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Long non‐coding RNA screening and identification of potential biomarkers for type 2 diabetes

BACKGROUND: To investigate new lncRNAs as molecular markers of T2D. METHODS: We used microarrays to identify differentially expressed lncRNAs and mRNAs from five patients with T2D and paired controls. Through bioinformatics analysis, qRT‐PCR validation, ELISA, and receiver operating characteristic (...

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Autores principales: Ma, Qi, Wang, Li, Wang, Zhiqiang, Su, Yinxia, Hou, Qinqin, Xu, Qiushuang, Cai, Ren, Wang, Tingting, Gong, Xueli, Yi, Qizhong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8993646/
https://www.ncbi.nlm.nih.gov/pubmed/35257412
http://dx.doi.org/10.1002/jcla.24280
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author Ma, Qi
Wang, Li
Wang, Zhiqiang
Su, Yinxia
Hou, Qinqin
Xu, Qiushuang
Cai, Ren
Wang, Tingting
Gong, Xueli
Yi, Qizhong
author_facet Ma, Qi
Wang, Li
Wang, Zhiqiang
Su, Yinxia
Hou, Qinqin
Xu, Qiushuang
Cai, Ren
Wang, Tingting
Gong, Xueli
Yi, Qizhong
author_sort Ma, Qi
collection PubMed
description BACKGROUND: To investigate new lncRNAs as molecular markers of T2D. METHODS: We used microarrays to identify differentially expressed lncRNAs and mRNAs from five patients with T2D and paired controls. Through bioinformatics analysis, qRT‐PCR validation, ELISA, and receiver operating characteristic (ROC) curve analysis of 100 patients with T2D and 100 controls to evaluate the correlation between lncRNAs and T2D, and whether lncRNAs could be used in the diagnosis of T2D patients. RESULTS: We identified 68 and 74 differentially expressed lncRNAs and mRNAs, respectively. The top five upregulated lncRNAs are ENST00000381108.3, ENST00000515544.1, ENST00000539543.1, ENST00000508174.1, and ENST00000564527.1, and the top five downregulated lncRNAs are TCONS_00017539, ENST00000430816.1, ENST00000533203.1, ENST00000609522.1, and ENST00000417079.1. The top five upregulated mRNAs are Q59H50, CYP27A1, DNASE1L3, GRIP2, and lnc‐TMEM18‐12, and the top five downregulated mRNAs are GSTM4, PODN, GLYATL2, ZNF772, and CLTC. Examination of lncRNA‐mRNA interaction pairs indicated that the target gene of lncRNA XR_108954.2 is E2F2. Multiple linear regression analysis showed that XR_108954.2 (r = 0.387, p < 0.01) and E2F2 (r = 0.368, p < 0.01) expression levels were positively correlated with glucose metabolism indicators. Moreover, E2F2 was positively correlated with lipid metabolism indicators (r = 0.333, p < 0.05). The area under the ROC curve was 0.704 (95% CI: 0.578–0.830, p = 0.05) for lncRNA XR_108954.2 and 0.653 (95% CI: 0.516–0.790, p = 0.035) for E2F2. CONCLUSIONS: This transcriptome analysis explored the aberrantly expressed lncRNAs and identified E2F2 and lncRNA XR_108954.2 as potential biomarkers for patients with T2D.
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spelling pubmed-89936462022-04-13 Long non‐coding RNA screening and identification of potential biomarkers for type 2 diabetes Ma, Qi Wang, Li Wang, Zhiqiang Su, Yinxia Hou, Qinqin Xu, Qiushuang Cai, Ren Wang, Tingting Gong, Xueli Yi, Qizhong J Clin Lab Anal Research Articles BACKGROUND: To investigate new lncRNAs as molecular markers of T2D. METHODS: We used microarrays to identify differentially expressed lncRNAs and mRNAs from five patients with T2D and paired controls. Through bioinformatics analysis, qRT‐PCR validation, ELISA, and receiver operating characteristic (ROC) curve analysis of 100 patients with T2D and 100 controls to evaluate the correlation between lncRNAs and T2D, and whether lncRNAs could be used in the diagnosis of T2D patients. RESULTS: We identified 68 and 74 differentially expressed lncRNAs and mRNAs, respectively. The top five upregulated lncRNAs are ENST00000381108.3, ENST00000515544.1, ENST00000539543.1, ENST00000508174.1, and ENST00000564527.1, and the top five downregulated lncRNAs are TCONS_00017539, ENST00000430816.1, ENST00000533203.1, ENST00000609522.1, and ENST00000417079.1. The top five upregulated mRNAs are Q59H50, CYP27A1, DNASE1L3, GRIP2, and lnc‐TMEM18‐12, and the top five downregulated mRNAs are GSTM4, PODN, GLYATL2, ZNF772, and CLTC. Examination of lncRNA‐mRNA interaction pairs indicated that the target gene of lncRNA XR_108954.2 is E2F2. Multiple linear regression analysis showed that XR_108954.2 (r = 0.387, p < 0.01) and E2F2 (r = 0.368, p < 0.01) expression levels were positively correlated with glucose metabolism indicators. Moreover, E2F2 was positively correlated with lipid metabolism indicators (r = 0.333, p < 0.05). The area under the ROC curve was 0.704 (95% CI: 0.578–0.830, p = 0.05) for lncRNA XR_108954.2 and 0.653 (95% CI: 0.516–0.790, p = 0.035) for E2F2. CONCLUSIONS: This transcriptome analysis explored the aberrantly expressed lncRNAs and identified E2F2 and lncRNA XR_108954.2 as potential biomarkers for patients with T2D. John Wiley and Sons Inc. 2022-03-07 /pmc/articles/PMC8993646/ /pubmed/35257412 http://dx.doi.org/10.1002/jcla.24280 Text en © 2022 The Authors. Journal of Clinical Laboratory Analysis published by Wiley Periodicals LLC. https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Articles
Ma, Qi
Wang, Li
Wang, Zhiqiang
Su, Yinxia
Hou, Qinqin
Xu, Qiushuang
Cai, Ren
Wang, Tingting
Gong, Xueli
Yi, Qizhong
Long non‐coding RNA screening and identification of potential biomarkers for type 2 diabetes
title Long non‐coding RNA screening and identification of potential biomarkers for type 2 diabetes
title_full Long non‐coding RNA screening and identification of potential biomarkers for type 2 diabetes
title_fullStr Long non‐coding RNA screening and identification of potential biomarkers for type 2 diabetes
title_full_unstemmed Long non‐coding RNA screening and identification of potential biomarkers for type 2 diabetes
title_short Long non‐coding RNA screening and identification of potential biomarkers for type 2 diabetes
title_sort long non‐coding rna screening and identification of potential biomarkers for type 2 diabetes
topic Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8993646/
https://www.ncbi.nlm.nih.gov/pubmed/35257412
http://dx.doi.org/10.1002/jcla.24280
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