Evidence mapPaperPMID 42015346Full record

ReviewGut microbes2026

Gut microbiome and metabolic health: mechanisms and precision interventions.

Zhengrui Li, Sudeshna Samui, Ji'an Liu, Yang Yang, Xue Liu, Qingyu Chen, Jing Li, Divya Gopinath, Peng Luo, Dan Shan

Abstract readReview
In one paragraph

Review in Gut microbes, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Review
  2. Review
  3. Review
  4. Review
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.

Zhengrui LiShanghai Jiao Tong University School of Medicine, Shanghai, People's Republic of China.ORCID 0000-0003-4923-0088
Sudeshna SamuiHooghly Women's College, University of Burdwan, West Bengal, India.
Ji'an LiuShanghai Jiao Tong University School of Medicine, Shanghai, People's Republic of China.
Yang YangHeilongjiang University of Traditional Chinese Medicine, Harbin, People's Republic of China.
Xue LiuShanghai Jiao Tong University School of Medicine, Shanghai, People's Republic of China.
Qingyu ChenThe Second School of Medicine, Wenzhou Medical University, Wenzhou, People's Republic of China.
Jing LiShanghai Stomatological Hospital & School of Stomatology, Fudan University, Shanghai, People's Republic of China.
Divya GopinathBasic Medical and Dental Sciences Department, College of Dentistry, Ajman University, Ajman, UAE.
Peng LuoDepartment of Oncology, Zhujiang Hospital, Southern Medical University, Guangzhou, People's Republic of China.
Dan ShanHealth Innovation One, Sir John Fisher Drive, Lancaster University, Lancaster, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The gut microbiome is increasingly recognized as a fundamental regulator of metabolic health, shaping energy balance, insulin sensitivity, inflammatory tone, and inter-organ communication through a broad spectrum of microbial metabolites that engage host signaling pathways. In this review, we synthesize current mechanistic insights into how gut microbial communities shape metabolic function, with particular emphasis on short-chain fatty acids, secondary bile acid signaling, gut barrier integrity, immune modulation, and the microbiota-gut-brain-pancreas axis. We further summarize disease-associated alterations in microbial composition and function across obesity, type 2 diabetes, metabolic dysfunction-associated steatotic liver disease, and metabolic syndrome, highlighting key microbial and metabolic features that contribute to metabolic dysfunction. Evidence from germ-free models, fecal microbiota transplantation studies, and strain-level interventions suggests that shifts in microbial ecology may causally shape metabolic outcomes. We also critically evaluate emerging microbiome-centered therapeutic strategies, including targeted probiotics, prebiotics, dietary modulation, and fecal microbiota transplantation, while addressing factors that underlie inter-individual variability in treatment responses. In addition, we discuss the growing influence of multi-omics technologies, microbial metabolic modeling, and machine learning approaches in advancing precision microbiome medicine. To integrate these advances within a coherent framework, we outline a precision microbiome intervention pipeline linking multidimensional profiling to functional stratification and targeted therapeutic design. We also introduce a conceptual Precision Microbiome Intervention Triangle to mechanistically explain heterogeneity in responses to microbiome-targeted therapies. Collectively, these insights establish and position the gut microbiome as both a mechanistic driver and a modifiable therapeutic target in metabolic disease, and highlight key challenges and future directions for the development of personalized microbiome-based metabolic interventions.

Indexed as

Gastrointestinal MicrobiomeMetabolic DiseasesAnimalsDiabetes Mellitus, Type 2Fatty Acids, VolatileFecal Microbiota TransplantationHumansMetabolic SyndromeMultiomicsObesityPrebioticsPrecision MedicineProbioticsFatty Acids, VolatilePrebioticsgut barrier functionGut microbiomemetabolic healthmicrobiome-targeted interventionsobesity and type 2 diabetesprecision microbiome medicineshort-chain fatty acids

Identifiers

PMID42015346
PMCPMC13108366

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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 Socratic graph.