Evidence map›Paper›PMID 32770212›Full record

ArticleAdvances in nutrition (Bethesda, Md.)2020

The "Virtual Digital Twins" Concept in Precision Nutrition.

Kalliopi Gkouskou, Ioannis Vlastos, Petros Karkalousos, Dimitrios Chaniotis, Despina Sanoudou, Aristides G Eliopoulos

Open access · greenAbstract read
In one paragraph

Article in Advances in nutrition (Bethesda, Md.), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
41citing papers in PubMed, 1 pooled it
3.7field-weighted citation impact, top 6% 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

41 citing papers in PubMed, 1 synthesis or guideline pooled it, 77 citations in OpenAlex.

  1. Digital Twins and Health Care: an Umbrella Review.Journal of medical systems · 2025
    Pooled it
  2. Trial
  3. Review
  4. Review
  5. Human-Centered Innovation: Precision Nutrition and the Future of Food.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Review
  6. iDT-diet: Toward Personalized Health Forecasting-An Intelligent Digital Twin Model for Diet-Influenced Biomarker Trajectories (Student Abstract).Proceedings of the ... AAAI Conference on Artificial Intelligence. AAAI Conference on Artificial Intelligence · 2026
    Article
  7. Review
  8. Review
  9. Review
  10. Review
  11. Review
  12. Review
  13. [Application of Digital Nutrition Technologies in Adult Weight Management].Sichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition · 2025
    Article
  14. Article
  15. Review
  16. Article
  17. Review
  18. Review
  19. Article
  20. Intelligent Digital Twins for Personalized Migraine Care.Journal of personalized medicine · 2023
    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

6 authors at 2 institutions in 1 country.

Kalliopi GkouskouDepartment of Biology, School of Medicine, National and Kapodistrian University of Athens, Athens, Greece.
Ioannis VlastosDepartment of Biology, School of Medicine, National and Kapodistrian University of Athens, Athens, Greece.
Petros KarkalousosDepartment of Biomedical Sciences, University of West Attica, Athens, Greece.
Dimitrios ChaniotisDepartment of Biomedical Sciences, University of West Attica, Athens, Greece.
Despina SanoudouClinical Genomics and Pharmacogenomics Unit, 4th Department of Internal Medicine, School of Medicine, National and Kapodistrian University of Athens, Athens, Greece.
Aristides G EliopoulosDepartment of Biology, School of Medicine, National and Kapodistrian University of Athens, Athens, Greece.
National and Kapodistrian University of Athens · GRUniversity of West Attica · GR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Nutritional and lifestyle changes remain at the core of healthy aging and disease prevention. Accumulating evidence underscores the impact of genetic, metabolic, and host gut microbial factors on individual responses to nutrients, paving the way for the stratification of nutritional guidelines. However, technological advances that incorporate biological, nutritional, lifestyle, and health data at an unprecedented scale and depth conceptualize a future where preventative dietary interventions will exceed stratification and will be highly individualized. We herein discuss how genetic information combined with longitudinal metabolomic, immune, behavioral, and gut microbial parameters, and bioclinical variables could define a digital replica of oneself, a "virtual digital twin," which could serve to guide nutrition in a personalized manner. Such a model may revolutionize the management of obesity and its comorbidities, and provide a pillar for healthy aging.

Indexed as

Nutritional StatusGastrointestinal MicrobiomeHumansLife StyleObesityPrecision Medicinedigital medicinedigital twinepigenomeimmunomemicrobiomenutrigeneticsnutritionobesity

Identifiers

PMID32770212
PMCPMC7666894
OpenAlexW3048083848

What OpenQuestion holds

Textmetadata
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.