Clinical significance of long noncoding RNA VIM-AS1 and CTBP1-AS2 expression in type 2 diabetes.


Journal

Journal of cellular biochemistry
ISSN: 1097-4644
Titre abrégé: J Cell Biochem
Pays: United States
ID NLM: 8205768

Informations de publication

Date de publication:
06 2019
Historique:
received: 09 10 2018
accepted: 15 11 2018
pubmed: 7 12 2018
medline: 18 7 2020
entrez: 4 12 2018
Statut: ppublish

Résumé

The risk of type 2 diabetes (T2D) is determined by a combination of genetic and environmental factors. Multiple studies have proposed that long noncoding RNAs (lncRNAs) are crucial molecules in regulating several biological processes and complex diseases. The study was aimed at investigating the association between the expression levels of lncRNA VIM-AS1, lncRNA CTBP1-AS2, and T2D susceptibility. lncRNA VIM-AS1 and lncRNA CTBP1-AS2 in the peripheral blood mononuclear cell (PBMC) of 100 healthy individuals and 100 T2D patients were collected for Quantitative Real-Time RT-PCR analysis. A logistic regression was performed to understand whether the likelihood of T2D can be predicted based on the expression levels of lncRNA VIM-AS1 and lncRNA CTBP1-AS2. Receiver operating characteristic (ROC) analysis was also performed to determine the statistical analysis of VIM-AS1 and CTBP1-AS2 levels in 200 samples. Our results display that decreased levels of VIM-AS1 and CTBP1-AS2 in PBMC were associated with diabetes in Iranian population. The logistic regression revealed that Systolic blood pressure (SBP), low-density lipoprotein cholesterol (LDL-C), Fasting blood glucose (FBG) and CTBP1-AS2 are substantial predictors of T2D. The ROC analysis of CTBP1-AS2 revealed the area under the ROC curve (AUC) of 0.68 with a sensitivity of 58.7% and specificity of 75.3% in distinguishing nondiabetic from diabetic subjects. The ROC analysis of VIM-AS1 determined AUC of 0.63 with a sensitivity of 56.1% and specificity of 68.37% in distinguishing the two diagnostic groups. lncRNA VIM-AS1 and lncRNA CTBP1-AS2 expression levels are associated with T2D susceptibility.

Sections du résumé

BACKGROUND/AIMS
The risk of type 2 diabetes (T2D) is determined by a combination of genetic and environmental factors. Multiple studies have proposed that long noncoding RNAs (lncRNAs) are crucial molecules in regulating several biological processes and complex diseases. The study was aimed at investigating the association between the expression levels of lncRNA VIM-AS1, lncRNA CTBP1-AS2, and T2D susceptibility.
METHODS
lncRNA VIM-AS1 and lncRNA CTBP1-AS2 in the peripheral blood mononuclear cell (PBMC) of 100 healthy individuals and 100 T2D patients were collected for Quantitative Real-Time RT-PCR analysis. A logistic regression was performed to understand whether the likelihood of T2D can be predicted based on the expression levels of lncRNA VIM-AS1 and lncRNA CTBP1-AS2. Receiver operating characteristic (ROC) analysis was also performed to determine the statistical analysis of VIM-AS1 and CTBP1-AS2 levels in 200 samples.
RESULTS
Our results display that decreased levels of VIM-AS1 and CTBP1-AS2 in PBMC were associated with diabetes in Iranian population. The logistic regression revealed that Systolic blood pressure (SBP), low-density lipoprotein cholesterol (LDL-C), Fasting blood glucose (FBG) and CTBP1-AS2 are substantial predictors of T2D. The ROC analysis of CTBP1-AS2 revealed the area under the ROC curve (AUC) of 0.68 with a sensitivity of 58.7% and specificity of 75.3% in distinguishing nondiabetic from diabetic subjects. The ROC analysis of VIM-AS1 determined AUC of 0.63 with a sensitivity of 56.1% and specificity of 68.37% in distinguishing the two diagnostic groups.
CONCLUSION
lncRNA VIM-AS1 and lncRNA CTBP1-AS2 expression levels are associated with T2D susceptibility.

Identifiants

pubmed: 30506719
doi: 10.1002/jcb.28206
doi:

Substances chimiques

Biomarkers 0
Cholesterol, LDL 0
RNA, Long Noncoding 0
Glucose IY9XDZ35W2

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

9315-9323

Informations de copyright

© 2018 Wiley Periodicals, Inc.

Auteurs

Maryam Erfanian Omidvar (M)

Department of Medical Laboratory Technology, School of Allied Medical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.

Hamid Ghaedi (H)

Department of Medical Genetics, Faculty of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran.

Faranak Kazerouni (F)

Department of Medical Laboratory Technology, School of Allied Medical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.

Saeid Kalbasi (S)

Department of endocrinology, Loghman Hospital, Shahid Beheshti University of Medical Sciences, Tehran, Iran.

Mehrnoosh Shanaki (M)

Department of Medical Laboratory Technology, School of Allied Medical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.

Ghasem Miraalamy (G)

Ali-Asghar Hospital, Iran University of Medical Sciences, Tehran, Iran.

Ali Zare (A)

Department of Medical Genetics, Faculty of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran.

Ali Rahimipour (A)

Department of Medical Laboratory Technology, School of Allied Medical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.

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Classifications MeSH