Journal of Environmental Biology

Comprehensive bioinformatic analysis of key genes associated with measles virus infection: Implications for immunological and inflammatory pathways

M.N.S. Adiga¹*, M. Abrar¹, S.S. Raju¹ and U. Adiga²       

¹Department of Pharmacology, Apollo Institute of Medical Sciences and Research Chittoor, Murukambattu - 517 127, India

²Department of Biochemistry, Apollo Institute of Medical Sciences and Research Chittoor, Murukambattu - 517 127, India

Received: 29 November 2025                   Revised: 04 May 2026                   Accepted: 04 June 2026

*Corresponding Author Email: sachidananda_adiga@aimsrchittoor.edu.in                        *ORCiD: https://orcid.org/0000-0002-6996-8592

Abstract

Aim: Measles remains a global health challenge despite widespread vaccination, causing significant morbidity and mortality especially among unvaccinated children. This study identifies and characterizes key genes associated with measles virus infection through comprehensive bioinformatic analysis.

Methodology: Thirty measles-associated genes from DisGeNET were analyzed using gene ontology enrichment, pathway mapping, protein complex analysis, tissue expression profiling, transcription factor prediction, and metabolite interaction analysis.

Results: Gene ontology enrichment highlighted cytokine production regulation (OR=48.98), STAT phosphorylation (OR=126.32), and immunoglobulin production (OR=181.35). Pathway analysis implicated the measles infection pathway (OR=91.91) and inflammatory responses. Protein analysis revealed enrichment in interleukin complexes. Tissue expression was highest in peritoneal exudate (OR=552.23) and synovial tissue (OR=134.43).

Interpretation: This integrative bioinformatic analysis uncovers key molecular processes underlying measles virus infection, emphasizing cytokine signaling, JAK-STAT phosphorylation, and inflammatory pathways as central mechanisms. The identified genes represent potential therapeutic targets for novel treatments against measles and related infections.

Key words: Bioinformatics, Cytokine signalling, Gene ontology, Inflammatory response, Measles virus

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