Bibliometric analysis of the intestinal microbiota and demyelinating diseases, particularly multiple sclerosis, since 2014 - Chen, Ling; Wu, Le-Le; Yu, Chang-Yin; Xu, Zu-Cai; Huang, Hao (Frontiers in Neuroscience, 2025)
BackgroundThe gut–brain axis (GBA) represents a complex, bidirectional communication network that connects the central nervous system (CNS) and the gastrointestinal system. Our study aimed to explore the correlation between the intestinal microbiota and demyelinating diseases from a bibliometric perspective, focusing on research since 2014.MethodsA comprehensive search was carried out on the Web of Science Core Collection (WoSCC) to locate studies on the intestinal microbiota and demyelinating diseases, with a focus on publications from 1 January 2014 to 29 March 2024. We visualized and analyzed the data using VOSviewer, CiteSpace, and Charticulator.ResultsWe gathered 429 scholarly articles on the intestinal microbiota and demyelinating disorders published in the past 10 years. Research concerning the intestinal microbiota and demyelinating diseases has demonstrated a consistent increase in frequency over time. The USA has the highest number of publications, while Canada has the highest average number of citations, reaching as high as 3,429, which is greater than that of the USA. Moreover, the journal with the highest number of publications was Frontiers in Immunology, with 33 publications and 1,494 citations. The majority of the scholars focused on “multiple sclerosis” and “gut microbiota,” which are the primary keywords in the field of the intestinal microbiota and demyelinating diseases.ConclusionThis study conducted a comprehensive analysis of existing research investigating the correlation between the intestinal microbiota and demyelinating diseases. Using advanced bibliometric tools such as VOSviewer and CiteSpace, this study analyzed the intricate relationship between the intestinal microbiota and the pathogenesis of demyelinating conditions. In addition, the study used literature statistical analysis to identify research hotspots and future directions in the field.