Explainability of the model's decision-making was achieved using SmoothGrad saliency maps, highlighting important brain regions. The CNN was trained using a 75%/10%/15% train/validation/test split stratified by diagnosis, sex, age, and study, achieving a ROC-AUC of 0.89, accuracy of 80.8%, specificity of 82.4%, and sensitivity of 79.1% on the test set. Saliency maps revealed that diffusion tensor imaging data, especially fractional anisotropy, was more important for the classification than T1-weighted data, highlighting subcortical regions such as the brainstem, thalamus, amygdala, hippocampus, and cortical areas. The proposed model, trained on a large multimodal MRI database, can classify PD patients and HC subjects with high accuracy and clinically reasonable explanations, suggesting that micro-structural brain changes play an essential role in the disease course.

Neuromelanin-sensitive MRI as a promising biomarker of catecholamine function

Disruptions to dopamine and noradrenergic neurotransmission are noted in several neurodegenerative and psychiatric disorders. Neuromelanin-sensitive (NM)-MRI offers a non-invasive approach to visualize and quantify the structural and functional integrity of the substantia nigra and locus coeruleus. This method may aid in the diagnosis and quantification of longitudinal changes of disease and could provide a stratification tool for predicting treatment success of pharmacological interventions targeting the dopaminergic and noradrenergic systems. Given the growing clinical interest in NM-MRI, understanding the contrast mechanisms that generate this signal is crucial for appropriate interpretation of NM-MRI outcomes and for the continued development of quantitative MRI biomarkers that assess disease severity and progression. To date, most studies associate NM-MRI measurements to the content of the neuromelanin pigment and/or density of neuromelanin-containing neurons, while recent studies suggest that the main source of the NM-MRI contrast is not the presence of neuromelanin but the high-water content in the dopaminergic and noradrenergic neurons. In this review, we consider the biological and physical basis for the NM-MRI contrast and discuss a wide range of interpretations of NM-MRI. We describe different acquisition and image processing approaches and discuss how these methods could be improved and standardized to facilitate large-scale multisite studies and translation into clinical use. We review the potential clinical applications in neurological and psychiatric disorders and the promise of NM-MRI as a biomarker of disease, and finally, we discuss the current limitations of NM-MRI that need to be addressed before this technique can be utilized as a biomarker and translated into clinical practice and offer suggestions for future research.

Caffeine alleviates anxiety-like behavior and brainstem lesions in a rotenone-induced rat model of Parkinson's disease

BACKGROUND

Parkinson's disease (PD) is a neurodegenerative disorder characterized by motor and non-motor symptoms. In 2016, approximately 6.1 million individuals were affected by PD, with 211,296 deaths attributed to the disease. The understanding of PD initially came from the observation of dopaminergic system alterations in a specific region of the brainstem, indicating that the core motor and non-motor features of PD are closely associated with brainstem dysfunction. The primary treatment approach for PD revolves around dopamine replacement, as many of the symptoms are responsive to this therapeutic intervention. However, long-term administration of this approach is linked to several complications, and a definitive gold-standard therapy for PD is yet to be identified. The pharmacological management of PD has been challenging and inconsistent, mainly due to the unclear underlying cause of the disease. This study aims to evaluate the effects of caffeine on the brainstem of rats with PD induced by rotenone.

METHODOLOGY

Fifty adult male Wistar rats weighing between 150 and 200 g were used in this study. The rats were randomly divided into five groups of ten rats each: Vehicle Group, Rotenone-only treated Group (rotenone only treated with 3 mg/kg, intraperitoneal administration [IP]), Preventive Group (caffeine 30 mg/kg + rotenone 3 mg/kg, IP), Curative Group (rotenone 3 mg/kg + caffeine 30 mg/kg, IP), and Caffeine only treated Group (caffeine only treated with 30 mg/kg, IP). The animals underwent neurobehavioral assessments, followed by sacrifice. The brains were then excised, weighed, and processed histologically. Appropriate brain sections were taken and processed. Photomicrographs were obtained, morphometric and statistical analysis was performed using an Omax LED digital RESULTS: The results demonstrated a significant (p < 0.05) reduction in body weight and relative brain weight, which were increased by caffeine treatments. Rotenone administration led to histological changes similar to those observed in PD, including neuronal structural derangement, degenerated nerve fibers, loss of myelinated neurons, and Nissl substance, as well as downregulation in the expressions of NRF2 and TH in the midbrain. However, these pathological features were counteracted or ameliorated by caffeine treatment.

CONCLUSION

Our study contributes additional evidence to the growing body of research supporting the therapeutic potential of caffeine in Parkinson's disease (PD). The results underscore the neuroprotective properties of caffeine and its capacity to mitigate oxidative stress by modulating TH (tyrosine hydroxylase) and cytoplasmic NRF2 (nuclear factor erythroid 2-related factor 2) in the mesencephalon. These findings suggest that caffeine holds promise as a viable treatment option for PD.

Neuroinflammation and Mitochondrial Dysfunction in Parkinson's Disease: Connecting Neuroimaging with Pathophysiology

There is a pressing need for disease-modifying therapies in patients suffering from neurodegenerative diseases, including Parkinson's disease (PD). However, these disorders face unique challenges in clinical trial designs to assess the neuroprotective properties of potential drug candidates. One of these challenges relates to the often unknown individual disease mechanisms that would, however, be relevant for targeted treatment strategies. Neuroinflammation and mitochondrial dysfunction are two proposed pathophysiological hallmarks and are considered to be highly interconnected in PD. Innovative neuroimaging methods can potentially help to gain deeper insights into one's predominant disease mechanisms, can facilitate patient stratification in clinical trials, and could potentially map treatment responses. This review aims to highlight the role of neuroinflammation and mitochondrial dysfunction in patients with PD (PwPD). We will specifically introduce different neuroimaging modalities, their respective technical hurdles and challenges, and their implementation into clinical practice. We will gather preliminary evidence for their potential use in PD research and discuss opportunities for future clinical trials.

Structural alterations of spinocerebellar ataxias type 3: from pre-symptomatic to symptomatic stage

OBJECTIVES

To investigate and characterize the structural alterations of the brain in SCA3, and their correlations with the scale for the assessment and rating of ataxia (SARA) and normal brain ATXN3 expression.

METHODS

We performed multimodal analyses in 52 SCA3 (15 pre-symptomatic) and healthy controls (HCs) (n = 35) to assess the abnormalities of gray and white matter (WM) of the cerebrum, brainstem, and cerebellum via FreeSurfer, SUIT, and TBSS, and their associations with disease severity. Twenty SCA3 patients (5 pre- and 15 symptomatic) were followed for at least a year. Besides, we uncovered the normal pattern of brain ATXN3 spatial distribution.

RESULTS

Pre-symptomatic patients showed only WM damage, mainly in the cerebellar peduncles, compared to HCs. In the advanced stage, the WM damage followed a caudal-rostral pattern. Meanwhile, continuous nonlinear structure damage was characterized by brainstem volumetric reduction and relatively symmetric cerebellar and basal ganglia atrophy but spared the cerebral cortex, partially explained by the ATXN3 overexpression. The bilateral pallidum, brainstem, and cerebellar peduncles demonstrated a very large effect size. Besides, all these alterations were significantly correlated with SARA; the pons (r = -0.65) and superior cerebellar peduncle (r = -0.68) volume demonstrated a higher correlation than the cerebellum with SARA. The longitudinal study further uncovered progressive atrophy of pons in symptomatic SCA3.

CONCLUSIONS

Significant WM damage starts before the ataxia onset. The bilateral pallidum, brainstem, and cerebellar peduncles are the most vulnerable targets. The volume of pons appears to be the most promising imaging biomarker for a longitudinal study.

TRIAL REGISTRATION

ClinicalTrial ID: ChiCTR2100045857 ( http://www.chictr.org.cn/edit.aspx?pid=55652&htm=4 ) KEY POINTS: • Pre- SCA3 showed WM damage mainly in cerebellar peduncles. Continuous brain damage was characterized by brainstem, widespread, and relatively symmetric cerebellar and basal ganglia atrophy. • Volumetric abnormalities were most evident in the bilateral pallidum, brainstem, and cerebellar peduncles in SCA3. • The volume of pons might identify the disease progression longitudinally.

Relevance of 18F-DOPA visual and semi-quantitative PET metrics for the diagnostic of Parkinson disease in clinical practice: a machine learning-based inference study

PURPOSE

To decipher the relevance of visual and semi-quantitative 6-fluoro-(18F)-L-DOPA (¹⁸F-DOPA) interpretation methods for the diagnostic of idiopathic Parkinson disease (IPD) in hybrid positron emission tomography (PET) and magnetic resonance imaging.

MATERIAL AND METHODS

A total of 110 consecutive patients (48 IPD and 62 controls) with 11 months of median clinical follow-up (reference standard) were included. A composite visual assessment from five independent nuclear imaging readers, together with striatal standard uptake value (SUV) to occipital SUV ratio, striatal gradients and putamen asymmetry-based semi-quantitative PET metrics automatically extracted used to train machine learning models to classify IPD versus controls. Using a ratio of 70/30 for training and testing sets, respectively, five classification models-k-NN, LogRegression, support vector machine, random forest and gradient boosting-were trained by using 100 times repeated nested cross-validation procedures. From the best model on average, the contribution of PET parameters was deciphered using the Shapley additive explanations method (SHAP). Cross-validated receiver operating characteristic curves (cv-ROC) of the most contributive PET parameters were finally estimated and compared.

RESULTS

The best machine learning model (k-NN) provided final cv-ROC of 0.81. According to SHAP analyses, visual PET metric was the most important contributor to the model overall performance, followed by the minimum between left and right striatal to occipital SUV ratio. The 10-time cv-ROC curves of visual, min SUVr or both showed quite similar performance (mean area under the ROC of 0.81, 0.81 and 0.79, respectively, for visual, min SUVr or both).

CONCLUSION

Visual expert analysis remains the most relevant parameter to predict IPD diagnosis at 11 months of median clinical follow-up in ¹⁸F-FDOPA. The min SUV ratio appears interesting in the perspective of simple semi-automated diagnostic workflows.

Combined regional T1w/T2w ratio and voxel-based morphometry in multiple system atrophy: A follow-up study

Several MRI techniques have become available to support the early diagnosis of multiple system atrophy (MSA), but few longitudinal studies on both MSA variants have been performed, and there are no established MRI markers of disease progression. We aimed to characterize longitudinal brain changes in 26 patients with MSA (14 MSA-P and 12 MSA-C) over a 1-year follow-up period in terms of local tissue density and T1w/T2w ratio in a-priori regions, namely, bilateral putamen, cerebellar gray matter (GM), white matter (WM), and substantia nigra (SN). A significant GM density decrease was found in cerebellum and left putamen in the entire group (10.7 and 33.1% variation, respectively) and both MSA subtypes (MSA-C: 15.4 and 33.0% variation; MSA-P: 7.7 and 33.2%) and in right putamen in the entire group (19.8% variation) and patients with MSA-C (20.9% variation). A WM density decrease was found in the entire group (9.3% variation) and both subtypes in cerebellum-brainstem (MSA-C: 18.0% variation; MSA-P: 5% variation). The T1w/T2w ratio increase was found in the cerebellar and left putamen GM (6.6 and 24.9% variation), while a significant T1w/T2w ratio decrease was detected in SN in the entire MSA group (31% variation). We found a more progressive atrophy of the cerebellum in MSA-C with a similar progression of putaminal atrophy in the two variants. T1w/T2w ratio can be further studied as a potential marker of disease progression, possibly reflecting decreased neuronal density or iron accumulation.

Diffusion Magnetic Resonance Imaging Microstructural Abnormalities in Multiple System Atrophy: A Comprehensive Review

Multiple system atrophy (MSA) is a neurodegenerative disease characterized by autonomic failure, ataxia, and/or parkinsonism. Its prominent pathological alterations can be investigated using diffusion magnetic resonance imaging (dMRI), a technique that exploits the characteristics of water random motion inside brain tissue. The aim of this report was to review currently available literature on the application of dMRI in MSA and to describe microstructural abnormalities, diagnostic applications, and pathophysiological correlates. Sixty-four published studies involving microstructural investigation using dMRI in MSA were included. Widespread microstructural abnormalities of white matter were described, especially in the middle cerebellar peduncle, corticospinal tract, and hemispheric fibers. Gray matter degeneration was identified as well, with diffuse involvement of subcortical structures, especially in the putamina. Diagnostic applications of dMRI were mostly explored for the differential diagnosis between MSA parkinsonism and Parkinson's disease. Recently, machine learning algorithms for image processing and disease classification have demonstrated high diagnostic accuracy, showing potential for translation into clinical practice. To a lesser extent, clinical correlates of microstructural abnormalities have also been investigated, and abnormalities related to motor, ocular, and cognitive impairments were described. dMRI in MSA has contributed to in vivo identification of known pathological abnormalities. Translation into clinical practice of the latest advancements for the differential diagnosis between MSA and other forms of parkinsonism seems feasible. Current limitations involve the possibility of correctly diagnosing MSA in the very early stages, when the clinical diagnosis is most uncertain. Furthermore, pathophysiological correlates of microstructural abnormalities remain understudied. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Multiple system atrophy

Multiple system atrophy (MSA) is a rare neurodegenerative disease that is characterized by neuronal loss and gliosis in multiple areas of the central nervous system including striatonigral, olivopontocerebellar and central autonomic structures. Oligodendroglial cytoplasmic inclusions containing misfolded and aggregated α-synuclein are the histopathological hallmark of MSA. A firm clinical diagnosis requires the presence of autonomic dysfunction in combination with parkinsonism that responds poorly to levodopa and/or cerebellar ataxia. Clinical diagnostic accuracy is suboptimal in early disease because of phenotypic overlaps with Parkinson disease or other types of degenerative parkinsonism as well as with other cerebellar disorders. The symptomatic management of MSA requires a complex multimodal approach to compensate for autonomic failure, alleviate parkinsonism and cerebellar ataxia and associated disabilities. None of the available treatments significantly slows the aggressive course of MSA. Despite several failed trials in the past, a robust pipeline of putative disease-modifying agents, along with progress towards early diagnosis and the development of sensitive diagnostic and progression biomarkers for MSA, offer new hope for patients.

Morphometric imaging and quantitative susceptibility mapping as complementary tools in the diagnosis of parkinsonisms

Background and purpose

In the quest for in vivo diagnostic biomarkers to discriminate Parkinson's disease (PD) from progressive supranuclear palsy (PSP) and multiple system atrophy (MSA, mainly p phenotype), many advanced magnetic resonance imaging (MRI) techniques have been studied. Morphometric indices, such as the Magnetic Resonance Parkinsonism Index (MRPI), demonstrated high diagnostic value in the comparison between PD and PSP. The potential of quantitative susceptibility mapping (QSM) was hypothesized, as increased magnetic susceptibility (Δχ) was reported in the red nucleus (RN) and medial part of the substantia nigra (SNImed) of PSP patients and in the putamen of MSA patients. However, disease‐specific susceptibility values for relevant regions of interest are yet to be identified. The aims of the study were to evaluate the diagnostic potential of a multimodal MRI protocol combining morphometric and QSM imaging in patients with determined parkinsonisms and to explore its value in a population of undetermined cases.

Method

Patients with suspected degenerative parkinsonism underwent clinical evaluation, 3 T brain MRI and clinical follow‐up. The MRPI was manually calculated on T1‐weighted images. QSM maps were generated from 3D multi‐echo T2*‐weighted sequences.

Results

In determined cases the morphometric evaluation confirmed optimal diagnostic accuracy in the comparison between PD and PSP but failed to discriminate PD from MSA‐p. Significant nigral and extranigral differences were found with QSM. RN Δχ showed excellent diagnostic accuracy in the comparison between PD and PSP and good accuracy in the comparison of PD and MSA‐p. Optimal susceptibility cut‐off values of RN and SNImed were tested in undetermined cases in addition to MRPI.

Conclusions

A combined use of morphometric imaging and QSM could improve the diagnostic phase of degenerative parkinsonisms.

Improving Imaging of the Brainstem and Cerebellum in Autistic Children: Transformation-Based High-Resolution Diffusion MRI (TiDi-Fused) in the Human Brainstem

Diffusion-weighted magnetic resonance imaging (dMRI) of the brainstem is technically challenging, especially in young autistic children as nearby tissue-air interfaces and motion (voluntary and physiological) can lead to artifacts. This limits the availability of high-resolution images, which are desirable for improving the ability to study brainstem structures. Furthermore, inherently low signal-to-noise ratios, geometric distortions, and sensitivity to motion not related to molecular diffusion have resulted in limited techniques for high-resolution data acquisition compared to other modalities such as T1-weighted imaging. Here, we implement a method for achieving increased apparent spatial resolution in pediatric dMRI that hinges on accurate geometric distortion correction and on high fidelity within subject image registration between dMRI and magnetization prepared rapid acquisition gradient echo (MPnRAGE) images. We call this post-processing pipeline T1 weighted-diffusion fused, or "TiDi-Fused". Data used in this work consists of dMRI data (2.4 mm resolution, corrected using FSL's Topup) and T1-weighted (T1w) MPnRAGE anatomical data (1 mm resolution) acquired from 128 autistic and non-autistic children (ages 6-10 years old). Accurate correction of geometric distortion permitted for a further increase in apparent resolution of the dMRI scan via boundary-based registration to the MPnRAGE T1w. Estimation of fiber orientation distributions and further analyses were carried out in the T1w space. Data processed with the TiDi-Fused method were qualitatively and quantitatively compared to data processed with conventional dMRI processing methods. Results show the advantages of the TiDi-Fused pipeline including sharper brainstem gray-white matter tissue contrast, improved inter-subject spatial alignment for group analyses of dMRI based measures, accurate spatial alignment with histology-based imaging of the brainstem, reduced variability in brainstem-cerebellar white matter tracts, and more robust biologically plausible relationships between age and brainstem-cerebellar white matter tracts. Overall, this work identifies a promising pipeline for achieving high-resolution imaging of brainstem structures in pediatric and clinical populations who may not be able to endure long scan times. This pipeline may serve as a gateway for feasibly elucidating brainstem contributions to autism and other conditions.

Comparative morphometric evaluation of the brainstem in neurodegenerative diseases with healthy individuals using magnetic resonance imaging

Objective

Measurement of a component within the reference value is a widely used parameter in Biomedical Science. This study highlights the value of morphometric changes in healthy individuals’ brainstem structure and their application in the detection and diagnosis of neurodegenerative disorders.

Methods

This retrospective study included magnetic resonance (MR) images of 50 healthy individuals without neurological diseases, 35 clinically diagnosed individuals with Parkinson's disease (PD), and 12 individuals with Progressive Supranuclear Palsy (PSP). Measurements of midbrain area, pons area, ratio of midbrain to pons area, superior profile of midbrain, thickness of substantia nigra (SN), cerebral crus width, interpeduncular distance, and concavity of the crus were analysed as per the standard protocol.

Results

Patients with PD had mean anteroposterior diameter of 1.11 ± 0.1 cm, which was more than the control group and PSP patients. Additionally, PSP patients showed the least midbrain and pons area of 1.06 ± 0.34 and 4.01 ± 1.2 sq.cm, respectively, compared to other groups. The ratio of midbrain to pons area was the least among PSP patients (0.21 ± 0.06 cm). Mean thickness of the right and left middle cerebellar peduncles (1.25 ± 0.19 and 1.24 ± 0.17 cm) was less in the PD group. The width of the SN gradually reduced in PD and more so in PSP patients. The convex superior profile of the midbrain was a consistent feature in all groups.

Conclusion

This study highlights the value of morphometrics of the brainstem profile in differentiating neurodegenerative diseases among aged, healthy individuals when combined with their clinical data.

Imaging of Substantia Nigra in Parkinson's Disease: A Narrative Review

Parkinson's disease (PD) is a progressive neurodegenerative disorder, characterized by motor and non-motor symptoms due to the degeneration of the pars compacta of the substantia nigra (SNc) with dopaminergic denervation of the striatum. Although the diagnosis of PD is principally based on a clinical assessment, great efforts have been expended over the past two decades to evaluate reliable biomarkers for PD. Among these biomarkers, magnetic resonance imaging (MRI)-based biomarkers may play a key role. Conventional MRI sequences are considered by many in the field to have low sensitivity, while advanced pulse sequences and ultra-high-field MRI techniques have brought many advantages, particularly regarding the study of brainstem and subcortical structures. Nowadays, nigrosome imaging, neuromelanine-sensitive sequences, iron-sensitive sequences, and advanced diffusion weighted imaging techniques afford new insights to the non-invasive study of the SNc. The use of these imaging methods, alone or in combination, may also help to discriminate PD patients from control patients, in addition to discriminating atypical parkinsonian syndromes (PS). A total of 92 articles were identified from an extensive review of the literature on PubMed in order to ascertain the-state-of-the-art of MRI techniques, as applied to the study of SNc in PD patients, as well as their potential future applications as imaging biomarkers of disease. Whilst none of these MRI-imaging biomarkers could be successfully validated for routine clinical practice, in achieving high levels of accuracy and reproducibility in the diagnosis of PD, a multimodal MRI-PD protocol may assist neuroradiologists and clinicians in the early and differential diagnosis of a wide spectrum of neurodegenerative disorders.

Inflaming the Brain with Iron

Iron accumulation and neuroinflammation are pathological conditions found in several neurodegenerative diseases, including Alzheimer's disease (AD) and Parkinson's disease (PD). Iron and inflammation are intertwined in a bidirectional relationship, where iron modifies the inflammatory phenotype of microglia and infiltrating macrophages, and in turn, these cells secrete diffusible mediators that reshape neuronal iron homeostasis and regulate iron entry into the brain. Secreted inflammatory mediators include cytokines and reactive oxygen/nitrogen species (ROS/RNS), notably hepcidin and nitric oxide (·NO). Hepcidin is a small cationic peptide with a central role in regulating systemic iron homeostasis. Also present in the cerebrospinal fluid (CSF), hepcidin can reduce iron export from neurons and decreases iron entry through the blood-brain barrier (BBB) by binding to the iron exporter ferroportin 1 (Fpn1). Likewise, ·NO selectively converts cytosolic aconitase (c-aconitase) into the iron regulatory protein 1 (IRP1), which regulates cellular iron homeostasis through its binding to iron response elements (IRE) located in the mRNAs of iron-related proteins. Nitric oxide-activated IRP1 can impair cellular iron homeostasis during neuroinflammation, triggering iron accumulation, especially in the mitochondria, leading to neuronal death. In this review, we will summarize findings that connect neuroinflammation and iron accumulation, which support their causal association in the neurodegenerative processes observed in AD and PD.