Journal of Environmental Biology

Decoding the genetic landscape of hypothyroidism: A comprehensive computational analysis

J. Kavya¹, Molakala Pavan Kumar Reddy²*, V.M. Hemanth Kumar¹, P.P. Reddemma³ and P. Supriya³       

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

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

³Department 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: pavankumarreddy_m@aimschittoor.edu.in                       *ORCiD: https://orcid.org/0000-0002-1520-6007

Abstract

Aim: Hypothyroidism is a multifactorial endocrine condition involving layered metabolic imbalance and inherited susceptibility. This study aimed to delineate key genes, molecular pathways, and metabolite associations contributing to impaired thyroid function through integrative computational biology approaches.

Methodology: Thirty highly ranked hypothyroidism-associated genes retrieved from DisGeNET were subjected to downstream computational interrogation using WikiPathways, Gene Ontology (GO), and curated metabolomic datasets. Gene–gene interactions, functional roles, and pathway-level involvement were examined through enrichment analyses identifying significant biological processes, molecular functions, and cellular components associated with thyroid hormone synthesis and regulation.

Results: Thyroid hormones and Peripheral Downstream Signalling Effects emerged as a prominently enriched pathway, indicating a central regulatory role. Network analyses revealed dense interconnections among disease-associated genes extending into metabolic and signalling domains. Metabolomic assessment identified several compounds with strong genetic associations relevant to thyroid dysfunction. Tissue-specific and transcriptional analyses further highlighted coordinated gene expression patterns linked to metabolic regulation, including previously undescribed molecular relationships.

Interpretation: This integrative framework consolidates the molecular complexity underlying hypothyroidism, revealing genetic and metabolic interdependencies collectively contributing to disease manifestation. These findings may serve as a reference for identifying candidate biomarkers and therapeutic targets relevant to thyroid disorders, particularly within the Indian population.

Key words: Computational biology, Genetic networks, Hypothyroidism, Metabolic interactions, Molecular mechanisms

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