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Reliability of microarray analysis for studying periodontitis: low consistency in 2 periodontitis cohort data sets from different platforms and an integrative meta-analysis

Authors
 Yoon Seon Jeon  ;  Manu Shivakumar  ;  Dokyoon Kim  ;  Chang Sung Kim  ;  Jung Seok Lee 
Citation
 JOURNAL OF PERIODONTAL AND IMPLANT SCIENCE, Vol.51(1) : 18-29, 2021-02 
Journal Title
 JOURNAL OF PERIODONTAL AND IMPLANT SCIENCE 
ISSN
 2093-2278 
Issue Date
2021-02
Keywords
Meta-analysis ; Microarray analysis ; Periodontitis ; Transcriptome
Abstract
Purpose: The aim of this study was to compare the characteristic expression patterns of advanced periodontitis in 2 cohort data sets analyzed using different microarray platforms, and to identify differentially expressed genes (DEGs) through a meta-analysis of both data sets. Methods: Twenty-two patients for cohort 1 and 40 patients for cohort 2 were recruited with the same inclusion criteria. The 2 cohort groups were analyzed using different platforms: Illumina and Agilent. A meta-analysis was performed to increase reliability by removing statistical differences between platforms. An integrative meta-analysis based on an empirical Bayesian methodology (ComBat) was conducted. DEGs for the integrated data sets were identified using the limma package to adjust for age, sex, and platform and compared with the results for cohorts 1 and 2. Clustering and pathway analyses were also performed. Results: This study detected 557 and 246 DEGs in cohorts 1 and 2, respectively, with 146 and 42 significantly enriched gene ontology (GO) terms. Overlapping between cohorts 1 and 2 was present in 59 DEGs and 18 GO terms. However, only 6 genes from the top 30 enriched DEGs overlapped, and there were no overlapping GO terms in the top 30 enriched pathways. The integrative meta-analysis detected 34 DEGs, of which 10 overlapped in all the integrated data sets of cohorts 1 and 2. Conclusions: The characteristic expression pattern differed between periodontitis and the healthy periodontium, but the consistency between the data sets from different cohorts and metadata was too low to suggest specific biomarkers for identifying periodontitis.
Files in This Item:
T202100888.pdf Download
DOI
10.5051/jpis.2002120106
Appears in Collections:
2. College of Dentistry (치과대학) > Dept. of Periodontics (치주과학교실) > 1. Journal Papers
Yonsei Authors
Kim, Chang Sung(김창성) ORCID logo https://orcid.org/0000-0003-3902-1071
Lee, Jung Seok(이중석) ORCID logo https://orcid.org/0000-0003-1276-5978
URI
https://ir.ymlib.yonsei.ac.kr/handle/22282913/182276
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