Evidence map›Paper›PMID 34677424›Full record

ReviewMetabolites2021

Metabolomics Meets Nutritional Epidemiology: Harnessing the Potential in Metabolomics Data.

Lorraine Brennan, Frank B Hu, Qi Sun

Abstract readReview
In one paragraph

Review in Metabolites, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed
–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

25 citing papers in PubMed.

  1. Trial
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  4. Review
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  9. Methods and protocols · 2025
    Article
  10. Recent advances in precision nutrition and cardiometabolic diseases.Revista espanola de cardiologia (English ed.) · 2025
    Review
  11. Review
  12. Article
  13. Article
  14. Article
  15. Review
  16. Review
  17. Article
  18. Article
  19. Review
  20. 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

3 authors.

Lorraine BrennanConway Institute, Institute of Food and Health, School of Agriculture and Food Science, UCD, Belfield, Dublin 4, Ireland.
Frank B HuChanning Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02115, USA.
Qi SunChanning Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02115, USA.

Funding

DIETARY PATTERNS AND RISK OF CARDIOVASCULAR DISEASER01HL060712 · NHLBI · HARVARD UNIVERSITY (SCH OF PUBLIC HLTH) · PI HU, FRANK B, QI, QIBIN · 1998 to 2021
$8.0M
Metabolomics Core for the Dietary Biomarkers Development Center at Harvard UniversityU2CDK129670 · NIDDK · HARVARD UNIVERSITY D/B/A HARVARD SCHOOL OF PUBLIC HEALTH · PI CLISH, CLARY B · 2021 to 2025
$7.0M
Environmental Obesogens and Weight Change in the POUNDS LOST TrialR01ES022981 · NIEHS · HARVARD UNIVERSITY D/B/A HARVARD SCHOOL OF PUBLIC HEALTH · PI SUN, QI · 2014 to 2024
$4.7M
Ultra-processed Foods, Diet Quality, and Cardiometabolic Health: An Inter-disciplinary Trans-Atlantic Collaborative ProjectR01DK120870 · NIDDK · HARVARD UNIVERSITY D/B/A HARVARD SCHOOL OF PUBLIC HEALTH · PI Qibin Qi, Qi Sun · 2019 to 2026
$4.2M
Circulating plasma metabolites, diet, and risk of type 2 diabetesR01DK112940 · NIDDK · BRIGHAM AND WOMEN'S HOSPITAL · PI HU, FRANK B, MORA, SAMIA · 2018 to 2021
$2.9M
Metabolomics signatures underlying diet, lifestyle and gut microbiota for diabetesR01DK119268 · NIDDK · ALBERT EINSTEIN COLLEGE OF MEDICINE · PI QI, QIBIN · 2019 to 2022
$2.4M
European Research Council 647783Health Research Board USIRL-2019-1NHLBI NIH HHS R01 HL060712NIDDK NIH HHS R01 DK112940NIDDK NIH HHS R01 DK119268NIDDK NIH HHS R01 DK120870NIDDK NIH HHS U2C DK129670NIEHS NIH HHS R01 ES022981NIH HHS 1U2CDK129670NIH HHS DK112940NIH HHS HL60712NIH HHS R01DK119268NIH HHS R01DK120870NIH HHS R01ES022981
6 · The paper itself

Abstract

Traditionally, nutritional epidemiology is the study of the relationship between diet and health and disease in humans at the population level. Commonly, the exposure of interest is food intake. In recent years, nutritional epidemiology has moved from a "black box" approach to a systems approach where genomics, metabolomics and proteomics are providing novel insights into the interplay between diet and health. In this context, metabolomics is emerging as a key tool in nutritional epidemiology. The present review explores the use of metabolomics in nutritional epidemiology. In particular, it examines the role that food-intake biomarkers play in addressing the limitations of self-reported dietary intake data and the potential of using metabolite measurements in assessing the impact of diet on metabolic pathways and physiological processes. However, for full realisation of the potential of metabolomics in nutritional epidemiology, key challenges such as robust biomarker validation and novel methods for new metabolite identification need to be addressed. The synergy between traditional epidemiologic approaches and metabolomics will facilitate the translation of nutritional epidemiologic evidence to effective precision nutrition.

Indexed as

biomarkersdietary intakedietary patternsmetabolitesmetabolomics

Identifiers

PMID34677424
PMCPMC8537466

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.