SynthesisFrontiers in endocrinology2022
A meta-analysis of genome-wide gene expression differences identifies promising targets for type 2 diabetes mellitus.
Synthesis in Frontiers in endocrinology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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6 citing papers in PubMed, 12 citations in OpenAlex.
- Microbial and proteomic signatures of type 2 diabetes in an Arab population.Journal of translational medicine · 2024Article
- Analysis, validation, and discussion of key genes in placenta of patients with gestational diabetes mellitus.Experimental biology and medicine (Maywood, N.J.) · 2023Article
- Transcription factor E4F1 as a regulator of cell life and disease progression.Science advances · 2023Review
- Identification and validation of differentially expressed genes for targeted therapy in NSCLC using integrated bioinformatics analysis.Frontiers in oncology · 2023Article
- Investigation of anti-diabetic potential and molecular simulation studies of dihydropyrimidinone derivatives.Frontiers in endocrinology · 2022Article
- Virtual screening and drug repositioning of FDA-approved drugs from the ZINC database to identify the potential hTERT inhibitors.Frontiers in pharmacology · 2022Article
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Authors and funding
11 authors at 6 institutions in 3 countries.
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Abstract
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: 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.
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