Evidence map›Paper›PMID 42528737›Full record

SynthesisFrontiers in clinical diabetes and healthcare2026

Global research landscape and trends of metabolomics in diabetic kidney disease: focus on immunometabolic interactions.

Yuting Li, Changlin Li, Jiamin Duan, Qingli Yang, Jing Zhang, Duo Yu, Yuwei Chen, Jianing Ni, Xiaomeng Lin, Xudong Cai

Abstract readSystematic Review
In one paragraph

Synthesis in Frontiers in clinical diabetes and healthcare, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Yuting LiNingbo Municipal Hospital of Traditional Chinese Medicine (TCM), Affiliated Hospital of Zhejiang Chinese Medical University, Ningbo, Zhejiang, China.
Changlin LiNingbo Municipal Hospital of Traditional Chinese Medicine (TCM), Affiliated Hospital of Zhejiang Chinese Medical University, Ningbo, Zhejiang, China.
Jiamin DuanNingbo Municipal Hospital of Traditional Chinese Medicine (TCM), Affiliated Hospital of Zhejiang Chinese Medical University, Ningbo, Zhejiang, China.
Qingli YangNingbo Municipal Hospital of Traditional Chinese Medicine (TCM), Affiliated Hospital of Zhejiang Chinese Medical University, Ningbo, Zhejiang, China.
Jing ZhangNingbo Municipal Hospital of Traditional Chinese Medicine (TCM), Affiliated Hospital of Zhejiang Chinese Medical University, Ningbo, Zhejiang, China.
Duo YuNingbo Municipal Hospital of Traditional Chinese Medicine (TCM), Affiliated Hospital of Zhejiang Chinese Medical University, Ningbo, Zhejiang, China.
Yuwei ChenNingbo Municipal Hospital of Traditional Chinese Medicine (TCM), Affiliated Hospital of Zhejiang Chinese Medical University, Ningbo, Zhejiang, China.
Jianing NiNingbo Municipal Hospital of Traditional Chinese Medicine (TCM), Affiliated Hospital of Zhejiang Chinese Medical University, Ningbo, Zhejiang, China.
Xiaomeng LinNingbo Municipal Hospital of Traditional Chinese Medicine (TCM), Affiliated Hospital of Zhejiang Chinese Medical University, Ningbo, Zhejiang, China.
Xudong CaiNingbo Municipal Hospital of Traditional Chinese Medicine (TCM), Affiliated Hospital of Zhejiang Chinese Medical University, Ningbo, Zhejiang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Diabetic kidney disease (DKD), a devastating microvascular complication of diabetes mellitus, arises from intricate crosstalk between metabolic disorders and immune dysregulation. Metabolomics has emerged as a powerful tool to unravel the immunometabolic mechanisms underlying DKD, facilitating early disease diagnosis, mechanistic pathway interpretation, and therapeutic biomarker discovery. This study aimed to systematically delineate the global research landscape and evolutionary trends of DKD metabolomics, with a key emphasis on immunometabolic interactions. Methods: Relevant publications on DKD metabolomics published between 2015 and 2025 were comprehensively retrieved from the Web of Science Core Collection and PubMed databases. Multiple bibliometric and visualisation tools, including CiteSpace and the online bibliometric platform (https://bibliometric.com/), were utilised for data processing, visual mapping, and integrated quantitative and qualitative analysis. Results: A total of 1,410 eligible articles were included in the final analysis, among which 1,110 were sourced from the Web of Science and 299 from PubMed, demonstrating a sustained annual growth in publication volume. China contributed the largest number of publications (663 articles), followed by the United States (207 articles). The University of Michigan and Shandong University were the most productive research institutions. Li Ping and Sharma Kumar were identified as the leading productive and highly cited authors, respectively, with Kidney International recognised as the flagship journal in this research field. Keyword co-occurrence and co-citation analyses confirmed that DKD pathogenesis is predominantly governed by immunometabolic crosstalk. Specifically, renal lipotoxicity, oxidative stress, and insulin resistance trigger persistent renal inflammatory responses, while aberrant glucose metabolism, amino acid dysfunction, and gut microbiota disturbance disrupt renal immune homeostasis via the gut-kidney axis. Branched-chain amino acids and gut microbiota-derived metabolites serve as pivotal immunometabolic biomarkers. Clinical trial data from PubMed further validate the potential applications of these biomarkers, alongside the functional roles of immune regulatory molecules and their correlations with pathological alterations in DKD. Conclusions: This bibliometric study systematically profiles the global research panorama of DKD metabolomics with a focus on immunometabolic regulation. It consolidates well-established research domains covering lipid- and oxidative stress-induced immune disorders, and further identifies amino acid metabolism-related immunomodulation as a burgeoning research frontier. These findings establish a refined research roadmap for future mechanistic investigations and the development of targeted immunometabolic therapeutic strategies for DKD.

Indexed as

citespacediabetic kidney diseaseinflammationmetabolomicspubmedweb of science

Identifiers

PMID42528737
PMCPMC13414803

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.