Computational biology and chemistry · 2026
Knowledge mapping of cholestatic liver disease and TGR5 research: A bibliometric study of trends and frontiers.
СтатьяНазвание и аннотация: Перевод в очереди
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Tang Yinpei, Qi Fangqing, Yu Yuchun, Fu Yaping, Zhu Pingsheng
Аннотация
OBJECTIVE: This study aims to provide a comprehensive bibliometric analysis of global research trends surrounding TGR5 in cholestatic liver diseases from 2006 to 2025, with the objective of elucidating publication outputs, geographic and institutional contributions, collaborative networks, journal co-citation analysis and reference co-citation mapping, key research themes, and emerging frontiers.
METHODS: Bibliographic data were retrieved from the Web of Science Core Collection (WoSCC) and supplemented by validation against Scopus and PubMed to mitigate database selection bias.Analyses were performed using CiteSpace (version 6.2.R2), VOSviewer (version 1.6.20), and the bibliometrix R package. Performance analysis was employed to evaluate productivity and impact across countries, institutions, and authors. Advanced science mapping techniques, including Thematic Map analysis, network topology metrics, and citation burst detection, were conducted to provide deeper computational and systems-level biological insights.
RESULTS: A total of 418 publications were included. Annual publications showed a steady upward trend, with the United States leading in productivity (n = 138), total citations (n = 14,638), and H-index (59), followed by China with high output but relatively lower citation impact. European countries, notably Italy and Germany, demonstrated strong collaborative networks and influence relative to output volume. Keyword and thematic analyses revealed a shift from molecular mechanisms to clinical applications and, more recently, to gut microbiota and metabolic interactions. Major research clusters encompassed bile acid receptors, gut-liver axis mechanisms, and metabolic disorders. Quantitative network analysis revealed a modularity of 0.8238 and mean silhouette of 0.96, indicating well-defined cluster structures. Although prominent research groups were identified, international collaboration remained limited.
CONCLUSION: The study illustrates the dynamic and evolving nature of TGR5 research, marked by a transition from basic science to translational and systems-level approaches. As the first comprehensive bibliometric and systems-level mapping analysis of TGR5 research in cholestatic liver diseases, this study uniquely integrates computational network analysis with microbiome-host interaction frameworks.While research productivity continues to grow, future efforts would benefit from enhanced international collaboration, microbiome engineering, systems medicine, biomarker discovery, and AI-integrated hepatology research. These findings provide valuable insights for researchers and policymakers aiming to navigate and advance this promising field.
METHODS: Bibliographic data were retrieved from the Web of Science Core Collection (WoSCC) and supplemented by validation against Scopus and PubMed to mitigate database selection bias.Analyses were performed using CiteSpace (version 6.2.R2), VOSviewer (version 1.6.20), and the bibliometrix R package. Performance analysis was employed to evaluate productivity and impact across countries, institutions, and authors. Advanced science mapping techniques, including Thematic Map analysis, network topology metrics, and citation burst detection, were conducted to provide deeper computational and systems-level biological insights.
RESULTS: A total of 418 publications were included. Annual publications showed a steady upward trend, with the United States leading in productivity (n = 138), total citations (n = 14,638), and H-index (59), followed by China with high output but relatively lower citation impact. European countries, notably Italy and Germany, demonstrated strong collaborative networks and influence relative to output volume. Keyword and thematic analyses revealed a shift from molecular mechanisms to clinical applications and, more recently, to gut microbiota and metabolic interactions. Major research clusters encompassed bile acid receptors, gut-liver axis mechanisms, and metabolic disorders. Quantitative network analysis revealed a modularity of 0.8238 and mean silhouette of 0.96, indicating well-defined cluster structures. Although prominent research groups were identified, international collaboration remained limited.
CONCLUSION: The study illustrates the dynamic and evolving nature of TGR5 research, marked by a transition from basic science to translational and systems-level approaches. As the first comprehensive bibliometric and systems-level mapping analysis of TGR5 research in cholestatic liver diseases, this study uniquely integrates computational network analysis with microbiome-host interaction frameworks.While research productivity continues to grow, future efforts would benefit from enhanced international collaboration, microbiome engineering, systems medicine, biomarker discovery, and AI-integrated hepatology research. These findings provide valuable insights for researchers and policymakers aiming to navigate and advance this promising field.