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Promise of pharmacogenomics for drug discovery, treatment and prevention of Parkinson's disease. A perspective.

ABSTRACT: Parkinson's disease (PD) is a progressive neurodegenerative disorder characterized by a heterogeneous array of motor and non-motor features. Anti-PD drugs that are in use target only the motor symptoms, may lose efficacy over time, and can cause serious adverse effects such as dyskinesia and psychosis. There are currently no preventative or disease modifying treatments. All attempts to develop disease modifying drugs have failed. Pharmacogenomics (PGx) has the potential to change the way new drugs are developed and the way drugs are prescribed. By using genetic markers that correlate with, and can therefore predict drug response, clinical trials can be designed to be enriched with individuals who are most likely to benefit from the drug, maximizing drug's efficacy, minimizing its adverse effects, and boosting the odds of successful drug discovery. Clinical application of PGx will help physicians to quickly and accurately determine the right drugs and the right doses for individuals, avoiding the lengthy trial and error approaches and adverse effects. In combination with known protective factors such as nicotine and caffeine, PGx may enable development of personalized methods for PD prevention and, by extension, care.

SUBMITTER: Payami H

PROVIDER: S-EPMC3899479 | biostudies-literature | 2014 Jan

REPOSITORIES: biostudies-literature

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Promise of pharmacogenomics for drug discovery, treatment and prevention of Parkinson's disease. A perspective.

Payami Haydeh H Factor Stewart A SA

Neurotherapeutics : the journal of the American Society for Experimental NeuroTherapeutics 20140101 1

Parkinson's disease (PD) is a progressive neurodegenerative disorder characterized by a heterogeneous array of motor and non-motor features. Anti-PD drugs that are in use target only the motor symptoms, may lose efficacy over time, and can cause serious adverse effects such as dyskinesia and psychosis. There are currently no preventative or disease modifying treatments. All attempts to develop disease modifying drugs have failed. Pharmacogenomics (PGx) has the potential to change the way new dru ...[more]

PMID: 24258196

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Project description:BackgroundParkinson's disease (PD) is the second most common neurodegenerative disease with a significant public health burden. It is characterized by the gradual degeneration of dopamine neurons in the central nervous system. Although symptomatic pharmacological management remains the primary therapeutic method for PD, clinical experience reveals significant inter-individual heterogeneity in treatment effectiveness and adverse medication responses. The mechanisms behind the observed interindividual variability may be elucidated by investigating the role of genetic variation in human-to-human variances in medication responses and adverse effects.ObjectiveThis review aims to explore the impact of gene polymorphism on the efficacy of antiparkinsonian drugs. The identification of factors associated with treatment effectiveness variability might assist the creation of a more tailored pharmacological therapy with higher efficacy, fewer side outcomes, and cheaper costs.MethodsIn this review, we conducted a thorough search in databases such as PubMed, Web of Science, and Google Scholar, and critically examined current discoveries on Parkinson's disease pharmacogenetics. The ethnicity of the individuals, research methodologies, and potential bias of these studies were thoroughly compared, with the primary focus on consistent conclusions.ResultsThis review provides a summary of the existing data on PD pharmacogenetics, identifies its limitations, and offers insights that may be beneficial for future research. Previous studies have investigated the impact of gene polymorphism on the effectiveness and adverse effects of levodopa. The trendiest genes are the COMT gene, DAT gene, and DRD2 gene. However, limited study on other anti-Parkinson's drugs has been conducted.ConclusionTherefore, In order to develop an individualized precision treatment for PD, it is an inevitable trend to carry out multi-center, prospective, randomized controlled clinical trials of PD pharmacogenomics covering common clinical anti-PD drugs in large, homogeneous cohorts.

Project description:Parkinson's disease (PD) is the second most important age-related neurodegenerative disorder in developed societies, after Alzheimer's disease, with a prevalence ranging from 41 per 100,000 in the fourth decade of life to over 1900 per 100,000 in people over 80 years of age. As a movement disorder, the PD phenotype is characterized by rigidity, resting tremor, and bradykinesia. Parkinson's disease -related neurodegeneration is likely to occur several decades before the onset of the motor symptoms. Potential risk factors include environmental toxins, drugs, pesticides, brain microtrauma, focal cerebrovascular damage, and genomic defects. Parkinson's disease neuropathology is characterized by a selective loss of dopaminergic neurons in the substantia nigra pars compacta, with widespread involvement of other central nervous system (CNS) structures and peripheral tissues. Pathogenic mechanisms associated with genomic, epigenetic and environmental factors lead to conformational changes and deposits of key proteins due to abnormalities in the ubiquitin-proteasome system together with dysregulation of mitochondrial function and oxidative stress. Conventional pharmacological treatments for PD are dopamine precursors (levodopa, l-DOPA, l-3,4 dihidroxifenilalanina), and other symptomatic treatments including dopamine agonists (amantadine, apomorphine, bromocriptine, cabergoline, lisuride, pergolide, pramipexole, ropinirole, rotigotine), monoamine oxidase (MAO) inhibitors (selegiline, rasagiline), and catechol-O-methyltransferase (COMT) inhibitors (entacapone, tolcapone). The chronic administration of antiparkinsonian drugs currently induces the "wearing-off phenomenon", with additional psychomotor and autonomic complications. In order to minimize these clinical complications, novel compounds have been developed. Novel drugs and bioproducts for the treatment of PD should address dopaminergic neuroprotection to reduce premature neurodegeneration in addition to enhancing dopaminergic neurotransmission. Since biochemical changes and therapeutic outcomes are highly dependent upon the genomic profiles of PD patients, personalized treatments should rely on pharmacogenetic procedures to optimize therapeutics.

Project description:BackgroundLarge-scale pharmacogenomic resources, such as the Connectivity Map (CMap), have greatly assisted computational drug discovery. However, despite their widespread use, CMap-based methods have thus far been agnostic to the biological activity of drugs as well as to the genomic effects of drugs in multiple disease contexts. Here, we present a network-based statistical approach, Pathopticon, that uses CMap to build cell type-specific gene-drug perturbation networks and integrates these networks with cheminformatic data and diverse disease phenotypes to prioritize drugs in a cell type-dependent manner.MethodsWe build cell type-specific gene-drug perturbation networks from CMap data using a statistical procedure we call Quantile-based Instance Z-score Consensus (QUIZ-C). Using these networks and a large-scale disease-gene network consisting of 569 disease signatures from the Enrichr database, we calculate Pathophenotypic Congruity Scores (PACOS) between input gene signatures and drug perturbation signatures and combine these scores with cheminformatic data from ChEMBL to prioritize drugs. We benchmark our approach by calculating area under the receiver operating characteristic curves (AUROC) for 73 gene sets from the Molecular Signatures Database (MSigDB) using target gene expression profiles from the Comparative Toxicogenomics Database (CTD). We validate the drugs predicted in our proofs-of-concept using real-time polymerase chain reaction (qPCR) experiments.ResultsCell type-specific gene-drug perturbation networks built using QUIZ-C are topologically distinct, reflecting the biological uniqueness of the cell lines in CMap, and are enriched in known drug targets. Pathopticon demonstrates a better prediction performance than solely cheminformatic measures as well as state-of-the-art network and deep learning-based methods. Top predictions made by Pathopticon have high chemical structural diversity, suggesting their potential for building compound libraries. In proof-of-concept applications on vascular diseases, we demonstrate that Pathopticon helps guide in vitro experiments by identifying pathways that are potentially regulated by the predicted therapeutic candidates.ConclusionsOur network-based analytical framework integrating pharmacogenomics and cheminformatics (available at https://github.com/r-duh/Pathopticon ) provides a feasible blueprint for a cell type-specific drug discovery and repositioning platform with broad implications for the efficiency and success of drug development.

Project description:BackgroundParkinson's disease (PD) is a disease of ⍺-synuclein aggregation-mediated dopaminergic neuronal loss in the substantia nigra pars compacta, which leads to motor and non-motor symptoms. Through the last two decades of research, there has been growing consensus that inflammation-mediated oxidative stress, mitochondrial dysfunction, and cytokine-induced toxicity are mainly involved in neuronal damage and loss associated with PD. However, it remains unclear how these mechanisms relate to sporadic PD, a more common form of PD. Both enteric and central nervous systems have been implicated in the pathogenesis of sporadic PD, thus highlighting the crosstalk between the gut and brain.Aimof Review: In this review, we summarize how alterations in the gut microbiome can affect PD pathogenesis. We highlight various mechanisms increasing/decreasing the risk of PD development. Based on the previous supporting evidence, we suggest how early interventions could protect against PD development and how controlling specific factors, including our diet, could modify our perspective on disease mechanisms and therapeutics. We explain the strong relationship between the gut microbiota and the brain in PD subjects, by delineating the multiple mechanisms involved inneuroinflammation and oxidative stress. We conclude that the neurodetrimental effects of western diet (WD) and the neuroprotective effects of Mediterranean diets should be further exploredin humans through clinical trials. Key Scientific Concepts of Review: Alterations in the gut microbiome and associated metabolites may contribute to pathogenesis in PD. In some studies, probiotics have been shown to exert anti-oxidative effects in PD via improved mitochondrial dynamics and homeostasis, thus reducing PD-related consequences. However, there is a significant unmet need for randomized clinical trials to investigate the effectiveness of microbial products, probiotic-based supplementation, and dietary intervention in reversing gut microbial dysbiosis in PD.

Dataset Information

Promise of pharmacogenomics for drug discovery, treatment and prevention of Parkinson's disease. A perspective.

Publications

Promise of pharmacogenomics for drug discovery, treatment and prevention of Parkinson's disease. A perspective.

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