Integrative mRNA-microRNA analyses reveal novel interactions related to insulin sensitivity in human adipose tissue

Tyler J. Kirby, R. Grace Walton, Brian Finlin, Beibei Zhu, Resat Unal, Neda Rasouli, Charlotte A. Peterson, Philip A. Kern

Research output: Contribution to journalArticlepeer-review

16 Scopus citations


Adipose tissue has profound effects on whole-body insulin sensitivity. However, the underlying biological processes are quite complex and likely multifactorial. For instance, the adipose transcriptome is post- transcriptionally modulated by microRNAs, but the relationship between microRNAs and insulin sensitivity in humans remains to be determined. To this end, we utilized an integrative mRNA-microRNA microarray approach to identify putative molecular interactions that regulate the transcriptome in subcutaneous adipose tissue of insulin- sensitive (IS) and insulin-resistant (IR) individuals. Using the NanoString nCounter Human v1 microRNA Expression Assay, we show that 17 microRNAs are differentially expressed in IR vs. IS. Of these, 16 microRNAs (94%) are downregulated in IR vs. IS, including miR-26b, miR-30b, and miR-145. Using Agilent Human Whole Genome arrays, we identified genes that were predicted targets of miR-26b, miR-30b, and miR-145 and were upregulated in IR subjects. This analysis produced ADAM22, MYO5A, LOX, and GM2A as predicted gene targets of these microRNAs. We then validated that miR-145 and miR-30b regulate these mRNAs in differentiated human adipose stem cells. We suggest that use of bioinformatic integration of mRNA and microRNA arrays yields verifiable mRNA-microRNA pairs that are associated with insulin resistance and can be validated in vitro.

Original languageEnglish
Pages (from-to)145-153
Number of pages9
JournalPhysiological Genomics
Issue number2
StatePublished - Feb 1 2016

Bibliographical note

Publisher Copyright:
© 2016 the American Physiological Society.


  • Adipose
  • Insulin sensitivity
  • MicroRNA
  • Microarray

ASJC Scopus subject areas

  • Physiology
  • Genetics


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