Gene Signals and SNPs Associated with Parkinson's Disease: A Nutrigenomics and Computational Prospective Insights.


Journal

Neuroscience
ISSN: 1873-7544
Titre abrégé: Neuroscience
Pays: United States
ID NLM: 7605074

Informations de publication

Date de publication:
21 11 2023
Historique:
received: 02 03 2023
revised: 05 05 2023
accepted: 11 10 2023
medline: 13 11 2023
pubmed: 20 10 2023
entrez: 20 10 2023
Statut: ppublish

Résumé

Parkinson's disease is the most prevalent chronic neurodegenerative disease. Neurological conditions for PD were influenced by a variety of epigenetic factors and SNPs in some of the coexisting genes that were expressed. This article focused on nutrigenomics of PD and the prospective highlighting of how these genes are regulated in terms of nutritive factors and the genetic basis of PD risk, onset, and progression. Multigenetic associations of the following genetic alterations in the genes of SNCA, LRRK2, UCHL1, PARK2,PINK1, DJ-1, and ATP13A2 have been reported with the familial and de novo genetic origins of PD. Over the past two decades, significant attempts have been made to understand the biological mechanisms that are potential causes for this disease, as well as to identify therapeutic substances for the prevention and management of PD. Nutrigenomics has sparked considerable interest due to its nutritional, safe, and therapeutic effects on a variety of chronic diseases. In this study, we summarise some of the nutritive supplements that have an impact on PD.

Identifiants

pubmed: 37858629
pii: S0306-4522(23)00457-8
doi: 10.1016/j.neuroscience.2023.10.007
pii:
doi:

Types de publication

Journal Article Review Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

77-95

Informations de copyright

Copyright © 2023 IBRO. Published by Elsevier Ltd. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Auteurs

Swetha Subramaniyan (S)

Department of Bioinformatics, Alagappa University, Karaikudi, Tamil Nadu, India.

Beena Briget Kuriakose (BB)

Department of Basic Medical Sciences, College of Applied Medical Sciences, King Khalid University, Khamis Mushayt, Saudi Arabia.

Sakeena Mushfiq (S)

Department of Public Health, College of Applied Medical Sciences, King Khalid University, Khamis Mushayt, Saudi Arabia.

Narayanaswamy Marimuthu Prabhu (NM)

Department of Animal Health and Management, Alagappa University, Karaikudi, Tamil Nadu, India.

Karthikeyan Muthusamy (K)

Department of Bioinformatics, Alagappa University, Karaikudi, Tamil Nadu, India. Electronic address: karthikeyanm@alagappauniversity.ac.in.

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Classifications MeSH