Evidence mapPaperPMID 39203810Full record

ReviewNutrients2024

Personalized Nutrition: Tailoring Dietary Recommendations through Genetic Insights.

Saiful Singar, Ravinder Nagpal, Bahram H Arjmandi, Neda S Akhavan

Abstract readReview
In one paragraph

Review in Nutrients, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 62 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
62citing papers in PubMed, 2 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

62 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Human-Centered Innovation: Precision Nutrition and the Future of Food.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Review
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  11. The Gut-Liver Axis in Metabolic Dysfunction-Associated Steatotic Liver Disease: From Mechanistic Insights to Precision Therapeutics.FASEB journal : official publication of the Federation of American Societies for Experimental Biology · 2026
    Review
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  14. Advancing Precision Nutrition Through Multimodal Data and Artificial Intelligence.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Review
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2 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

4 authors.

Saiful SingarDepartment of Health, Nutrition, and Food Sciences, College of Education, Health, and Human Sciences, Florida State University, Tallahassee, FL 32306, USA.
Ravinder NagpalDepartment of Health, Nutrition, and Food Sciences, College of Education, Health, and Human Sciences, Florida State University, Tallahassee, FL 32306, USA.ORCID 0000-0002-4250-1749
Bahram H ArjmandiDepartment of Health, Nutrition, and Food Sciences, College of Education, Health, and Human Sciences, Florida State University, Tallahassee, FL 32306, USA.ORCID 0000-0003-1358-0238
Neda S AkhavanDepartment of Kinesiology and Nutrition Sciences, School of Integrated Health Sciences, University of Nevada, Las Vegas, NV 89154, USA.ORCID 0009-0001-1260-0877

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Personalized nutrition (PN) represents a transformative approach in dietary science, where individual genetic profiles guide tailored dietary recommendations, thereby optimizing health outcomes and managing chronic diseases more effectively. This review synthesizes key aspects of PN, emphasizing the genetic basis of dietary responses, contemporary research, and practical applications. We explore how individual genetic differences influence dietary metabolisms, thus underscoring the importance of nutrigenomics in developing personalized dietary guidelines. Current research in PN highlights significant gene-diet interactions that affect various conditions, including obesity and diabetes, suggesting that dietary interventions could be more precise and beneficial if they are customized to genetic profiles. Moreover, we discuss practical implementations of PN, including technological advancements in genetic testing that enable real-time dietary customization. Looking forward, this review identifies the robust integration of bioinformatics and genomics as critical for advancing PN. We advocate for multidisciplinary research to overcome current challenges, such as data privacy and ethical concerns associated with genetic testing. The future of PN lies in broader adoption across health and wellness sectors, promising significant advancements in public health and personalized medicine.

Indexed as

NutrigenomicsPrecision MedicineDietGenetic TestingHumansNutrition PolicyObesitybioinformatics in nutritionchronic disease managementdietary interventionsgenetic variabilitynutrigenomicspersonalized nutrition

Identifiers

PMID39203810
PMCPMC11357412

What Socratic 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 Socratic graph.