Kidney diseases and single-cell sequencing research: a bibliometric analysis from 2015 to 2024 - Yaotan Li; Jinyi Hou; Xinghua Zhang; Xiaochang Wu; Shijia Lin; Weijing Liu; Yaoxian Wang; Huijuan Zheng (Renal Failure)
Background Single-cell RNA sequencing (scRNA-seq) has revolutionized kidney disease research by enabling high-resolution transcriptomic analysis at the cellular level. This technology can overcome the limitations of traditional bulk-sequencing; reveal disease-progression trajectories, intercellular communication networks, and cellular heterogeneity; and provide crucial insights into disease mechanisms, thereby facilitating the development of targeted therapies and personalized treatment strategies. We conducted a bibliometric analysis of publications describing the use of scRNA-seq in kidney disease research from 2015 to 2024 using the Web of Science Core Collection (WoSCC) database. Data analysis was performed using the R packages Bibliometrix, VOSviewer, and CiteSpace to systematically evaluate the research landscape and emerging trends.Results A total of 1,210 publications on scRNA-seq in kidney diseases were identified. China was the largest contributor among the participating countries, demonstrating consistent annual growth in publication numbers. The major research institutions were Harvard Medical School, Sun Yat-sen University, and Shanghai Jiao Tong University. Most articles in this field were published by Frontiers in Immunology. In a list of 8,984 authors, the most productive authors were B. D. Humphreys, Haojia Wu, and Matthias Kretzler. The dominant categories identified in this search were scRNA-seq, disease progression/mechanisms, and gene regulation/expression. Several budding areas of investigation were also noted, including immunotherapy and scRNA-seq innovations, which allude to active evolution in the field.Conclusion This bibliometric analysis revealed the rapid growth and evolving landscape of scRNA-seq applications in kidney disease research and highlighted promising opportunities for understanding disease mechanisms and developing personalized therapeutic strategies.