Residential College | false |
Status | 已發表Published |
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 Publication | PLoS ONE |
ISSN | 1664-0640 |
Volume | 16Issue: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. |
DOI | 10.1371/journal.pone.0247556 |
URL | View the original |
Indexed By | SCIE |
Language | 英語English |
WOS Research Area | Science & Technology - Other Topics |
WOS Subject | Multidisciplinary Sciences |
WOS ID | WOS:000637879100039 |
Scopus ID | 2-s2.0-85104099357 |
Fulltext Access | |
Citation statistics | |
Document Type | Journal article |
Collection | Institute of Chinese Medical Sciences THE STATE KEY LABORATORY OF QUALITY RESEARCH IN CHINESE MEDICINE (UNIVERSITY OF MACAU) |
Corresponding Author | Leung, Siu Wai |
Affiliation | 1.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 Affilication | Institute of Chinese Medical Sciences |
Corresponding Author Affilication | Institute 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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