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Sustainable Development Goals
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IN SILICO TRANSCRIPTIONAL ANALYSIS OF MRNA AND MIRNA REVEALS UNIQUE BIOSIGNATURES THAT CHARACTERIZES DIFFERENT TYPES OF DIABETES
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Abstract
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.
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