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Transcriptome analysis of Newly Diagnosed Type 2 Diabetes Subjects identifies genes to predict Metformin drug Response

ABSTRACT: Transcriptome analysis of Newly Diagnosed Type 2 Diabetes Subjects identifies genes to predict Metformin drug Response

PROVIDER: PRJNA642130 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	SRR12096015.fastq.gz	Fastqsanger.gz
	SRR12096016.fastq.gz	Fastqsanger.gz
	SRR12096017.fastq.gz	Fastqsanger.gz
	SRR12096018.fastq.gz	Fastqsanger.gz
	SRR12096019.fastq.gz	Fastqsanger.gz

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Transcriptome analysis of Newly Diagnosed Type 2 Diabetes Subjects identifies genes to predict Metformin drug Response

Project description:Aims: Metformin is a widely used, primary drug of choice to treat individuals with type 2 diabetes (T2D). Clinically, inter-individual variability of drug response is of significant concern. The targets and precise mechanisms of action for metformin is still under interrogation. In the present study, a whole transcriptome analysis was performed with an intent to identify predictive biomarkers of metformin response in T2D individuals. Methods: Twenty drug naïve individuals with T2D and ten healthy controls were enrolled. T2D individuals were administrated with metformin monotherapy and were defined as responders and non-responders based on the changes in their glycated haemoglobin (HbA1c) over a period of three months. Poly(A) RNA Seq was performed using Ion Torrent Proton platform and differentially expressed genes were identified from the transcriptome profiles. The gene prioritization, enrichment analysis, drug-gene interactions, disease gene association analysis were performed using various tools and databases. A correlation analysis was also performed between gene expression and change in HbA1c levels after 3 months of metformin therapy. Results: The expression analysis highlighted differentially expressed genes in metformin responders, non-responders and healthy individuals. The gene prioritization and enrichment analysis highlighted potential targets for predicting metformin response (n=35) as well as T2D disease (n=14). The drug-gene interactions did not show any direct association with diabetes drugs. However, the expression of GDF15, TWISTNB and RPL36A genes showed maximum correlation with change in HbA1c levels after 3 months of metformin therapy. The disease gene association analysis highlighted rs113805659 in MAGI2 gene to be linked with T2D in African Americans. Conclusion: The results of the present study provide evidence for the perturbed transcriptome and pathways associated with metformin drug response in T2D individuals.

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