Evidence map›Paper›PMID 37137684›Full record

Trial reportGut2023

Gut microbiome modulates the effects of a personalised postprandial-targeting (PPT) diet on cardiometabolic markers: a diet intervention in pre-diabetes.

Orly Ben-Yacov, Anastasia Godneva, Michal Rein, Smadar Shilo, Maya Lotan-Pompan, Adina Weinberger, Eran Segal

Registry-linked trialOpen access · hybridAbstract readRandomized Controlled Trial
In one paragraph

Trial report in Gut, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT03222791 (Personalized Nutrition for Pre-Diabetes), which is not on this map. Cited by 61 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
61citing papers in PubMed, 3 pooled it
10.5field-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.

NCT03222791 nacompletednot on this map

Personalized Nutrition for Pre-Diabetes

TypeinterventionalSponsorWeizmann Institute of ScienceRan2017 to 2020Enrolled244ConditionsPre DiabetesArmsAlgorithm-based diet, Mediterranean-style low-fat diet
3 · Its place in the literature

Who cites it

61 citing papers in PubMed, 3 syntheses or guidelines pooled it, 68 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Trial
  5. Trial
  6. Trial
  7. Trial
  8. Trial
  9. Trial
  10. Review
  11. Review
  12. Review
  13. Review
  14. Human-Centered Innovation: Precision Nutrition and the Future of Food.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Review
  15. Review
  16. Review
  17. Article
  18. Review
  19. Advancing Precision Nutrition Through Multimodal Data and Artificial Intelligence.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Review
  20. Article

1 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

7 authors at 2 institutions in 1 country.

Orly Ben-YacovDepartment of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel.ORCID 0000-0002-9608-2893
Anastasia GodnevaDepartment of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel.
Michal ReinDepartment of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel.
Smadar ShiloDepartment of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel.
Maya Lotan-PompanDepartment of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel.
Adina WeinbergerDepartment of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel.
Eran SegalDepartment of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel Eran.Segal@weizmann.ac.il.
Weizmann Institute of Science · ILSchneider Children's Medical Center · IL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo explore the interplay between dietary modifications, microbiome composition and host metabolic responses in a dietary intervention setting of a personalised postprandial-targeting (PPT) diet versus a Mediterranean (MED) diet in pre-diabetes.

designIn a 6-month dietary intervention, adults with pre-diabetes were randomly assigned to follow an MED or PPT diet (based on a machine-learning algorithm for predicting postprandial glucose responses). Data collected at baseline and 6 months from 200 participants who completed the intervention included: dietary data from self-recorded logging using a smartphone application, gut microbiome data from shotgun metagenomics sequencing of faecal samples, and clinical data from continuous glucose monitoring, blood biomarkers and anthropometrics.

resultsPPT diet induced more prominent changes to the gut microbiome composition, compared with MED diet, consistent with overall greater dietary modifications observed. Particularly, microbiome alpha-diversity increased significantly in PPT (p=0.007) but not in MED arm (p=0.18). Post hoc analysis of changes in multiple dietary features, including food-categories, nutrients and PPT-adherence score across the cohort, demonstrated significant associations between specific dietary changes and species-level changes in microbiome composition. Furthermore, using causal mediation analysis we detect nine microbial species that partially mediate the association between specific dietary changes and clinical outcomes, including three species (from

conclusionsOur findings support the role of gut microbiome in modulating the effects of dietary modifications on cardiometabolic outcomes, and advance the concept of precision nutrition strategies for reducing comorbidities in pre-diabetes. TRIAL REGISTRATION NUMBER: NCT03222791.

Indexed as

Cardiovascular DiseasesDiet, MediterraneanGastrointestinal MicrobiomePrediabetic StateAdultBlood GlucoseBlood Glucose Self-MonitoringDietHumansBlood Glucosediabetes mellitusdietnutrition

Identifiers

PMID37137684
PMCPMC10359530
OpenAlexW4367842717

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

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.