Identification and Analysis of Genetic Markers Associated With Type 1 Diabetes in the Pediatric Population

Type 1 diabetes (T1D) is a chronic autoimmune disorder primarily affecting children and adolescents, characterized by the destruction of insulin-producing beta cells. Genetic factors are crucial in T1D susceptibility, yet the complete genetic underpinnings remain partially understood. Identifying genetic markers associated with T1D can enhance our understanding of its pathogenesis and facilitate the development of predictive tools and personalized therapies. Objective: To identify and analyze genetic markers associated with type 1 diabetes in pediatric populations to improve understanding of diagnosis and targeted therapeutic interventions. Methods: This case-control study in Allied Hospital Faisalabad from August 2023 to April 2024 involved 150 pediatric T1D patients and 150 age-matched healthy controls. Genomic DNA was extracted and analyzed using genome-wide association studies (GWAS) with high-density SNP arrays. Significant SNPs were identified through logistic regression, adjusting for potential confounders. Functional annotation and pathway enrichment analyses were performed. Validation was achieved by replicating an independent cohort of 200 T1D patients and 200 controls. Results: Fifteen SNPs reached genome-wide significance (p < 5 x 10^-8), with the strongest association at rs9273363 (OR = 3.2, 95% CI: 2.4-4.2, p = 1.2 x 10^-10). Other notable SNPs included rs2476601 (OR = 2.5, 95% CI: 1.9-3.3, p = 4.5 x 10^-8) and rs689 (OR = 2.0, 95% CI: 1.5-2.7, p = 7.1 x 10^-7). Pathway analysis highlighted the significant involvement of immune-related pathways. Replication confirmed these associations with consistent effect sizes and significance levels. Conclusion: This study identified multiple genetic markers associated with T1D in pediatric populations, particularly in the HLA, PTPN22, and INS regions. These findings enhance the understanding of T1D genetics and underscore the importance of immune regulation. The identified markers hold the potential for predictive tools and personalized therapeutic strategies, paving the way for precision medicine in T1D management.