Evidence map›Paper›PMID 40625623›Full record

ArticleFrontiers in microbiology2025

Network pharmacology-based insights into the role of gut microbiota metabolites in insulin resistance.

Bing Xiao, Xin Chen, Ruiyu Zong, Yiming Guan, Zhu Zhu, Siling Bi

Abstract read
In one paragraph

Article in Frontiers in microbiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

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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

2 citing papers in PubMed.

  1. Article
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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

6 authors.

Bing Xiao *College of Acupuncture and Massage, Shandong University of Traditional Chinese Medicine, Jinan, China.
Xin Chen *College of Acupuncture and Massage, Shandong University of Traditional Chinese Medicine, Jinan, China.
Ruiyu ZongCollege of Acupuncture and Massage, Shandong University of Traditional Chinese Medicine, Jinan, China.
Yiming GuanCollege of Health Sciences, Shandong University of Traditional Chinese Medicine, Jinan, China.
Zhu ZhuCollege of Acupuncture and Massage, Shandong University of Traditional Chinese Medicine, Jinan, China.
Siling BiMedical College, Shandong University of Traditional Chinese Medicine, Jinan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Extensive research has demonstrated that the gut microbiota plays a critical role in maintaining homeostasis and promoting overall human health. However, the pharmacological mechanisms and functional roles of gut microbiota metabolites remain insufficiently understood. This study employs a network pharmacology approach to elucidate the metabolic transformation processes of gut microbiota metabolites and their molecular mechanisms in the pathogenesis of insulin resistance (IR), aiming to uncover the complex interactions among gut microbiota, metabolites, and therapeutic targets. Methods: Gut microbiota metabolites and their corresponding target genes were retrieved from the gutMGene database. Potential targets of the metabolites were predicted using the SEA and STP databases. Disease-related targets for insulin resistance were collected from the GeneCards, DisGeNET, and OMIM databases. Core targets were identified via a protein-protein interaction (PPI) network, followed by comprehensive GO and KEGG enrichment analyses. Finally, a network illustrating the relationship among microbiota-substrate-metabolite-target was established. Results: Thirteen overlapping targets between the gut microbiota and insulin resistance were identified, among which IL6, JUN, and PPARG were recognized as hub genes. The MSMT (microbiota-substrate-metabolite-target) network revealed that these three hub genes exert therapeutic effects through 10 gut microbiota metabolites, 10 substrates, and 21 microbial species. KEGG pathway analysis indicated that the IL-17, Toll-like receptor, HIF-1, NOD-like receptor, TNF, and VEGF signaling pathways are the primary pathways involved in the pathogenesis of IR. Conclusion: Gut microbiota metabolites may exert therapeutic effects on insulin resistance primarily through the targets IL6, JUN, and PPARG. The regulatory mechanisms are likely associated with several key signaling pathways, including the IL-17, Toll-like receptor and HIF-1, pathways. These three pathways collectively form an interconnected inflammation-metabolism-hypoxia network. Targeting key nodes within this network-such as the IL-17 receptor, TLR4, or HIF-1α-may offer a multidimensional therapeutic strategy for insulin resistance (IR) and its associated complications.

Indexed as

gut microbiotagut microbiota metabolitesinsulin resistancemolecular mechanismnetwork pharmacology

Identifiers

PMID40625623
PMCPMC12233160

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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.