Evidence map›Paper›PMID 36216932›Full record

ArticleNature medicine2022

Influence of the microbiome, diet and genetics on inter-individual variation in the human plasma metabolome.

Lianmin Chen, Daria V Zhernakova, Alexander Kurilshikov, Sergio Andreu-Sánchez, Daoming Wang, Hannah E Augustijn, Arnau Vich Vila, Lifelines Cohort Study, Rinse K Weersma, Marnix H Medema and 5 more

Open access · hybridAbstract read
In one paragraph

Article in Nature medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 196 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
196citing papers in PubMed, 1 pooled it
21.9field-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

196 citing papers in PubMed, 1 synthesis or guideline pooled it, 283 citations in OpenAlex.

  1. Pooled it
  2. Trial
  3. Trial
  4. Trial
  5. Trial
  6. Trial
  7. Trial
  8. Placebo-resistant gut bacteria:Frontiers in cellular and infection microbiology · 2024
    Trial
  9. Review
  10. Review
  11. Article
  12. Article
  13. Article
  14. Article
  15. Review
  16. Article
  17. Article
  18. Article
  19. Review
  20. Article

136 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

15 authors at 2 institutions in 4 countries.

Lianmin ChenDepartment of Genetics, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands.ORCID http://orcid.org/0000-0003-0660-3518
Daria V ZhernakovaDepartment of Genetics, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands.ORCID http://orcid.org/0000-0001-6531-3890
Alexander KurilshikovDepartment of Genetics, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands.ORCID http://orcid.org/0000-0003-2541-5627
Sergio Andreu-SánchezDepartment of Genetics, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands.ORCID http://orcid.org/0000-0002-3503-9971
Daoming WangDepartment of Genetics, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands.ORCID http://orcid.org/0000-0003-4623-8527
Hannah E AugustijnDepartment of Genetics, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands.
Arnau Vich VilaDepartment of Genetics, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands.ORCID http://orcid.org/0000-0003-4691-5583
Lifelines Cohort Study
Rinse K WeersmaDepartment of Gastroenterology and Hepatology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands.
Marnix H MedemaBioinformatics Group, Wageningen University, Wageningen, the Netherlands.ORCID http://orcid.org/0000-0002-2191-2821
Mihai G NeteaDepartment of Internal Medicine and Radboud Center for Infectious Diseases, Radboud University Medical Center, Nijmegen, the Netherlands.ORCID http://orcid.org/0000-0003-2421-6052
Folkert KuipersDepartment of Pediatrics, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands.ORCID http://orcid.org/0000-0003-2518-737X
Cisca WijmengaDepartment of Genetics, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands.ORCID http://orcid.org/0000-0002-5635-1614
Alexandra ZhernakovaDepartment of Genetics, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands.ORCID http://orcid.org/0000-0002-4574-0841
Jingyuan FuDepartment of Genetics, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands. j.fu@umcg.nl.ORCID http://orcid.org/0000-0001-5578-1236
University Medical Center Groningen · NLRadboud University Nijmegen · NL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The levels of the thousands of metabolites in the human plasma metabolome are strongly influenced by an individual's genetics and the composition of their diet and gut microbiome. Here, by assessing 1,183 plasma metabolites in 1,368 extensively phenotyped individuals from the Lifelines DEEP and Genome of the Netherlands cohorts, we quantified the proportion of inter-individual variation in the plasma metabolome explained by different factors, characterizing 610, 85 and 38 metabolites as dominantly associated with diet, the gut microbiome and genetics, respectively. Moreover, a diet quality score derived from metabolite levels was significantly associated with diet quality, as assessed by a detailed food frequency questionnaire. Through Mendelian randomization and mediation analyses, we revealed putative causal relationships between diet, the gut microbiome and metabolites. For example, Mendelian randomization analyses support a potential causal effect of Eubacterium rectale in decreasing plasma levels of hydrogen sulfite-a toxin that affects cardiovascular function. Lastly, based on analysis of the plasma metabolome of 311 individuals at two time points separated by 4 years, we observed a positive correlation between the stability of metabolite levels and the amount of variance in the levels of that metabolite that could be explained in our analysis. Altogether, characterization of factors that explain inter-individual variation in the plasma metabolome can help design approaches for modulating diet or the gut microbiome to shape a healthy metabolome.

Indexed as

Gastrointestinal MicrobiomeMicrobiotaDietFecesHumansMetabolomePhenotype

Identifiers

PMID36216932
PMCPMC9671809
OpenAlexW4304084108

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.