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Combining Bioinformatics Techniques to Study Diabetes Biomarkers and Related Molecular Mechanisms

OBJECTIVE: To explore the mechanism of plasma circulating miRNA-126 and miRNA-28-3p in diabetes mellitus (DM) patients, and to identify the related bioinformatics analysis. METHODS: Randomly selected 120 DM patients as the observation group and 120 non- DM patients as the control group. The plasma c...

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Autores principales: Nie, Han, Zhang, Kaihua, Xu, Jiasheng, Liao, Kaili, Zhou, Weimin, Fu, Zhonghua
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7204005/
https://www.ncbi.nlm.nih.gov/pubmed/32425976
http://dx.doi.org/10.3389/fgene.2020.00367
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author Nie, Han
Zhang, Kaihua
Xu, Jiasheng
Liao, Kaili
Zhou, Weimin
Fu, Zhonghua
author_facet Nie, Han
Zhang, Kaihua
Xu, Jiasheng
Liao, Kaili
Zhou, Weimin
Fu, Zhonghua
author_sort Nie, Han
collection PubMed
description OBJECTIVE: To explore the mechanism of plasma circulating miRNA-126 and miRNA-28-3p in diabetes mellitus (DM) patients, and to identify the related bioinformatics analysis. METHODS: Randomly selected 120 DM patients as the observation group and 120 non- DM patients as the control group. The plasma circulating miRNA-126 and miRNA-28-3p were analyzed by qRT-PCR, and their target genes, biological information, related lncRNA and circRNA were predicted. RESULTS: The circulating miRNA-126 (0.1162 ± 0.0236 vs. 0.0018 ± 0.0862) and miRNA-28-3p (0.1378 ± 0.0268 vs. 0.0006 ± 0.0167) levels in the observation group were significantly higher than those in the control group, and differences were statistically significant (P < 0.01). The Pearson correlation coefficient of miRNA-126 and miRNA- 28-3p was 0.4337 (P < 0.01). ROC curve analysis of miRNA-126 and miRNA-28-3p showed that the differences of the area under curve were statistically significant between the two groups (P < 0.01). Bioinformatics prediction showed that miRNA-126 and miRNA-28-3p may be involved in regulation of the insulin signaling pathway, insulin receptor signaling pathway, insulin/insulin growth factor signaling pathway, mitogen-activated protein kinase (MAPK) signaling pathway and angiogenesis. Moreover, it may be associated with a variety of lncRNA and cir-cRNA. CONCLUSION: Circulating miRNA-126 and miRNA-28-3p can be a potential biomarker of DM and it may play an important role in the DM by regulating insulin or insulin growth factor related signaling pathways.
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spelling pubmed-72040052020-05-18 Combining Bioinformatics Techniques to Study Diabetes Biomarkers and Related Molecular Mechanisms Nie, Han Zhang, Kaihua Xu, Jiasheng Liao, Kaili Zhou, Weimin Fu, Zhonghua Front Genet Genetics OBJECTIVE: To explore the mechanism of plasma circulating miRNA-126 and miRNA-28-3p in diabetes mellitus (DM) patients, and to identify the related bioinformatics analysis. METHODS: Randomly selected 120 DM patients as the observation group and 120 non- DM patients as the control group. The plasma circulating miRNA-126 and miRNA-28-3p were analyzed by qRT-PCR, and their target genes, biological information, related lncRNA and circRNA were predicted. RESULTS: The circulating miRNA-126 (0.1162 ± 0.0236 vs. 0.0018 ± 0.0862) and miRNA-28-3p (0.1378 ± 0.0268 vs. 0.0006 ± 0.0167) levels in the observation group were significantly higher than those in the control group, and differences were statistically significant (P < 0.01). The Pearson correlation coefficient of miRNA-126 and miRNA- 28-3p was 0.4337 (P < 0.01). ROC curve analysis of miRNA-126 and miRNA-28-3p showed that the differences of the area under curve were statistically significant between the two groups (P < 0.01). Bioinformatics prediction showed that miRNA-126 and miRNA-28-3p may be involved in regulation of the insulin signaling pathway, insulin receptor signaling pathway, insulin/insulin growth factor signaling pathway, mitogen-activated protein kinase (MAPK) signaling pathway and angiogenesis. Moreover, it may be associated with a variety of lncRNA and cir-cRNA. CONCLUSION: Circulating miRNA-126 and miRNA-28-3p can be a potential biomarker of DM and it may play an important role in the DM by regulating insulin or insulin growth factor related signaling pathways. Frontiers Media S.A. 2020-04-30 /pmc/articles/PMC7204005/ /pubmed/32425976 http://dx.doi.org/10.3389/fgene.2020.00367 Text en Copyright © 2020 Nie, Zhang, Xu, Liao, Zhou and Fu. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Genetics
Nie, Han
Zhang, Kaihua
Xu, Jiasheng
Liao, Kaili
Zhou, Weimin
Fu, Zhonghua
Combining Bioinformatics Techniques to Study Diabetes Biomarkers and Related Molecular Mechanisms
title Combining Bioinformatics Techniques to Study Diabetes Biomarkers and Related Molecular Mechanisms
title_full Combining Bioinformatics Techniques to Study Diabetes Biomarkers and Related Molecular Mechanisms
title_fullStr Combining Bioinformatics Techniques to Study Diabetes Biomarkers and Related Molecular Mechanisms
title_full_unstemmed Combining Bioinformatics Techniques to Study Diabetes Biomarkers and Related Molecular Mechanisms
title_short Combining Bioinformatics Techniques to Study Diabetes Biomarkers and Related Molecular Mechanisms
title_sort combining bioinformatics techniques to study diabetes biomarkers and related molecular mechanisms
topic Genetics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7204005/
https://www.ncbi.nlm.nih.gov/pubmed/32425976
http://dx.doi.org/10.3389/fgene.2020.00367
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