An Integrative Data Mining Approach to Identify Purinergic Signaling Genes and Associated Neurodegenerative Diseases

Pradhan, Ranjan K. and Dash, Abhishek (2021) An Integrative Data Mining Approach to Identify Purinergic Signaling Genes and Associated Neurodegenerative Diseases. In: 12th International Conference on Computing Communication and Networking Technologies, ICCCNT 2021, 6 July 2021 through 8 July 2021, Kharagpur.

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Abstract

Purinergic receptor-mediated signaling play important roles in the regulation of numerous physiological and pathological processes, including neurodegenerative diseases. Purinergic receptors are a class of membrane-bound proteins that signal through ATP, ADP or Adenosine during endothelial-mediated vasodilatation, inflammation, immune response, inflammation, platelet aggregation and blood flow regulation in different tissues. Although a number of genes are known to involve in the diseases of central nervous system, it is unclear how genes encoding purinoceptors are associated with neurodegeneration process of human brain. In this work, we applied an integrative data mining approach to the curated genomic and RNA-sequence databases for identifying genes that are functionally associated with purinergic signaling, and most common neurodegenerative diseases. Based on gene ontology and functional enrichment analyses of extensive data on genes and tissue-level gene expressions, 33 purinergic genes were identified. Functional mapping of these genes with hereditary disease genes revealed association of genes ADORA2A, P2RX7, P2RY1, P2RY2, P2RY4, P2RY6 with Alzheimer's disease, ADORA2A with Parkinson's disease, ADA, ADORA2A, P2RX7 with Huntington's disease, respectively. © 2021 IEEE.

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