AUTHOR=shan Chen L., fei Chen J., Ming Wu , Yan Kang p., ping Zhou X. TITLE=Analyzing the bibliometrics of brain-gut axis and Parkinson’s disease JOURNAL=Frontiers in Neurology VOLUME=15 YEAR=2024 URL=https://www.frontiersin.org/journals/neurology/articles/10.3389/fneur.2024.1343303 DOI=10.3389/fneur.2024.1343303 ISSN=1664-2295 ABSTRACT=Background

Parkinson’s disease (PD), characterized by the loss of dopaminergic neurons, is a progressive neurodegenerative disorder. Recent research has revealed a significant connection between gut microbiota and PD. To gain insight into research interests, disciplinary contexts, and potential future directions, a comprehensive bibliometric analysis was conducted on the brain-gut axis and PD literature published between 2014 and 2023.

Methods

Relevant literature records were gathered from the Web of Science Core Collection on August 11, 2023. The data were then analyzed by Biblioshiny R packages and VOSviewer (version 1.6.19).

Results

The dataset revealed an upward trend in annual scientific publications on the brain-gut axis and PD, with an annual growth rate of 50.24%. China, the United States, and Italy were the top three most productive countries/regions. The journal “International Journal Of Molecular Sciences” published the most articles, while “Movement Disorders” received the highest number of citations. Professor Keshavarzian A emerged as the most prolific author, while Professor Scheperjans F held the highest h-index. Keyword analysis highlighted “alpha-synuclein” as the most frequent term, with “mouse model,” “inflammation,” and “risk” as emerging research topics. Additionally, “central nervous system” and “intestinal bacterial overgrowth” attracted increasing attention.

Conclusion

This study examined current trends and hotspots in the bibliometric landscape of the brain-gut axis and PD research. Future research directions should explore the functional and metabolic activities of gut microbiota. Additionally, transitioning from observational to interventional study designs offers the potential for personalized interventions and disease prediction. These findings can guide researchers in navigating the latest developments and shaping the future directions of this field.