Evidence map›Paper›PMID 33646347›Full record

ReviewMammalian genome : official journal of the International Mammalian Genome Society2021

Approaching precision medicine by tailoring the microbiota.

Gaeun Ryu, Hyojin Kim, Ara Koh

Abstract readReview
PubMed Publisher
In one paragraph

Review in Mammalian genome : official journal of the International Mammalian Genome Society, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
  4. Antibacterial activity and impact on keratinocyte cell growth ofCurrent research in microbial sciences · 2025
    Article
  5. Review
  6. Review
  7. Article
  8. Review
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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

3 authors.

Gaeun Ryu *Department of Precision Medicine, School of Medicine, Sungkyunkwan University (SKKU), Suwon, 16419, Republic of Korea.
Hyojin Kim *Department of Precision Medicine, School of Medicine, Sungkyunkwan University (SKKU), Suwon, 16419, Republic of Korea.
Ara KohDepartment of Precision Medicine, School of Medicine, Sungkyunkwan University (SKKU), Suwon, 16419, Republic of Korea. arakoh@g.skku.edu.ORCID http://orcid.org/0000-0001-7673-034X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Accumulating evidence has revealed the link between the microbiota and various human diseases. Advances in high-throughput sequencing technologies have identified some consistent disease-associated microbial features, leading to the emerging concept of microbiome-based therapeutics. However, it is also becoming clear that there are considerable variations in the microbiota among patients with the same disease. Variations in the microbial composition and function contribute to substantial differences in metabolic status of the host via production of a myriad of biochemically and functionally different microbial metabolites. Indeed, compelling evidence indicates that individuality of the microbiome may result in individualized responses to microbiome-based therapeutics and other interventions. Mechanistic understanding of the role of the microbiota in diseases and drug metabolism would help us to identify causal relationships and thus guide the development of microbiome-based precision or personalized medicine. In this review, we provide an overview of current efforts to use microbiome-based interventions for the treatment of diseases such as cancer, neurological disorders, and diabetes to approach precision medicine.

Indexed as

Precision MedicineDiabetes MellitusGastrointestinal MicrobiomeGenome, HumanHumansInactivation, MetabolicNeoplasmsNervous System Diseases

Identifiers

What OpenQuestion holds

Textmetadata
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.