A meta-analysis of genome-wide gene expression differences identifies promising targets for type 2 diabetes mellitus.

Autor:	Huang T; Henan Provincial Key Laboratory of Pediatric Hematology, Children's Hospital Affiliated to Zhengzhou University, Zhengzhou University, Zhengzhou, China.; Medical School, Huanghe Science and Technology University, Zhengzhou, China., Nazir B; Riphah Institute of Pharmaceutical Sciences, Riphah International University, Islamabad, Pakistan., Altaf R; Department of Pharmacy, Islamabad, Pakistan., Zang B; Henan Provincial Key Laboratory of Pediatric Hematology, Children's Hospital Affiliated to Zhengzhou University, Zhengzhou University, Zhengzhou, China., Zafar H; School of Pharmacy, Shanghai Jiao Tong University, Shanghai, China., Paiva-Santos AC; Department of Pharmaceutical Technology, Faculty of Pharmacy, University of Coimbra, Coimbra, Portugal.; REQUIMTE/LAQV, Group of Pharmaceutical Technology, Faculty of Pharmacy, University of Coimbra, Coimbra, Portugal., Niaz N; Department of Pharmacy, Sarhad University of Science and Technology, Peshawar, Pakistan., Imran M; Department of Pharmacy, Islamabad, Pakistan., Duan Y; Henan Provincial Key Laboratory of Pediatric Hematology, Children's Hospital Affiliated to Zhengzhou University, Zhengzhou University, Zhengzhou, China., Abbas M; Riphah Institute of Pharmaceutical Sciences, Riphah International University, Islamabad, Pakistan., Ilyas U; Riphah Institute of Pharmaceutical Sciences, Riphah International University, Islamabad, Pakistan.
Jazyk:	angličtina
Zdroj:	Frontiers in endocrinology [Front Endocrinol (Lausanne)] 2022 Aug 16; Vol. 13, pp. 985857. Date of Electronic Publication: 2022 Aug 16 (Print Publication: 2022).
DOI:	10.3389/fendo.2022.985857
Abstrakt:	Aims/introduction: Due to the heterogeneous nature of type 2 diabetes mellitus and its complex effects on hemodynamics, 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 to identify the possible biomarkers of type 2 diabetes mellitus with the help of the 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 short-listed. These DEGs were as follows: MCL1 , PTX3 , CYP3A4 , PTGS1 , SSTR2 , SERPINA3 , TDO2 , and GALNT7 . Results: The cluster analysis showed clear differences between the control and treated groups. The functional relationship of the signature genes showed a protein-protein interaction network with the 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 the important markers for diabetes mellitus that have shown interaction with other proteins having a role in the progression of diabetes mellitus that can serve as new targets in the management of DM. Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest (Copyright © 2022 Huang, Nazir, Altaf, Zang, Zafar, Paiva-Santos, Niaz, Imran, Duan, Abbas and Ilyas.)
Databáze:	MEDLINE
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