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Yu Liu  (Liu Y) 2 Articles
Type 1 Diabetes
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Differential Profile of Plasma Circular RNAs in Type 1 Diabetes Mellitus
Yangyang Li, Ying Zhou, Minghui Zhao, Jing Zou, Yuxiao Zhu, Xuewen Yuan, Qianqi Liu, Hanqing Cai, Cong-Qiu Chu, Yu Liu
Diabetes Metab J. 2020;44(6):854-865.   Published online July 13, 2020
DOI: https://doi.org/10.4093/dmj.2019.0151
  • 6,864 View
  • 151 Download
  • 23 Web of Science
  • 23 Crossref
AbstractAbstract PDFSupplementary MaterialPubReader   ePub   
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.

Citations

Citations to this article as recorded by  
  • Non-coding RNAs and exosomal non-coding RNAs in diabetic retinopathy: A narrative review
    Yuhong Zhong, Juan Xia, Li Liao, Mohammad Reza Momeni
    International Journal of Biological Macromolecules.2024; 259: 128182.     CrossRef
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    Ziwei Zhang, Shuoming Luo, Zilin Xiao, Wenfeng Yin, Xiajie Shi, Hongzhi Chen, Zhiguo Xie, Zhenqi Liu, Xia Li, Zhiguang Zhou
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    Diagnostics.2024; 14(10): 1045.     CrossRef
  • Circulating non-coding RNA in type 1 diabetes mellitus as a source of potential biomarkers – An emerging role of sex difference
    Lucyna Stachowiak, Weronika Kraczkowska, Aleksandra Świercz, Paweł Piotr Jagodziński
    Biochemical and Biophysical Research Communications.2024; 736: 150482.     CrossRef
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    Manuela Cabiati, Giovanni Federico, Silvia Del Ry
    Biomedicines.2024; 12(9): 1988.     CrossRef
  • Circular RNAs in human diseases
    Yuanyong Wang, Jin Zhang, Yuchen Yang, Zhuofeng Liu, Sijia Sun, Rui Li, Hui Zhu, Tian Li, Jin Zheng, Jie Li, Litian Ma
    MedComm.2024;[Epub]     CrossRef
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    Zhidan Zhang, Yuling Huang, AYao Guo, Lina Yang
    Ageing Research Reviews.2023; 87: 101913.     CrossRef
  • CircRNAs and RNA-Binding Proteins Involved in the Pathogenesis of Cancers or Central Nervous System Disorders
    Yuka Ikeda, Sae Morikawa, Moeka Nakashima, Sayuri Yoshikawa, Kurumi Taniguchi, Haruka Sawamura, Naoko Suga, Ai Tsuji, Satoru Matsuda
    Non-Coding RNA.2023; 9(2): 23.     CrossRef
  • Decrypting the circular RNAs does a favor for us: Understanding, diagnosing and treating diabetes mellitus and its complications
    Zi Li, Yuanyuan Ren, Ziwei Lv, Man Li, Yujia Li, Xiaobin Fan, Yuyan Xiong, Lu Qian
    Biomedicine & Pharmacotherapy.2023; 168: 115744.     CrossRef
  • Circular RNA PIP5K1A Promotes Glucose and Lipid Metabolism Disorders and Inflammation in Type 2 Diabetes Mellitus
    Ge Song, YiQian Zhang, YiHua Jiang, Huan Zhang, Wen Gu, Xiu Xu, Jing Yao, ZhengFang Chen
    Molecular Biotechnology.2023;[Epub]     CrossRef
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    Lei Ren
    Bioengineered.2022; 13(3): 5724.     CrossRef
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    Wenqi Fan, Haipeng Pang, Zhiguo Xie, Gan Huang, Zhiguang Zhou
    Frontiers in Endocrinology.2022;[Epub]     CrossRef
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    Jianni Chen, Guanfei Jia, Xue Lv, Shufa Li, Christos K. Kontos
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    Monisha Prasad, Selvaraj Jayaraman, Vishnu Priya Veeraraghavan
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    Miao Liu, Junli Zhao
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    Zeyu Liu, Yanhong Zhou, Jian Xia
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  • Pro-Inflammatory Cytokines Promote the Transcription of Circular RNAs in Human Pancreatic β Cells
    Simranjeet Kaur, Caroline Frørup, Aashiq H. Mirza, Tina Fløyel, Reza Yarani, Maikel L. Colli, Jesper Johannesen, Joachim Størling, Decio L. Eizirik, Flemming Pociot
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  • Differential Expression and Bioinformatics Analysis of Plasma-Derived Exosomal circRNA in Type 1 Diabetes Mellitus
    Haipeng Pang, Wenqi Fan, Xiajie Shi, Shuoming Luo, Yimeng Wang, Jian Lin, Yang Xiao, Xia Li, Gan Huang, Zhiguo Xie, Zhiguang Zhou, Jinhui Liu
    Journal of Immunology Research.2022; 2022: 1.     CrossRef
  • Circular RNAs in diabetes and its complications: Current knowledge and future prospects
    Wenfeng Yin, Ziwei Zhang, Zilin Xiao, Xia Li, Shuoming Luo, Zhiguang Zhou
    Frontiers in Genetics.2022;[Epub]     CrossRef
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    Xuanzi Yi, Xu Cheng
    Diabetes, Metabolic Syndrome and Obesity: Targets and Therapy.2021; Volume 14: 3865.     CrossRef
Technology/Device
Glutamic Acid Decarboxylase Autoantibody Detection by Electrochemiluminescence Assay Identifies Latent Autoimmune Diabetes in Adults with Poor Islet Function
Yuxiao Zhu, Li Qian, Qing Liu, Jing Zou, Ying Zhou, Tao Yang, Gan Huang, Zhiguang Zhou, Yu Liu
Diabetes Metab J. 2020;44(2):260-266.   Published online November 12, 2019
DOI: https://doi.org/10.4093/dmj.2019.0007
  • 6,214 View
  • 139 Download
  • 12 Web of Science
  • 13 Crossref
AbstractAbstract PDFPubReader   
Background

The detection of glutamic acid decarboxylase 65 (GAD65) autoantibodies is essential for the prediction and diagnosis of latent autoimmune diabetes in adults (LADA). The aim of the current study was to compare a newly developed electrochemiluminescence (ECL)-GAD65 antibody assay with the established radiobinding assay, and to explore whether the new assay could be used to define LADA more precisely.

Methods

Serum samples were harvested from 141 patients with LADA, 95 with type 1 diabetes mellitus, and 99 with type 2 diabetes mellitus, and tested for GAD65 autoantibodies using both the radiobinding assay and ECL assay. A glutamic acid decarboxylase antibodies (GADA) competition assay was also performed to assess antibody affinity. Furthermore, the clinical features of these patients were compared.

Results

Eighty-eight out of 141 serum samples (62.4%) from LADA patients were GAD65 antibody-positive by ECL assay. Compared with ECL-GAD65 antibody-negative patients, ECL-GAD65 antibody-positive patients were leaner (P<0.0001), had poorer β-cell function (P<0.05), and were more likely to have other diabetes-associated autoantibodies. The β-cell function of ECL-GAD65 antibody-positive patients was similar to that of type 1 diabetes mellitus patients, whereas ECL-GAD65 antibody-negative patients were more similar to type 2 diabetes mellitus patients.

Conclusion

Patients with ECL-GAD65 antibody-negative share a similar phenotype with type 2 diabetes mellitus patients, whereas patients with ECL-GAD65 antibody-positive resemble those with type 1 diabetes mellitus. Thus, the detection of GADA using ECL may help to identify the subtype of LADA.

Citations

Citations to this article as recorded by  
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