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A prognostic view on the application of individualized genomics in Parkinson's disease.

ABSTRACT: Parkinson's disease is a common age-related progressive neurodegenerative disorder. Over the last 15 years advances have been made in our understanding of the etiology of the disease, with the greatest insights perhaps coming from genetic studies. The identification of a number of genes that harbor pathogenic mutations causing Parkinson's disease have on the whole driven the development of disease model systems and nominated a number of therapeutic targets. As we move towards an era of personalized medicine, genetic determinants will become even more crucial for accurate diagnosis, and assessing prognosis and outcomes. The individual genomic profile and risk assessments will in the long-term determine clinical trial participation, treatment plans and therapeutic dosing. Herein we discuss the status of genetics in Parkinson's disease and how these factors may affect the patient care in the future.

SUBMITTER: Ross OA

PROVIDER: S-EPMC3596092 | biostudies-literature | 2013 Mar

REPOSITORIES: biostudies-literature

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A prognostic view on the application of individualized genomics in Parkinson's disease.

Ross Owen A OA

Current genetic medicine reports 20130112 1

Parkinson's disease is a common age-related progressive neurodegenerative disorder. Over the last 15 years advances have been made in our understanding of the etiology of the disease, with the greatest insights perhaps coming from genetic studies. The identification of a number of genes that harbor pathogenic mutations causing Parkinson's disease have on the whole driven the development of disease model systems and nominated a number of therapeutic targets. As we move towards an era of personali ...[more]

PMID: 23504498

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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.

Dataset Information

A prognostic view on the application of individualized genomics in Parkinson's disease.

Publications

A prognostic view on the application of individualized genomics in Parkinson's disease.

Similar Datasets

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