This is a preprint, a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Research article
Xueyuan Liu
Shanghai Tenth People's Hospital, Tongji University School of Medicine
Corresponding Author
ORCiD: https://orcid.org/0000-0002-3869-8809
License:
This work is licensed under a CC BY 4.0 License. Read Full License
Background: Diabetes is a metabolic disease that has been widely demonstrated to be correlated with many microvascular and macrovascular diseases that seriously damage the patient’s life quality. This study intended to investigate the underlying molecular mechanisms of endothelial dysfunction under hyperglycemia.
Methods: The gene expression profile of GSE49524 was downloaded and differentially expressed genes (DEGs) in hyperglycemia human umbilical cord endothelial cells (HUVECs) samples compared with normoglycemia HUVECs samples were identified by R software. Afterward, we analyzed the data by applying a combination of the bioinformatics method and used the microRNAs (miRNAs) databases to predict microRNAs that target key genes. The expression of the top 10 differentially expressed genes was validated through quantitative real-time PCR (qRT-PCR).
Results: A total of 65 genes were distinguished as DEGs. The dominant GO (gene ontology) terms and KEGG (Kyoto Encyclopedia of Genes and Genomes) pathways which were significantly overrepresented in the hyperglycemia HUVECs were identified. The results of the protein-protein interaction networks demonstrated that fibronectin 1 (FN1) is of the highest degree. In addition, several predicted miRNAs that target FN1 were obtained too. The further verification of the top 10 DEGs through qRT-PCR illustrated that nine of the up-regulated DEGs were up-regulated significantly in the hyperglycemia group when compared to the control group.
Conclusions:
This exploratory study may help to prompt an understanding of the underlying molecular mechanisms of the effect of hyperglycemia on the behavior of HUVECs and contribute to the production of effective therapeutic interventions.
Keywords
Human umbilical vein endothelial cells, MicroRNA, Diabetes mellitus, Hyperglycemia, Fibronectin
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This is a preprint, a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Research article
Xueyuan Liu
Shanghai Tenth People's Hospital, Tongji University School of Medicine
Corresponding Author
ORCiD: https://orcid.org/0000-0002-3869-8809
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
History
CURRENT STATUS: Posted
Version 1
Posted 18 May, 2020
No community comments so far
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
Subject Areas
Epigenetics & Genomics
License:
This work is licensed under a CC BY 4.0 License. Read Full License
Background: Diabetes is a metabolic disease that has been widely demonstrated to be correlated with many microvascular and macrovascular diseases that seriously damage the patient’s life quality. This study intended to investigate the underlying molecular mechanisms of endothelial dysfunction under hyperglycemia.
Methods: The gene expression profile of GSE49524 was downloaded and differentially expressed genes (DEGs) in hyperglycemia human umbilical cord endothelial cells (HUVECs) samples compared with normoglycemia HUVECs samples were identified by R software. Afterward, we analyzed the data by applying a combination of the bioinformatics method and used the microRNAs (miRNAs) databases to predict microRNAs that target key genes. The expression of the top 10 differentially expressed genes was validated through quantitative real-time PCR (qRT-PCR).
Results: A total of 65 genes were distinguished as DEGs. The dominant GO (gene ontology) terms and KEGG (Kyoto Encyclopedia of Genes and Genomes) pathways which were significantly overrepresented in the hyperglycemia HUVECs were identified. The results of the protein-protein interaction networks demonstrated that fibronectin 1 (FN1) is of the highest degree. In addition, several predicted miRNAs that target FN1 were obtained too. The further verification of the top 10 DEGs through qRT-PCR illustrated that nine of the up-regulated DEGs were up-regulated significantly in the hyperglycemia group when compared to the control group.
Conclusions:
This exploratory study may help to prompt an understanding of the underlying molecular mechanisms of the effect of hyperglycemia on the behavior of HUVECs and contribute to the production of effective therapeutic interventions.
Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
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