Locus Coeruleus Degeneration Correlated with Levodopa Resistance in Parkinson's Disease: A Retrospective Analysis

Grid cells: the missing link in understanding Parkinson's disease?

The mechanisms underlying Parkinson's disease (PD) are complex and not fully understood, and the box-and-arrow model among other current models present significant challenges. This paper explores the potential role of the allocentric brain and especially its grid cells in several PD motor symptoms, including bradykinesia, kinesia paradoxa, freezing of gait, the bottleneck phenomenon, and their dependency on cueing. It is argued that central hubs, like the locus coeruleus and the pedunculopontine nucleus, often narrowly interpreted in the context of PD, play an equally important role in governing the allocentric brain as the basal ganglia. Consequently, the motor and secondary motor (e.g., spatially related) symptoms of PD linked with dopamine depletion may be more closely tied to erroneous computation by grid cells than to the basal ganglia alone. Because grid cells and their associated central hubs introduce both spatial and temporal information to the brain influencing velocity perception they may cause bradykinesia or hyperkinesia as well. In summary, PD motor symptoms may primarily be an allocentric disturbance resulting from virtual faulty computation by grid cells revealed by dopamine depletion in PD.

Diagnostic value of combined magnetic resonance imaging techniques in the evaluation of Parkinson disease

Background

The incidence of Parkinson disease (PD) has been increasing each year. The development of new magnetic resonance imaging (MRI) technology can help understand its pathogenesis and identify more effective imaging-based biological indicators.

Methods

The clinical and MRI imaging data of 40 patients with PD and 40 healthy controls were analyzed. All participants underwent susceptibility-weighted imaging (SWI), neuromelanin-sensitive magnetic resonance imaging (NM-MRI), and T2*mapping sequence examination. The diagnostic value of single and combined multiparameter indicators was analyzed using the receiver operating characteristic curve.

Results

Compared with the healthy control group, the PD group showed significant differences in the disappearance of bilateral "swallow tail sign", the distribution volume of melanocytes in the substantia nigra and the smaller volume in the bilateral substantia nigra, the maximum signal of the locus coeruleus and the smaller and average volume in the bilateral substantia nigra, and the values of T2* and R2* in the bilateral substantia nigra (P<0.01). The maximum and smaller value and the average value of the bilateral locus coeruleus signal were negatively correlated with the disease course duration (P<0.05), and the smaller distribution volume of the melanin neurons in the bilateral substantia nigra was negatively correlated with Hoehn and Yahr (H-Y) grade (P<0.05). In the joint diagnosis with multiple indicators, some composite parameters were found to be negatively correlated with H-Y grading (P<0.05), while others were negatively correlated with disease course duration (P<0.05). Joint use of multiple parameter indicators greatly improved diagnostic efficacy [area under the curve (AUC) =0.958].

Conclusions

The distribution volume of melanin in substantia nigra and the maximum value of locus coeruleus signal may be the biological imaging indicators for the early diagnosis, severity, and follow-up evaluation of PD. Compared with a single indicator, composite indicators used in combination with multiple techniques have a significantly better diagnostic efficacy for PD.

Two distinct trajectories of clinical and neurodegeneration events in Parkinson's disease

Increasing evidence suggests that Parkinson's disease (PD) exhibits disparate spatial and temporal patterns of progression. Here we used a machine-learning technique-Subtype and Stage Inference (SuStaIn) - to uncover PD subtypes with distinct trajectories of clinical and neurodegeneration events. We enrolled 228 PD patients and 119 healthy controls with comprehensive assessments of olfactory, autonomic, cognitive, sleep, and emotional function. The integrity of substantia nigra (SN), locus coeruleus (LC), amygdala, hippocampus, entorhinal cortex, and basal forebrain were assessed using diffusion and neuromelanin-sensitive MRI. SuStaIn model with above clinical and neuroimaging variables as input was conducted to identify PD subtypes. An independent dataset consisting of 153 PD patients and 67 healthy controls was utilized to validate our findings. We identified two distinct PD subtypes: subtype 1 with rapid eye movement sleep behavior disorder (RBD), autonomic dysfunction, and degeneration of the SN and LC as early manifestations, and cognitive impairment and limbic degeneration as advanced manifestations, while subtype 2 with hyposmia, cognitive impairment, and limbic degeneration as early manifestations, followed later by RBD and degeneration of the LC in advanced disease. Similar subtypes were shown in the validation dataset. Moreover, we found that subtype 1 had weaker levodopa response, more GBA mutations, and poorer prognosis than subtype 2. These findings provide new insights into the underlying disease biology and might be useful for personalized treatment for patients based on their subtype.

Levodopa responsive freezing of gait is associated with reduced norepinephrine transporter binding in Parkinson's disease

BACKGROUND

Freezing of gait (FOG) is a major cause of falling in Parkinson's disease (PD) and can be responsive or unresponsive to levodopa. Pathophysiology is poorly understood.

OBJECTIVE

To examine the link between noradrenergic systems, the development of FOG in PD and its responsiveness to levodopa.

METHODS

We examined norepinephrine transporter (NET) binding via brain positron emission tomography (PET) to evaluate changes in NET density associated with FOG using the high affinity selective NET antagonist radioligand [¹¹C]MeNER (2S,3S)(2-[α-(2-methoxyphenoxy)benzyl]morpholine) in 52 parkinsonian patients. We used a rigorous levodopa challenge paradigm to characterize PD patients as non-freezing (NO-FOG, N = 16), levodopa responsive freezing (OFF-FOG, N = 10), and levodopa-unresponsive freezing (ONOFF-FOG, N = 21), and also included a non-PD FOG group, primary progressive freezing of gait (PP-FOG, N = 5).

RESULTS

Linear mixed models identified significant reductions in whole brain NET binding in the OFF-FOG group compared to the NO-FOG group (-16.8%, P = 0.021) and regionally in the frontal lobe, left and right thalamus, temporal lobe, and locus coeruleus, with the strongest effect in right thalamus (P = 0.038). Additional regions examined in a post hoc secondary analysis including the left and right amygdalae confirmed the contrast between OFF-FOG and NO-FOG (P = 0.003). A linear regression analysis identified an association between reduced NET binding in the right thalamus and more severe New FOG Questionnaire (N-FOG-Q) score only in the OFF-FOG group (P = 0.022).

CONCLUSION

This is the first study to examine brain noradrenergic innervation using NET-PET in PD patients with and without FOG. Based on the normal regional distribution of noradrenergic innervation and pathological studies in the thalamus of PD patients, the implications of our findings suggest that noradrenergic limbic pathways may play a key role in OFF-FOG in PD. This finding could have implications for clinical subtyping of FOG as well as development of therapies.

Presence but not the timing of onset of REM sleep behavior disorder distinguishes evolution patterns in Parkinson's disease

BACKGROUND

Rapid eye movement (REM) sleep behavior disorder (RBD) could develop preceding or come after motor symptoms during Parkinson's disease (PD). It remains unknown that whether PD with different timing of RBD onset relative to motor symptoms suggests different spatiotemporal sequence of neurodegeneration. This study aimed to explore the sequence of disease progression in crucially involved brain regions in PD with different timing of RBD onset.

METHOD

We recruited 157 PD, 16 isolated RBD (iRBD), and 78 healthy controls. PD patients were identified as (1) PD with RBD preceding motor symptoms (PD-preRBD, n = 50), (2) PD with RBD posterior to motor symptoms (PD-postRBD, n = 31), (3) PD without RBD (PD-nonRBD, n = 75). The volumes of crucial brain regions, including the basal ganglia and limbic structures in T1-weighted imaging, and the contrast-noise-ratios of locus coeruleus (LC) and substantia nigra (SN) in neuromelanin-sensitive magnetic resonance imaging, were extracted. To simulate the sequence of disease progression for cross-sectional data, an event-based model was introduced to estimate the maximum likelihood sequence of regions' involvement for each group. Then, a statistical parameter, the Bhattacharya coefficient (BC), was used to evaluate the similarity of the sequence.

RESULTS

The model predicted that SN occupied the highest likelihood in the maximum likelihood sequence of disease progression in the all PD subgroups, while LC was specifically positioned earlier to SN in iRBD, a prodromal phase of PD. Subsequent early involvement of LC was observed in the both PD-preRBD and PD-postRBD. In contrast, atrophy in the para-hippocampal gyrus but relatively intact LC in the early stage was demonstrated in PD-nonRBD. Then, the similarity comparisons indicated higher BC between PD-postRBD and PD-preRBD (BC = 0.76) but lower BC between PD-postRBD and PD-nonRBD group (BC = 0.41). iRBD had higher BC against PD-preRBD (BC = 0.66) and PD-postRBD (BC = 0.63) but lower BC against PD- nonRBD (BC = 0.48).

CONCLUSION

The spatiotemporal sequence of neurodegeneration between PD-pre and PD-post were similar but distinct from PD-nonRBD. The presence of RBD may be the essential factor for differentiating the degeneration patterns of PD, but the timing of RBD onset has currently proved to be not.

Application of Neuromelanin MR Imaging in Parkinson Disease

MRI has been used to develop biomarkers for movement disorders such as Parkinson disease (PD) and other neurodegenerative disorders with parkinsonism such as progressive supranuclear palsy and multiple system atrophy. One of these imaging biomarkers is neuromelanin (NM), whose integrity can be assessed from its contrast and volume. NM is found mainly in certain brain stem structures, namely, the substantia nigra pars compacta (SNpc), the ventral tegmental area, and the locus coeruleus. Another major biomarker is brain iron, which often increases in concert with NM degeneration. These biomarkers have the potential to improve diagnostic certainty in differentiating between PD and other neurodegenerative disorders similar to PD, as well as provide a better understanding of pathophysiology. Mapping NM in vivo has clinical importance for gauging the premotor phase of PD when there is a greater than 50% loss of dopaminergic SNpc melanized neurons. As a metal ion chelator, NM can absorb iron. When NM is released from neurons, it deposits iron into the intracellular tissues of the SNpc; the result is iron that can be imaged and measured using quantitative susceptibility mapping. An increase of iron also leads to the disappearance of the nigrosome-1 sign, another neuroimage biomarker for PD. Therefore, mapping NM and iron changes in the SNpc are a practical means for improving early diagnosis of PD and in monitoring disease progression. In this review, we discuss the functions and location of NM, how NM-MRI is performed, the automatic mapping of NM and iron content, how NM-related imaging biomarkers can be used to enhance PD diagnosis and differentiate it from other neurodegenerative disorders, and potential advances in NM imaging methods. With major advances currently evolving for rapid imaging and artificial intelligence, NM-related biomarkers are likely to have increasingly important roles for enhancing diagnostic capabilities in PD. EVIDENCE LEVEL: 1 TECHNICAL EFFICACY: Stage 2.

Locus coeruleus degeneration and cerebellar gray matter changes in essential tremor

BACKGROUND

The pathophysiology of essential tremor (ET) is not fully understood, and studies suggest pathological changes mainly occur in the cerebellum and locus coeruleus (LC).

METHODS

Fifty-three ET patients, including 30 patients with head tremor (h-ET), 23 patients without head tremor (nh-ET), 71 age and education matched healthy controls (HCs) were enrolled. All participants underwent Neuromelanin-sensitive magnetic resonance imaging (NM-MRI) and T1 scans on a 3-Tesla MR system. Next, we assessed the relationship between the contrast-to-noise ratio of LC (CNR_LC) and the score of The Essential Tremor Rating Assessment Scale (TETRAS) and cerebellum gray matter (GM) volume.

RESULTS

Significant difference of CNR_LC was found between ET and HC groups. The CNR_LC of ET groups is lower than the HC group (p = 0.031). Subgroup analysis showed that the CNR_LC in nh-ET was significantly lower than HCs (p = 0.016). Compared to HCs, h-ETs showed marked atrophy in the cerebellum: the vermis IV-V and lobule VI (GRF corrected, p < 0.05). A significant negative correlation was found between CNR_LC and the vermis lobule IV-V in h-ETs (r = - 0.651, p < 0.001). No significant correlation was found between CNR_LC and TETRAS scores.

CONCLUSION

The LC and the cerebellum might both involve in the pathophysiology of ET. LC evaluation using NM-MRI might be an effective tool for us to explore the pathophysiology of ET further.

Locus coeruleus degeneration is associated with disorganized functional topology in Parkinson's disease

Degeneration of the locus coeruleus (LC) is recognized as a critical hallmark of Parkinson's disease (PD). Recent studies have reported that noradrenaline produced from the LC has critical effects on brain functional organization. However, it is unknown if LC degeneration in PD contributes to cognitive/motor manifestations through modulating brain functional organization. This study enrolled 94 PD patients and 68 healthy controls, and LC integrity was measured using the contrast-to-noise ratio of the LC (CNR_LC) calculated from T1-weighted magnetic resonance imaging. We used graph-theory-based network analysis to characterize brain functional organization. The relationships among LC degeneration, network disruption, and cognitive/motor manifestations in PD were assessed. Whether network disruption was a mediator between LC degeneration and cognitive/motor impairments was assessed further. In addition, an independent PD subgroup (n = 35) having functional magnetic resonance scanning before and after levodopa administration was enrolled to evaluate whether LC degeneration-related network deficiencies were independent of dopamine deficiency. We demonstrated that PD patients have significant LC degeneration compared to healthy controls. CNR_LC was positively correlated with Montreal Cognitive Assessment score and the nodal efficiency (NE) of several cognitive-related regions. Lower NE of the superior temporal gyrus was a mediator between LC degeneration and cognitive impairment in PD. However, levodopa treatment could not normalize the reduced NE of the superior temporal gyrus (mediator). In conclusion, we provided evidence for the relationship between LC degeneration and extensive network disruption in PD, and highlight the role of network disorganization in LC degeneration-related cognitive impairment.