{"title":"Decoding precision medicine in prediabetes: a citespace-based bibliometric analysis of current trends and future directions","authors":"Manru Xu, Hanyue Gan, Furong Zhong, Mengyuan Qiao, Pan Ren, Yue Zhu, Qi Wang, Wenbin Wu","doi":"10.1186/s43088-026-00762-x","DOIUrl":null,"url":null,"abstract":"<div><h3>Background</h3><p>Prediabetes is characterized by its high global prevalence and significant risk of progression to diabetes. The current research focus lies in precise risk stratification and intervention, wherein precision medicine plays a critical role by integrating multi-omics data with clinical information. This study examines how precision medicine concepts, including risk stratification, biomarker-guided subtyping, and individualized intervention, have progressively permeated prediabetes research, acknowledging that these ideas often integrate with, rather than replace, traditional prevention frameworks.</p><h3>Methods</h3><p>Publications were retrieved from the Web of Science Core Collection (WoSCC). Visualization and quantitative analyses were conducted using CiteSpace 6.4.R1 and VOSviewer 1.6.20.</p><h3>Result</h3><p>A total of 103 publications were included, involving 607 authors from 347 institutions across 50 countries/regions. The USA led in publication volume and international collaboration, with Harvard Medical School and the University of Copenhagen emerging as the most influential institutions. Journals with high impact factors, such as The Lancet Diabetes and Endocrinology and The New England Journal of Medicine, accounted for a substantial share of citations in this corpus. Keyword co-occurrence and burst analyses revealed that research hotspots have shifted from metabolic risk factors such as hypertension and impaired glucose tolerance toward insulin resistance, genetic biomarkers, precision nutrition, and artificial intelligence–assisted patient stratification.</p><h3>Conclusions</h3><p>Current research emphasizes individualized intervention strategies supported by multi-omics technologies, continuous glucose monitoring, and artificial intelligence. Future efforts should focus on integrating dynamic biomarkers and personalized nutrition into scalable precision prevention frameworks, offering new avenues for early diagnosis, timely treatment, and stratified interventions in prediabetes.</p></div>","PeriodicalId":481,"journal":{"name":"Beni-Suef University Journal of Basic and Applied Sciences","volume":"15 1","pages":""},"PeriodicalIF":2.6000,"publicationDate":"2026-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1186/s43088-026-00762-x.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Beni-Suef University Journal of Basic and Applied Sciences","FirstCategoryId":"1085","ListUrlMain":"https://link.springer.com/article/10.1186/s43088-026-00762-x","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
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Abstract
Background
Prediabetes is characterized by its high global prevalence and significant risk of progression to diabetes. The current research focus lies in precise risk stratification and intervention, wherein precision medicine plays a critical role by integrating multi-omics data with clinical information. This study examines how precision medicine concepts, including risk stratification, biomarker-guided subtyping, and individualized intervention, have progressively permeated prediabetes research, acknowledging that these ideas often integrate with, rather than replace, traditional prevention frameworks.
Methods
Publications were retrieved from the Web of Science Core Collection (WoSCC). Visualization and quantitative analyses were conducted using CiteSpace 6.4.R1 and VOSviewer 1.6.20.
Result
A total of 103 publications were included, involving 607 authors from 347 institutions across 50 countries/regions. The USA led in publication volume and international collaboration, with Harvard Medical School and the University of Copenhagen emerging as the most influential institutions. Journals with high impact factors, such as The Lancet Diabetes and Endocrinology and The New England Journal of Medicine, accounted for a substantial share of citations in this corpus. Keyword co-occurrence and burst analyses revealed that research hotspots have shifted from metabolic risk factors such as hypertension and impaired glucose tolerance toward insulin resistance, genetic biomarkers, precision nutrition, and artificial intelligence–assisted patient stratification.
Conclusions
Current research emphasizes individualized intervention strategies supported by multi-omics technologies, continuous glucose monitoring, and artificial intelligence. Future efforts should focus on integrating dynamic biomarkers and personalized nutrition into scalable precision prevention frameworks, offering new avenues for early diagnosis, timely treatment, and stratified interventions in prediabetes.
期刊介绍：
Beni-Suef University Journal of Basic and Applied Sciences (BJBAS) is a peer-reviewed, open-access journal. This journal welcomes submissions of original research, literature reviews, and editorials in its respected fields of fundamental science, applied science (with a particular focus on the fields of applied nanotechnology and biotechnology), medical sciences, pharmaceutical sciences, and engineering. The multidisciplinary aspects of the journal encourage global collaboration between researchers in multiple fields and provide cross-disciplinary dissemination of findings.
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