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Record W2315456159 · doi:10.2174/187569209788654023

Nutrigenomics and Personalized Diet: What are the Anticipated Impacts for Research on Chronic Diseases and Public Health?

2009· article· en· W2315456159 on OpenAlexaff
Julie Robitaille

Bibliographic record

VenueCurrent pharmacogenomics and personalized medicine (Online)/Current pharmacogenomics and personalized medicine · 2009
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicNutrition, Genetics, and Disease
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsNutrigenomicsBiomedicineGenomicsPublic healthDiseasePopulationMedicinePersonalized medicineBiotechnologyEnvironmental healthBioinformaticsBiologyGenomeGeneticsPathology

Abstract

fetched live from OpenAlex

With parallel advances in genomics and in nutrition research, a new hybrid science has emerged at their intersection, often referred to as nutritional genomics which includes nutrigenomics and nutrigenetics. While the operational definitions will continue to evolve as nutritional genomics matures as a new field of inquiry, a central tenet will likely be on ways in which the human genome interacts with nutritional exposures. This emerging form of science has considerable implications for research in biomedicine and for public health. The progress in nutrigenomics research will likely increase our understanding of chronic disease etiology and the relationship between nutrients and common complex diseases. The potential for nutritional genomics in chronic disease prevention is also of great interest given that diet is a modifiable risk factor and because of the marked interindividual variability in response to the diet. The inclusion of genetic information as part of an overall strategy to improve the population health will be critical as more genomic data accumulate in nutrition science and used to develop recommendations for specific dietary requirements based on individual genetic make-up. In addition, use of genetic information from companies offering at-home direct-to-consumer nutrigenomics tests may have significant consequences for the population health and how we perceive and relate to food and other members of the society depending on human genetic variation. These implications of nutrigenomics and nutrigenetics such as the translation of research into public health practice will be discussed. Another dimension of interest is the need for well-trained health professionals. To this end, registered dietitians are essential to the efforts for incorporation of genomics into public health. Finally, future perspectives of nutrigenomics and nutrigenetics will be examined, with a view to how best to integrate the nascent field of nutrigenomics with established public health research and practices. Keywords: Nutrigenomics, chronic disease, public health, preventive medicine, personalized diet

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.860
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.003
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.184
GPT teacher head0.460
Teacher spread0.276 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations7
Published2009
Admission routes1
Has abstractyes

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