Visualization of the relationship between metabolism and lung diseases from the perspective of bibliometric analysis: research trends and future prospects

Abstract

Background: Extensive research has examined the role of metabolism in lung disease development, yet a comprehensive literature review remains absent despite numerous publications.

Objective: This study aims to visualize and assess the advancements in research on metabolism and its role in lung diseases.

Methods: Publications from January 1, 1991, to April 30, 2024, related to lung diseases and metabolism were sourced from the Web of Science Core Collection and analyzed using CiteSpace 6.2.R4, VOSviewer 1.6.19, Bibliometrix, R Studio, and various online tools.

Results: A total of 1,542 studies were collected and processed through these platforms for literature analysis and data visualization. The analysis revealed a sharp increase in annual publications on metabolism and lung diseases, with the United States and China emerging as leading contributors. Current research trends highlight a shift toward investigating metabolic reprogramming of immune cells in the context of lung diseases. Moreover, genes such as TNF, DIF, AKT1, INS, IL-6, CXCL8, IL-1β, TP53, NF-κB1, MTOR, IFNG, TGF-β1, HIF1α, VEGFA, IL-10, NFE2L2, PPARG, AKT, CRP, STAT3, and CD4 have received significant attention in this research domain. Employing a bibliometric approach, this study offers a comprehensive and objective examination of the knowledge landscape, shedding light on the evolving trends in this field. The findings serve as a valuable resource for researchers, offering a clearer perspective on the advancements in metabolism-related lung disease studies.

Keywords: CiteSpace; VOSviewer; bibliometrics; cell metabolism; lung diseases.

Figure 1

Research process and screening objectives.

Figure 2

Annual number of publications of articles on lung diseases and metabolism, 2000–2024. (A) To analyze the annual growth trend of the top ten countries in the number of articles published on the online analysis platform of metrology on lung diseases and metabolism from 2000 to 2024. (B) Analysis of international cooperation between different countries. (C) Visualization analysis of country scientific production.

Figure 3

Collaborative visualization maps generated by VOSviewer for the top 58 institutions in terms of publication volume.

Figure 4

Network map of the authors’ collaborative analysis of pulmonary disease and metabolism 1991–2024.

Figure 5

Analysis of reference co-citation and burst references. (A) Visualization of the literature co-citation analysis network constructed by CiteSpace. (B) Top 10 articles with a spike in citations. The red segments correspond to the start and end years of the outbreak duration.

Figure 6

Analysis of co-occurrence and burst keywords. (A) VOSviewer keyword visualization map. Keywords are represented by labeled circles. The size of the circles and labels is proportional to the keyword frequency, and circles of the same color belong to the same cluster. Visualization of keyword co-occurrence analysis density. The heatmap visually represents the frequency of keywords by using a range of color shades. Intense red shading indicates active study areas where keywords occur more frequently, while cooler yellow shading indicates inactive areas where keywords occur less frequently. (B) Visualization of keyword co-occurrence analysis density. The heatmap visually represents the temporal changes in the occurrence of keywords by using a series of colors. (C) Top 25 most frequently used keywords in the research field.

Figure 7

Analysis of hot spot genes. (A) The top 21 most studied genes at the intersection of lung disease and metabolism, using online tools to construct gene interaction networks. (B) Bar graphs show the GO enrichment analysis of these top related genes.