The Differential Expression of Long Noncoding RNAs in Type 2 Diabetes Mellitus and Latent Autoimmune Diabetes in Adults.

BACKGROUND: Long noncoding RNAs (lncRNAs) were previously found to be closely related to the pathogenesis of diabetes. OBJECTIVES: To reveal the differentially expressed lncRNAs and messenger RNAs (mRNAs) involved in type 2 diabetes mellitus (T2DM) and latent autoimmune diabetes in adults (LADA) and predict the lncRNA target genes to derive their expression profiles for the diagnosis of T2DM and LADA and their differential diagnosis. METHODS: Twelve venous blood samples were collected from T2DM patients, LADA patients, and nondiseased subjects to obtain total RNAs. After removing rRNA from total RNAs to establish the desired library for sequencing, quality control and quantification analyses were carried out. The fragments per kilobase of exon model per million reads mapped (FPKM) of lncRNAs were calculated to construct the gene expression profiles of lncRNAs and mRNAs. Fold changes (fold change: 2.0) and p values (p values (. RESULTS: Compared to nondiseased controls, 68,763 versus 28,523 lncRNAs and 133 versus 1035 mRNAs were significantly upregulated and significantly downregulated, respectively, in T2DM patients. For LADA patients, 68,748 versus 28,538 lncRNAs and 219 versus 805 mRNAs were significantly upregulated and significantly downregulated, respectively, relative to nondiseased controls. Compared to T2DM patients, 74,207 versus 23,079 lncRNAs and 349 versus 137 mRNAs were significantly upregulated and significantly downregulated, respectively, in LADA patients. Based on the correlation analysis, seven lncRNA-mRNA pairs (BTG2, A2M, HECTD4, MBTPS1, DBH, FLVCR1, and NCBP2) were significantly coexpressed, and two lncRNAs (ENST00000608916 and ENST00000436373) were newly discovered. CONCLUSION: Significant differences in lncRNA expression were discovered among the three groups. Furthermore, after predicting lncRNA expression profiles, GO/KEGG pathway analysis could deduce the target gene function.

Differential Profile of Plasma Circular RNAs in Type 1Diabetes Mellitus

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.

Differential Profile of Plasma Circular RNAs in Type 1 Diabetes Mellitus

BackgroundNo 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.MethodsWe 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.ResultsWe 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.ConclusionOur 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.

Differential Profile of Plasma Circular RNAs in Type 1 Diabetes Mellitus

BackgroundNo 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.MethodsWe 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.ResultsWe 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.ConclusionOur 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.

Study on bone metobolism change in thirty hyperthyroidism patients / 吉林大学学报(医学版)

Objective:To study the effect of thyroid function on bone metabolism. Methods:Serum FT3,FT4 were investigated by radioimmunoassay (RIA) and bone mineral density of spine (L2～4) weremeasured by dual energy x-ray absorptinmetry and other markers related to bone metabolism were alsomonitored in 30 patients with hyperthyroidism and 30 healthy volunteers. Results :The levels of FT3,FT4,ALP were significantly higher than those of the normal controls. BMD of spine decreased significantly incomparison with the controls ,and the degree of severity and incidence increased with age. Conclusion:Thy-roid hormone might speed up bone turnover directly with increased bone resorption to induce bone massloss.