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MicroRNA biomarkers of type 2 diabetes: A protocol for corroborating evidence by computational genomics and meta-analyses
Zhu, Hongmei1; Leung, Siu Wai1,2,3
2021-04-01
Source PublicationPLoS ONE
ISSN1664-0640
Volume16Issue:4Pages:e0247556
Abstract

Background Few microRNAs were found consistently dysregulated in type 2 diabetes (T2D) that would gain confidence from Big Pharma to develop diagnostic or therapeutic biomarkers. This study aimed to corroborate evidence from eligible microRNAs-T2D association studies according to stringent quality criteria covering both biological and statistical significance in T2D for biomarker development. Methods and analyses Controlled microRNA expression profiling studies on human with T2D will be retrieved from PubMed, ScienceDirect, and Embase for selecting the statistically significant microRNAs according to pre-specified search strategies and inclusion criteria. Multiple meta-analyses with restricted maximum-likelihood estimation and empirical Bayes estimation under the random-effects model will be conducted by metafor package in R. Subgroup and sensitivity analyses further examine the microRNA candidates for their disease specificity, tissue specificity, blood fraction specificity, and statistical robustness of evidence. Biologically relevant microRNAs will then be selected through genomic database corroboration. Their association with T2D is further measured by area under the curve (AUC) of receive operating characteristic (ROC). Meta-analysis of AUC of potential biomarkers will also be conducted. Enrichment analysis on potential microRNA biomarkers and their target genes will be performed by iPathwayGuide and clusterProfiler, respectively. The corresponding reporting guidelines will be used to assess the quality of included studies according to their profiling methods (microarray, RT-PCR, and RNA-Seq). Ethics and dissemination No ethics approval is required since this study does not include identifiable personal patient data.

DOI10.1371/journal.pone.0247556
URLView the original
Indexed BySCIE
Language英語English
WOS Research AreaScience & Technology - Other Topics
WOS SubjectMultidisciplinary Sciences
WOS IDWOS:000637879100039
Scopus ID2-s2.0-85104099357
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Citation statistics
Document TypeJournal article
CollectionInstitute of Chinese Medical Sciences
THE STATE KEY LABORATORY OF QUALITY RESEARCH IN CHINESE MEDICINE (UNIVERSITY OF MACAU)
Corresponding AuthorLeung, Siu Wai
Affiliation1.State Key Laboratory of Quality Research in Chinese Medicine, Institute of Chinese Medical Sciences, University of Macau, Macao
2.Shenzhen Institute of Artificial Intelligence and Robotics for Society, Shenzhen, China
3.Edinburgh Bayes Centre for AI Research in Shenzhen, College of Science and Engineering, University of Edinburgh, Scotland, United Kingdom
First Author AffilicationInstitute of Chinese Medical Sciences
Corresponding Author AffilicationInstitute of Chinese Medical Sciences
Recommended Citation
GB/T 7714
Zhu, Hongmei,Leung, Siu Wai. MicroRNA biomarkers of type 2 diabetes: A protocol for corroborating evidence by computational genomics and meta-analyses[J]. PLoS ONE, 2021, 16(4), e0247556.
APA Zhu, Hongmei., & Leung, Siu Wai (2021). MicroRNA biomarkers of type 2 diabetes: A protocol for corroborating evidence by computational genomics and meta-analyses. PLoS ONE, 16(4), e0247556.
MLA Zhu, Hongmei,et al."MicroRNA biomarkers of type 2 diabetes: A protocol for corroborating evidence by computational genomics and meta-analyses".PLoS ONE 16.4(2021):e0247556.
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