Subregional analysis of striatum iron in Parkinson's disease and rapid eye movement sleep behaviour disorder

Multimodal magnetic resonance imaging studies on non-motor symptoms of Parkinson's disease

Objective

This study aims to investigate the diagnostic value of multi-modal magnetic resonance imaging (MRI) utilizing arterial spin labeling (ASL), quantitative susceptibility mapping (QSM), and 3D T1-weighted imaging (3DT1WI) in patients with Parkinson's disease (PD). Additionally, it evaluates the relationship between MRI findings and non-motor symptoms associated with PD.

Methods

ASL, QSM, and 3DT1WI scans were performed on 48 PD patients and 46 healthy controls (HC). We extracted and analyzed differences in regional cerebral blood flow (rCBF), magnetic susceptibility, and gray matter density parameters between the two groups. These MRI parameters were correlated with clinical scale scores assessing non-motor symptoms, including cognitive function, sleep quality, olfaction, autonomic function, anxiety, depression, and fatigue. Receiver operating characteristic (ROC) curves were used to evaluate the diagnostic accuracy of each imaging modality in distinguishing PD from HC.

Results

The areas under the ROC curve (AUC) for rCBF, magnetic susceptibility, and gray matter density were 0.941, 0.979, and 0.624, respectively. In PD patients, a negative correlation was found between Unified Parkinson's Disease Rating Scale Part II (UPDRS II) scores and rCBF in the bilateral precuneus. The Pittsburgh Sleep Quality Index (PSQI) scores negatively correlated with rCBF in the left middle temporal gyrus and right middle occipital gyrus. Hamilton Depression Rating Scale (HAMD) scores positively correlated with QSM values in the right supplementary motor area, while scores on the Argentine Smell Identification Test (AHRS) negatively correlated with QSM values in the same area. Disease duration showed a positive correlation with QSM values in the right middle cingulate gyrus. Additionally, PSQI scores positively correlated with QSM values in the left middle cingulate gyrus, and fatigue severity scale (FSS) scores also positively correlated with QSM values in the left middle cingulate gyrus. Gray matter atrophy in the left inferior temporal gyrus was associated with cognitive impairment in PD.

Conclusion

Occipital hypoperfusion and cortical atrophy in the left inferior temporal gyrus may serve as novel imaging biomarkers for PD and are associated with sleep disturbances and cognitive impairment in PD patients. Extensive iron deposition in the bilateral cerebral cortex of PD patients may be a contributing factor to non-motor symptoms such as sleep disturbances and fatigue. Multimodal imaging techniques, including ASL, QSM, and 3DT1WI, can enhance the diagnostic accuracy for PD.

Establishment of a Biomarker-Directed Clinical Endpoint Model for Early-Stage Parkinson's Disease Patients

Parkinson's Disease (PD) is a neurodegenerative disorder characterized by dopaminergic cell death in the substantia nigra. While the interplay between dopamine loss and symptoms is well-recognized, a respective quantitative link has yet to be established. The objective was to establish a biomarker-directed clinical endpoint model for early-stage PD patients. We developed a disease progression model using DATscan data in 196 healthy subjects and 419 Parkinson's patients to characterize the onset and progression of disease in early-stage PD patients. This disease progression model was then linked to MDS-UPDRS Parts I, II, and III data from the Parkinson's Progression Markers Initiative (PPMI) using a modified item response theory (IRT) analysis to characterize and predict the impact of dopamine loss on motor and non-motor symptoms. Disease onset occurs ~4-15 years pre-diagnosis. There is correlation (Spearman's rank correlation: 0.73-0.78, P < 0.001) between striatal binding ratio values (SBR) and MDS-UPDRS total scores in early-stage PD patients once interindividual differences in age at diagnosis and onset of symptoms are considered. Stratification by degree of damage improved the model's performance for putamen/motor symptoms but not for caudate/cognitive symptoms. The model captured changes in MDS-UPDRS Parts I, II, and III in early-stage, moderately progressing PD patients (60-65% of PPMI patients). In conclusion, we developed an SBR-directed IRT model that characterizes changes in MDS-UPDRS in > 60% of early-stage PPMI patients for ~15 years.

Midbrain and pallidal iron changes identify patients with REM sleep behaviour disorder and Parkinson's disease

Idiopathic REM sleep behaviour disorder (iRBD) is considered a prodromal form of Parkinson's Disease (PD), potentially exhibiting similar patterns of neurodegeneration, such as brain iron changes. We investigated midbrain and pallidal iron using quantitative susceptibility mapping (QSM) in 16 iRBD patients, 30 PD patients, and 38 age-matched healthy controls (HCs) with 3T MRI. QSM revealed elevated substantia nigra pars compacta (SNc) mean susceptibility in both iRBD and PD patient groups compared to HCs, though iRBD and PD QSM measures did not differ. There were no SN pars reticulata group differences. Mean susceptibility was reduced for PD relative to iRBD and HCs in the globus pallidus externa (GPe). Furthermore, mean susceptibility was reduced for PD relative to iRBD in the GP interna (GPi). GPe/GPi mean susceptibility decreased with PD subgroup motor severity. Consistent with this, QSM in left GPi and MDS-UPDRS-III scores correlated negatively in PD patients, as well as in iRBD and PD patients combined. PD patients also evidenced higher mean susceptibility in the right ventral tegmental area (VTA) compared to iRBD and HCs, consistent with later VTA degeneration. RBD symptomatology did not correlate with QSM values. Combining SNc, GPe, GPi, and VTA QSM values, we distinguished iRBD-HCs, PD-HCs, and iRBD-PD patients at single-subject levels (0.84, 0.86, and 0.81 accuracies), using ROC curve analyses with repeated k-folds cross-validation. Using 3T MRI, QSM values in SNc, GPe, GPi, and VTA demonstrate promise as investigational measures and diagnostic/progression biomarkers of prodromal and early PD.

Understanding Causal Relationships Between Imaging-Derived Phenotypes and Parkinson's Disease: A Mendelian Randomization and Observational Study

Background/Objectives: Observational studies have suggested a correlation between brain imaging alterations and Parkinson's disease (PD). However, data on causal relationships are still lacking. This study aimed to examine the causal relationship between brain imaging-derived phenotypes (IDPs) and PD. Methods: A bidirectional two-sample Mendelian randomization analysis was conducted to explore the causal association between IDPs and PD. Summary-level data for IDPs (n = 39,691), PD (n = 482,730), and PD symptoms (n = 4093) were obtained from genome-wide association studies of European ancestry. Clinical validation was performed in an Asian cohort, which involved healthy controls (n = 81), patients with idiopathic rapid-eye-movement sleep behavior disorder (iRBD) (n = 47), and patients with PD (n = 85). Results: We found 13 IDPs with significant causal effects on PD and seven reciprocal effects of PD on IDPs. For instance, increased median T2star in the right caudate (odds ratio = 1.23, 95% confidence interval 1.08-1.40, p = 0.0057) and bilateral putamen (left: odds ratio = 1.25, 95% confidence interval 1.09-1.43, p = 0.0056; right: odds ratio = 1.25, 95% confidence interval 1.10-1.43, p = 0.0056) were associated with PD. Enlargement of the left thalamus (odds ratio = 1.50, 95% confidence interval 1.14-1.96, p = 0.016) demonstrated causal links with PD. No reverse causal effects were detected. Observational analyses results in the Asian cohort (healthy controls, iRBD, PD) aligned with the Mendelian randomization results. Conclusions: Our results suggest bidirectional causal links between IDPs and PD, offering insights into disease mechanisms and potential imaging biomarkers for PD.

Reduced Oxygen Extraction Fraction as a Biomarker for Cognitive Deficits in Obstructive Sleep Apnea

BACKGROUND

Obstructive sleep apnea (OSA) is characterized by disruptive breathing, resulting in a decline in cognitive performance. This study investigates the role of oxygen extraction fraction (OEF) and quantitative susceptibility mapping (QSM) in OSA-related cognitive impairment.

METHODS

The study recruited 15 patients with confirmed OSA and 16 healthy controls, who underwent overnight polysomnography and brain MRI using a 3 Tesla machine and 64-channel head coil. A two-step MRI analysis was employed to measure OEF. QSM was first created by processing separate phase and magnitude images. OEF maps were then generated by identifying veins based on their susceptibility. Volumetric analysis was performed using the FreeSurfer. Neuropsychological tests were administered to evaluate cognition.

RESULTS

The analysis of OEF revealed significantly lower values in various cerebral cortical regions of OSA patients than in controls. Notably, OEF in the cerebral cortex and frontal, temporal, and occipital regions showed negative correlations with the duration of stage N2 sleep (highest correlation between N2 and right temporal OEF: p = 0.005, r = -0.681). Furthermore, poorer performance on neuropsychological tests, such as the backward digit span test, was significantly correlated with reduced OEF in the left hemisphere (p = 0.016), left cerebral cortex (p = 0.019), right frontal (p = 0.034), left frontal (p = 0.014), left parietal (p = 0.008), left temporal (p = 0.048), and left occipital lobes (p = 0.015). No significant differences in QSM or brain volume were observed.

CONCLUSIONS

Decreased OEF emerges as a potential biomarker for cognitive deficits in OSA, suggesting disturbances in cerebral oxygen metabolism may underlie cognitive impairments. These findings underscore the importance of investigating physiological markers in understanding OSA-related cognitive dysfunction.

Relaxometry network based on MRI R2⁎ mapping revealing brain iron accumulation patterns in Parkinson's disease

BACKGROUND

Excessive iron accumulation in the brain has been implicated in Parkinson's disease (PD). However, the patterns and probable sequences of iron accumulation across the PD brain remain largely unknown. This study aimed to explore the sequence of iron accumulation across the PD brain using R2* mapping and a relaxometry covariance network (RCN) approach.

METHODS

R2* quantification maps were obtained from PD patients (n = 34) and healthy controls (n = 25). RCN was configured on R2* maps to identify covariance differences in iron levels between the two groups. Regions with excessive iron accumulation and large covariance changes in PD patients compared to controls were defined as propagators of iron. In the PD group, causal RCN analysis was performed on the R2* maps sequenced according to disease duration to investigate the dynamics of iron accumulations from the propagators. The associations between individual connections of the RCN and clinical information were analyzed in PD patients.

RESULTS

The left substantia nigra pars reticulata (SNpr), left substantia nigra pars compacta (SNpc), and lobule VII of the vermis (VER7) were identified as primary regions for iron accumulation and propagation (propagator). As the disease duration increased, iron accumulation in these three propagators demonstrated positive causal effects on the bilateral pallidum, bilateral gyrus rectus, right middle frontal gyrus, and medial and anterior orbitofrontal cortex (OFC). Furthermore, individual connections of VER7 with the left gyrus rectus and anterior OFC were positively associated with disease duration.

CONCLUSIONS

Our results indicate that the aberrant iron accumulation in PD involves several regions, mainly starts from the SN and cerebellum and extends to the pallidum and cortices. These findings provide preliminary information on sequences of iron accumulation in PD, which may advance our understanding of the disease.

Putamen iron quantification in diseases with neurodegeneration: a meta-analysis of the quantitative susceptibility mapping technique

Quantitative susceptibility mapping (QSM) is an MRI technique that accurately measures iron concentration in brain tissues. This meta-analysis synthesized evidence from 30 studies that used QSM to quantify the iron levels in the putamen. The PRISMA statement was adhered to when conducting the systematic reviews and meta-analyses. We conducted a meta-analysis using a random-effects model, as well as subgroup analyses (disease type, geographic region, field strength, coil, disease type, age, and sex) and sensitivity analysis. A total of 1247 patients and 1035 controls were included in the study. Pooled results showed a standardized mean difference (SMD) of 0.41 (95% CI 0.19 to 0.64), with the strongest effect seen in Alzheimer's disease (AD) at 1.01 (95% CI 0.50 to 1.52). Relapsing-remitting multiple sclerosis (RRMS) also showed increased putaminal iron at 0.37 (95% CI 0.177 to 0.58). No significant differences were observed in Parkinson's disease (PD). No significant differences were found between subgroups based on geographic region, field strength, coil, disease type, age, and sex. The studies revealed significant heterogeneity, with field strength as the primary source, while other factors, such as disease type, location, age, sex, and coil type, may have contributed. The sensitivity analysis showed that these factors did not have a significant influence on the overall results. In summary, this meta-analysis supports abnormalities in putaminal iron content across different diseases with neurodegeneration, especially AD and RRMS, as measured by QSM. This highlights the potential of QSM as an imaging biomarker to better understand disease mechanisms involving disturbances in brain iron homeostasis.

Increased mean diffusivity of the caudal motor SNc identifies patients with REM sleep behaviour disorder and Parkinson's disease

Idiopathic rapid eye movement sleep behaviour disorder (iRBD)-a Parkinson's disease (PD) prodrome-might exhibit neural changes similar to those in PD. Substantia nigra pars compacta (SNc) degeneration underlies motor symptoms of PD. In iRBD and early PD (ePD), we measured diffusion MRI (dMRI) in the caudal motor SNc, which overlaps the nigrosome-1-the earliest-degenerating dopaminergic neurons in PD-and in the striatum. Nineteen iRBD, 26 ePD (1.7 ± 0.03 years), and 46 age-matched healthy controls (HCs) were scanned at Western University, and 47 iRBD, 115 ePD (0.9 ± 0.01 years), and 56 HCs were scanned through the Parkinson's Progression Markers Initiative, using 3T MRI. We segmented the SNc and striatum into subregions using automated probabilistic tractography to the cortex. We measured mean diffusivity (MD) and fractional anisotropy (FA) along white-matter bundles and subregional surfaces. We performed group-level and classification analyses. Increased caudal motor SNc surface MD was the only iRBD-HCs and ePD-HCs difference replicating across datasets (padj < 0.05). No iRBD-ePD differences emerged. Caudal motor SNc surface MD classified patient groups from HCs at the single-subject level with good-to-excellent balanced accuracy in an independent sample (0.91 iRBD and 0.86 iRBD and ePD combined), compared to fair performance for total SNc surface MD (0.72 iRBD and ePD). Caudal motor SNc surface MD correlated significantly with MDS-UPDRS-III scores in ePD patients. Using dMRI and automated segmentation, we detected changes suggesting altered microstructural integrity in iRBD and ePD in the nigrostriatal subregion known to degenerate first in PD. Surface MD of the caudal motor SNc presents a potential measure for inclusion in neuroimaging biomarkers of iRBD and PD.

Analysis of striatal connectivity corresponding to striosomes and matrix in de novo Parkinson's disease and isolated REM behavior disorder

Striosomes and matrix are two compartments that comprise the striatum, each having its own distinct immunohistochemical properties, function, and connectivity. It is currently not clear whether prodromal or early manifest Parkinson's disease (PD) is associated with any striatal matrix or striosomal abnormality. Recently, a method of striatal parcellation using probabilistic tractography has been described and validated, using the distinct connectivity of these two compartments to identify voxels with striosome- and matrix-like connectivity. The goal of this study was to use this approach in tandem with DAT-SPECT, a method used to quantify the level of nigrostriatal denervation, to analyze the striatum in populations of de novo diagnosed, treatment-naïve patients with PD, isolated REM behavioral disorder (iRBD) patients, and healthy controls. We discovered a shift in striatal connectivity, which showed correlation with nigrostriatal denervation. Patients with PD exhibited a significantly higher matrix-like volume and associated connectivity than healthy controls and higher matrix-associated connectivity than iRBD patients. In contrast, the side with less pronounced nigrostriatal denervation in PD and iRBD patients showed a decrease in striosome-like volume and associated connectivity indices. These findings could point to a compensatory neuroplastic mechanism in the context of nigrostriatal denervation and open a new avenue in the investigation of the pathophysiology of Parkinson's disease.

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.

Imaging Biomarkers in Prodromal and Earliest Phases of Parkinson's Disease

Assessing imaging biomarker in the prodromal and early phases of Parkinson's disease (PD) is of great importance to ensure an early and safe diagnosis. In the last decades, imaging modalities advanced and are now able to assess many different aspects of neurodegeneration in PD. MRI sequences can measure iron content or neuromelanin. Apart from SPECT imaging with Ioflupane, more specific PET tracers to assess degeneration of the dopaminergic system are available. Furthermore, metabolic PET patterns can be used to anticipate a phenoconversion from prodromal PD to manifest PD. In this regard, it is worth mentioning that PET imaging of inflammation will gain significance. Molecular imaging of neurotransmitters like serotonin, noradrenaline and acetylcholine shed more light on non-motor symptoms. Outside of the brain, molecular imaging of the heart and gut is used to measure PD-related degeneration of the autonomous nervous system. Moreover, optical coherence tomography can noninvasively detect degeneration of retinal fibers as a potential biomarker in PD. In this review, we describe these state-of-the-art imaging modalities in early and prodromal PD and point out in how far these techniques can and will be used in the future to pave the way towards a biomarker-based staging of PD.