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KMID : 1200020200440060854
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Diabetes & Metabolism Journal
2020 Volume.44 No. 6 p.854 ~ p.865
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Differential Profile of Plasma Circular RNAs in Type 1 Diabetes Mellitus
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Li Yangyang
Zhou Ying
Zhao Minghui
Zou Jing
Zhu Yuxiao
Yuan Xuewen
Liu Qianqi
Cai Hanqing
Chu Cong-Qiu
Liu Yu
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Abstract
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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.
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KEYWORD
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Autoimmune diseases, Biomarkers, Diabetes mellitus, type 1, Inflammation, MicroRNAs, Plasma, RNA, circular
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