Dataset Information

Differential Profile of Plasma Circular RNAs in Type 1 Diabetes Mellitus.

ABSTRACT:

Background

No currently available biomarkers or treatment regimens fully meet therapeutic needs of type 1 diabetes mellitus (T1DM). Circular RNA (circRNA) is a recently identified class of stable noncoding RNA that have been documented as potential biomarkers for various diseases. Our objective was to identify and analyze plasma circRNAs altered in T1DM.

Methods

We used microarray to screen differentially expressed plasma circRNAs in patients with new onset T1DM (n=3) and age-/gender-matched healthy controls (n=3). Then, we selected six candidates with highest fold-change and validated them by quantitative real-time polymerase chain reaction in independent human cohort samples (n=12). Bioinformatic tools were adopted to predict putative microRNAs (miRNAs) sponged by these validated circRNAs and their downstream messenger RNAs (mRNAs). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed to gain further insights into T1DM pathogenesis.

Results

We identified 68 differentially expressed circRNAs, with 61 and seven being up- and downregulated respectively. Four of the six selected candidates were successfully validated. Curations of their predicted interacting miRNAs revealed critical roles in inflammation and pathogenesis of autoimmune disorders. Functional relations were visualized by a circRNA-miRNA-mRNA network. GO and KEGG analyses identified multiple inflammation-related processes that could be potentially associated with T1DM pathogenesis, including cytokine-cytokine receptor interaction, inflammatory mediator regulation of transient receptor potential channels and leukocyte activation involved in immune response.

Conclusion

Our study report, for the first time, a profile of differentially expressed plasma circRNAs in new onset T1DM. Further in silico annotations and bioinformatics analyses supported future application of circRNAs as novel biomarkers of T1DM.

SUBMITTER: Li Y

PROVIDER: S-EPMC7801755 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature

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Publications

Differential Profile of Plasma Circular RNAs in Type 1 Diabetes Mellitus.

Li Yangyang Y Zhou Ying Y Zhao Minghui M Zou Jing J Zhu Yuxiao Y Yuan Xuewen X Liu Qianqi Q Cai Hanqing H Chu Cong-Qiu CQ Liu Yu Y

Diabetes & metabolism journal 20200713 6

<h4>Background</h4>No currently available biomarkers or treatment regimens fully meet therapeutic needs of type 1 diabetes mellitus (T1DM). Circular RNA (circRNA) is a recently identified class of stable noncoding RNA that have been documented as potential biomarkers for various diseases. Our objective was to identify and analyze plasma circRNAs altered in T1DM.<h4>Methods</h4>We used microarray to screen differentially expressed plasma circRNAs in patients with new onset T1DM (n=3) and age-/gen ...[more]

PMID: 32662258

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Project description:Circular RNAs (circRNAs) are an abundant class of endogenous non?coding RNAs and are associated with numerous diseases, including cancer, cardiovascular diseases, and type 2 diabetes mellitus (T2DM). However, the association between circRNAs and inflammation or inflammatory cytokines in patients with T2DM remains to be fully elucidated. The purpose of the present study was to investigate the expression profiles of circRNAs in peripheral leucocytes of patients with T2DM and their association with inflammatory cytokines. Peripheral blood from patients with T2DM (n=43) and healthy individuals (n=45) were collected for RNA sequencing and later verification. Reverse transcription?polymerase chain reaction (RT?PCR) and reverse transcription?quantitative polymerase chain reaction (RT?qPCR) analyses were used to detect the expression levels of circRNAs. The expression of inflammatory factors, including interleukin (IL)?1, (IL)?6, and tumor necrosis factor (TNF)?? were measured via enzyme?linked immunosorbent assay. Furthermore, the mRNA expression level of ankyrin repeat domain 36 (ANKRD36), a protein located at 2q11.2 that interacts with the GAPDH gene, was measured using RT?qPCR analysis. The circRNA/microRNA (miRNA) interaction was predicted using RegRNA and mirPath software. In total, 220 circRNAs were found to be differentially expressed between patients with T2DM and healthy individuals, of which 107 were upregulated and 113 were downregulated. Among the nine selected circRNAs, circANKRD36 was significantly upregulated in patients with T2DM compared with control subjects (P=0.02). The expression level of circANKRD36 was positively correlated with glucose and glycosylated hemoglobin (r=0.3250, P=0.0047 and r=0.3171, P=0.0056, respectively). The expression level of IL?6 was significantly different between the T2DM group and control group (P=0.028) and was positively correlated with circANKRD36. The difference of circANKRD36 host gene expression between patients with T2DM and healthy controls was significant (P=0.04). Taken together, circANKRD36 may be involved in T2DM and inflammation?associated pathways via interaction with miRNAs, including hsa?miR?3614?3p, hsa?miR?498, and hsa?miR?501?5p. The expression of circANKRD36 was up-regulated in peripheral blood leucocytes and was correlated with chronic inflammation in T2DM. Therefore, circANKRD36 can be used as a potential biomarker for screening chronic inflammation in patients with T2DM.

Project description:Background/Objectives: Coronary artery disease (CAD) and type-2 diabetes mellitus (T2DM) are characterized by chronic low-grade inflammation. However, measuring cytokines typically involves invasive blood sampling, which can be problematic for CAD patients. This study aimed to assess ophthalmological parameters and tear cytokines in patients with CAD, comparing those with comorbid T2DM to those without to understand their inflammatory profiles. Methods: One hundred subjects with suspected chronic or acute CAD were initially included in this single-center cross-sectional study after clinical stabilization. Seventy-two patients with confirmed CAD were divided into two groups: 32 patients with T2DM and 40 patients without T2DM. A total of 144 eyes were examined, and tear fluid samples were collected to determine cytokine concentrations. Ophthalmological parameters and tear concentrations of cytokines were analyzed, controlling for age, sex, and other cardiovascular risk factors. Results: Patients with CAD and T2DM exhibited decreased ophthalmological parameters and increased cytokine concentrations in comparison to those without T2DM. Significant inverse correlations between ophthalmological parameters and cytokine concentrations were observed. Following adjustment, a full logistic regression model for distinguishing patients with CAD and comorbid T2DM included macular cube volume, mean macular thickness, interleukin (IL)-4, IL-5, IL-6, IL-8, IL-9, IL-13, granulocyte colony-stimulating factor (G-CSF), CCL3, CCL4, and CCL11/eotaxin-1, demonstrating excellent discriminatory power (Area Under the Curve = 0.95, 95% Confidence Interval = 0.91-0.99; p < 0.001). Subsequently, IL-5 (Odds Ratio = 1.68, 95% CI = 1.26-2.24; p < 0.001), G-CSF (OR = 1.06, 95% CI = 1.02-1.11; p < 0.01), and CCL11/eotaxin-1 (OR = 1.56, 95% CI = 1.19-2.05; p = 0.001) emerged as the most distinguishing variables in a reduced model (AUC = 0.89, 95% CI = 0.84-0.95; p < 0.001). Conclusions: Differences in ophthalmological variables, mainly in cytokine concentrations, suggest distinct pathophysiological mechanisms in patients with CAD based on the presence of T2DM. These findings demonstrate that the inflammatory profile can be readily detected through tear sample cytokines, proving valuable for establishing more accurate prognoses and monitoring in cardiometabolic disorders.

Dataset Information

Differential Profile of Plasma Circular RNAs in Type 1 Diabetes Mellitus.

Background

Methods

Results

Conclusion

Publications

Differential Profile of Plasma Circular RNAs in Type 1 Diabetes Mellitus.

Similar Datasets

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