Detection of Parkinson’s disease tremor-onset with a frequency analysing artificial neural network

Deep Brain Stimulator devices are becoming widely used for therapeutic benefits in movement disorders such as Parkinson's disease. Prolonging the battery life span of such devices could dramatically reduce the risks and accumulative costs associated with surgical replacement. This paper demonstrates how an artificial neural network can be trained using pre-processing frequency analysis of deep brain electrode recordings to detect the onset of tremor in Parkinsonian patients. Implementing this solution into an 'intelligent' neurostimulator device will remove the need for continuous stimulation currently used, and open up the possibility of demand-driven stimulation. Such a methodology could potentially decrease the power consumption of a deep brain pulse generator.

Identification of Parkinson’s disease tremor onset using artificial neural networks

In this paper we consider the possibility of using an artificial neural network to accurately identify the onset of Parkinson’s Disease tremors in human subjects. Data for the network is obtained by means of deep brain implantation in the human brain. Results presented have been obtained from a practical study (i.e. real not simulated data) but should be regarded as initial trials to be discussed further. It can be seen that a tuned artificial neural network can act as an extremely effective predictor in these circumstances.

Prediction of Parkinson’s disease tremor onset using radial basis function neural networks

The possibility of using a radial basis function neural network (RBFNN) to accurately recognise and predict the onset of Parkinson’s disease tremors in human subjects is discussed in this paper. The data for training the RBFNN are obtained by means of deep brain electrodes implanted in a Parkinson disease patient’s brain. The effectiveness of a RBFNN is initially demonstrated by a real case study.

Prediction of Parkinson’s Disease tremor onset using a radial basis function neural network based on particle swarm optimization

Deep Brain Stimulation (DBS) has been successfully used throughout the world for the treatment of Parkinson's disease symptoms. To control abnormal spontaneous electrical activity in target brain areas DBS utilizes a continuous stimulation signal. This continuous power draw means that its implanted battery power source needs to be replaced every 18–24 months. To prolong the life span of the battery, a technique to accurately recognize and predict the onset of the Parkinson's disease tremors in human subjects and thus implement an on-demand stimulator is discussed here. The approach is to use a radial basis function neural network (RBFNN) based on particle swarm optimization (PSO) and principal component analysis (PCA) with Local Field Potential (LFP) data recorded via the stimulation electrodes to predict activity related to tremor onset. To test this approach, LFPs from the subthalamic nucleus (STN) obtained through deep brain electrodes implanted in a Parkinson patient are used to train the network. To validate the network's performance, electromyographic (EMG) signals from the patient's forearm are recorded in parallel with the LFPs to accurately determine occurrences of tremor, and these are compared to the performance of the network. It has been found that detection accuracies of up to 89% are possible. Performance comparisons have also been made between a conventional RBFNN and an RBFNN based on PSO which show a marginal decrease in performance but with notable reduction in computational overhead.

Riluzole neuroprotection in a parkinson’s disease model involves suppression of reactive astrocytosis but not GLT-1 regulation

Background Riluzole is a neuroprotective drug used in the treatment of motor neurone disease. Recent evidence suggests that riluzole can up-regulate the expression and activity of the astrocyte glutamate transporter, GLT-1. Given that regulation of glutamate transport is predicted to be neuroprotective in Parkinson's disease, we tested the effect of riluzole in parkinsonian rats which had received a unilateral 6-hydroxydopamine injection into the median forebrain bundle. Results Rats were treated with intraperitoneal riluzole (4 mg/kg or 8 mg/kg), 1 hour before the lesion then once daily for seven days. Riluzole produced a modest but significant attenuation of dopamine neurone degeneration, assessed by suppression of amphetamine-induced rotations, preservation of tyrosine hydroxylase positive neuronal cell bodies in the substantia nigra pars compacta and attenuation of striatal tyrosine hydroxylase protein loss. Seven days after 6-hydroxydopamine lesion, reactive astrocytosis was observed in the striatum, as determined by increases in expression of glial fibrillary acidic protein, however the glutamate transporter, GLT-1, which is also expressed in astrocytes was not regulated by the lesion. Conclusions The results confirm that riluzole is a neuroprotective agent in a rodent model of parkinson’s disease. Riluzole administration did not regulate GLT-1 levels but significantly reduced GFAP levels, in the lesioned striatum. Riluzole suppression of reactive astrocytosis is an intriguing finding which might contribute to the neuroprotective effects of this drug.

Parkinson’s Disease tremor classification – a comparison between Support Vector Machines and neural networks

Deep Brain Stimulation has been used in the study of and for treating Parkinson’s Disease (PD) tremor symptoms since the 1980s. In the research reported here we have carried out a comparative analysis to classify tremor onset based on intraoperative microelectrode recordings of a PD patient’s brain Local Field Potential (LFP) signals. In particular, we compared the performance of a Support Vector Machine (SVM) with two well known artificial neural network classifiers, namely a Multiple Layer Perceptron (MLP) and a Radial Basis Function Network (RBN). The results show that in this study, using specifically PD data, the SVM provided an overall better classification rate achieving an accuracy of 81% recognition.

Pathogenic Parkinson’s disease mutations across the functional domains of LRRK2 alter the autophagic/lysosomal response to starvation

LRRK2 is one of the most important genetic contributors to Parkinson’s disease (PD). Point mutations in this gene cause an autosomal dominant form of PD, but to date no cellular phenotype has been consis- tently linked with mutations in each of the functional domains (ROC, COR and Kinase) of the protein product of this gene. In this study, primary fibroblasts from individuals carrying pathogenic mutations in the three central domains of LRRK2 were assessed for alterations in the autophagy/lysosomal pathway using a combination of biochemical and cellular approaches. Mutations in all three domains resulted in alterations in markers for autophagy/lysosomal function compared to wild type cells. These data high- light the autophagy and lysosomal pathways as read outs for pathogenic LRRK2 function and as a marker for disease, and provide insight into the mechanisms linking LRRK2 function and mutations.

Latent learning in end stage renal disease (ESRD)

Cognitive functions such as attention and memory are known to be impaired in End Stage Renal Disease (ESRD), but the sites of the neural changes underlying these impairments are uncertain. Patients and controls took part in a latent learning task, which had previously shown a dissociation between patients with Parkinson’s disease and those with medial temporal damage. ESRD patients (n=24) and age and education-matched controls (n=24) were randomly assigned to either an exposed or unexposed condition. In Phase 1 of the task, participants learned that a cue (word) on the back of a schematic head predicted that the subsequently seen face would be smiling. For the exposed (but not unexposed) condition, an additional (irrelevant) colour cue was shown during presentation. In Phase 2, a different association, between colour and facial expression, was learned. Instructions were the same for each phase: participants had to predict whether the subsequently viewed face was going to be happy or sad. No difference in error rate between the groups was found in Phase 1, suggesting that patients and controls learned at a similar rate. However, in Phase 2, a significant interaction was found between group and condition, with exposed controls performing significantly worse than unexposed (therefore demonstrating learned irrelevance). In contrast, exposed patients made a similar number of errors to unexposed in Phase 2. The pattern of results in ESRD was different from that previously found in Parkinson’s disease, suggesting a different neural origin.

Neuroinflammation and its modulation by flavonoids

There is increasing evidence to suggest that neuroinflammatory processes contribute to the cascade of events that lead to the progressive neuronal damage observed in neurodegenerative disorders such as Parkinson’s disease and Alzheimer’s disease. Therefore, treatment regimes aimed at modulating neuroinflammatory processes may act to slow the progression of these debilitating brain disorders. Recently, a group of dietary polyphenols known as flavonoids have been shown to exert neuroprotective effects in vivo and in neuronal cell models. In this review we discuss the evidence relating to the modulation of neuroinflammation by flavonoids. We highlight the evidence which suggests their mechanism of action involves: 1) attenuation of the release of cytokines, such as interleukin-1β (IL-1β) and tumor necrosis factor-alpha (TNF-α); 2) an inhibitory action against inducible nitric oxide synthase (iNOS) induction and subsequent nitric oxide (NO•) production; 3) inhibition of the activation of NADPH oxidase and subsequent reactive oxygen species generation; 4) a capacity to down-regulate the activity of pro-inflammatory transcription factors such as nuclear factor-κB (NF-κB); and 5) the potential to modulate signalling pathways such as mitogen-activated protein kinase (MAPK) cascade. We also consider the potential of these dietary compounds to represent novel therapeutic agents by considering their metabolism in the body and their ability to access the brain via the blood brain barrier. Finally, we discuss future areas of study which are necessary before dietary flavonoids can be established as therapeutic agents against neuroinflammation.

Modulation of neuroinflammation by dietary flavonoids

There is increasing evidence to suggest neuroinflammatory processes contribute to the cascade of events that lead to the progressive neuronal damage observed in neurodegenerative disorders such as Parkinson’s disease and Alzheimer’s disease. The molecular mechanisms underlying such neurodegenerative processes are rather complex and involve modulation of the mitogen-activated protein kinase (MAPK) and NF-κB pathways leading to the generation of nitric oxide (NO). Such a small molecule may diffuse to the neighbouring neurons and trigger neuronal death through the inhibition of mitochondrial respiration and increases in the reactive oxygen and nitrogen species. Recently, attention has focused on the neuroprotective effects of flavonoids which have been effective in protecting against both age-related cognitive and motor decline in vivo. Although, the precise mechanisms by which flavonoids may exert their neuroprotective effects remain unclear, accumulating evidence suggest that they may exert their neuroprotective effects through the modulation of the MAP Kinase and PI3 Kinase signaling pathways. The aim of the present chapter is to highlight the potential neuroprotective role of dietary flavonoids in terms of their ability to modulate neuroinflammation in the central nervous system. We will provide an outline of the role glial cells play in neuroinflammation and describe the involvement of inflammatory mediators, produced by glia, in the cascade of events leading to neuronal degeneration. We will then present the evidence that flavonoids may modulate neuroinflammation by inhibiting the production of these inflammatory agents and summarise their potential mechanisms of action.

Regulation of NF-κB activity in astrocytes: effects of flavonoids at dietary-relevant concentrations

Neuroinflammation plays an important role in the progression of neurodegenerative disorders such as Alzheimer’s disease and Parkinson’s disease. Sustained activation of nuclear transcription factor κB (NF-κB) is thought to play an important role in the pathogenesis of neurodegenerative disorders. Flavonoids have been shown to possess antioxidant and anti-inflammatory properties and we investigated whether flavonoids, at submicromolar concentrations relevant to their bioavailability from the diet, were able to modulate NF-κB signalling in astrocytes. Using luciferase reporter assays, we found that tumour necrosis factor (TNFα, 150 ng/ml) increased NF-κB-mediated transcription in primary cultures of mouse cortical astrocytes, which was abolished on co-transfection of a dominant-negative IκBα construct. In addition, TNFα increased nuclear localisation of p65 as shown by immunocytochemistry. To investigate potential flavonoid modulation of NF-κB activity, astrocytes were treated with flavonoids from different classes; flavan-3-ols ((−)-epicatechin and (+)-catechin), flavones (luteolin and chrysin), a flavonol (kaempferol) or the flavanones (naringenin and hesperetin) at dietary-relevant concentrations (0.1–1 μM) for 18 h. None of the flavonoids modulated constitutive or TNFα-induced NF-κB activity. Therefore, we conclude that NF-κB signalling in astrocytes is not a major target for flavonoids.

Genetic, structural, and molecular insights into the function of ras of complex proteins domains

Ras of complex proteins (ROC) domains were identified in 2003 as GTP binding modules in large multidomain proteins from Dictyostelium discoideum. Research into the function of these domains exploded with their identification in a number of proteins linked to human disease, including leucine-rich repeat kinase 2 (LRRK2) and death-associated protein kinase 1 (DAPK1) in Parkinson’s disease and cancer, respectively. This surge in research has resulted in a growing body of data revealing the role that ROC domains play in regulating protein function and signaling pathways. In this review, recent advances in the structural informa- tion available for proteins containing ROC domains, along with insights into enzymatic function and the integration of ROC domains as molecular switches in a cellular and organismal context, are explored.

Computational analysis of the LRRK2 interactome

LRRK2 was identified in 2004 as the causative protein product of the Parkinson’s disease locus designated PARK8. In the decade since then, genetic studies have revealed at least 6 dominant mutations in LRRK2 linked to Parkinson’s disease, alongside one associated with cancer. It is now well established that coding changes in LRRK2 are one of the most common causes of Parkinson’s. Genome-wide association studies (GWAs) have, more recently, reported single nucleotide polymorphisms (SNPs) around the LRRK2 locus to be associated with risk of developing sporadic Parkinson’s disease and inflammatory bowel disorder. The functional research that has followed these genetic breakthroughs has generated an extensive literature regarding LRRK2 pathophysiology; however, there is still no consensus as to the biological function of LRRK2. To provide insight into the aspects of cell biology that are consistently related to LRRK2 activity, we analysed the plethora of candidate LRRK2 interactors available through the BioGRID and IntAct data repositories. We then performed GO terms enrichment for the LRRK2 interactome. We found that, in two different enrichment portals, the LRRK2 interactome was associated with terms referring to transport, cellular organization, vesicles and the cytoskeleton. We also verified that 21 of the LRRK2 interactors are genetically linked to risk for Parkin- son’s disease or inflammatory bowel disorder. The implications of these findings are discussed, with particular regard to potential novel areas of investigation.

Distinct clinical and neuropathological features of G51D SNCA mutation cases compared with SNCA duplication and H50Q mutation

Background: We and others have described the neurodegenerative disorder caused by G51D SNCA mutation which shares characteristics of Parkinson’s disease (PD) and multiple system atrophy (MSA). The objective of this investigation was to extend the description of the clinical and neuropathological hallmarks of G51D mutant SNCA-associated disease by the study of two additional cases from a further G51D SNCA kindred and to compare the features of this group with a SNCA duplication case and a H50Q SNCA mutation case. Results: All three G51D patients were clinically characterised by parkinsonism, dementia, visual hallucinations, autonomic dysfunction and pyramidal signs with variable age at disease onset and levodopa response. The H50Q SNCA mutation case had a clinical picture that mimicked late-onset idiopathic PD with a good and sustained levodopa response. The SNCA duplication case presented with a clinical phenotype of frontotemporal dementia with marked behavioural changes, pyramidal signs, postural hypotension and transiently levodopa responsive parkinsonism. Detailed post-mortem neuropathological analysis was performed in all cases. All three G51D cases had abundant α-synuclein pathology with characteristics of both PD and MSA. These included widespread cortical and subcortical neuronal α-synuclein inclusions together with small numbers of inclusions resembling glial cytoplasmic inclusions (GCIs) in oligodendrocytes. In contrast the H50Q and SNCA duplication cases, had α-synuclein pathology resembling idiopathic PD without GCIs. Phosphorylated α-synuclein was present in all inclusions types in G51D cases but was more restricted in SNCA duplication and H50Q mutation. Inclusions were also immunoreactive for the 5G4 antibody indicating their highly aggregated and likely fibrillar state. Conclusions: Our characterisation of the clinical and neuropathological features of the present small series of G51D SNCA mutation cases should aid the recognition of this clinico-pathological entity. The neuropathological features of these cases consistently share characteristics of PD and MSA and are distinct from PD patients carrying the H50Q or SNCA duplication.

Genetic and phenotypic characterization of complex hereditary spastic paraplegia

The hereditary spastic paraplegias are a heterogeneous group of degenerative disorders that are clinically classified as either pure with predominant lower limb spasticity, or complex where spastic paraplegia is complicated with additional neurological features, and are inherited in autosomal dominant, autosomal recessive or X-linked patterns. Genetic defects have been identified in over 40 different genes, with more than 70 loci in total. Complex recessive spastic paraplegias have in the past been frequently associated with mutations in SPG11 (spatacsin), ZFYVE26/SPG15, SPG7 (paraplegin) and a handful of other rare genes, but many cases remain genetically undefined. The overlap with other neurodegenerative disorders has been implied in a small number of reports, but not in larger disease series. This deficiency has been largely due to the lack of suitable high throughput techniques to investigate the genetic basis of disease, but the recent availability of next generation sequencing can facilitate the identification of disease- causing mutations even in extremely heterogeneous disorders. We investigated a series of 97 index cases with complex spastic paraplegia referred to a tertiary referral neurology centre in London for diagnosis or management. The mean age of onset was 16 years (range 3 to 39). The SPG11 gene was first analysed, revealing homozygous or compound heterozygous mutations in 30/97 (30.9%) of probands, the largest SPG11 series reported to date, and by far the most common cause of complex spastic paraplegia in the UK, with severe and progressive clinical features and other neurological manifestations, linked with magnetic resonance imaging defects. Given the high frequency of SPG11 mutations, we studied the autophagic response to starvation in eight affected SPG11 cases and control fibroblast cell lines, but in our restricted study we did not observe correlations between disease status and autophagic or lysosomal markers. In the remaining cases, next generation sequencing was carried out revealing variants in a number of other known complex spastic paraplegia genes, including five in SPG7 (5/97), four in FA2H (also known as SPG35) (4/97) and two in ZFYVE26/SPG15. Variants were identified in genes usually associated with pure spastic paraplegia and also in the Parkinson’s disease-associated gene ATP13A2, neuronal ceroid lipofuscinosis gene TPP1 and the hereditary motor and sensory neuropathy DNMT1 gene, highlighting the genetic heterogeneity of spastic paraplegia. No plausible genetic cause was identified in 51% of probands, likely indicating the existence of as yet unidentified genes.