Diabetologia

, Volume 45, Issue 11, pp 1584–1593

Microarray profiling of skeletal muscle tissues from equally obese, non-diabetic insulin-sensitive and insulin-resistant Pima Indians

Authors

  •  X. Yang
    • Lundberg Laboratory for Diabetes Research, Sahlgrenska University Hospital, Göteborg, Sweden
  •  R. Pratley
    • Department of Cardiovascular, Metabolic and Endocrine Clinical Research, Novartis Pharmaceutical Corp., East Hanover, New Jersey, USA
  •  S. Tokraks
    • Clinical Diabetes and Nutrition Section, Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Phoenix, Arizona, USA
  •  C. Bogardus
    • Clinical Diabetes and Nutrition Section, Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Phoenix, Arizona, USA
  •  P. Permana
    • National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, 4212 N. 16th Street, Phoenix, AZ 85016, USA
Article

DOI: 10.1007/s00125-002-0905-7

Cite this article as:
Yang, X., Pratley, R., Tokraks, S. et al. Diabetologia (2002) 45: 1584. doi:10.1007/s00125-002-0905-7

Abstract

Aims/hypothesis. We carried out global transcript profiling to identify differentially expressed skeletal muscle genes in insulin resistance, a major risk factor for Type II (non-insulin-dependent) diabetes mellitus. This approach also complemented the ongoing genomic linkage analyses to identify genes linked to insulin resistance and diabetes in Pima Indians.

Methods. We compared gene expression profiles of skeletal muscle tissues from 18 insulin-sensitive versus 17 insulin-resistant equally obese, non-diabetic Pima Indians using oligonucleotide arrays consisting of about 40,600 transcripts of known genes and expressed sequence tags, and analysed the results with the Wilcoxon rank sum test. We verified the mRNA expression of ten differentially (best-ranked) and ten similarly (worst-ranked) genes using quantitative Real Time PCR.

Results. There were 185 differentially expressed transcripts by the rank sum test. The differential expressions of two out of the ten best-ranked genes were confirmed and the similar expressions of all ten worst-ranked genes were reproduced.

Conclusion/interpretation. Of the 185 differentially expressed transcripts, 20 per cent were true positives and some could generate new hypotheses about the aetiology or pathophysiology of insulin resistance. Furthermore, differentially expressed genes in chromosomal regions with linkage to diabetes and insulin resistance serve as new diabetes susceptibility genes.

Genes oligonucleotide array RT-PCR insulin resistance diabetes
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Copyright information

© Springer-Verlag 2002