Profiling the low-beta characteristics of the subthalamic nucleus in early- and late-onset Parkinson's disease

Association of SCN2A single nucleotide polymorphisms with Parkinson's disease: Evidence from a case-control Study

BACKGROUND

A growing body of strong evidence shows that voltage-gated sodium channels genes play key roles in the development of sporadic Parkinson's disease (sPD). However, little data have been reported on the association between single nucleotide polymorphisms (SNPs) and sPD. This study aimed to investigate the association between SCN2A gene polymorphisms and sPD.

METHODS

267 patients with sPD and 267 healthy controls were included in this study. Polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) was performed. Reverse transcription-quantitative polymerase chain reaction (RT-qPCR) was used to detect the expression of SCN2A in the serum of patients and healthy individuals.

RESULTS

The distribution of the G allele of rs2304016 or the A allele of rs17183814 in SCN2A was significantly higher in patients with sPD (P = 0.001). In subtype analysis, the frequency of the rs2304016 AG heterozygote significantly differed between the early onset PD (EOPD) and late-onset PD (LOPD) groups (P < 0.001). The frequency of the rs17183814 AG heterozygote was significantly higher in the male patients (P = 0.002). Furthermore, we found that the level of SCN2A mRNA transcription in the serum of sPD patients was significantly lower than that in the control group (P < 0.05). The serum expression level of SCN2A in patients with the AA genotype at rs17183814 was lower (P < 0.05).

CONCLUSIONS

This study demonstrated a significant association between SNPs and the expression of SCN2A with sPD. These findings contribute to a better understanding of the role of SCN2A and SCN2A SNPs in sPD.

Comparison of oscillatory activity in substantia nigra pars reticulata between Parkinson's disease and dystonia

Parkinson's disease (PD) is associated with disrupted neural activity in the substantia nigra, but its electrophysiological changes remain underexplored. This study investigates the oscillatory patterns of substantia nigra pars reticulata (SNr) in PD, compared to dystonia (DT). Intraoperative recordings of the SNr were obtained from 20 PD and 16 DT patients during DBS surgery. Spectral power, neuronal firing rate, beta burst dynamics, and correlation analysis of the SNr signal were analyzed. PD patients exhibited increased alpha and beta power, elevated firing rates, and reduced aperiodic exponent values in SNr compared to DT. PD beta bursts showed prolonged durations and fewer short bursts. Beta power negatively correlated with motor symptom improvement rates in PD but not in DT patients. These findings highlight pathological beta power in SNr of PD, which indicates that SNr-DBS may offer a future therapeutic avenue for PD.

Contribution of basal ganglia activity to REM sleep disorder in Parkinson's disease

BACKGROUND

Rapid eye movement (REM) sleep behaviour disorder (RBD) is one of the most common sleep problems and represents a key prodromal marker in Parkinson's disease (PD). It remains unclear whether and how basal ganglia nuclei, structures that are directly involved in the pathology of PD, are implicated in the occurrence of RBD.

METHOD

Here, in parallel with whole-night video polysomnography, we recorded local field potentials from two major basal ganglia structures, the globus pallidus internus and subthalamic nucleus, in two cohorts of patients with PD who had varied severity of RBD. Basal ganglia oscillatory patterns during RBD and REM sleep without atonia were analysed and compared with another age-matched cohort of patients with dystonia that served as controls.

RESULTS

We found that beta power in both basal ganglia nuclei was specifically elevated during REM sleep without atonia in patients with PD, but not in dystonia. Basal ganglia beta power during REM sleep positively correlated with the extent of atonia loss, with beta elevation preceding the activation of chin electromyogram activities by ~200 ms. The connectivity between basal ganglia beta power and chin muscular activities during REM sleep was significantly correlated with the clinical severity of RBD in PD.

CONCLUSIONS

These findings support that basal ganglia activities are associated with if not directly contribute to the occurrence of RBD in PD. Our study expands the understanding of the role basal ganglia played in RBD and may foster improved therapies for RBD by interrupting the basal ganglia-muscular communication during REM sleep in PD.

STN localization using local field potentials based on wavelet packet features and stacking ensemble learning

BACKGROUND

DBS entails the insertion of an electrode into the patient brain, enabling Subthalamic nucleus (STN) stimulation. Accurate delineation of STN borders is a critical but time-consuming task, traditionally reliant on the neurosurgeon experience in deciphering the intricacies of microelectrode recording (MER). While clinical outcomes of MER have been satisfactory, they involve certain risks to patient safety. Recently, there has been a growing interest in exploring the potential of local field potentials (LFP) due to their correlation with the STN motor territory.

METHOD

A novel STN detection system, integrating LFP and wavelet packet transform (WPT) with stacking ensemble learning, is developed. Initial steps involve the inclusion of soft thresholding to increase robustness to LFP variability. Subsequently, non-linear WPT features are extracted. Finally, a unique ensemble model, comprising a dual-layer structure, is developed for STN localization. We harnessed the capabilities of support vector machine, Decision tree and k-Nearest Neighbor in conjunction with long short-term memory (LSTM) network. LSTM is pivotal for assigning adequate weights to every base model.

RESULTS

Results reveal that the proposed model achieved a remarkable accuracy and F1-score of 89.49% and 91.63%.

COMPARISON WITH EXISTING METHODS

Ensemble model demonstrated superior performance when compared to standalone base models and existing meta techniques.

CONCLUSION

This framework is envisioned to enhance the efficiency of DBS surgery and reduce the reliance on clinician experience for precise STN detection. This achievement is strategically significant to serve as an invaluable tool for refining the electrode trajectory, potentially replacing the current methodology based on MER.