Evidence map›Paper›PMID 40979718›Full record

ReviewFrontiers in endocrinology2025

Metabolomics uncovers the diabetes metabolic network: from pathophysiological mechanisms to clinical applications.

Zijie Xu, Yujia Zhou, Ruijie Xie, Zhongxing Ning

Abstract readReview
In one paragraph

Review in Frontiers in endocrinology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed, 1 pooled it
–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

17 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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

4 authors.

Zijie XuGuangxi Hospital Division of The First Affiliated Hospital, Sun Yat-sen University, Nanning, China.
Yujia ZhouDepartment of Infectious Diseases and Public Health, City University of Hong Kong, Hong Kong, Hong Kong SAR, China.
Ruijie XieFaculty of Medicine, Heidelberg University, Heidelberg, Germany.
Zhongxing NingGuangxi Hospital Division of The First Affiliated Hospital, Sun Yat-sen University, Nanning, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Diabetes mellitus (DM) represents a complex metabolic disorder posing urgent diagnostic and therapeutic challenges worldwide. Traditional biomarkers such as HbA1c and OGTT fail to capture the dynamic nature of metabolic remodeling underlying DM pathophysiology. Metabolomics, by offering real-time, systems-level insights into small-molecule dynamics, has emerged as a promising strategy for both early disease detection and therapeutic target discovery. Recent studies have highlighted the diagnostic and prognostic value of metabolites, including branched-chain amino acids, lipid derivatives, and bile acids. Despite its immense potential, the clinical application of metabolomics remains hindered by technical limitations, such as cross-cohort standardization and data interpretation complexity. Future advances integrating artificial intelligence and multi-omics strategies may transform metabolomics from an exploratory tool to a clinical mainstay in diabetes management. This review offers a comprehensive synthesis of recent advances in metabolomics-driven diabetes research, with a particular focus on elucidating key metabolic pathways, identifying emerging biomarkers, and exploring translational opportunities. To fully realize the clinical potential of metabolomics, further efforts toward analytical standardization, cross-cohort validation, and the integration of artificial intelligence-powered tools will be essential to bridge the gap from bench to bedside in diabetes care.

Indexed as

Diabetes MellitusMetabolic Networks and PathwaysMetabolomicsAnimalsArtificial IntelligenceBiomarkersHumansBiomarkersbiomarkersclinical translationdiabetes mellitusmetabolic reprogrammingmetabolomicsprecision medicine

Identifiers

PMID40979718
PMCPMC12443576

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.