Human Genetics

, Volume 113, Issue 4, pp 353–358 | Cite as

Evaluation of the microsomal glutathione S-transferase 3 (MGST3) locus on 1q23 as a Type 2 diabetes susceptibility gene in Pima Indians

  • Farook Thameem
  • Xiaolin Yang
  • Paska A. Permana
  • Johanna K. Wolford
  • Clifton Bogardus
  • Michal Prochazka
Original Investigation


Elevation of plasma glucose concentration may induce generation of oxygen-free radicals, which can play an important role in the progression of diabetes and/or development of its complications. Various glutathione transferases utilize the availability of reduced glutathione for the cellular defense against oxygen-free radicals. One such enzyme is microsomal glutathione S-transferase 3 encoded by MGST3, which maps to chromosome 1q23, a region linked to Type 2 diabetes mellitus (T2DM) in Pima Indians, Caucasian, and Chinese populations. We investigated the MGST3 gene as a potential susceptibility gene for T2DM by screening this locus for single nucleotide polymorphisms (SNPs) in diabetic and non-diabetic Pima Indians. We also measured the skeletal muscle MGST3 mRNA level by Real-Time (RT) PCR and its relationship with insulin action in non-diabetic individuals. We identified 25 diallelic variants, most of which, based on their genotypic concordance, could be divided into three distinct linkage disequilibrium (LD) groups. We genotyped unique representative SNPs in selected diabetic and non-diabetic Pima Indians and found no evidence for association with T2DM. Furthermore, inter-individual variation of skeletal muscle MGST3 mRNA was not correlated with differences in insulin action in non-diabetic subjects. We conclude that alterations of MGST3 are unlikely to contribute to T2DM or differences in insulin sensitivity in the Pima Indians.


Skeletal Muscle Biopsy Translation Stop Codon Gila River Indian Community Microsomal Glutathione Representative SNPs 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



We thank the members of the Gila River Indian Community for their continued participation in the ongoing longitudinal studies of Type 2 diabetes. We also thank Dr. Richard Pratley, Mike Millner and Carol Massengil for clinical studies and patient care, and Vicky Ossowski and Shawnell Damon for variant detection and validation.


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Copyright information

© Springer-Verlag 2003

Authors and Affiliations

  • Farook Thameem
    • 1
  • Xiaolin Yang
    • 1
  • Paska A. Permana
    • 1
  • Johanna K. Wolford
    • 1
  • Clifton Bogardus
    • 1
  • Michal Prochazka
    • 1
  1. 1.Clinical Diabetes and Nutrition Section, Phoenix Epidemiology and Clinical Research BranchNational Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of HealthPhoenix USA

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