The role of pharmacogenomics in the personalization of Parkinson's disease treatment

Pharmacogenomics-a New Frontier for Individualized Treatment of Parkinson's Disease

BACKGROUND

Parkinson'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.

OBJECTIVE

This 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.

METHODS

In 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.

RESULTS

This 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.

CONCLUSION

Therefore, 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.

Integrated Brain Metabolomics and Network Pharmacology Analysis to Reveal the Improvement Effect of Bai Chan Ting on Parkinson's Disease

BACKGROUND

Baichanting (BCT),a traditional Chinese medicine prescription, is a combination of Acanthopanax senticosus, Paeonia lactiflora, and Uncaria three herbs, which has the effect of benefiting the kidney and calming the liver. The study was aimed at investigating the protective effect of BCT against Parkinson's disease using an integrated strategy of network pharmacology and brain metabolomics.

MATERIALS AND METHODS

By integrating network pharmacology with metabolomic research, the protective effect of BCT against PD was investigated using a transgenic mouse model for α-synuclein. The metabolite level and gene level components of BCT that might be anti-PD were separated out. Indicators of behavior and pharmacodynamics were employed to gauge the effectiveness of BCT on PD in the preliminary stages. Network pharmacology, which may be the target of BCT, screened the active substances and target genes. The use of metabolomics to identify potential biomarkers of PD, and then through network pharmacology and metabolic pathways to determine their regulatory enzymes and regulatory genes, improve the pathway mechanism of the disease, has important guiding significance for the in-depth study of the pathogenesis of PD.

RESULTS

101 putative target genes were identified by the network pharmacology analysis in relation to the treatment of PD with BCT. According to the functional enrichment analysis, the proposed mechanism was primarily related to the transport of neurotransmitters, the metabolism of arachidonic acid, dopamine, and alpha-amino acids, as well as the transport of dopamine and the negative regulation of amino acid transport. 25 distinct endogenous metabolites were shown to be potential biomarkers for the BCT for treating PD based on metabolomics. These metabolites were mostly implicated in the important methionine and cysteine, tyrosine, histidine, and arginine and proline metabolic pathways. These results somewhat agreed with those of the network pharmacology analysis.

CONCLUSIONS

In conclusion, this study showed that BCT could delay the occurrence and development of PD by improving the brain metabolic disorder of α-Syn mice, which revealed the mechanism of BCT through multitarget and multipathway treatment, and provided a new explanation for the mechanism of anti-PD action. Our research, on the other hand, demonstrated that the network pharmacology-integrated metabolomics approach was a potent tool for discovering the active ingredients and mechanisms underlying the pharmacological effects of traditional Chinese medicine.

The Genetics of Parkinson's Disease and Implications for Clinical Practice

The genetic landscape of Parkinson’s disease (PD) is characterised by rare high penetrance pathogenic variants causing familial disease, genetic risk factor variants driving PD risk in a significant minority in PD cases and high frequency, low penetrance variants, which contribute a small increase of the risk of developing sporadic PD. This knowledge has the potential to have a major impact in the clinical care of people with PD. We summarise these genetic influences and discuss the implications for therapeutics and clinical trial design.