Periodontitis has been reported to relate to metabolic syndrome traits such as obesity, blood pressure, and so on. However, the relation between periodontitis and metabolic syndrome remains unclear. The present study aimed to confirm common genetic factors between periodontitis and metabolic traits using Candidate gene association study (CGAS) in the Korean population. Based on the analysis of CGAS, this study performed linear regression analyses to examine the single-nucleotide polymorphisms (SNPs) between periodontitis and metabolic syndrome traits. Among the analyzed SNPs, 2649 SNPs in five genes ( TENM2 , LDLRAD4 , SLC9C2 , MFSD1 , and A2BP1 ) showed a statistical significance at p < 0.05. Interestingly, A2BP1 and TENM2 were related to obesity. Also, elevated levels of LDLRAD4 , SLC9C2, and MFSD1 were observed in the patients with high blood pressure. Taken together, the present study suggests that some of the SNPs are related to periodontitis. Therefore, if any of TENM2 , A2BP1 , LDLRAD4 , SLC9C2, and MFSD1 is detected in the patients with periodontitis, obesity and blood pressure have to be treated simultaneously. Electronic supplementary material The online version of this article (10.1007/s10528-018-9899-9) contains supplementary material, which is available to authorized users.

This research team extracted keywords from 953 papers published in the Journal of Dental Hygiene Science from 2001 to 2018 for keyword and centrality analyses using the Keyword Network Analysis method. Data were analyzed using Excel 2016 and NetMiner Version 4.4.1. By conducting a deeper analysis between keywords by overall keyword and time frame, we arrived at the following conclusions.

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Objective: This study collected articles released by BIGKinds (www.bigkinds.or.kr), which is a big data service made available by the Korea Press Foundation, by applying search keywords including "corona" and "dentistry" from January 6, 2020 to June 30, 2021.Methods: Data extracted using NetMiner (Cyram Inc., Seongnam, Korea) was subject to a refining process to extract only keywords with a Term Frequency-Inverse Document Frequency coefficient of 0.5 or higher and Latent Dirichlet Allocation topic modeling was performed to derive the topics.Results: Of the 5 derived topics, the topic accounting for the greatest portion was "vaccination", followed by "dental health care", "medical industry", "time of confusion during the COVID-19 pandemic", and "changes in daily life during the COVID-19 pandemic". Conclusion:The biggest issue in the dental sector in 2020 and the first half of 2021 due to the spread of COVID-19 were found to be "vaccination", "dental health care", "medical industry", "time of confusion during the COVID-19 pandemic", and "changes in daily life during the COVID-19 pandemic". In the future, research should be conducted to better understand changes in the dental sector and plans for systematically resolving such issues.

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