Identifying common and specific microRNAs expressed in peripheral blood mononuclear cell of type 1, type 2, and gestational diabetes mellitus patients

BMC Research Notes

Eduardo A Donadi²  Geraldo A Passos²  Elza T Sakamoto-Hojo⁵  Denis Puthier³  Milton C Foss¹  Maria C Foss-Freitas¹  Thais Arns²  Diane M Rassi⁴  Danilo J Xavier²  Adriane F Evangelista²  Cristhianna VA Collares² 

[1] Department of Medicine, Division of Endocrinology, Faculty of Medicine of Ribeirao Preto, University of São Paulo, 14048-900 Ribeirao Preto, SP, Brazil;Department of Genetics, Molecular Immunogenetics Group, Faculty of Medicine of Ribeirao Preto, University of São Paulo, 14040-900 Ribeirao Preto, SP, Brazil;Aix-Marseille University, Marseille, France;Department of Medicine, Division of Clinical Immunology, Faculty of Medicine of Ribeirao Preto, University of São Paulo, 14048-900 Ribeirao Preto, SP, Brazil;Faculty of Philosophy Sciences and Letters of Ribeirao Preto, University of Sao Paulo, Ribeirao Preto, SP, Brazil

关键词: Microarray;    mRNA;    microRNA;    Gestational diabetes mellitus;    Type 2 diabetes mellitus;    Type 1 diabetes mellitus;   

Others  :  1140640
DOI  :  10.1186/1756-0500-6-491

 received in 2013-06-23, accepted in 2013-11-15,  发布年份 2013

【 摘 要 】

Background

Regardless the regulatory function of microRNAs (miRNA), their differential expression pattern has been used to define miRNA signatures and to disclose disease biomarkers. To address the question of whether patients presenting the different types of diabetes mellitus could be distinguished on the basis of their miRNA and mRNA expression profiling, we obtained peripheral blood mononuclear cell (PBMC) RNAs from 7 type 1 (T1D), 7 type 2 (T2D), and 6 gestational diabetes (GDM) patients, which were hybridized to Agilent miRNA and mRNA microarrays. Data quantification and quality control were obtained using the Feature Extraction software, and data distribution was normalized using quantile function implemented in the Aroma light package. Differentially expressed miRNAs/mRNAs were identified using Rank products, comparing T1DxGDM, T2DxGDM and T1DxT2D. Hierarchical clustering was performed using the average linkage criterion with Pearson uncentered distance as metrics.

Results

The use of the same microarrays platform permitted the identification of sets of shared or specific miRNAs/mRNA interaction for each type of diabetes. Nine miRNAs (hsa-miR-126, hsa-miR-1307, hsa-miR-142-3p, hsa-miR-142-5p, hsa-miR-144, hsa-miR-199a-5p, hsa-miR-27a, hsa-miR-29b, and hsa-miR-342-3p) were shared among T1D, T2D and GDM, and additional specific miRNAs were identified for T1D (20 miRNAs), T2D (14) and GDM (19) patients. ROC curves allowed the identification of specific and relevant (greater AUC values) miRNAs for each type of diabetes, including: i) hsa-miR-1274a, hsa-miR-1274b and hsa-let-7f for T1D; ii) hsa-miR-222, hsa-miR-30e and hsa-miR-140-3p for T2D, and iii) hsa-miR-181a and hsa-miR-1268 for GDM. Many of these miRNAs targeted mRNAs associated with diabetes pathogenesis.

Conclusions

These results indicate that PBMC can be used as reporter cells to characterize the miRNA expression profiling disclosed by the different diabetes mellitus manifestations. Shared miRNAs may characterize diabetes as a metabolic and inflammatory disorder, whereas specific miRNAs may represent biological markers for each type of diabetes, deserving further attention.

【 授权许可】

   
2013 Collares et al.; licensee BioMed Central Ltd.

【 图 表 】

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