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Record W4413035034 · doi:10.3389/fimmu.2025.1619160

Changes in the Subdoligranulum genus in patients with autoimmune disease: a systematic review and meta-analysis

2025· review· en· W4413035034 on OpenAlexaboutno aff
Lu Shen, Ying Zhao, Shuting Liu, Shangfeng Li, Shuang Li, Tao‐Hsin Tung, Bo Shen

Bibliographic record

VenueFrontiers in Immunology · 2025
Typereview
Languageen
FieldMedicine
TopicSalivary Gland Disorders and Functions
Canadian institutionsnot available
Fundersnot available
KeywordsMeta-analysisMedicineCritical appraisalAutoimmune diseaseDiseaseImmunologyMicrobiomeInflammatory bowel diseaseInternal medicineBioinformaticsBiologyAlternative medicinePathology

Abstract

fetched live from OpenAlex

Background Autoimmune diseases have different pathogenic mechanisms but share underlying patterns of gut microbiome perturbation and intestinal barrier dysfunction. Recent evidence suggests that an arthritogenic strain of Subdoligranulum causes a local inflammatory response in the gut. Therefore, the aim of this review was to systematically summarize the relationships between Subdoligranulum and multiple autoimmune diseases. Objective To evaluate the changes of Subdoligranulum in different autoimmune diseases. Methods Four databases, including PubMed, Cochrane, Web of Science, and Embase, were searched up to June 17, 2025, to identify studies that detected Subdoligranulum in autoimmune diseases. A meta-analysis was conducted to compare the differences in Subdoligranulum between healthy people and patients with autoimmune diseases, and the changes in these bacteria under different treatments were compared for similar diseases. The relationships between Subdoligranulum and inflammation-related biomarkers were also analyzed. Study selection We included articles that addressed both autoimmune diseases without intervention and the detection of Subdoligranulum in feces, and we presented a description of changes in bacteria in patients and healthy controls. Quality assessment We used the Newcastle–Ottawa Scale (NOS) to independently assess the methodological quality of the case–control studies. The Journal of Biomedical Informatics (JBI) critical appraisal checklists were utilized to assess the quality and risk of bias in cross-sectional studies. Results Twelve studies were included. These studies were conducted in four different countries and included a total of 1,792 participants (patients with autoimmune disease and healthy controls). Our meta-analysis results indicate that, compared with healthy controls, most patients with autoimmune diseases included in the study had lower levels of Subdoligranulum ( p = 0.027). In addition, it was found that bacteria were associated with several inflammation-related biomarkers. For example, bacterial levels were positively correlated with C-reactive protein (CRP), lipopolysaccharide (LPS)-binding protein (LBP), and Treg cells. However, the levels were negatively correlated with IL-8. These relationships may underlie both the occurrence and development of autoimmune diseases. Conclusion The abundance of Subdoligranulum in patients with organ-specific autoimmune diseases was decreased, whereas no consistent findings were observed for systemic autoimmune diseases. Systematic review registration https://www.crd.york.ac.uk/PROSPERO/view/CRD42024543767 , identifier CRD42024543767.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.853
Threshold uncertainty score0.856

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0070.001
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.022
GPT teacher head0.275
Teacher spread0.254 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

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