Global trends in research on miRNA-microbiome interaction from 2011 to 2021: A bibliometric analysis

Abstract

An increasing number of research suggests that the microRNA (miRNA)-microbiome interaction plays an essential role in host health and diseases. This bibliometric analysis aimed to identify the status of global scientific output, research hotspots, and frontiers regarding the study of miRNA-microbiome interaction over the past decade. We retrieved miRNA-microbiome-related studies published from 2011 to 2021 from the Web of Science Core Collection database; the R package bibliometrix was used to analyze bibliometric indicators, and VOSviewer was used to visualize the field status, hotspots, and research trends of miRNA-microbiome interplay. In total, 590 articles and reviews were collected. A visual analysis of the results showed that significant increase in the number of publications over time. China produced the most papers, and the United States contributed the highest number of citations. Shanghai Jiaotong University and the University of California Davis were the most active institutions in the field. Most publications were published in the areas of biochemistry and molecular biology. Yu Aiming was the most prolific writer, as indicated by the h-index and m-index, and Liu Shirong was the most commonly co-cited author. A paper published in the International Journal of Molecular Sciences in 2017 had the highest number of citations. The keywords "expression" and "gut microbiota" appeared most frequently, and the top three groups of diseases that appeared among keywords were cancer (colorectal, et al.), inflammatory bowel disease (Crohn's disease and ulcerative colitis), and neurological disorders (anxiety, Parkinson's disease, et al.). This bibliometric study revealed that most studies have focused on miRNAs (e.g., miR-21, miR-155, and miR-146a), gut microbes (e.g., Escherichia coli, Bifidobacterium, and Fusobacterium nucleatum), and gut bacteria metabolites (e.g., butyric acid), which have the potential to improve the diagnosis, treatment, and prognosis of diseases. We found that therapeutic strategies targeting the miRNA-microbiome axis focus on miRNA drugs produced in vitro; however, some studies suggest that in vivo fermentation can greatly increase the stability and reduce the degradation of miRNA. Therefore, this method is worthy of further research.

Keywords: VOSviewer; bibliometrics; bibliometrix; interaction; miRNA-microbiome.

FIGURE 1

Trends of global publications on the topic of miRNA-microbiome interaction. (A) Annual publication output from 2011 to 2021. (B) Logistic regression model of growth trends in publications.

FIGURE 2

Countries contributing to the study of miRNA-microbiome interaction. (A) Distribution of countries in this area on a global map. The darker the blue, the more the number of documents produced by the country. (B) The number of publications of the top 15 countries. (C) Total number of citations of relevant papers from the 15 leading countries.

FIGURE 3

VOSviewer’s network analysis of country and institution co-authorship. The width of the lines represents the strength of the connection. (A) The co-authorship analysis of countries with more than five publications. (B) The co-authorship analysis of institutions with more than four publications.

FIGURE 4

VOSviewer’s network analysis of co-cited journals with more than 50 publications. The node size represents the number of journal papers. The larger the node, the more journal papers.

FIGURE 5

Analysis of authors focus on miRNA-microbiome interaction research. (A) VOSviewer’s network analysis of authors’ co-citation with more than 25 citations by VOSviewer. (B) Top 15 authors in the number of publications. (C) Top 15 authors in total citations. (D) Top 15 authors in h-index of publications. (E) Top 15 authors in m-index of publication.

FIGURE 6

(A) VOSviewer’s network analysis of documents’ citation with more than 50 citations. (B) VOSviewer’s network analysis of references’ co-citation with more than 20 citations.

FIGURE 7

Keyword co-occurrence and cluster analysis. (A) VOSviewer’s network analysis of keywords. Distribution of keywords according to the mean frequency of appearance. (B) The clustering map based on occurrence analysis was divided into seven parts.

FIGURE 8

The mechanisms of interplay between miRNA and the microbiome. (A) Host-derived miRNA influences microbiota. Mature miRNAs from intestinal epithelial cells can enter microbiota in the form of fecal miRNA or exosomal miRNA. By regulating gene transcription in microbiota, miRNA affects microbial growth, thereby shaping the microbiota. (B) Microbiota influences host miRNA. Microbiota and microbiota-derived metabolites regulate miRNA expression, possibly through toll-like receptor/Myd88-dependent pathways. Moreover, microbiota-derived extracellular vesicle can modulate gut barrier function and the immune response directly.