Emerging trends and focus for the link between the gastrointestinal microbiome and kidney disease

The clinical value of the relationship between gastrointestinal microbiome imbalance and its corresponding interventions with kidney disease is emerging. This study describes the hotspots and evolution of gastrointestinal microbiome and kidney disease research over the past three decades by scientific collaboration networks and finally predicts future trends in the field through bibliometric analysis and visualization studies. CiteSpace was used to explore the original articles from January 1990 to August 2021 to visualize the knowledge network of journals, countries, institutions, authors, references, and keywords in this field. Publications were extracted from Web of Science Core Collection database using the terms “gastrointestinal microbiome” and “kidney disease” (and their synonyms in MeSH). A total of 2145 publications with 93880 references in 102 journals were included in the analyses. The number of studies combining gastrointestinal microbiomes with kidney diseases has increased significantly over the past two decades. The United States is the leading country in the number of documents, and the leading institution is the Cleveland Clinic. The most landmark articles in the field are on chronic renal failure, L-Carnitin, and cardiovascular disease. The pathogenesis of uremia toxin is an emerging trend in gastrointestinal microbiomes and kidney diseases. In addition, probiotic or synbiotic supplements have strong clinical value in adjusting abnormal intestinal symbiotic environments. This study demonstrates a growing understanding of the interaction between gut microbiota and kidney disease over time. Using microbial supplements to improve the living conditions of kidney disease patients is a promising and hot research focus. Based on publications extracted from the database, this study may provide clinicians and researchers with valuable information to identify potential collaborators and partner institutions and better predict their dynamic progression.