Evidence map›Paper›PMID 42539659›Full record

ReviewFrontiers in immunology2026

Frontier research and clinical application prospects of microbiome biomarkers in autoimmune diseases.

Qianqian He, Pinjun Zhang, Zhenni Chen, Chengping Wen, Mingzhu Wang

Abstract readReview
In one paragraph

Review in Frontiers in immunology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

5 authors.

Qianqian He *Research Institute of Chinese Medical Clinical Foundation and Immunology, School of Basic Medical Science, Zhejiang Chinese Medical University, Hangzhou, China.
Pinjun Zhang *Research Institute of Chinese Medical Clinical Foundation and Immunology, School of Basic Medical Science, Zhejiang Chinese Medical University, Hangzhou, China.
Zhenni Chen *Research Institute of Chinese Medical Clinical Foundation and Immunology, School of Basic Medical Science, Zhejiang Chinese Medical University, Hangzhou, China.
Chengping WenResearch Institute of Chinese Medical Clinical Foundation and Immunology, School of Basic Medical Science, Zhejiang Chinese Medical University, Hangzhou, China.
Mingzhu WangResearch Institute of Chinese Medical Clinical Foundation and Immunology, School of Basic Medical Science, Zhejiang Chinese Medical University, Hangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The microbiome is increasingly recognized as a master regulator of immune homeostasis and a key environmental factor associated with the pathogenesis of autoimmune diseases (ADs). This review comprehensively synthesizes current knowledge on how microbial communities and their metabolites may contribute to ADs' development through microbial-immune interactions, dysbiosis, and the involvement of viral and fungal components within an integrated inter-kingdom ecosystem. We propose an operational definition of microbiome biomarkers as measurable microbiome-associated features reflecting disease susceptibility, activity, prognosis, or therapeutic response and categorize them into three classes: taxonomic, functional/metabolic, and host-microbiome interaction-derived biomarkers. We critically evaluate the evidence for specific microbial signatures as biomarkers for early diagnosis, disease monitoring, and prediction of therapeutic responses, incorporating evidence grading that distinguishes validated biomarkers from those that remain exploratory and discussing shared versus disease-specific signatures across ADs. The translational potential of microbiome-targeted interventions, including probiotics, prebiotics, and fecal microbiota transplantation, is examined within a personalized medicine framework, with barriers to clinical implementation explicitly addressed. Key confounding factors such as diet, geographic origin, and medication use are highlighted as critical variables shaping microbiome signatures independently of disease. Looking forward, the convergence of multi-omics technologies and artificial intelligence for biomarker discovery, multi-omics integration, and clinical validation promises to unravel the complex microbiome-immune crosstalk, enabling more accurate diagnosis, prognostic stratification, and ultimately, individualized microbiota-informed therapy.

Indexed as

Autoimmune DiseasesMicrobiotaAnimalsBiomarkersDysbiosisHumansMultiomicsPrecision MedicineBiomarkersautoimmune diseasesbiomarkersclinical translationmicrobiomeprecision medicine

Identifiers

PMID42539659
PMCPMC13423975

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.