Exercise-Responsive Endocrine, Metabolic and Immune Drug Targets: A Dual-Database Bibliometric and Knowledge-Mapping Analysis
Incretin-based pharmacotherapy — glucagon-like peptide-1 (GLP-1) receptor agonists, dual GIP/GLP-1 co-agonists, and dipeptidyl peptidase-4 (DPP-4) inhibitors — has reshaped the treatment of type 2 diabetes and obesity since 2005. Exercise acts on many of the same endocrine, metabolic and immune targets, yet the interface between exercise-responsive biology and incretin drug targets has never been mapped quantitatively. We conducted a dual-database bibliometric and knowledge-mapping analysis of Web of Science Core Collection and Scopus records (2005–2026) to describe (i) the collaboration structure of the field by author, institution and country; (ii) its intellectual base through document co-citation clustering; and (iii) its emerging fronts through keyword burst detection. Four thousand two hundred sixty unique articles were retained after screening and three-step deduplication. The co-citation network (3,203 nodes; 11,124 edges; modularity Q = 0.9358; weighted mean silhouette S = 0.9508) resolves into 18 clusters that consolidate into six mechanistically coherent thematic domains: exercise-responsive molecular and metabolic targets, pharmacological targets and exercise mimetics, multi-omics target discovery, exerkine secretion dynamics, drug–exercise interactions, and epigenetic–pancreatic endocrine targets. Eight keyword bursts consolidate into three emerging trends: outcome-oriented epidemiology, renal and haemodynamic endpoint validation, and lifestyle-integrated combination care. This registration freezes the search strings, inclusion and exclusion criteria, deduplication algorithm, entity-normalisation rules and analysis parameters; the analysis scripts are deposited with the registration. Registration type: Open-Ended Registration. Bibliographic data were retrieved on 10 October 2026 and the analyses were completed before this registration was submitted; the registration documents the research questions, data pipeline and analysis plan as implemented, and no analytic decision was modified after results were observed.
Authors
- Liang Shuai (ORCID: https://orcid.org/0009-0003-2427-3206)
Publication Details
- Journal
- Open Science Framework
- Published
- 2026-10-27
- DOI
- https://doi.org/10.17605/osf.io/hdj62
- Primary Topic
- Diabetes Treatment and Management
- Type
- article
- Field-Weighted Citation Impact
- 0.00