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Nutrient-Gene Interactions

2013· book-chapter· en· W4233942907 on OpenAlexfundno aff

Bibliographic record

VenueAmerican Academy of Pediatrics eBooks · 2013
Typebook-chapter
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicNutrition, Genetics, and Disease
Canadian institutionsnot available
FundersNational Heart, Lung, and Blood InstituteAgriculture and Agri-Food CanadaAgricultural Research ServiceAlberta Canola Producers CommissionNational Institutes of HealthCenters for Disease Control and PreventionMinistry of Education, Science and TechnologyNational Institute of Diabetes and Digestive and Kidney DiseasesInstituto de Salud Carlos IIIUniversity of North Carolina at GreensboroCentro de Investigación Biomédica en Red-Fisiopatología de la Obesidad y NutriciónNational Research FoundationCanola Council of CanadaSaskatchewan Canola Development CommissionNational Research Foundation of KoreaU.S. Department of Agriculture
KeywordsNutrientBiologyComputational biologyEnvironmental scienceEcology

Abstract

fetched live from OpenAlex

Objective:The aim of this study was to investigate whether 4 functional single nucleotide polymorphisms (SNPs) in glutathione peroxidases (GPX1 and GPX4) and selenoprotein P (SEPP) modify the effect of intervention with selenium-rich foods on concentrations of blood selenium and selenoprotein expression (erythrocyte GPX activity and plasma SEPP concentration).Methods: In a parallel dietary intervention study 83 healthy men and women aged 50-74 y were randomly assigned to either a control or an intervention group.Participants in the intervention group were provided with 5 portions of 200 g raw fish and shellfish once a week for 26 wk, corresponding to ∼50.3 μg Se/d.The participants in the control group received no intervention and were advised to maintain their habitual diets.Selected functional polymorphisms were GPX1/rs1050450, GPX4/rs713041, SEPP1/rs3877899, and SEPP1/rs7579.Genotypes were determined through the use of reverse transcriptase-polymerase chain reaction and allelic discrimination on ABI 7900HT instruments.Samples were run in duplicates with known positive controls and 3 negative controls.Duplicates yielded 100% identical genotypes.Whole-blood selenium analyses were conducted by inductively coupled plasma mass spectrometry with an ELAN 6100 DRC, and plasma SEPP concentration was determined from its selective retention by heparin-affinity HPLC and online detection by inductively coupled plasma dynamic reaction cell mass spectrometry of selenium.GPX activity was spectrophotometrically assayed in erythrocyte lysates on a Pentra 400 with t-butylhydroperoxide as substrate and related to the amount of hemoglobin in the lysates.Results: The intervention diet resulted in higher concentrations of both SEPP (P = 0.018) and blood selenium (P = 0.088) in wild-type allele carriers of the SEPP1/rs3877899 polymorphism compared with variant allele carriers.None of the other polymorphisms modified the biomarker responses following the intervention.Carriers of the variant GPX1 allele had significantly lower erythrocyte GPX enzyme activity compared with wild-type carriers independent of intervention.Conclusions: Our study shows that variation in the SEPP1 gene modifies biomarkers of selenium status after intake of selenium-rich foods.This opens the way for a more personalized approach to micronutrient requirements.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.298
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.014
GPT teacher head0.265
Teacher spread0.251 · 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; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2013
Admission routes1
Has abstractyes

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