Global trends in endothelial cell senescence research in cardiovascular diseases: A multi-tool bibliometric analysis (2001–2024)
Yan Zhao, Lingling Xie, Tingting Chen, Shishi Huang, Yuqing Pan, Yuxin Shang, Wei MaoBackground:
Cardiovascular diseases (CVDs) remain the leading cause of death worldwide, and endothelial cell senescence (EC senescence) is increasingly recognized as a key driver of vascular dysfunction and age-related cardiovascular pathology. Although recent studies have clarified the molecular mechanisms and therapeutic potential of EC senescence in CVDs, a dedicated bibliometric analysis of this field is still lacking. This study aimed to map the global research landscape, identify major contributors and influential sources, and reveal evolving hotspots and emerging frontiers from 2001 to 2024.
Methods:
Publications on EC senescence in CVDs were retrieved from the Web of Science Core Collection (WoSCC) using a topic-based search strategy. Bibliometric analyses and visualizations were performed using CiteSpace, VOSviewer, and the R package Bibliometrix.
Results:
A total of 1679 papers were analyzed, with China and the United States collectively accounting for nearly half of the global output. Zoltan Ungvari was the most prolific author and one of the most influential co-cited researchers in this field. The journals publishing the largest number of articles in this field were the International Journal of Molecular Sciences, Aging Cell, and PLOS ONE. The 5 most productive institutions were Sun Yat-sen University, the University of Oklahoma, Huazhong University of Science and Technology, Semmelweis University, and Southern Medical University. High-frequency keywords identified “oxidative stress” and “inflammation” as the primary mechanistic themes. Temporal trends indicated a progressive shift in research emphasis from fundamental mechanisms to translational applications.
Conclusion:
This study shows that research in this field has grown rapidly, although a substantial translational gap remains. In the future, the integration of single-cell multi-omics and artificial intelligence may help accelerate the clinical translation of senolytics and extracellular vesicle-based therapies.