Identification of Electrophysiological Changes in Alzheimer's Disease: A Microarray Based Transcriptomics and Molecular Pathway Analysis Study

Background & Objective: Involvement of amyloid beta and tau proteins in pathogenesis of Alzheimer's disease (AD) has been studied extensively. However, electrophysiological activity, and cellular processes like membrane transport are mostly unstudied. Electrophysiological processes provide a bridge between brain activity and cognition, and show promise as translatable biomarkers in preclinical and clinical applications. Biochemical imbalance leads to change in glutamate-based neurotransmission, antioxidant capacity, and in membrane polarization-repolarization events, eventually, resulting in AD. We hypothesize that in AD, these processes are unified at a single metabolic hub and we carried out a holistic system-biology approach. Method: In the present study, we integrated and analyzed multiple AD expression datasets from the GEO database to identify significant genes associated with electrophysiological pathways and attempted determination of interconnected canonical molecular pathways. Partek Genomic suite based expression analysis identified 200 significantly expressed genes using cut-off value of ≤ 0.05 and 2 fold change. Transducer of ERBB2, 2 (TOB2); lactotransferrin (LFT) and RAS-like, family 12 (RASL12) were most up-regulated genes, while neurofilament light polypeptide (NEFL); collagen, type V, alpha 2 (COL5A2); visinin-like 1 (VSNL1); cannabinoid receptor 1 (brain) (CNR1); neurofilament, medium polypeptide (NEFM); regulator of G-protein signaling 4 (RGS4), and synaptosomalassociated protein, 25kDa (SNAP25) were most down-regulated ones. Conclusion: Interestingly, we found majority of transporter genes identified in dataset as downregulated. Ingenuity pathways analysis revealed glutamate receptor signaling, CREB signaling, dopamine- DARPP32 feedback in cAMP signaling, fMLP signaling in neutrophils, and synaptic long term potentiation pathway playing critical role in AD pathophysiology and having correlation with electrophysiological dysfunction. Keywords: Alzheimer's disease, electrophysiology, microarray, genomics, meta-analysis, pathogenesis.