IDENTIFICATION OF UNIQUE PARKINSON’S DISEASE SIGNATURE USING INTEGRATIVE BIOINFORMATIC AND NETWORK PHARMACOLOGY APPROACHES IN TRANSCRIPTOMIC DATA
Author(s)
Hafsa Muhammed, PhD.
Department of Pharmacy Practice and Clinical Research, National institute of pharmaceutical education and research S.A.S Nagar Mohali.INDIA, Mohali, India.
Department of Pharmacy Practice and Clinical Research, National institute of pharmaceutical education and research S.A.S Nagar Mohali.INDIA, Mohali, India.
OBJECTIVES: Identification of shared transcriptomic signature between the blood and brain for developing minimally invasive biomarkers and understanding systemic disease progression
METHODS: Microarray datasets from the Gene Expression Omnibus (GEO) comprising both blood and brain cohorts have been employed in this study. The limma software was used to perform Differential Gene Expression (DEG) analysis with a significant threshold of Log2FC ≥1 and Padj<0.05. DAVID functional enrichment and Protein-Protein Interaction (PPI) network analysis, using STRING and CytoHubba, were employed to identify functional characteristics and regulatory hubs.
RESULTS: A robust nine-gene signature—ANK1, CMAS, GUCY1B1, PRKAR2B, PSD3, RAB27B, SLC18A2, SNCA, and UCHL1—was consistently downregulated in both blood and brain tissue, according to comparative analysis. Functional enrichment revealed a basic deficiency in vesicle processing and synaptic maintenance. Non-compensated cellular homeostatic collapse is indicated by concurrent decreases in RAB27B (vesicular clearance), UCHL1 (protein recycling), and SLC18A2 (synaptic transmission). NANOG, SNCA, UCHL1, SLC18A2, and ANK1 were identified as important regulatory hubs through topological analysis.
CONCLUSIONS: This consistent nine-gene pattern offers high-confidence peripheral blood indicators for early detection and progression tracking, as well as a molecular blueprint for the collapse of systemic homeostasis in Parkinson's disease.
METHODS: Microarray datasets from the Gene Expression Omnibus (GEO) comprising both blood and brain cohorts have been employed in this study. The limma software was used to perform Differential Gene Expression (DEG) analysis with a significant threshold of Log2FC ≥1 and Padj<0.05. DAVID functional enrichment and Protein-Protein Interaction (PPI) network analysis, using STRING and CytoHubba, were employed to identify functional characteristics and regulatory hubs.
RESULTS: A robust nine-gene signature—ANK1, CMAS, GUCY1B1, PRKAR2B, PSD3, RAB27B, SLC18A2, SNCA, and UCHL1—was consistently downregulated in both blood and brain tissue, according to comparative analysis. Functional enrichment revealed a basic deficiency in vesicle processing and synaptic maintenance. Non-compensated cellular homeostatic collapse is indicated by concurrent decreases in RAB27B (vesicular clearance), UCHL1 (protein recycling), and SLC18A2 (synaptic transmission). NANOG, SNCA, UCHL1, SLC18A2, and ANK1 were identified as important regulatory hubs through topological analysis.
CONCLUSIONS: This consistent nine-gene pattern offers high-confidence peripheral blood indicators for early detection and progression tracking, as well as a molecular blueprint for the collapse of systemic homeostasis in Parkinson's disease.
Conference/Value in Health Info
2026-05, ISPOR 2026, Philadelphia, PA, USA
Value in Health, Volume 29, Issue S6
Code
RWD12
Topic
Real World Data & Information Systems
Topic Subcategory
Distributed Data & Research Networks, Reproducibility & Replicability
Disease
SDC: Neurological Disorders