Jeon Yoon Seon, Shivakumar Manu, Kim Dokyoon, Kim Chang Sung, Lee Jung Seok
Department of Periodontology, Research Institute for Periodontal Regeneration, Yonsei University College of Dentistry, Seoul, Korea.
Department of Biostatistics, Epidemiology and Informatics, The Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
J Periodontal Implant Sci. 2021 Feb;51(1):18-29. doi: 10.5051/jpis.2002120106.
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.
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 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.
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.
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.
本研究旨在比较使用不同微阵列平台分析的2个队列数据集中晚期牙周炎的特征性表达模式，并通过对两个数据集的荟萃分析来鉴定差异表达基因（DEG）。
按照相同的纳入标准招募了队列1的22名患者和队列2的40名患者。使用不同平台对这2个队列组进行分析：Illumina和安捷伦。进行荟萃分析以消除平台间的统计差异，从而提高可靠性。基于经验贝叶斯方法（ComBat）进行综合荟萃分析。使用该软件包鉴定综合数据集的DEG，以调整年龄、性别和平台，并与队列1和队列2的结果进行比较。还进行了聚类和通路分析。
本研究在队列1和队列2中分别检测到557个和246个DEG，分别有146个和42个基因本体（GO）术语显著富集。队列1和队列2之间有59个DEG和18个GO术语存在重叠。然而，在富集程度最高的前30个DEG中只有6个基因重叠，在富集程度最高的前30个通路中没有重叠的GO术语。综合荟萃分析检测到34个DEG，其中10个在队列1和队列2的所有综合数据集中重叠。
牙周炎与健康牙周组织的特征性表达模式不同，但不同队列数据集与元数据之间的一致性过低，无法提示用于鉴定牙周炎的特定生物标志物。
