ArticleMolecular metabolism2018
A computational biology approach of a genome-wide screen connected miRNAs to obesity and type 2 diabetes.
Article in Molecular metabolism, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.
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33 citing papers in PubMed, 59 citations in OpenAlex.
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- miR-31 ameliorates type 2 diabetic vascular damage through up-regulation of hypoxia-inducible factor-1α/vascular endothelial growth factor-A.Journal of diabetes investigation · 2023Article
- Small RNA Profiling in an HTLV-1-Infected Patient with Acute Adult T-Cell Leukemia-Lymphoma at Diagnosis and after Maintenance Therapy: A Case Study.International journal of molecular sciences · 2023Article
- Brown Adipose Tissue-A Translational Perspective.Endocrine reviews · 2023Review
- Integrated analysis of expression profiles with meat quality traits in cattle.Scientific reports · 2022Article
- Distinct Adipogenic and Fibrogenic Differentiation Capacities of Mesenchymal Stromal Cells from Pancreas and White Adipose Tissue.International journal of molecular sciences · 2022Article
- Article
- Review
- Knockdown of miR-423-5p simultaneously upgrades the eNOS and VEGFa pathways in ADSCs and improves erectile function in diabetic rats.Journal of cellular and molecular medicine · 2021Article
- Enriched Alternative Splicing in Islets of Diabetes-Susceptible Mice.International journal of molecular sciences · 2021Article
- Adipose Tissue-Derived Extracellular Vesicles and the Tumor Microenvironment: Revisiting the Hallmarks of Cancer.Cancers · 2021Review
- MicroRNAs: The Link between the Metabolic Syndrome and Oncogenesis.International journal of molecular sciences · 2021Review
- Experimental validation of a predicted microRNA within humanMolecular biology research communications · 2021Article
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Authors and funding
16 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveObesity and type 2 diabetes (T2D) arise from the interplay between genetic, epigenetic, and environmental factors. The aim of this study was to combine bioinformatics and functional studies to identify miRNAs that contribute to obesity and T2D.
methodsA computational framework (miR-QTL-Scan) was applied by combining QTL, miRNA prediction, and transcriptomics in order to enhance the power for the discovery of miRNAs as regulative elements. Expression of several miRNAs was analyzed in human adipose tissue and blood cells and miR-31 was manipulated in a human fat cell line.
resultsIn 17 partially overlapping QTL for obesity and T2D 170 miRNAs were identified. Four miRNAs (miR-15b, miR-30b, miR-31, miR-744) were recognized in gWAT (gonadal white adipose tissue) and six (miR-491, miR-455, miR-423-5p, miR-132-3p, miR-365-3p, miR-30b) in BAT (brown adipose tissue). To provide direct functional evidence for the achievement of the miR-QTL-Scan, miR-31 located in the obesity QTL Nob6 was experimentally analyzed. Its expression was higher in gWAT of obese and diabetic mice and humans than of lean controls. Accordingly, 10 potential target genes involved in insulin signaling and adipogenesis were suppressed. Manipulation of miR-31 in human SGBS adipocytes affected the expression of GLUT4, PPARγ, IRS1, and ACACA. In human peripheral blood mononuclear cells (PBMC) miR-15b levels were correlated to baseline blood glucose concentrations and might be an indicator for diabetes.
conclusionThus, miR-QTL-Scan allowed the identification of novel miRNAs relevant for obesity and T2D.
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