A meta-analysis of genome-wide gene expression differences identifies promising targets for type 2 diabetes mellitus - Huang, Tao; Nazir, Bisma; Altaf, Reem; Zang, Bolun; Zafar, Hajra; Paiva-Santos, Ana Cláudia; Niaz, Nabeela; Imran, Muhammad; Duan, Yongtao; Abbas, Muhammad; Ilyas, Umair (Frontiers in Endocrinology, 2022)
Aims/Introduction: Due to the heterogeneous nature of type 2 diabetes mellitus and complex effects on haemodynamics, there is a need to identify new candidate markers which are involved in the development of type 2 diabetes mellitus (DM) and can serve as potential targets. As the global diabetes prevalence in 2019 was estimated as 9.3% (463 million people), rising to 10.2% (578 million) by 2030 and 10.9% (700 million) by 2045, the need to limit this rapid prevalence is of concern. The study aims in identifying the possible biomarkers of type 2 diabetes mellitus with the help of system biology approach using R programming. Materials and Methods: Several target proteins that were found to be associated with the source genes were further curated for their role in type 2 diabetes mellitus. The differential expression analysis provided 50 differentially expressed genes by pairwise comparison between the biologically comparable groups out of which eight differentially expressed genes were shortlisted. These included, MCL1, PTX3, CYP3A4, PTGS1, SSTR2, SERPINA3, TDO2 and GALNT7. Results: The cluster analysis showed clear differences between control and treated groups. The functional relationship of the signature genes showed protein-protein interaction network with target protein. Moreover, several transcriptional factors such as DBX2, HOXB7, POU3F4, MSX2, EBF1 and E4F1 showed association with these identified differentially expressed genes. Conclusions: The study highlighted important markers for diabetes mellitus that have shown interaction with other proteins having role in the progression of diabetes mellitus that can serve as new targets in the management of DM.