Identification of Key LncRNAs and Pathways in Prediabetes and Type 2 Diabetes Mellitus for Hypertriglyceridemia Patients Based on Weighted Gene Co-Expression Network Analysis

Yan, Shoumeng; Sun, Mengzi; Gao, Limin; Yao, Nan; Feng, Tianyu; Yang, Yilin; Li, Xiaotong; Hu, Wen‐Yu; Cui, Weiwei; Li, Bo

doi:10.3389/fendo.2021.800123

Cited by 13 publications

(12 citation statements)

References 49 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…C. Gar et al [ 19 ] demonstrated that elevated branched-chain amino acids and decreased glycine are currently the most stable amino acid markers for prediabetes, insulin resistance, and future type 2 diabetes. In addition, some long non-coding RNAs (lncRNAs) [ 20 , 21 ] and microRNAs (miRNAs or miRs) [ 22 ] may also be potential diagnostic biomarkers for prediabetes. Although these results provide the basis for novel pathophysiological hypotheses and treatments for prediabetes, no biomarkers have yet been incorporated into routine screening.…”

Section: Introductionmentioning

confidence: 99%

Identification of FGF13 as a Potential Biomarker and Target for Diagnosis of Impaired Glucose Tolerance

Chen

Gao

et al. 2023

IJMS

View full text Add to dashboard Cite

Early identification of pre-diabetes provides an opportunity for intervention and treatment to delay its progression to type 2 diabetes mellitus (T2DM). We aimed to identify the biomarkers of impaired glucose tolerance (IGT) through bioinformatics analysis. The GSE76896 dataset, including non-diabetic (ND), IGT, and T2DM clinical samples, was deeply analyzed to identify 309 Co-DEGs for IGT and T2DM. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses indicated that inflammatory responses and the PI3K-AKT signaling pathway are important patho-physiological features of IGT and T2DM. Protein–protein interaction (PPI) network analysis and cytoHubba technolgy identified seven hub genes: namely, CCL2, CXCL1, CXCL8, EDN1, FGF13, MMP1, and NGF. The expression and ROC curves of these hub genes were validated using the GSE38642 dataset. Through an immunofluorescence assay, we found that the expression of FGF13 in islets of mice in the HFD and T2DM groups was significantly lower than in the control group. Similarly, the level of FGF13 in the sera of IGT and T2DM patients was lower than that in the healthy group. Together, these results suggest that FGF13 can be treated as a novel biomarker of IGT, which may provide new targets for the diagnosis and treatment of pre-diabetes and T2DM.

show abstract

Section: Introductionmentioning

confidence: 99%

Identification of FGF13 as a Potential Biomarker and Target for Diagnosis of Impaired Glucose Tolerance

Chen

Gao

et al. 2023

IJMS

View full text Add to dashboard Cite

show abstract

“…Compared to conventional differential expression analysis, it is a more effective technique for detecting gene expression with low variation and abundance, as well as being less prone to information loss [19]. Quite a few researches have demonstrated the value of WGCNA in systematically identifying critical genes and relevant mechanisms about stroke or diabetes [19][20][21][22].…”

Section: Discussionmentioning

confidence: 99%

Identification of potential biological processes and key genes in diabetes-related stroke through Weighted gene co-expression network analysis

Bai

Huang

et al. 2023

Preprint

View full text Add to dashboard Cite

Background Diabetes mellitus (DM) is an established risk factor for acute ischemic stroke (AIS). Although there are reports on the correlation of diabetes and stroke, data on its pathogenesis is limited. This study aimed to explore the underlying biological mechanisms and promising intervention targets of diabetes-related stroke.Methods Diabetes-related datasets (GSE38642 and GSE44035) and stroke-related datasets (GSE16561 and GSE22255) were obtained from the Gene Expression omnibus (GEO) database. The key modules for stroke and diabetes were identified by weight gene co-expression network analysis (WGCNA). Gene Ontology (GO) and Kyoto Encyclopedia of Genes Genomes (KEGG) analyses were employed in the key module. Genes in stroke- and diabetes-related key modules were intersected to obtain common genes for DM-related stroke. In order to discover the key genes in DM-related stroke, the Cytoscape and protein-protein interaction (PPI) network were constructed. The key genes were functionally annotated in the Reactome database.Results By intersecting the diabetes- and stroke-related crucial modules, 24 common genes for DM-related stroke were identified. Metascape showed that neutrophil extracellular trap formation was primarily enriched. The hub gene was granulin precursor (GRN), which had the highest connectivity among the common genes. In addition, functional enrichment analysis indicated that GRN was involved in neutrophil degranulation, thus regulating neutrophil extracellular trap formation.Conclusions This study firstly revealed that neutrophil extracellular trap formation may represent the common biological processes of diabetes and stroke, and GRN may be potential intervention targets for DM-related stroke.

show abstract

“…LncRNA RPL13p5 is highly expressed in GDM patients, forming a co-expression chain with TSC2 gene through PI3K-Akt signaling pathway to promote IR ( 113 ). A recent study showed that lncRNAs ENST00000503273, ENST00000462720, and ENST00000480633 are expressed at abnormal levels in hypertriglyceridemic patients with different blood glucose levels and are potential biomarkers of T2DM ( 114 ). EPB41L4A-AS1 induced by persistent high glucose inhibits glucose uptake through crotonylation and acetylation of GCN5-mediated proteins, thereby exacerbating the progression of T2DM ( 115 ).…”

Section: Ncrnas In Diabetesmentioning

confidence: 99%

Non-coding RNAs in diabetes mellitus and diabetic cardiovascular disease

Wang

Jiang

et al. 2022

Front. Endocrinol.

View full text Add to dashboard Cite

More than 10% of the world’s population already suffers from varying degrees of diabetes mellitus (DM), but there is still no cure for the disease. Cardiovascular disease (CVD) is one of the most common and dangerous of the many health complications that can be brought on by DM, and has become the leading cause of death in people with diabetes. While research on DM and associated CVD is advancing, the specific mechanisms of their development are still unclear. Given the threat of DM and CVD to humans, the search for new predictive markers and therapeutic ideas is imminent. Non-coding RNAs (ncRNAs) have been a popular subject of research in recent years. Although they do not encode proteins, they play an important role in living organisms, and they can cause disease when their expression is abnormal. Numerous studies have observed aberrant ncRNAs in patients with DM complications, suggesting that they may play an important role in the development of DM and CVD and could potentially act as biomarkers for diagnosis. There is additional evidence that treatment with existing drugs for DM, such as metformin, alters ncRNA expression levels, suggesting that regulation of ncRNA expression may be a key mechanism in future DM treatment. In this review, we assess the role of ncRNAs in the development of DM and CVD, as well as the evidence for ncRNAs as potential therapeutic targets, and make use of bioinformatics to analyze differential ncRNAs with potential functions in DM.

show abstract

Identification of Key LncRNAs and Pathways in Prediabetes and Type 2 Diabetes Mellitus for Hypertriglyceridemia Patients Based on Weighted Gene Co-Expression Network Analysis

Cited by 13 publications

References 49 publications

Identification of FGF13 as a Potential Biomarker and Target for Diagnosis of Impaired Glucose Tolerance

Identification of FGF13 as a Potential Biomarker and Target for Diagnosis of Impaired Glucose Tolerance

Identification of potential biological processes and key genes in diabetes-related stroke through Weighted gene co-expression network analysis

Non-coding RNAs in diabetes mellitus and diabetic cardiovascular disease

Contact Info

Product

Resources

About