Inferring microarray datasets reveals critical biomarkers and potential drug targets of Parkinson’s disease

Authors

  • Anuradha Bhardwaj Department of Biotechnology, Gautam Buddha University, Greater Noida, Uttar Pradesh- 201312, India
  • Ahmad Obaid Laboratory Medicine Department, Faculty of Applied Medical Sciences, Umm Al-Qura University, Makkah, Saudi Arabia.
  • Anmar Anwar Khan Laboratory Medicine Department, College of Applied Medical Sciences, Umm Al-Qura University, Saudi Arabia
  • Mahendra P Singh
  • Mohammed M. Jalal Department of Medical Laboratory Technology, Faculty of Applied Medical Sciences, University of Tabuk, Tabuk 71491, Saudi Arabia
  • Zuhair M. Mohammedsaleh Department of Medical Laboratory Technology, Faculty of Applied Medical Sciences, University of Tabuk, Tabuk 71491, Saudi Arabia
  • Mamdoh S. Moawadh Department of Medical Laboratory Technology, Faculty of Applied Medical Sciences, University of Tabuk, Tabuk 71491, Saudi Arabia
  • Walaa F. Alsanie Department of Clinical Laboratory Sciences, The faculty of Applied Medical Sciences, Taif University, Taif, Saudi Arabia
  • Abdulhakeem S. Alamri Department of Clinical Laboratory Sciences, The faculty of Applied Medical Sciences, Taif University, Taif, Saudi Arabia
  • Majid Alhomrani Department of Clinical Laboratory Sciences, The faculty of Applied Medical Sciences, Taif University, Taif, Saudi Arabia
  • Abdulaziz Alsharif Department of Clinical Laboratory Sciences, The faculty of Applied Medical Sciences, Taif University, Taif, Saudi Arabia
  • Sandeep Singh Indian Scientific Education and Technology Foundation

DOI:

https://doi.org/10.54029/2024stx

Keywords:

microarray, parkinson’s disease, enrichment analysis, PPI network, KEGG pathway

Abstract

Parkinson’s disease (PD) is a critical neurological disorder characterized by loss of voluntary motor control and substantial slowing of movement. While traditionally attributed to environmental factors, recent studies underscore the significant role of genetics in the onset and progression of PD. This study aimed to identify differentially expressed genes (DEGs) and relevant pathways in PD by analyzing gene expression data from four datasets (83 PD and 53 control substantia nigra samples) sourced from the Gene Expression Omnibus (GEO) database. Using GEO2R, we identified common DEGs and performed functional annotation and KEGG pathway enrichment analysis through Enrichr. We constructed a protein–protein interaction (PPI) network using StringDB and identified hub genes via CytoHubba. Results revealed 18 critical DEGs enriched in pathways such as dopaminergic synapse and cocaine addiction. Key hub genes included Tyrosine Hydroxylase (TH), Solute Carrier Family 18 Member A2 (SLC18A2), and Potassium Inwardly Rectifying Channel Subfamily J Member 6 (KCNJ6). These findings provide insights into the molecular mechanisms of PD, highlighting potential biomarkers and therapeutic targets. This study offers a robust framework for future research and the development of effective treatment strategies for Parkinson’s disease.

Published

2024-12-25

Issue

Vol. 29 No. 4 (2024)

Section

Original Article