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©The Author(s) 2024. Published by Baishideng Publishing Group Inc. All rights reserved.
Global status and trends of metabolomics in diabetes: A literature visualization knowledge graph study
Hong Li, Liu Li, Qiu-Qing Huang, Si-Yao Yang, Jun-Ju Zou, Fan Xiao, Qin Xiang, Xiu Liu, Rong Yu
Hong Li, Liu Li, Qiu-Qing Huang, Si-Yao Yang, Jun-Ju Zou, College of Chinese Medicine, Hunan University of Chinese Medicine, Changsha 410208, Hunan Province, China
Fan Xiao, College of International Education, Hunan University of Chinese Medicine, Changsha 410208, Hunan Province, China
Qin Xiang, Department of Science and Technology, Hunan University of Chinese Medicine, Changsha 410208, Hunan Province, China
Xiu Liu, Rong Yu, Hunan Key Laboratory of TCM Prescription and Syndromes Translational Medicine, Hunan University of Chinese Medicine, Changsha 410208, Hunan Province, China
Rong Yu, College of Graduate, Hunan University of Chinese Medicine, Hunan Changsha, Hunan Province, China
Co-first authors: Hong Li and Xiu Liu.
Co-corresponding authors: Qin Xiang and Rong Yu.
Author contributions: Li H designed the study; Li H, Liu X, and Xiang Q participated in data processing and statistical analysis; Li H, Liu X, Huang QQ, and Yang SY drafted the manuscript; XF, Xiang Q and Zou JJ contributed to data analysis and interpretation; Xiang Q and Yu R supervised the review of the study; Li H and Liu X contributed equally to this work as co-first authors; Li H and Liu X collaborated closely on basic research related to this study, which inspired the writing of this study. Both authors have made crucial and indispensable contributions towards the completion of the project and thus qualified as the co-first authors of the manuscript; Xiang Q and Yu R have played important and indispensable roles in the data interpretation and manuscript supervision as the co-corresponding authors; Li H and Liu X as co-first authors and Xiang Q, and Yu R as co-corresponding authors, this is fitting for our manuscript as it accurately reflects our team's collaborative spirit, equal contributions, and diversity. all authors seriously revised and approved the final manuscript.
Supported by National Natural Science Foundation of China, No. U21A20411; and the Graduate Research and Innovation Project of Hunan Province, No. CX20220772.
Conflict-of-interest statement: The authors declare that they have no conflict of interest.
PRISMA 2009 Checklist statement: The authors have read the PRISMA 2009 Checklist, and the manuscript was prepared and revised according to the PRISMA 2009 Checklist.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See:
https://creativecommons.org/Licenses/by-nc/4.0/ Corresponding author: Rong Yu, PhD, Professor, Hunan Key Laboratory of TCM Prescription and Syndromes Translational Medicine, Hunan University of Chinese Medicine, No. 300 Bachelor Road, Bachelor Street, Yuelu District, Changsha 410208, Hunan Province, China. 1208466238@qq.com
Received: December 26, 2023
Peer-review started: December 27, 2023
First decision: January 17, 2024
Revised: January 28, 2024
Accepted: March 18, 2024
Article in press: March 18, 2024
Published online: May 15, 2024
Processing time: 136 Days and 8.9 Hours
BACKGROUND
Diabetes is a metabolic disease characterized by hyperglycemia, which has increased the global medical burden and is also the main cause of death in most countries.
AIM
To understand the knowledge structure of global development status, research focus, and future trend of the relationship between diabetes and metabolomics in the past 20 years.
METHODS
The articles about the relationship between diabetes and metabolomics in the Web of Science Core Collection were retrieved from 2002 to October 23, 2023, and the relevant information was analyzed using CiteSpace6.2.2R (CiteSpace), VOSviewer6.1.18 (VOSviewer), and Bibliometrix software under R language.
RESULTS
A total of 3123 publications were included from 2002 to 2022. In the past two decades, the number of publications and citations in this field has continued to increase. The United States, China, Germany, the United Kingdom, and other relevant funds, institutions, and authors have significantly contributed to this field. Scientific Reports and PLoS One are the journals with the most publications and the most citations. Through keyword co-occurrence and cluster analysis, the closely related keywords are "insulin resistance", "risk", "obesity", "oxidative stress", "metabolomics", "metabolites" and "biomarkers". Keyword clustering included cardiovascular disease, gut microbiota, metabonomics, diabetic nephropathy, molecular docking, gestational diabetes mellitus, oxidative stress, and insulin resistance. Burst detection analysis of keyword depicted that "Gene", "microbiota", "validation", "kidney disease", "antioxidant activity", "untargeted metabolomics", "management", and "accumulation" are knowledge frontiers in recent years.
CONCLUSION
The relationship between metabolomics and diabetes is receiving extensive attention. Diabetic nephropathy, diabetic cardiovascular disease, and kidney disease are key diseases for future research in this field. Gut microbiota, molecular docking, and untargeted metabolomics are key research directions in the future. Antioxidant activity, gene, validation, mass spectrometry, management, and accumulation are at the forefront of knowledge frontiers in this field.
Core Tip: Metabolomics is an important method to study diabetes, and we use bibliometrics to reveal the research status and future trends of the two. Through analysis and summary, diabetic nephropathy, diabetic cardiovascular disease, and kidney disease are key diseases for future research in this field. Gut microbiota, molecular docking, and untargeted metabolomics are key research directions in the future. Antioxidant activity, gene, validation, mass spectrometry, management, and accumulation are at the forefront of knowledge frontiers in this field.
