Evidence map›Paper›PMID 32463598›Full record

ArticleMolecular systems biology2020

Personalized whole-body models integrate metabolism, physiology, and the gut microbiome.

Ines Thiele, Swagatika Sahoo, Almut Heinken, Johannes Hertel, Laurent Heirendt, Maike K Aurich, Ronan Mt Fleming

Abstract read
In one paragraph

Article in Molecular systems biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 123 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
123citing papers in PubMed, 1 pooled it
–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

123 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Preclinical techniques to investigate exercise training in vascular pathophysiology.American journal of physiology. Heart and circulatory physiology · 2021
    Pooled it
  2. Review
  3. Article
  4. Article
  5. Article
  6. Review
  7. Article
  8. Nutrient control enables metabolic reconstruction ofbioRxiv : the preprint server for biology · 2026
    Article
  9. Article
  10. Article
  11. Reconstruction of human metabolic models with large language models.Proceedings of the National Academy of Sciences of the United States of America · 2026
    Article
  12. Article
  13. The nutrition toolbox permitsBioinformatics advances · 2026
    Article
  14. Review
  15. Review
  16. Article
  17. Article
  18. Trial Readiness: Understanding the Natural History of Rare Diseases.Journal of inherited metabolic disease · 2025
    Review
  19. Article
  20. Article

63 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.

Ines ThieleSchool of Medicine, National University of Ireland, Galway, Ireland.ORCID 0000-0002-8071-7110
Swagatika SahooLuxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg.
Almut HeinkenSchool of Medicine, National University of Ireland, Galway, Ireland.ORCID 0000-0001-6938-8072
Johannes HertelSchool of Medicine, National University of Ireland, Galway, Ireland.
Laurent HeirendtLuxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg.ORCID 0000-0003-1861-0037
Maike K AurichLuxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg.
Ronan Mt FlemingSchool of Medicine, National University of Ireland, Galway, Ireland.ORCID 0000-0001-5346-9812

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Comprehensive molecular-level models of human metabolism have been generated on a cellular level. However, models of whole-body metabolism have not been established as they require new methodological approaches to integrate molecular and physiological data. We developed a new metabolic network reconstruction approach that used organ-specific information from literature and omics data to generate two sex-specific whole-body metabolic (WBM) reconstructions. These reconstructions capture the metabolism of 26 organs and six blood cell types. Each WBM reconstruction represents whole-body organ-resolved metabolism with over 80,000 biochemical reactions in an anatomically and physiologically consistent manner. We parameterized the WBM reconstructions with physiological, dietary, and metabolomic data. The resulting WBM models could recapitulate known inter-organ metabolic cycles and energy use. We also illustrate that the WBM models can predict known biomarkers of inherited metabolic diseases in different biofluids. Predictions of basal metabolic rates, by WBM models personalized with physiological data, outperformed current phenomenological models. Finally, integrating microbiome data allowed the exploration of host-microbiome co-metabolism. Overall, the WBM reconstructions, and their derived computational models, represent an important step toward virtual physiological humans.

Indexed as

Gastrointestinal MicrobiomeMetabolomeAlgorithmsBiomarkersComputer SimulationEnergy MetabolismFemaleGene Expression RegulationHumansMaleMetabolic Networks and PathwaysMetabolomicsOrgan SpecificityProteomicsSystems BiologyBiomarkersflux balance analysishuman metabolismmetabolic modelingmicrobiome

Identifiers

PMID32463598
PMCPMC7285886

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.