Bibliometric and visual analysis of RAN methylation in cardiovascular disease

Front Cardiovasc Med. 2023 Mar 30:10:1110718. doi: 10.3389/fcvm.2023.1110718. eCollection 2023.

Abstract

Background: RNA methylation is associated with cardiovascular disease (CVD) occurrence and development. The purpose of this study is to visually analyze the results and research trends of global RNA methylation in CVD.

Methods: Articles and reviews on RNA methylation in CVD published before 6 November 2022 were searched in the Web of Science Core Collection. Visual and statistical analysis was performed using CiteSpace 1.6.R4 advanced and VOSviewer 1.6.18.

Results: There were 847 papers from 1,188 institutions and 63 countries/regions. Over approximately 30 years, there was a gradual increase in publications and citations on RNA methylation in CVD. America and China had the highest output (284 and 259 papers, respectively). Nine of the top 20 institutions that published articles were from China, among which Fudan University represented the most. The International Journal of Molecular Sciences was the journal with the most studies. Nature was the most co-cited journal. The most influential writers were Zhang and Wang from China and Mathiyalagan from the United States. After 2015, the primary keywords were cardiac development, heart, promoter methylation, RNA methylation, and N6-methyladenosine. Nuclear RNA, m6A methylation, inhibition, and myocardial infarction were the most common burst keywords from 2020 to the present.

Conclusions: A bibliometric analysis reveals research hotspots and trends of RNA methylation in CVD. The regulatory mechanisms of RNA methylation related to CVD and the clinical application of their results, especially m6A methylation, are likely to be the focus of future research.

Keywords: RNA methylation; VOSviewer; bibliometric analysis; cardiovascular disease; citespace; visual analysis.

Grants and funding

Details of all funding sources will be provided, including grant numbers if applicable. This work was supported by the Natural Science Foundation of China (grant no. 81973674) and Beijing Municipal Natural Science Foundation (grant no. 7202175).