Evidence map›Paper›PMID 36446790›Full record

ArticleNature communications2022

Genetically personalised organ-specific metabolic models in health and disease.

Carles Foguet, Yu Xu, Scott C Ritchie, Samuel A Lambert, Elodie Persyn, Artika P Nath, Emma E Davenport, David J Roberts, Dirk S Paul, Emanuele Di Angelantonio and 4 more

Open access · goldAbstract read
In one paragraph

Article in Nature communications, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
2.1field-weighted citation impact, top 12% 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

15 citing papers in PubMed, 24 citations in OpenAlex.

  1. Article
  2. Reconstruction of human metabolic models with large language models.Proceedings of the National Academy of Sciences of the United States of America · 2026
    Article
  3. Article
  4. Article
  5. Article
  6. Review
  7. Review
  8. Genome-scale models in human metabologenomics.Nature reviews. Genetics · 2025
    Review
  9. Article
  10. Article
  11. Article
  12. Transcriptional regulation of metabolism in the intestinal epithelium.American journal of physiology. Gastrointestinal and liver physiology · 2023
    Review
  13. Review
  14. Article
  15. Review
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

14 authors at 6 institutions in 3 countries.

Carles FoguetCambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK. cf545@medschl.cam.ac.uk.ORCID 0000-0001-8494-9595
Yu XuCambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.ORCID 0000-0002-7304-5045
Scott C RitchieCambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.ORCID 0000-0002-8454-9548
Samuel A LambertCambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.ORCID 0000-0001-8222-008X
Elodie PersynCambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
Artika P NathCambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
Emma E DavenportWellcome Sanger Institute, Hinxton, UK.
David J RobertsBRC Haematology Theme, Radcliffe Department of Medicine, and NHSBT-Oxford, John Radcliffe Hospital, Oxford, UK.
Dirk S PaulBritish Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.ORCID 0000-0002-8230-0116
Emanuele Di AngelantonioHealth Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, UK.
John DaneshHealth Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, UK.
Adam S ButterworthHealth Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, UK.ORCID 0000-0002-6915-9015
Christopher YauNuffield Department of Women's and Reproductive Health, University of Oxford, Oxford, OX3 9DU, UK.
Michael InouyeCambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK. mi336@medschl.cam.ac.uk.ORCID 0000-0001-9413-6520
University of Cambridge · GBBaker Heart and Diabetes Institute · AUNHS Blood and Transplant · GBTuring Institute · GBUniversity of Oxford · GBWellcome Sanger Institute · GB

Funding

British Heart Foundation CH/12/2/29428British Heart Foundation RG/13/13/30194British Heart Foundation RG/18/13/33946British Heart Foundation SP/09/002Medical Research Council MC_PC_17228Medical Research Council MC_QA137853Medical Research Council MR/L003120/1Wellcome Trust
6 · The paper itself

Abstract

Understanding how genetic variants influence disease risk and complex traits (variant-to-function) is one of the major challenges in human genetics. Here we present a model-driven framework to leverage human genome-scale metabolic networks to define how genetic variants affect biochemical reaction fluxes across major human tissues, including skeletal muscle, adipose, liver, brain and heart. As proof of concept, we build personalised organ-specific metabolic flux models for 524,615 individuals of the INTERVAL and UK Biobank cohorts and perform a fluxome-wide association study (FWAS) to identify 4312 associations between personalised flux values and the concentration of metabolites in blood. Furthermore, we apply FWAS to identify 92 metabolic fluxes associated with the risk of developing coronary artery disease, many of which are linked to processes previously described to play in role in the disease. Our work demonstrates that genetically personalised metabolic models can elucidate the downstream effects of genetic variants on biochemical reactions involved in common human diseases.

Indexed as

Adipose TissueCoronary Artery DiseaseBrainGenome, HumanHeartHumans

Identifiers

PMID36446790
PMCPMC9708841
OpenAlexW4310707155

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.