Diabetes (DM) has a significant impact on public health. We performed an in silico study of paired datasets of messenger RNA (mRNA) micro-RNA (miRNA) transcripts to delineate potential biosignatures that could distinguish prediabetes (pre-DM), type-1DM (T1DM) and type-2DM (T2DM). Two publicly available datasets containing expression values of mRNA and miRNA obtained from individuals diagnosed with pre-DM, T1DM or T2DM, and normoglycemic controls (NC), were analyzed using systems biology approaches to define combined signatures to distinguish different clinical groups. The mRNA profile of both pre-DM and T2DM was hallmarked by several differentially expressed genes (DEGs) compared to NC. Nevertheless, T1DM was characterized by an overall low number of DEGs. The miRNA signature profiles were composed of a substantially lower number of differentially expressed targets. Gene enrichment analysis revealed several inflammatory pathways in T2DM and fewer in pre-DM, but with shared findings such as Tuberculosis. The integration of mRNA and miRNA datasets improved the identification and discriminated the group composed by pre-DM and T2DM patients from that constituted by normoglycemic and T1DM individuals. The integrated transcriptomic analysis of mRNA and miRNA expression revealed a unique biosignature able to characterize different types of DM.

糖尿病（DM）对公共健康有重大影响。我们进行了计算机模拟研究信使RNA（mRNA）微小RNA（miRNA）转录本的配对数据集，以描绘出可能区分糖尿病前（DM），1DM（T1DM）和2DM（T2DM）的潜在生物特征。使用系统生物学方法分析了两个可公开获得的数据集，其中包含从诊断为DM前，T1DM或T2DM以及正常血糖控制（NC）的个体获得的mRNA和miRNA的表达值，以定义组合特征来区分不同的临床组。与NC相比，pre-DM和T2DM的mRNA谱均由几个差异表达基因（DEG）标记。尽管如此，T1DM的特点是DEG的总数很少。miRNA标记图谱由数量较少的差异表达靶标组成。基因富集分析揭示了T2DM中的几种炎症途径，而在DM前中则较少，但存在结核病等共同发现。mRNA和miRNA数据集的整合提高了识别能力，并将前DM和T2DM患者组成的组与正常血糖和T1DM患者组成的组区别开来。对mRNA和miRNA表达的综合转录组学分析揭示了能够表征不同类型DM的独特生物印记。