Machine learning discriminates a movement disorder in a zebrafish model of Parkinson's disease

ABSTRACTAnimal models of human disease provide an in vivo system that can reveal molecular mechanisms by which mutations cause pathology, and, moreover, have the potential to provide a valuable tool for drug development. Here, we have developed a zebrafish model of Parkinson's disease (PD) together with a novel method to screen for movement disorders in adult fish, pioneering a more efficient drug-testing route. Mutation of the PARK7 gene (which encodes DJ-1) is known to cause monogenic autosomal recessive PD in humans, and, using CRISPR/Cas9 gene editing, we generated a Dj-1 loss-of-function zebrafish with molecular hallmarks of PD. To establish whether there is a human-relevant parkinsonian phenotype in our model, we adapted proven tools used to diagnose PD in clinics and developed a novel and unbiased computational method to classify movement disorders in adult zebrafish. Using high-resolution video capture and machine learning, we extracted novel features of movement from continuous data streams and used an evolutionary algorithm to classify parkinsonian fish. This method will be widely applicable for assessing zebrafish models of human motor diseases and provide a valuable asset for the therapeutics pipeline. In addition, interrogation of RNA-seq data indicate metabolic reprogramming of brains in the absence of Dj-1, adding to growing evidence that disruption of bioenergetics is a key feature of neurodegeneration.This article has an associated First Person interview with the first author of the paper.

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Targeting bone morphogenetic protein signalling in midbrain dopaminergic neurons as a therapeutic approach in Parkinson's disease

Neuronal Signaling ◽

10.1042/ns20170027 ◽

2017 ◽

Vol 1 (2) ◽

Cited By ~ 2

Author(s):

Gerard W. O'Keeffe ◽

Shane V. Hegarty ◽

Aideen M. Sullivan

Keyword(s):

Parkinson’S Disease ◽

Parkinson's Disease ◽

Neurotrophic Factors ◽

Neurotrophic Factor ◽

Molecular Mechanisms ◽

Axon Growth ◽

Nervous System Development ◽

Adult Brain ◽

Bmp Receptors

Parkinson's disease (PD) is the second most common neurodegenerative disease, characterized by the degeneration of midbrain dopaminergic (mDA) neurons and their axons, and aggregation of α-synuclein, which leads to motor and late-stage cognitive impairments. As the motor symptoms of PD are caused by the degeneration of a specific population of mDA neurons, PD lends itself to neurotrophic factor therapy. The goal of this therapy is to apply a neurotrophic factor that can slow down, halt or even reverse the progressive degeneration of mDA neurons. While the best known neurotrophic factors are members of the glial cell line-derived neurotrophic factor (GDNF) family, their lack of clinical efficacy to date means that it is important to continue to study other neurotrophic factors. Bone morphogenetic proteins (BMPs) are naturally secreted proteins that play critical roles during nervous system development and in the adult brain. In this review, we provide an overview of the BMP ligands, BMP receptors (BMPRs) and their intracellular signalling effectors, the Smad proteins. We review the available evidence that BMP–Smad signalling pathways play an endogenous role in mDA neuronal survival in vivo, before outlining how exogenous application of BMPs exerts potent effects on mDA neuron survival and axon growth in vitro and in vivo. We discuss the molecular mechanisms that mediate these effects, before highlighting the potential of targeting the downstream effectors of BMP–Smad signalling as a novel neuroprotective approach to slow or stop the degeneration of mDA neurons in PD.

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Automated leg tracking reveals distinct conserved gait and tremor signatures in Drosophila models of Parkinson’s Disease and Spinocerebellar ataxia 3

10.1101/425405 ◽

2018 ◽

Author(s):

Shuang Wu ◽

Kah Junn Tan ◽

Lakshmi Narasimhan Govindarajan ◽

James Charles Stewart ◽

Lin Gu ◽

...

Keyword(s):

Parkinson’S Disease ◽

Parkinson's Disease ◽

Spinocerebellar Ataxia ◽

Movement Disorders ◽

High Speed ◽

Molecular Mechanisms ◽

Feature Learning ◽

High Throughput Analysis ◽

Abnormal Gait ◽

Spinocerebellar Ataxia 3

SummaryGenetic models in Drosophila have made invaluable contributions to our understanding of the molecular mechanisms underlying neurodegeneration. In human patients, some neurodegenerative diseases lead to characteristic movement dysfunctions, such as abnormal gait and tremors. However, it is currently unknown whether similar movement defects occur in the respective fly models, which could be used to model and better understand the pathophysiology of movement disorders. To address this question, we developed a machine-learning image-analysis programme — Feature Learning-based LImb segmentation and Tracking (FLLIT) — that automatically tracks leg claw positions of freely moving flies recorded on high-speed video, generating a series of body and leg movement parameters. Of note, FLLIT requires no user input for learning. We used FLLIT to characterise fly models of Parkinson’s Disease (PD) and Spinocerebellar ataxia 3 (SCA3). Between these models, walking gait and tremor characteristics differed markedly, and recapitulated signatures of the respective human diseases. Selective expression of mutant SCA3 in dopaminergic neurons led to phenotypes resembling that of PD flies, suggesting that the behavioural phenotype may depend on the circuits affected, rather than the specific nature of the mutation. Different mutations produced tremors in distinct leg pairs, indicating that different motor circuits are affected. Almost 190,000 video frames were tracked in this study, allowing, for the first time, high-throughput analysis of gait and tremor features in Drosophila mutants. As an efficient assay of mutant gait and tremor features in an important model system, FLLIT will enable the analysis of the neurogenetic mechanisms that underlie movement disorders.

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Parkinson's disease and mitophagy: an emerging role for LRRK2

Biochemical Society Transactions ◽

10.1042/bst20190236 ◽

2021 ◽

Author(s):

Francois Singh ◽

Ian G. Ganley

Keyword(s):

Parkinson’S Disease ◽

Parkinson's Disease ◽

Molecular Mechanisms ◽

Neurodegenerative Disorder ◽

Current Knowledge ◽

Muscle Stiffness ◽

Substantia Nigra Pars Compacta ◽

Common Mutation ◽

Common Denominator

Parkinson's disease (PD) is a progressive neurodegenerative disorder that affects around 2% of individuals over 60 years old. It is characterised by the loss of dopaminergic neurons in the substantia nigra pars compacta of the midbrain, which is thought to account for the major clinical symptoms such as tremor, slowness of movement and muscle stiffness. Its aetiology is poorly understood as the physiological and molecular mechanisms leading to this neuronal loss are currently unclear. However, mitochondrial and lysosomal dysfunction seem to play a central role in this disease. In recent years, defective mitochondrial elimination through autophagy, termed mitophagy, has emerged as a potential contributing factor to disease pathology. PINK1 and Parkin, two proteins mutated in familial PD, were found to eliminate mitochondria under distinct mitochondrial depolarisation-induced stress. However, PINK1 and Parkin are not essential for all types of mitophagy and such pathways occur in most cell types and tissues in vivo, even in the absence of overt mitochondrial stress — so-called basal mitophagy. The most common mutation in PD, that of glycine at position 2019 to serine in the protein kinase LRRK2, results in increased activity and this was recently shown to disrupt basal mitophagy in vivo. Thus, different modalities of mitophagy are affected by distinct proteins implicated in PD, suggesting impaired mitophagy may be a common denominator for the disease. In this short review, we discuss the current knowledge about the link between PD pathogenic mutations and mitophagy, with a particular focus on LRRK2.

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In silico docking of Novel Phytoalkaloid Camalexin in the Management of Benomyl Induced Parkinson's disease and its In vivo Evaluation by Zebrafish Model

CNS & Neurological Disorders - Drug Targets ◽

10.2174/1871527320666210903091447 ◽

2021 ◽

Vol 20 ◽

Author(s):

Tamilanban T ◽

Manasa K ◽

Chitra V

Keyword(s):

Parkinson’S Disease ◽

Parkinson's Disease ◽

Aldehyde Dehydrogenase ◽

Neuronal Degeneration ◽

In Vivo Model ◽

Zebrafish Model ◽

Standard Drug ◽

In Silico Docking ◽

Dehydrogenase Enzyme

Background: Parkinson’s disease (PD) exhibits the extra pyramidal symptoms caused due to the dopaminergic neuronal degeneration in the substantia nigra of the brain and depletion of aldehyde dehydrogenase (ALDH) enzyme. Objective: This study was designed to enlighten the importance of Aldehyde dehydrogenase enzyme in protecting the dopamine levels in a living system. Camalexin, a potentially active compound has been evaluated for its dopamine enhancing and aldehyde dehydrogenase protecting role in pesticide induced Parkinson’s disease. Methods: AutoDock 4.2 software was employed to perform the docking simulations between the ligand camalexin and standard drugs Alda-1, Ropirinole with three proteins 4WJR, 3INL, 5AER. Consequently, the compound was evaluated for its in vivo neuroprotective role in zebrafish model by attaining Institutional Animal Ethical Committee permission. The behavioral assessments and catecholamine analysis in zebrafish were performed. Results: The Autodock result shows that the ligand camalexin has a lower binding energy (-3.84) that indicate higher affinity with the proteins when compared to the standard drug of proteins (-3.42). In zebrafish model, behavioral studies provided an evidence that camalexin helps in improvement of motor functions and cognition. The catecholamine assay has proved there is an enhancement in dopamine levels, as well as an improvement in aldehyde dehydrogenase enzyme also. Conclusion: The novel compound, camalexin, hence offers a protective role in Parkinson’s disease model by its interaction with neurochemical proteins and also in alternative in vivo model.

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Human loss-of-function variants suggest that partial LRRK2 inhibition is a safe therapeutic strategy for Parkinson’s disease

10.1101/561472 ◽

2019 ◽

Cited By ~ 6

Author(s):

Nicola Whiffin ◽

Irina M. Armean ◽

Aaron Kleinman ◽

Jamie L. Marshall ◽

Eric V. Minikel ◽

...

Keyword(s):

Parkinson’S Disease ◽

Parkinson's Disease ◽

Large Scale ◽

Therapeutic Strategy ◽

Kinase Activity ◽

Model Organisms ◽

Loss Of Function ◽

Genomic Databases ◽

Protein Coding

AbstractHuman genetic variants causing loss-of-function (LoF) of protein-coding genes provide natural in vivo models of gene inactivation, which are powerful indicators of gene function and the potential toxicity of therapeutic inhibitors targeting these genes1,2. Gain-of-kinase-function variants in LRRK2 are known to significantly increase the risk of Parkinson’s disease3,4, suggesting that inhibition of LRRK2 kinase activity is a promising therapeutic strategy. Whilst preclinical studies in model organisms have raised some on-target toxicity concerns5–8, the biological consequences of LRRK2 inhibition have not been well characterized in humans. Here we systematically analyse LoF variants in LRRK2 observed across 141,456 individuals sequenced in the Genome Aggregation Database (gnomAD)9 and over 4 million participants in the 23andMe genotyped dataset, to assess their impact at a molecular and phenotypic level. After thorough variant curation, we identify 1,358 individuals with high-confidence predicted LoF variants in LRRK2, several with experimental validation. We show that heterozygous LoF of LRRK2 reduces LRRK2 protein level by ~50% but is not associated with reduced life expectancy, or with any specific phenotype or disease state. These data suggest that therapeutics that downregulate LRRK2 levels or kinase activity by up to 50% are unlikely to have major on-target safety liabilities. Our results demonstrate the value of large scale genomic databases and phenotyping of human LoF carriers for target validation in drug discovery.

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Opposing functions of β-arrestin 1 and 2 in Parkinson’s disease via microglia inflammation and Nprl3

Cell Death and Differentiation ◽

10.1038/s41418-020-00704-9 ◽

2021 ◽

Author(s):

Yinquan Fang ◽

Qingling Jiang ◽

Shanshan Li ◽

Hong Zhu ◽

Rong Xu ◽

...

Keyword(s):

Parkinson’S Disease ◽

Parkinson's Disease ◽

Inflammatory Responses ◽

Functional Divergence ◽

Primary Cultures ◽

Loss Of Function ◽

Neuron Damage ◽

Dopaminergic Neuron Loss

AbstractAlthough β-arrestins (ARRBs) regulate diverse physiological and pathophysiological processes, their functions and regulation in Parkinson’s disease (PD) remain poorly defined. In this study, we show that the expression of β-arrestin 1 (ARRB1) and β-arrestin 2 (ARRB2) is reciprocally regulated in PD mouse models, particularly in microglia. ARRB1 ablation ameliorates, whereas ARRB2 knockout aggravates, the pathological features of PD, including dopaminergic neuron loss, neuroinflammation and microglia activation in vivo, and microglia-mediated neuron damage in vitro. We also demonstrate that ARRB1 and ARRB2 produce adverse effects on inflammation and activation of the inflammatory STAT1 and NF-κB pathways in primary cultures of microglia and macrophages and that two ARRBs competitively interact with the activated form of p65, a component of the NF-κB pathway. We further find that ARRB1 and ARRB2 differentially regulate the expression of nitrogen permease regulator-like 3 (Nprl3), a functionally poorly characterized protein, as revealed by RNA sequencing, and that in the gain- and loss-of-function studies, Nprl3 mediates the functions of both ARRBs in microglia inflammatory responses. Collectively, these data demonstrate that two closely related ARRBs exert opposite functions in microglia-mediated inflammation and the pathogenesis of PD which are mediated at least in part through Nprl3 and provide novel insights into the understanding of the functional divergence of ARRBs in PD.

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Machine Learning Approaches in Parkinson’s Disease

Current Medicinal Chemistry ◽

10.2174/0929867328999210111211420 ◽

2021 ◽

Vol 28 ◽

Author(s):

Annamaria Landolfi ◽

Carlo Ricciardi ◽

Leandro Donisi ◽

Giuseppe Cesarelli ◽

Jacopo Troisi ◽

...

Keyword(s):

Machine Learning ◽

Parkinson’S Disease ◽

Parkinson's Disease ◽

Neurodegenerative Disorder ◽

Learning Algorithms ◽

Disease Diagnosis ◽

Machine Learning Algorithms ◽

Clinical Aspects ◽

Learning Approaches

Background:: Parkinson’s disease is the second most frequent neurodegenerative disorder. Its diagnosis is challenging and mainly relies on clinical aspects. At present, no biomarker is available to obtain a diagnosis of certainty in vivo. Objective:: The present review aims at describing machine learning algorithms as they have been variably applied to different aspects of Parkinson’s disease diagnosis and characterization. Methods:: A systematic search was conducted on PubMed in December 2019, resulting in 230 publications obtained with the following search query: “Machine Learning” “AND” “Parkinson Disease”. Results:: the obtained publications were divided into 6 categories, based on different application fields: “Gait Analysis - Motor Evaluation”, “Upper Limb Motor and Tremor Evaluation”, “Handwriting and typing evaluation”, “Speech and Phonation evaluation”, “Neuroimaging and Nuclear Medicine evaluation”, “Metabolomics application”, after excluding the papers of general topic. As a result, a total of 166 articles were analyzed, after elimination of papers written in languages other than English or not directly related to the selected topics. Conclusion:: Machine learning algorithms are computer-based statistical approaches which can be trained and are able to find common patterns from big amounts of data. The machine learning approaches can help clinicians in classifying patients according to several variables at the same time.

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The In Vitro and In Vivo Molecular Mechanisms of Neuroprotection by the Major Green Tea Polyphenol, (–)-Epigallocatechin-3-gallate, with Special Reference to Parkinson’s Disease

Oxidative Stress and Disease - Molecular Interventions in Lifestyle-Related Diseases ◽

10.1201/9781420027174.ch13 ◽

2005 ◽

pp. 155-174

Author(s):

Silvia Mandel ◽

Tamar Amit ◽

Moussa Youdim ◽

Orly Weinreb

Keyword(s):

Parkinson’S Disease ◽

Parkinson's Disease ◽

Special Reference ◽

Green Tea ◽

Molecular Mechanisms ◽

Tea Polyphenol ◽

Green Tea Polyphenol

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Targeting mitophagy in Parkinson's disease

Journal of Biological Chemistry ◽

10.1074/jbc.rev120.014294 ◽

2020 ◽

pp. jbc.REV120.014294

Author(s):

Emily H Clark ◽

Aurelio Vázquez de la Torre ◽

Tamaki Hoshikawa ◽

Thomas Briston

Keyword(s):

Parkinson’S Disease ◽

Parkinson's Disease ◽

Quality Control ◽

High Throughput Screening ◽

Drug Targets ◽

Therapeutic Potential ◽

Biological Properties ◽

Loss Of Function ◽

Mitochondrial Quality Control

The genetics and pathophysiology of Parkinson’s disease (PD) strongly implicate mitochondria in disease aetiology. Elegant studies over the last two decades have elucidated complex molecular signalling governing the identification and removal of dysfunctional mitochondria from the cell, a process of mitochondrial quality control known as mitophagy. Mitochondrial deficits and specifically reduced mitophagy are evident in both sporadic and familial PD. Mendelian genetics attributes loss-of-function mutations in key mitophagy regulators PINK1 and Parkin to early-onset PD. Pharmacologically enhancing mitophagy and accelerating the removal of damaged mitochondria are of interest for developing a disease-modifying PD therapeutic. However, despite significant understanding of both PINK1/Parkin-dependent and -independent mitochondrial quality control pathways, the therapeutic potential of targeting mitophagy remains to be fully explored. Here, we provide a summary of the genetic evidence supporting the role for mitophagy-failure as a pathogenic mechanism in PD. We assess the tractability of mitophagy pathways and prospects for drug discovery and consider intervention points for mitophagy enhancement. We explore the numerous hit molecules beginning to emerge from high-content/high-throughput screening as well as the biochemical and phenotypic assays that enabled these screens. The chemical and biological properties of these reference compounds suggest many could be used to interrogate and perturb mitochondrial biology to validate promising drug targets. Finally, we address key considerations and challenges in achieving pre-clinical proof-of-concept, including in vivo mitophagy reporter methodologies and disease models, as well as patient stratification and biomarker development for mitochondrial forms of the disease.

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