Graph Theory-Guided Transcranial Magnetic Stimulation in Neurodegenerative Disorders

Resting state EEG as biomarker of cognitive training and physical activity's joint effect in Parkinson's patients with mild cognitive impairment

BACKGROUND

Cognitive decline is a major factor for the deterioration of the quality of life in patients suffering from Parkinson's disease (PD). Recently, it was reported that cognitive training (CT) in PD patients with mild cognitive impairment (PD-MCI) led to an increase of physical activity (PA) accompanied by improved executive function (EF). Moreover, PA has been shown to alter positively brain function and cognitive abilities in PD. Both observations suggest an interaction between CT and PA.

OBJECTIVES

A previous multicenter (MC) study was slightly significant when considering independent effects of interventions (CT and PA) on EF. Here, we use MC constituent single center data that showed no effect of interventions on EF. Thus, this exploratory study considers pooling data from both interventions to gain insight into a recently reported interaction between CT and PA and provide a proof of principle for the usefulness of resting state EEG as a neurophysiological biomarker of joint intervention's effect on EF and attention in PD-MCI.

METHODS

Pre- and post-intervention resting state EEG and neuropsychological scores (EF and attention) were obtained from 19 PD-MCI patients (10 (CT) and 9 (PA)). We focused our EEG analysis on frontal cortical areas due to their relevance on cognitive function.

RESULTS

We found a significant joint effect of interventions on EF and a trend on attention, as well as trends for the negative correlation between attention and theta power (pre), the positive correlation between EF and alpha power (post) and a significant negative relationship between attention and theta power over time (post-pre).

CONCLUSIONS

Our results support the role of theta and alpha power at frontal areas as a biomarker for the therapeutic joint effect of interventions.

Understanding Abnormal c-JNK/p38MAPK Signaling Overactivation Involved in the Progression of Multiple Sclerosis: Possible Therapeutic Targets and Impact on Neurodegenerative Diseases

Demyelination, immune dysregulation, and neuroinflammation are the most common triggers of motor neuron disorders such as multiple sclerosis (MS). MS is a chronic demyelinating neurodegenerative disease of the central nervous system caused by abnormal immune activation, which causes myelin sheath damage. Cell signal transduction pathways are required for a variety of physiological and pathological processes in the brain. When these signaling systems become overactive, they can lead to disease progression. In various physiological conditions, abnormal mitogen-activated protein kinase (MAPK) activation is associated with several physiological dysfunctions that cause neurodegeneration. Previous research indicates that c-JNK and p38MAPK signaling play critical roles in neuronal growth and differentiation. c-JNK/p38MAPK is a member of the MAPK family, which regulates metabolic pathways, cell proliferation, differentiation, and apoptosis that control certain neurological activities. During brain injuries, c-JNK/p38MAPK also affects neuronal elastic properties, nerve growth, and cognitive processing. This review systematically linked abnormal c-JNK/p38MAPK signaling activation to multiple neuropathological pathways in MS and related neurological dysfunctions. MS progression is linked to genetic defects, oligodendrocyte destruction, glial overactivation, and immune dysregulation. We concluded that inhibiting both the c-JNK/p38MAPK signaling pathways can promote neuroprotection and neurotrophic effects against the clinical-pathological presentation of MS and influence other neurological disorders. As a result, the potential benefits of c-JNK/p38MAPK downregulation for the development of disease-modifying treatment interventions in the future could include MS prevention and related neurocomplications.

Identifying Mild Cognitive Impairment in Parkinson's Disease With Electroencephalogram Functional Connectivity

Objective

Cognitive impairment occurs frequently in Parkinson’s disease (PD) and negatively impacts the patient’s quality of life. However, its pathophysiological mechanism remains unclear, hindering the development of new therapies. Changes in brain connectivity are related to cognitive impairment in patients with PD, with the dorsolateral prefrontal cortex (DLPFC) being considered the essential region related to PD cognitive impairment. Nevertheless, few studies have focused on the global connectivity responsible for communication with the DLPFC node, the posterior division of the middle frontal gyrus (PMFG) in patients with PD; this was the focus of this study.

Methods

We applied resting-state electroencephalography (EEG) and calculated a reliable functional connectivity measurement, the debiased weighted phase lag index (dWPLI), to examine inter-regional functional connectivity in 68 patients with PD who were classified into two groups according to their cognitive condition.

Results

We observed that altered left and right PMFG-based functional connectivity associated with cognitive impairment in patients with PD in the theta frequency bands under the eyes closed condition (r = −0.426, p < 0.001 and r = −0.437, p < 0.001, respectively). Exploratory results based on the MoCA subdomains indicated that poorer visuospatial function was associated with higher right PMFG-based functional connectivity (r = −0.335, p = 0.005), and poorer attention function was associated with higher left and right PMFG-based functional connectivity (r = −0.380, p = 0.001 and r = −0.256, p = 0.035, respectively). Further analysis using logistic regression and receiver operating characteristic (ROC) curves found that this abnormal functional connectivity was an independent risk factor for cognitive impairment [odds ratio (OR): 2.949, 95% confidence interval (CI): 1.294–6.725, p = 0.01 for left PMFG; OR: 11.278, 95% CI: 2.578–49.335, p = 0.001 for right PMFG, per 0.1 U], and provided moderate classification power to discriminate between cognitive abilities in patients with PD [area under the ROC curve (AUC) = 0.770 for left PMFG; AUC = 0.809 for right PMFG].

Conclusion

These preliminary findings indicate that abnormal PMFG-based functional connectivity patterns associated with cognitive impairment in the theta frequency bands under the eyes closed condition and altered functional connectivity patterns have the potential to act as reliable biomarkers for identifying cognitive impairment in patients with PD.

LRRK2 and GBA Variants Exert Distinct Influences on Parkinson's Disease-Specific Metabolic Networks

The natural history of idiopathic Parkinson's disease (PD) varies considerably across patients. While PD is generally sporadic, there are known genetic influences: the two most common, mutations in the LRRK2 or GBA1 gene, are associated with slower and more aggressive progression, respectively. Here, we applied graph theory to metabolic brain imaging to understand the effects of genotype on the organization of previously established PD-specific networks. We found that closely matched PD patient groups with the LRRK2-G2019S mutation (PD-LRRK2) or GBA1 variants (PD-GBA) expressed the same disease networks as sporadic disease (sPD), but PD-LRRK2 and PD-GBA patients exhibited abnormal increases in network connectivity that were not present in sPD. Using a community detection strategy, we found that the location and modular distribution of these connections differed strikingly across genotypes. In PD-LRRK2, connections were gained within the network core, with the formation of distinct functional pathways linking the cerebellum and putamen. In PD-GBA, by contrast, the majority of functional connections were formed outside the core, involving corticocortical pathways at the network periphery. Strategically localized connections within the core in PD-LRRK2 may maintain PD network activity at lower levels than in PD-GBA, resulting in a less aggressive clinical course.

Network Structure and Function in Parkinson's Disease

Little is known of the structural and functional properties of abnormal brain networks associated with neurological disorders. We used a social network approach to characterize the properties of the Parkinson's disease (PD) metabolic topography in 4 independent patient samples and in an experimental non-human primate model. The PD network exhibited distinct features. Dense, mutually facilitating functional connections linked the putamen, globus pallidus, and thalamus to form a metabolically active core. The periphery was formed by weaker connections linking less active cortical regions. Notably, the network contained a separate module defined by interconnected, metabolically active nodes in the cerebellum, pons, frontal cortex, and limbic regions. Exaggeration of the small-world property was a consistent feature of disease networks in parkinsonian humans and in the non-human primate model; this abnormality was only partly corrected by dopaminergic treatment. The findings point to disease-related alterations in network structure and function as the basis for faulty information processing in this disorder.