In silico transcriptional analysis of mRNA and miRNA reveals unique biosignatures that characterizes different types of diabetes

dc.creatorCubillos-Angulo, Juan Manuel
dc.creatorVinhaes, Caian L.
dc.creatorFukutani, Eduardo R.
dc.creatorAlbuquerque, Victor V. S.
dc.creatorQueiroz, Artur Trancoso Lopo de
dc.creatorAndrade, Bruno de Bezerril
dc.creatorFukutani, Kiyoshi Ferreira
dc.date2020-11-03T12:43:55Z
dc.date2020-11-03T12:43:55Z
dc.date2020
dc.date.accessioned2023-09-27T00:15:52Z
dc.date.available2023-09-27T00:15:52Z
dc.identifierCUBILLOS-ANGULO, Juan Manuel et al. In silico transcriptional analysis of mRNA and miRNA reveals unique biosignatures that characterizes different types of diabetes. Plos One, p. 1-17, Sept. 2020.
dc.identifier1932-6203
dc.identifierhttps://www.arca.fiocruz.br/handle/icict/44297
dc.identifier10.1371/journal.pone.0239061
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/8899097
dc.descriptionIntramural Program of Fundac¸ão Oswaldo Cruz (FIOCRUZ) and by the Brazilian National Council for Scientific and Technological Development (CNPq). K.F.F. received a fellowship from the Programa Nacional de Po´s-Doutorado, Coordenac¸ão de Aperfeic¸oamento de Pessoal de Nı´vel Superior (CAPES) (Finance Code 001). The work of B.B.A. was supported by grants from the NIH (U01AI115940, R01AI069923-08, R01AI20790- 02). BBA and A.T.L.Q are senior investigators from CNPq. J. M. C-A. was supported by the Organization of American States - Partnerships Program for Education and Training (OAS-PAEC) and Coordenac¸ão de Aperfeic¸oamento de Pessoal de Nı´vel Superior (CAPES) (Finance Code 001). C. L.V. is a research fellow from CNPq.
dc.descriptionDiabetes (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.
dc.formatapplication/pdf
dc.languageeng
dc.publisherPublic Library of Science
dc.rightsopen access
dc.subjectDiabetes
dc.subjectSaúde pública
dc.subjectMicroRNAs
dc.subjectEstado Pré-Diabético
dc.subjectDiabetes
dc.subjectHealth public
dc.subjectMicroRNAs
dc.subjectPrediabetic State
dc.titleIn silico transcriptional analysis of mRNA and miRNA reveals unique biosignatures that characterizes different types of diabetes
dc.typeArticle


Este ítem pertenece a la siguiente institución