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Circulating miR-3659 may be a potential biomarker of dyslipidemia in patients with obesity.


ABSTRACT:

Background

The present study attempted to identify potential key genes and miRNAs of dyslipidemia in obese, and to investigate the possible mechanisms associated with them.

Methods

The microarray data of GSE66676 were downloaded, including 67 obese samples from the Gene Expression Omnibus (GEO) database. The weighted gene co-expression network (WGCNA) analysis was performed using WGCNA package and grey60 module was considered as the highest correlation. Gene Ontology annotation and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses for this module were performed by clusterProfiler and DOSE package. A protein-protein interaction (PPI) network was established using Cytoscape software, and significant modules were analyzed using molecular complex detection.

Results

Collagen type I alpha 1 chain gene (COL1A1) had the best significant meaning. After bioinformatic analysis, we identified four miRNAs (hsa-miR-3659, hsa-miR-4658, hsa-miR151a-5p and hsa-miR-151b) which can bind SNPs in 3'UTR in COL1A1. After validation with RT-qPCR, only two miRNAs (hsa-miR-3659 and hsa-miR151a-5p) had statistical significance.

Conclusions

The area of 0.806 for miR-3659 and 0.769 for miR-151a-5p under the ROC curve (AUC) may have good diagnostic value for dyslipidemia. Circulating miR-3659 may be a potential biomarker of dyslipidemia in patients with obesity.

SUBMITTER: Miao L 

PROVIDER: S-EPMC6332685 | biostudies-literature | 2019 Jan

REPOSITORIES: biostudies-literature

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Publications

Circulating miR-3659 may be a potential biomarker of dyslipidemia in patients with obesity.

Miao Liu L   Yin Rui-Xing RX   Pan Shang-Ling SL   Yang Shuo S   Yang De-Zhai DZ   Lin Wei-Xiong WX  

Journal of translational medicine 20190114 1


<h4>Background</h4>The present study attempted to identify potential key genes and miRNAs of dyslipidemia in obese, and to investigate the possible mechanisms associated with them.<h4>Methods</h4>The microarray data of GSE66676 were downloaded, including 67 obese samples from the Gene Expression Omnibus (GEO) database. The weighted gene co-expression network (WGCNA) analysis was performed using WGCNA package and grey60 module was considered as the highest correlation. Gene Ontology annotation an  ...[more]

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