Evidence map›Paper›PMID 36289064›Full record

ArticleGut microbes

Functional profile of host microbiome indicates

Etienne Nzabarushimana, Haixu Tang

Open access · goldAbstract read
In one paragraph

Article in Gut microbes. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.5field-weighted citation impact, top 35% 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

5 citing papers in PubMed, 5 citations in OpenAlex.

  1. Review
  2. Article
  3. Insights into the Interaction BetweenJournal of personalized medicine · 2025
    Review
  4. Review
  5. 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

2 authors at 2 institutions in 1 country.

Etienne NzabarushimanaLuddy School of Informatics, Computing and Engineering, Indiana University, Bloomington, Indiana, USA.ORCID 0000-0001-6010-1506
Haixu TangLuddy School of Informatics, Computing and Engineering, Indiana University, Bloomington, Indiana, USA.
Indiana University Bloomington · USMassachusetts General Hospital · US

Funding

Subtractive assembly approaches for inferring disease-associated microbial genes and pathways from microbiome sequencing dataR01AI143254 · NIAID · TRUSTEES OF INDIANA UNIVERSITY · PI YE, YUZHEN · 2019 to 2023
$1.1M
NIAID NIH HHS R01 AI143254
6 · The paper itself

Abstract

Clostridioides difficile infection (CDI) is a gastro-intestinal (GI) infection that illustrates how perturbations in symbiotic host-microbiome interactions render the GI tract vulnerable to the opportunistic pathogens. CDI also serves as an example of how such perturbations could be reversed via gut microbiota modulation mechanisms, especially fecal microbiota transplantation (FMT). However, microbiome-mediated diagnosis of CDI remains understudied. Here, we evaluated the diagnostic capabilities of the fecal microbiome on the prediction of CDI. We used the metagenomic sequencing data from ten previous studies, encompassing those acquired from CDI patients treated by FMT, CDI-negative patients presenting other intestinal health conditions, and healthy volunteers taking antibiotics. We designed a hybrid species/function profiling approach that determines the abundances of microbial species in the community contributing to its functional profile. These functionally informed taxonomic profiles were then used for classification of the microbial samples. We used logistic regression (LR) models using these features, which showed high prediction accuracy (with an average

Indexed as

Clostridioides difficileClostridium InfectionsGastrointestinal MicrobiomeMicrobiotaAnti-Bacterial AgentsFecal Microbiota TransplantationHumansTreatment OutcomeAnti-Bacterial Agentsantibiotic impactantibioticsClostridioides difficile infectionfecal microbiota transplantationFunctional profilelogistic regressionmachine learningmetagenomicsmicrobiome

Identifiers

PMID36289064
PMCPMC9621045
OpenAlexW4307446612

What OpenQuestion 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 OpenQuestion graph.