Gene expression meta-analysis identifies novel pathways of the avian influenza virus disease

Humans and other animals are both susceptible to avian influenza virus. The avian influenza (AI) pandemic could be brought on by the appearance of a new, radical AI virus capable of spreading disease and maintaining prolonged human-to-human transmissions. The possibility of an AI pandemic makes it important for public health. Despite efforts to identify a linkage between them, the hierarchical relationship between all the factors that influence the pathophysiology of this disease, the shared biological pathways, and the exact identities of its important triggers are yet unknown. To find shared gene expression profiles and overlapping biological processes, an integrated gene expression meta-analysis was carried out for three independent microarray data of the avian influenza virus. This study found 1284 common differentially expressed genes (DEGs), of which 73 were overexpressed and 119 were under-expressed, analyzed using various packages in the R tool. The extensive biological, functional enrichment and pathway analysis was performed using the EnrichR tool and identified the defence response to the symbiont (GO:0140546), Interferon Alpha/Beta Signaling (R-HSA-909733), and spliceosome as the most enriched terms of biological process and pathways respectively. In a network meta-analysis, ISG15 and RELA were pinpointed as the top hub genes for over and under-expression, respectively. This meta-analysis technique for avian influenza infection highlights important gene profiles and their linked pathways. These findings highlight the value of using meta-analysis to detect novel gene markers that may offer key insight into disease pathogenesis and perhaps pave the way for creating more effective therapeutic approaches.

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Publication Details

Journal
Journal of Biomolecular Structure and Dynamics
Published
2024-11-26
DOI
https://doi.org/10.1080/07391102.2024.2431662
Primary Topic
Influenza Virus Research Studies
Type
article
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article

Gene expression meta-analysis identifies novel pathways of the avian influenza virus disease

Swati Rani, Rajan Kumar Pandey, Varsha Ramesh, B. Madhumitha et al.
Journal of Biomolecular Structure and Dynamics
Influenza Virus Research Studies
article

Gene expression meta-analysis identifies novel pathways of the avian influenza virus disease

Swati Rani, Rajan Kumar Pandey, Varsha Ramesh, B. Madhumitha, M Shijili, Uma Bharathi, S. S. Patil, Nagendra Nath Barman, Kuralayanapalya Puttahonnappa Suresh, R. Raaga, Yamini Sri Sekar
article en

Abstract

Humans and other animals are both susceptible to avian influenza virus. The avian influenza (AI) pandemic could be brought on by the appearance of a new, radical AI virus capable of spreading disease and maintaining prolonged human-to-human transmissions. The possibility of an AI pandemic makes it important for public health. Despite efforts to identify a linkage between them, the hierarchical relationship between all the factors that influence the pathophysiology of this disease, the shared biological pathways, and the exact identities of its important triggers are yet unknown. To find shared gene expression profiles and overlapping biological processes, an integrated gene expression meta-analysis was carried out for three independent microarray data of the avian influenza virus. This study found 1284 common differentially expressed genes (DEGs), of which 73 were overexpressed and 119 were under-expressed, analyzed using various packages in the R tool. The extensive biological, functional enrichment and pathway analysis was performed using the EnrichR tool and identified the defence response to the symbiont (GO:0140546), Interferon Alpha/Beta Signaling (R-HSA-909733), and spliceosome as the most enriched terms of biological process and pathways respectively. In a network meta-analysis, ISG15 and RELA were pinpointed as the top hub genes for over and under-expression, respectively. This meta-analysis technique for avian influenza infection highlights important gene profiles and their linked pathways. These findings highlight the value of using meta-analysis to detect novel gene markers that may offer key insight into disease pathogenesis and perhaps pave the way for creating more effective therapeutic approaches.

Journal of Biomolecular Structure and DynamicsVol. 44(4)
Karolinska Institutet (SE), Assam Agricultural University (IN), National Institute Of Veterinary Epidemiology And Disease Informatics (IN)
Good health and well-being
Openalex Percentile: Top 68%
Influenza Virus Research Studies
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