PFTK1 kinase regulates axogenesis during development via RhoA activation

BACKGROUND

PFTK1/Eip63E is a member of the cyclin-dependent kinases (CDKs) family and plays an important role in normal cell cycle progression. Eip63E expresses primarily in postnatal and adult nervous system in Drosophila melanogaster but its role in CNS development remains unknown. We sought to understand the function of Eip63E in the CNS by studying the fly ventral nerve cord during development.

RESULTS

Our results demonstrate that Eip63E regulates axogenesis in neurons and its deficiency leads to neuronal defects. Functional interaction studies performed using the same system identify an interaction between Eip63E and the small GTPase Rho1. Furthermore, deficiency of Eip63E homolog in mice, PFTK1, in a newly generated PFTK1 knockout mice results in increased axonal outgrowth confirming that the developmental defects observed in the fly model are due to defects in axogenesis. Importantly, RhoA phosphorylation and activity are affected by PFTK1 in primary neuronal cultures. We report that GDP-bound inactive RhoA is a substrate of PFTK1 and PFTK1 phosphorylation is required for RhoA activity.

CONCLUSIONS

In conclusion, our work establishes an unreported neuronal role of PFTK1 in axon development mediated by phosphorylation and activation of GDP-bound RhoA. The results presented add to our understanding of the role of Cdks in the maintenance of RhoA-mediated axon growth and its impact on CNS development and axonal regeneration.

Ocular microtremor: a structured review

Ocular microtremor (OMT) is the smallest of three involuntary fixational micro eye movements, which has led to it being under researched in comparison. The link between OMT and brain function generates a strong rationale for further study as there is potential for its use as a biomarker in populations with neurological injury and disease. This structured review focused on populations previously studied, instrumentation used for measurement, commonly reported OMT outcomes, and recommendations concerning protocol design and future studies. Current methods of quantifying OMT will be reviewed to analyze their efficacy and efficiency and guide potential development and understanding of novel techniques. Electronic databases were systematically searched and compared with predetermined inclusion criteria. 216 articles were identified in the search and screened by two reviewers. 16 articles were included for review. Findings showed that piezoelectric probe is the most common method of measuring OMT, with fewer studies involving non-invasive approaches, such as contact lenses and laser imaging. OMT frequency was seen to be reduced during general anesthesia at loss of consciousness and in neurologically impaired participants when compared to healthy adults. We identified the need for a non-invasive technique for measuring OMT and highlight its potential in clinical applications as an objective biomarker for neurological assessments. We highlight the need for further research on the clinical validation of OMT to establish its potential to identify or predict a meaningful clinical or functional state, specifically, regarding accuracy, precision, and reliability of OMT.

Elevated Gaussian-modeled beta power in the cortex characterizes aging, but not Parkinson's disease

Aging is a key risk factor for the development of Parkinson's disease (PD). PD is characterized by excessive synchrony of beta oscillations (13-30 Hz) in the basal ganglia thalamo-cortical network. However, cortical beta power is not reliably elevated in individuals with PD. Here, we sought to disentangle how resting cortical beta power compares in younger controls, older controls, and individuals with PD using scalp electroencephalogram (EEG) and a novel approach for quantifying beta power. Specifically, we used a Gaussian model to determine if sensorimotor beta power distinguishes these groups. In addition, we looked at the distribution of beta power across the entire cortex. Our findings showed that Gaussian-modeled beta power does not differentiate individuals with PD (on medication) from healthy younger or older controls in sensorimotor cortex. However, beta power (and not theta or alpha) was higher in healthy older versus younger controls. This effect was most pronounced in regions near sensorimotor cortex including the frontal and parietal areas [P < 0.05, false discovery rate (FDR) corrected]. In addition, the bandwidth of the periodic beta was also higher in healthy older than young individuals in parietal regions. Finally, the aperiodic component, specifically the exponent of the signal, was higher (steeper) in younger controls than in individuals with PD in the right parietal-occipital region (P < 0.05, FDR corrected), possibly reflecting differences in neuronal spiking. Our findings suggest that cortical Gaussian beta power is possibly modulated by age and could be further explored in longitudinal studies to determine whether sensorimotor beta increases with increasing age.NEW & NOTEWORTHY Altered sensorimotor beta activity has been shown to be a feature in aging and PD. Using a novel approach, we clarify that resting sensorimotor beta power does not distinguish subjects with PD from healthy younger and older controls. However, beta power was higher in older compared with younger controls in central sensorimotor, frontal, and parietal regions. These results provide a clearer picture of sensorimotor beta power, demonstrating that it is elevated in aging but not PD.

Cerebrospinal fluid lipoproteins inhibit α-synuclein aggregation by interacting with oligomeric species in seed amplification assays

BACKGROUND

Aggregation of α-synuclein (α-syn) is a prominent feature of Parkinson's disease (PD) and other synucleinopathies. Currently, α-syn seed amplification assays (SAAs) using cerebrospinal fluid (CSF) represent the most promising diagnostic tools for synucleinopathies. However, CSF itself contains several compounds that can modulate the aggregation of α-syn in a patient-dependent manner, potentially undermining unoptimized α-syn SAAs and preventing seed quantification.

METHODS

In this study, we characterized the inhibitory effect of CSF milieu on detection of α-syn aggregates by means of CSF fractionation, mass spectrometry, immunoassays, transmission electron microscopy, solution nuclear magnetic resonance spectroscopy, a highly accurate and standardized diagnostic SAA, and different in vitro aggregation conditions to evaluate spontaneous aggregation of α-syn.

RESULTS

We found the high-molecular weight fraction of CSF (> 100,000 Da) to be highly inhibitory on α-syn aggregation and identified lipoproteins to be the main drivers of this effect. Direct interaction between lipoproteins and monomeric α-syn was not detected by solution nuclear magnetic resonance spectroscopy, on the other hand we observed lipoprotein-α-syn complexes by transmission electron microscopy. These observations are compatible with hypothesizing an interaction between lipoproteins and oligomeric/proto-fibrillary α-syn intermediates. We observed significantly slower amplification of α-syn seeds in PD CSF when lipoproteins were added to the reaction mix of diagnostic SAA. Additionally, we observed a decreased inhibition capacity of CSF on α-syn aggregation after immunodepleting ApoA1 and ApoE. Finally, we observed that CSF ApoA1 and ApoE levels significantly correlated with SAA kinetic parameters in n = 31 SAA-negative control CSF samples spiked with preformed α-syn aggregates.

CONCLUSIONS

Our results describe a novel interaction between lipoproteins and α-syn aggregates that inhibits the formation of α-syn fibrils and could have relevant implications. Indeed, the donor-specific inhibition of CSF on α-syn aggregation explains the lack of quantitative results from analysis of SAA-derived kinetic parameters to date. Furthermore, our data show that lipoproteins are the main inhibitory components of CSF, suggesting that lipoprotein concentration measurements could be incorporated into data analysis models to eliminate the confounding effects of CSF milieu on α-syn quantification efforts.

Brain activity response to cues during gait in Parkinson’s disease: A study protocol

Various cueing strategies (internal and external) have been used to alleviate gait deficits in Parkinson’s disease (PD). However, it remains unclear which type of cueing strategy is most effective at different disease stages or with more severe walking impairment, such as freezing of gait (FOG). The underlying neural mechanisms of response to cueing are also unknown. This trial aims to: (i) determine brain activity response to cue stimulus (internal, visual, auditory or tactile) when walking in PD and; (ii) examine changes in brain activity to cues at different stages of PD. This ongoing single-site study uses an exploratory observational design, with laboratory application of cues for gait deficit. A total of 80 people with PD who meet the inclusion criteria will be enrolled. Participants are split into groups dependent on their disease stage (classified with the Hoehn and Yahr (H&Y) scale); n = 20 H&YI; n = 30 H&YII; n = 30 H&YIII. Within the H&Y stage II and III groups, we will also ensure recruitment of a sub-group of 15 individuals with FOG within each group. Participants perform walking tasks under several conditions: baseline walking without cues; randomized cued walking conditions [internal and external (visual, auditory and tactile) cues]. A combined functional near-infrared spectroscopy and electroencephalography system quantifies cortical brain activity while walking. Inertial sensors are used to assess gait. Primary outcome measures are cue-related changes in cortical brain activity while walking, including the relative change in cortical HbO₂ and the power spectral densities at alpha (8-13Hz), beta (13-30Hz), delta (0.5-4Hz), theta (4-8Hz) and gamma (30-40Hz) frequency bandwidths. Secondary outcome measures are cue-related changes in spatiotemporal gait characteristics. Findings will enhance our understanding about the cortical responses to different cueing strategies and how they are influenced by PD progression and FOG status. This trial is registered at clinicaltrials.gov (NCT04863560; April 28, 2021, https://clinicaltrials.gov/ct2/show/NCT04863560).

Wearable Inertial Gait Algorithms: Impact of Wear Location and Environment in Healthy and Parkinson's Populations

Wearable inertial measurement units (IMUs) are used in gait analysis due to their discrete wearable attachment and long data recording possibilities within indoor and outdoor environments. Previously, lower back and shin/shank-based IMU algorithms detecting initial and final contact events (ICs-FCs) were developed and validated on a limited number of healthy young adults (YA), reporting that both IMU wear locations are suitable to use during indoor and outdoor gait analysis. However, the impact of age (e.g., older adults, OA), pathology (e.g., Parkinson's Disease, PD) and/or environment (e.g., indoor vs. outdoor) on algorithm accuracy have not been fully investigated. Here, we examined IMU gait data from 128 participants (72-YA, 20-OA, and 36-PD) to thoroughly investigate the suitability of ICs-FCs detection algorithms (1 × lower back and 1 × shin/shank-based) for quantifying temporal gait characteristics depending on IMU wear location and walking environment. The level of agreement between algorithms was investigated for different cohorts and walking environments. Although mean temporal characteristics from both algorithms were significantly correlated for all groups and environments, subtle but characteristically nuanced differences were observed between cohorts and environments. The lowest absolute agreement level was observed in PD (ICC_2,1 = 0.979, 0.806, 0.730, 0.980) whereas highest in YA (ICC_2,1 = 0.987, 0.936, 0.909, 0.989) for mean stride, stance, swing, and step times, respectively. Absolute agreement during treadmill walking (ICC_2,1 = 0.975, 0.914, 0.684, 0.945), indoor walking (ICC_2,1 = 0.987, 0.936, 0.909, 0.989) and outdoor walking (ICC_2,1 = 0.998, 0.940, 0.856, 0.998) was found for mean stride, stance, swing, and step times, respectively. Findings of this study suggest that agreements between algorithms are sensitive to the target cohort and environment. Therefore, researchers/clinicians should be cautious while interpreting temporal parameters that are extracted from inertial sensors-based algorithms especially for those with a neurological condition.

Deep learning-based point-scanning super-resolution imaging

Point-scanning imaging systems are among the most widely used tools for high-resolution cellular and tissue imaging, benefiting from arbitrarily defined pixel sizes. The resolution, speed, sample preservation and signal-to-noise ratio (SNR) of point-scanning systems are difficult to optimize simultaneously. We show these limitations can be mitigated via the use of deep learning-based supersampling of undersampled images acquired on a point-scanning system, which we term point-scanning super-resolution (PSSR) imaging. We designed a 'crappifier' that computationally degrades high SNR, high-pixel resolution ground truth images to simulate low SNR, low-resolution counterparts for training PSSR models that can restore real-world undersampled images. For high spatiotemporal resolution fluorescence time-lapse data, we developed a 'multi-frame' PSSR approach that uses information in adjacent frames to improve model predictions. PSSR facilitates point-scanning image acquisition with otherwise unattainable resolution, speed and sensitivity. All the training data, models and code for PSSR are publicly available at 3DEM.org.

Niacin and Butyrate: Nutraceuticals Targeting Dysbiosis and Intestinal Permeability in Parkinson's Disease

Dysbiosis is implicated by many studies in the pathogenesis of Parkinson's disease (PD). Advances in sequencing technology and computing have resulted in confounding data regarding pathogenic bacterial profiles in conditions such as PD. Changes in the microbiome with reductions in short-chain fatty acid (SCFA)-producing bacteria and increases in endotoxin-producing bacteria likely contribute to the pathogenesis of PD. GPR109A, a G-protein coupled receptor found on the surface of the intestinal epithelium and immune cells, plays a key role in controlling intestinal permeability and the inflammatory cascade. The absence of GPR109A receptors is associated with decreased concentration of tight junction proteins, leading to increased intestinal permeability and susceptibility to inflammation. In inflammatory states, butyrate acts via GPR109A to increase concentrations of tight junction proteins and improve intestinal permeability. Niacin deficiency is exacerbated in PD by dopaminergic medications. Niacin supplementation has been shown to shift macrophage polarization from pro-inflammatory to an anti-inflammatory profile. Niacin and butyrate, promising nutrients and unique ligands for the G protein-coupled receptor GPR109A, are reviewed in this paper in detail.

The role of TDP-43 mislocalization in amyotrophic lateral sclerosis

Since its discovery as a primary component in cytoplasmic aggregates in post-mortem tissue of patients with Amyotrophic Lateral Sclerosis (ALS), TAR DNA Binding Protein 43 kDa (TDP-43) has remained a central focus to understand the disease. TDP-43 links both familial and sporadic forms of ALS as mutations are causative for disease and cytoplasmic aggregates are a hallmark of nearly all cases, regardless of TDP-43 mutational status. Research has focused on the formation and consequences of cytosolic protein aggregates as drivers of ALS pathology through both gain- and loss-of-function mechanisms. Not only does aggregation sequester the normal function of TDP-43, but these aggregates also actively block normal cellular processes inevitably leading to cellular demise in a short time span. Although there may be some benefit to therapeutically targeting TDP-43 aggregation, this step may be too late in disease development to have substantial therapeutic benefit. However, TDP-43 pathology appears to be tightly linked with its mislocalization from the nucleus to the cytoplasm, making it difficult to decouple the consequences of nuclear-to-cytoplasmic mislocalization from protein aggregation. Studies focusing on the effects of TDP-43 mislocalization have demonstrated both gain- and loss-of-function consequences including altered splicing regulation, over responsiveness to cellular stressors, increases in DNA damage, and transcriptome-wide changes. Additionally, mutations in TARDBP confer a baseline increase in cytoplasmic TDP-43 thus suggesting that small changes in the subcellular localization of TDP-43 could in fact drive early pathology. In this review, we bring forth the theme of protein mislocalization as a key mechanism underlying ALS, by highlighting the importance of maintaining subcellular proteostasis along with the gain- and loss-of-functional consequences when TDP-43 localization is dysregulated. Additional research, focusing on early events in TDP-43 pathogenesis (i.e. to the protein mislocalization stage) will provide insight into disease mechanisms, therapeutic targets, and novel biomarkers for ALS.

Mild Innate Immune Activation Overrides Efficient Nanoparticle-Mediated RNA Delivery

Clinical mRNA delivery remains challenging, in large part because how physiology alters delivery in vivo remains underexplored. For example, mRNA delivered by lipid nanoparticles (LNPs) is being considered to treat inflammation, but whether inflammation itself changes delivery remains understudied. Relationships between immunity, endocytosis, and mRNA translation lead to hypothesize that toll-like receptor 4 (TLR4) activation reduced LNP-mediated mRNA delivery. Therefore, LNP uptake, endosomal escape, and mRNA translation with and without TLR4 activation are quantified. In vivo DNA barcoding is used to discover a novel LNP that delivers mRNA to Kupffer cells at clinical doses; unlike most LNPs, this LNP does not preferentially target hepatocytes. TLR4 activation blocks mRNA translation in all tested cell types, without reducing LNP uptake; inhibiting TLR4 or its downstream effector protein kinase R improved delivery. The discrepant effects of TLR4 on i) LNP uptake and ii) translation suggests TLR4 activation can "override" LNP targeting, even after mRNA is delivered into target cells. Given near-future clinical trials using mRNA to modulate inflammation, this highlights the need to understand inflammatory signaling in on- and off-target cells. More generally, this suggests an LNP which delivers mRNA to one inflammatory disease may not deliver mRNA to another.

Using Large Datasets to Understand Nanotechnology

Advances in sequencing technologies have made studying biological processes with genomics, transcriptomics, and proteomics commonplace. As a result, this suite of increasingly integrated techniques is well positioned to study drug delivery, a process that is influenced by many biomolecules working in concert. Omics-based approaches can be used to study the vast nanomaterial chemical space as well as the biological factors that affect the safety, toxicity, and efficacy of nanotechnologies. The generation and analysis of large datasets, methods to interpret them, and dataset applications to nanomaterials to date, are demonstrated here. Finally, new approaches for how sequencing-generated datasets can answer fundamental questions in nanotechnology based drug delivery are proposed.

Modulatory Effects of Levodopa on Cerebellar Connectivity in Parkinson's Disease

Levodopa has been the mainstay of symptomatic therapy for Parkinson's disease (PD) for the last five decades. However, it is associated with the development of motor fluctuations and dyskinesia, in particular after several years of treatment. The aim of this study was to shed light on the acute brain functional reorganization in response to a single levodopa dose. Functional magnetic resonance imaging (fMRI) was performed after an overnight withdrawal of dopaminergic treatment and 1 h after a single dose of 250 mg levodopa in a group of 24 PD patients. Eigenvector centrality was calculated in both treatment states using resting-state fMRI. This offers a new data-driven and parameter-free approach, similar to Google's PageRank algorithm, revealing brain connectivity alterations due to the effect of levodopa treatment. In all PD patients, levodopa treatment led to an improvement of clinical symptoms as measured with the Unified Parkinson's Disease Rating Scale motor score (UPDRS-III). This therapeutic effect was accompanied with a major connectivity increase between cerebellar brain regions and subcortical areas of the motor system such as the thalamus, putamen, globus pallidus, and brainstem. The degree of interconnectedness of cerebellar regions correlated with the improvement of clinical symptoms due to the administration of levodopa. We observed significant functional cerebellar connectivity reorganization immediately after a single levodopa dose in PD patients. Enhanced general connectivity (eigenvector centrality) was associated with better motor performance as assessed by UPDRS-III score. This underlines the importance of considering cerebellar networks as therapeutic targets in PD.

SMPD1 mutations, activity, and α-synuclein accumulation in Parkinson's disease

BACKGROUND

SMPD1 (acid-sphingomyelinase) variants have been associated with Parkinson's disease in recent studies. The objective of this study was to further investigate the role of SMPD1 mutations in PD.

METHODS

SMPD1 was sequenced in 3 cohorts (Israel Ashkenazi Jewish cohort, Montreal/Montpellier, and New York), including 1592 PD patients and 975 controls. Additional data were available for 10,709 Ashkenazi Jewish controls. Acid-sphingomyelinase activity was measured by a mass spectrometry-based assay in the New York cohort. α-Synuclein levels were measured in vitro following CRISPR/Cas9-mediated knockout and siRNA knockdown of SMPD1 in HeLa and BE(2)-M17 cells. Lysosomal localization of acid-sphingomyelinase with different mutations was studied, and in silico analysis of their effect on acid-sphingomyelinase structure was performed.

RESULTS

SMPD1 mutations were associated with PD in the Ashkenazi Jewish cohort, as 1.4% of PD patients carried the p.L302P or p.fsP330 mutation, compared with 0.37% in 10,709 Ashkenazi Jewish controls (OR, 3.7; 95%CI, 1.6-8.2; P = 0.0025). In the Montreal/Montpellier cohort, the p.A487V variant was nominally associated with PD (1.5% versus 0.14%; P = 0.0065, not significant after correction for multiple comparisons). Among PD patients, reduced acid-sphingomyelinase activity was associated with a 3.5- to 5.8-year earlier onset of PD in the lowest quartile versus the highest quartile of acid-sphingomyelinase activity (P = 0.01-0.001). We further demonstrated that SMPD1 knockout and knockdown resulted in increased α-synuclein levels in HeLa and BE(2)-M17 dopaminergic cells and that the p.L302P and p.fsP330 mutations impair the traffic of acid-sphingomyelinase to the lysosome.

CONCLUSIONS

Our results support an association between SMPD1 variants, acid-sphingomyelinase activity, and PD. Furthermore, they suggest that reduced acid-sphingomyelinase activity may lead to α-synuclein accumulation. © 2019 International Parkinson and Movement Disorder Society.

Alpha-synuclein oligomers: a new hope

Alpha-synuclein is a protein implicated in Parkinson’s disease and thought to be one of the main pathological drivers in the disease, although it remains unclear how this protein elicits its neurotoxic effects. Recent findings indicate that the assembly of toxic oligomeric species of alpha-synuclein may be one of the key processes for the pathology and spread of the disease. The absence of a sensitive in situ detection method has hindered the study of these oligomeric species and the role they play in the human brain until recently. In this review, we assess the evidence for the toxicity and prion-like activity of oligomeric forms of alpha-synuclein and discuss the advances in our understanding of the role of alpha-synuclein in Parkinson’s disease that may be brought about by the specific and sensitive detection of distinct oligomeric species in post-mortem patient brain. Finally, we discuss current approaches being taken to therapeutically target alpha-synuclein oligomers and their implications.

A Bayesian mathematical model of motor and cognitive outcomes in Parkinson's disease

Background

There are few established predictors of the clinical course of PD. Prognostic markers would be useful for clinical care and research.

Objective

To identify predictors of long-term motor and cognitive outcomes and rate of progression in PD.

Methods

Newly diagnosed PD participants were followed for 7 years in a prospective study, conducted at 55 centers in the United States and Canada. Analyses were conducted in 244 participants with complete demographic, clinical, genetic, and dopamine transporter imaging data. Machine learning dynamic Bayesian graphical models were used to identify and simulate predictors and outcomes. The outcomes rate of cognition changes are assessed by the Montreal Cognitive Assessment scores, and rate of motor changes are assessed by UPDRS part-III.

Results

The most robust and consistent longitudinal predictors of cognitive function included older age, baseline Unified Parkinson’s Disease Rating Scale (UPDRS) parts I and II, Schwab and England activities of daily living scale, striatal dopamine transporter binding, and SNP rs11724635 in the gene BST1. The most consistent predictor of UPDRS part III was baseline level of activities of daily living (part II). Key findings were replicated using long-term data from an independent cohort study.

Conclusions

Baseline function near the time of Parkinson’s disease diagnosis, as measured by activities of daily living, is a consistent predictor of long-term motor and cognitive outcomes. Additional predictors identified may further characterize the expected course of Parkinson’s disease and suggest mechanisms underlying disease progression. The prognostic model developed in this study can be used to simulate the effects of the prognostic variables on motor and cognitive outcomes, and can be replicated and refined with data from independent longitudinal studies.

Activation of FADD-Dependent Neuronal Death Pathways as a Predictor of Pathogenicity for LRRK2 Mutations

Background

Despite the plethora of sequence variants in LRRK2, only a few clearly segregate with PD. Even within this group of pathogenic mutations, the phenotypic profile can differ widely.

Objective

We examined multiple properties of LRRK2 behavior in cellular models over-expressing three sequence variants described in Greek PD patients in comparison to several known pathogenic and non-pathogenic LRRK2 mutations, to determine if specific phenotypes associated with pathogenic LRRK2 can be observed in other less-common sequence variants for which pathogenicity is unclear based on clinical and/or genetic data alone.

Methods

The oligomerization, activity, phosphorylation, and interaction with FADD was assessed in HEK293T cells over-expressing LRRK2; while the induction of neuronal death was determined by quantifying apoptotic nuclei in primary neurons transiently expressing LRRK2.

Results

One LRRK2 variant, A211V, exhibited a modest increase in kinase activity, whereas only the pathogenic mutants G2019S and I2020T displayed significantly altered auto-phosphorylation. We observed an induction of detergent-insoluble high molecular weight structures upon expression of pathogenic LRRK2 mutants, but not the other LRRK2 variants. In contrast, each of the variants tested induced apoptotic death of cultured neurons similar to pathogenic LRRK2 in a FADD-dependent manner.

Conclusions

Overall, despite differences in some properties of LRRK2 function such as kinase activity and its oligomerization, each of the LRRK2 variants examined induced neuronal death to a similar extent. Furthermore, our findings further strengthen the notion of a convergence on the extrinsic cell death pathway common to mutations in LRRK2 that are capable of inducing neuronal death.