Background: Obesity is a complex genetic-based pediatric disorder which triggers life-threatening conditions. Therefore, the understanding the molecular mechanisms of obesity has been a significant approach in medicine. Computational methods allow rapid and comprehensive pathway analysis, which is important for generation of diagnosis and treatment of obesity.
Methods and results: Aims of our study are to comprehensively investigate genetic characteristics of obesity in children with non-syndromic, early-onset (< 7 years), and severe obesity (BMI-SDS > 3) through computational approaches. First, the mutational analyses of 41 of obesity-related genes in 126 children with non-syndromic early-onset severe obesity and 76 healthy non-obese controls were performed using the next generation sequencing (NGS) technique, and the NGS data analyzed by using bioinformatics methods. Then, the relationship between pathogenic variants and anthropometric/biochemical parameters was further evaluated. Obtained results demonstrated that the 15 genes (ADIPOQ, ADRB2, ADRB3, IRS1, LEPR, NPY, POMC, PPARG, PPARGC1A, PPARGC1B, PTPN1, SLC22A1, SLC2A4, SREBF1 and UCP1) which directly related to obesity found linked together via biological pathways and/or functions. Among these genes, IRS1, PPARGC1A, and SLC2A4 stand out as the most central ones. Furthermore, 12 of non-synonymous pathogenic variants, including six novels, were detected on ADIPOQ (G90S and D242G), ADRB2 (V87M), PPARGC1A (E680G, A477T, and R656H), UCP1 (Q44R), and IRS1 (R302Q, R301H, R301C, H250P, and H250N) genes.
Conclusion: We propose that 12 of non-synonymous pathogenic variations detected on ADIPOQ, ADRB2, PPARGC1A, UCP1, and IRS1 genes might have a cumulative effect on the development and progression of obesity.
Keywords: Bioinformatics; Genetics; Obesity; Pathway analysis; SNP.
© 2021. The Author(s), under exclusive licence to Springer Nature B.V.