Evidence map›Paper›PMID 38110694›Full record

ReviewNature reviews. Microbiology2024

Utilization of the microbiome in personalized medicine.

Karina Ratiner, Dragos Ciocan, Suhaib K Abdeen, Eran Elinav

Abstract readReview
PubMed Publisher
In one paragraph

Review in Nature reviews. Microbiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 94 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
94citing papers in PubMed, 3 pooled it
19.4field-weighted citation impact, top 1% 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

94 citing papers in PubMed, 3 syntheses or guidelines pooled it, 126 citations in OpenAlex.

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  13. Formulation-dependent kinetics ofMicrobiology spectrum · 2026
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34 more citing papers are in PubMed but not listed here.

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

4 authors at 2 institutions in 2 countries.

Karina Ratiner *Systems Immunology Department, Weizmann Institute of Science, Rehovot, Israel.ORCID http://orcid.org/0000-0002-3458-5604
Dragos Ciocan *Systems Immunology Department, Weizmann Institute of Science, Rehovot, Israel.ORCID http://orcid.org/0000-0003-0416-1584
Suhaib K Abdeen *Systems Immunology Department, Weizmann Institute of Science, Rehovot, Israel. suhib.abdin@weizmann.ac.il.ORCID http://orcid.org/0009-0008-6787-1069
Eran ElinavSystems Immunology Department, Weizmann Institute of Science, Rehovot, Israel. eran.elinav@weizmann.ac.il.ORCID http://orcid.org/0000-0002-5775-2110
Weizmann Institute of Science · ILGerman Cancer Research Center · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Inter-individual human variability, driven by various genetic and environmental factors, complicates the ability to develop effective population-based early disease detection, treatment and prognostic assessment. The microbiome, consisting of diverse microorganism communities including viruses, bacteria, fungi and eukaryotes colonizing human body surfaces, has recently been identified as a contributor to inter-individual variation, through its person-specific signatures. As such, the microbiome may modulate disease manifestations, even among individuals with similar genetic disease susceptibility risks. Information stored within microbiomes may therefore enable early detection and prognostic assessment of disease in at-risk populations, whereas microbiome modulation may constitute an effective and safe treatment tailored to the individual. In this Review, we explore recent advances in the application of microbiome data in precision medicine across a growing number of human diseases. We also discuss the challenges, limitations and prospects of analysing microbiome data for personalized patient care.

Indexed as

MicrobiotaPrecision MedicineBacteriaFungiHumans

Identifiers

PMID38110694
OpenAlexW4389893422

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.