Integrative Transcriptomic Profiling of Human Neural Tissues Reveals Core Molecular Signatures of Neurodegeneration

Abstract: Background: Neurodegenerative disorders are characterized by progressive neuronal dysfunction and loss, yet their underlying molecular mechanisms remain incompletely understood. Advances in transcriptomic technologies and public data availability enable integrative bioinformatic approaches to identify conserved molecular features of neurodegeneration directly from human neural tissues. Methods and Results: In this study, an integrative transcriptomic analysis was performed using publicly available human neural tissue datasets from multiple neurodegenerative conditions. Differential gene expression analysis identified conserved differentially expressed genes across datasets, followed by functional enrichment and protein–protein interaction network analyses. The results revealed consistent dysregulation of pathways related to neuronal signaling, synaptic function, mitochondrial metabolism, neuroinflammation, and proteostasis. Network analysis further identified key hub genes with high connectivity, highlighting central molecular regulators involved in neurodegenerative processes. Conclusion: This integrative bioinformatic approach uncovers robust and conserved molecular signatures of neurodegeneration across human neural tissues. The identified pathways and hub genes provide a systems-level perspective on disease mechanisms and represent promising candidates for future biomarker development and therapeutic targeting in neurodegenerative diseases.