Evidence map›Paper›PMID 34517888›Full record

ArticleGenome medicine2021

Gut microbial determinants of clinically important improvement in patients with rheumatoid arthritis.

Vinod K Gupta, Kevin Y Cunningham, Benjamin Hur, Utpal Bakshi, Harvey Huang, Kenneth J Warrington, Veena Taneja, Elena Myasoedova, John M Davis, Jaeyun Sung

Open access · goldAbstract read
In one paragraph

Article in Genome medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 50 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
50citing papers in PubMed, 4 pooled it
6.5field-weighted citation impact, top 2% of its field
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

50 citing papers in PubMed, 4 syntheses or guidelines pooled it, 100 citations in OpenAlex.

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  6. Impact of oral administration of single strainFrontiers in immunology · 2022
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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

10 authors at 3 institutions in 1 country.

Vinod K GuptaMicrobiome Program, Center for Individualized Medicine, Mayo Clinic, Rochester, MN, USA.
Kevin Y CunninghamBioinformatics and Computational Biology Program, University of Minnesota, Minneapolis, MN, USA.
Benjamin HurMicrobiome Program, Center for Individualized Medicine, Mayo Clinic, Rochester, MN, USA.
Utpal BakshiMicrobiome Program, Center for Individualized Medicine, Mayo Clinic, Rochester, MN, USA.
Harvey HuangMayo Clinic Medical Scientist Training Program, Mayo Clinic, Rochester, MN, USA.
Kenneth J WarringtonDivision of Rheumatology, Department of Medicine, Mayo Clinic, Rochester, MN, USA.
Veena TanejaDepartment of Immunology, Mayo Clinic, Rochester, MN, USA.
Elena MyasoedovaDivision of Rheumatology, Department of Medicine, Mayo Clinic, Rochester, MN, USA.
John M Davis *Division of Rheumatology, Department of Medicine, Mayo Clinic, Rochester, MN, USA.
Jaeyun Sung *Microbiome Program, Center for Individualized Medicine, Mayo Clinic, Rochester, MN, USA. Sung.Jaeyun@mayo.edu.ORCID 0000-0002-3005-2798
Mayo Clinic · USMayo Clinic in Arizona · USUniversity of Minnesota · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundRapid advances in the past decade have shown that dysbiosis of the gut microbiome is a key hallmark of rheumatoid arthritis (RA). Yet, the relationship between the gut microbiome and clinical improvement in RA disease activity remains unclear. In this study, we explored the gut microbiome of patients with RA to identify features that are associated with, as well as predictive of, minimum clinically important improvement (MCII) in disease activity.

methodsWe conducted a retrospective, observational cohort study on patients diagnosed with RA between 1988 and 2014. Whole metagenome shotgun sequencing was performed on 64 stool samples, which were collected from 32 patients with RA at two separate time-points approximately 6-12 months apart. The Clinical Disease Activity Index (CDAI) of each patient was measured at both time-points to assess achievement of MCII; depending on this clinical status, patients were distinguished into two groups: MCII+ (who achieved MCII; n = 12) and MCII- (who did not achieve MCII; n = 20). Multiple linear regression models were used to identify microbial taxa and biochemical pathways associated with MCII while controlling for potentially confounding factors. Lastly, a deep-learning neural network was trained upon gut microbiome, clinical, and demographic data at baseline to classify patients according to MCII status, thereby enabling the prediction of whether a patient will achieve MCII at follow-up.

resultsWe found age to be the largest determinant of the overall compositional variance in the gut microbiome (R

conclusionsOur findings confirm the presence of taxonomic and functional signatures of the gut microbiome associated with MCII in RA patients. Ultimately, modifying the gut microbiome to enhance clinical outcome may hold promise as a future treatment for RA.

Indexed as

AgedAged, 80 and overArthritis, RheumatoidCohort StudiesDysbiosisEubacterialesFemaleGastrointestinal MicrobiomeHumansMaleMetagenomeMetagenomicsMiddle AgedRetrospective StudiesRNA, Ribosomal, 16SSeverity of Illness IndexRNA, Ribosomal, 16SClinical disease activity indexDeep-learning neural networkGut microbiomeMachine-learningMinimum clinically important improvementRheumatoid arthritisShotgun metagenomic sequencing

Identifiers

PMID34517888
PMCPMC8439035
OpenAlexW3199193607

What OpenQuestion holds

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LicenceCC BY
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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.