ArticleJournal of endocrinological investigation2023
Implications of genetic variations, differential gene expression, and allele-specific expression on metformin response in drug-naïve type 2 diabetes.
Article in Journal of endocrinological investigation, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 12 citations in OpenAlex.
- Transporter gene variants influencing metformin pharmacokinetics and pharmacodynamics common in European populations: a pharmacogenetic narrative review.Frontiers in pharmacology · 2026Review
- Inter-Individual Heterogeneity in Aerobic Training Adaptations: Systematic Review of the Evidence Base for Personalized Exercise Prescription.Life (Basel, Switzerland) · 2025Review
- Article
- Glycaemic responses to metformin monotherapy by SNP clusters in patients with type 2 diabetes.Diabetes, obesity & metabolism · 2025Article
- Patient-specific effects of metformin on the hepatic metabolism in adolescents with metabolic dysfunction-associated steatotic liver disease (MASLD).Journal of molecular medicine (Berlin, Germany) · 2025Article
- Translational disease modeling of peripheral blood identifies type 2 diabetes biomarkers predictive of Alzheimer's disease.NPJ systems biology and applications · 2025Article
- Multi-Omics Analysis Revealed the rSNPs Potentially Involved in T2DM Pathogenic Mechanism and Metformin Response.International journal of molecular sciences · 2024Article
- Article
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Authors and funding
8 authors at 1 institution in 1 country.
Funding
Abstract
purposeMetformin is widely used to treat type 2 diabetes mellitus (T2DM) individuals. Clinically, inter-individual variability of metformin response is of significant concern and is under interrogation. In this study, a targeted exome and whole transcriptome analysis were performed to identify predictive biomarkers of metformin response in drug-naïve T2DM individuals.
methodsThe study followed a prospective study design. Drug-naïve T2DM individuals (n = 192) and controls (n = 223) were enrolled. T2DM individuals were administered with metformin monotherapy and defined as responders and non-responders based on their glycated haemoglobin change over three months. 146 T2DM individuals were used for the final analysis and remaining samples were lost during the follow-up. Target exome sequencing and RNA-seq was performed to analyze genetic and transcriptome profile. The selected SNPs were validated by genotyping and allele specific gene expression using the TaqMan assay. The gene prioritization, enrichment analysis, drug-gene interactions, disease-gene association, and correlation analysis were performed using various tools and databases.
resultsrs1050152 and rs272893 in SLC22A4 were associated with improved response to metformin. The copy number loss was observed in PPARGC1A in the non-responders. The expression analysis highlighted potential differentially expressed targets for predicting metformin response (n = 35) and T2DM (n = 14). The expression of GDF15, TWISTNB, and RPL36A genes showed a maximum correlation with the change in HbA1c levels. The disease-gene association analysis highlighted MAGI2 rs113805659 to be linked with T2DM.
conclusionThe results provide evidence for the genetic variations, perturbed transcriptome, allele-specific gene expression, and pathways associated with metformin drug response in T2DM.
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