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Ola Hansson

Ola Hansson

Principal investigator

Ola Hansson

Genomic editing of metformin efficacy-associated genetic variants in SLC47A1 does not alter SLC47A1 expression


  • Sebastian Kalamajski
  • Mi Huang
  • Jonathan Dalla-Riva
  • Maria Keller
  • Adem Y Dawed
  • Ola Hansson
  • Ewan R Pearson
  • Hindrik Mulder
  • Paul W Franks

Summary, in English

Several pharmacogenetics studies have identified an association between a greater metformin-dependent reduction in HbA1c levels and the minor A allele at rs2289669 in intron 10 of SLC47A1, encoding multidrug and toxin extrusion 1 (MATE1), a presumed metformin transporter. It is currently unknown if the rs2289669 locus is a cis-eQTL, which would validate its role as predictor of metformin efficacy. We looked at association between common genetic variants in the SLC47A1 gene region and HbA1c reduction after metformin treatment using locus-wise meta-analysis from the MetGen consortium. CRISPR-Cas9 was applied to perform allele editing of, or genomic deletion around, rs2289669 and of the closely linked rs8065082 in HepG2 cells. The genome-edited cells were evaluated for SLC47A1 expression and splicing. None of the common variants including rs2289669 showed significant association with metformin response. Genomic editing of either rs2289669 or rs8065082 did not alter SLC47A1 expression or splicing. Experimental and in silico analyses show that the rs2289669-containing haploblock does not appear to carry genetic variants that could explain its previously reported association with metformin efficacy.


  • EXODIAB: Excellence of Diabetes Research in Sweden
  • Genetic and Molecular Epidemiology
  • Genomics, Diabetes and Endocrinology
  • Diabetes - Molecular Metabolism
  • EpiHealth: Epidemiology for Health

Publishing year







Human Molecular Genetics





Document type

Journal article


Oxford University Press


  • Endocrinology and Diabetes
  • Medical Genetics
  • Cardiac and Cardiovascular Systems



Research group

  • Genetic and Molecular Epidemiology
  • Genomics, Diabetes and Endocrinology
  • Diabetes - Molecular Metabolism


  • ISSN: 0964-6906