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Record W4220712961 · doi:10.7554/elife.71332

Urinary metabolic biomarkers of diet quality in European children are associated with metabolic health

2022· article· en· W4220712961 on OpenAlexaff
Nikos Stratakis, Alexandros Siskos, Eleni Papadopoulou, Anh N. Nguyen, Yinqi Zhao, Katerina Margetaki, Chung‐Ho E. Lau, Muireann Coen, Léa Maître, Sílvia Fernández‐Barrés, Lydiane Agier, Sandra Andrušaitytė, Xavier Basagaña, Anne Lise Brantsæter, Maribel Casas, Serena Fossati, Regina Gražulevičienė, Barbara Heude, Rosemary McEachan, Helle Margrete Meltzer, Christopher Millett, Fernanda Rauber, Oliver Robinson, Theano Roumeliotaki, Eva Borràs, Eduard Sabidó, José Urquiza, Marina Vafeiadi, Paolo Vineis, Trudy Voortman, John Wright, David V. Conti, Martine Vrijheid, Hector C. Keun, Leda Chatzi

Bibliographic record

VenueeLife · 2022
Typearticle
Languageen
FieldMedicine
TopicNutritional Studies and Diet
Canadian institutionsAstraZeneca (Canada)
FundersNational Institute of Diabetes and Digestive and Kidney DiseasesInstituto de Salud Carlos IIIHorizon 2020Medical Research CouncilNational Institutes of HealthNational Cancer InstituteSeventh Framework ProgrammeCentre Hospitalier Universitaire de PoitiersNorges ForskningsrådDepartament de Salut, Generalitat de CatalunyaHelse- og OmsorgsdepartementetMinisterio de Economía y CompetitividadNational Institute for Health and Care ResearchGeneralitat de CatalunyaFundação de Amparo à Pesquisa do Estado de São PauloNational Institute of Environmental Health SciencesInstitut National de la Santé et de la Recherche MédicaleEuropean Regional Development FundEuropean CommissionMinisterio de Ciencia, Innovación y UniversidadesImperial College LondonDepartment of Health and Social CareWellcome Trust
KeywordsMediterranean dietInsulin resistanceMetaboliteMetabolomicsUrinary systemMedicineObesityBiologyPhysiologyEnvironmental healthEndocrinologyInternal medicineBioinformatics

Abstract

fetched live from OpenAlex

Urinary metabolic profiling is a promising powerful tool to reflect dietary intake and can help understand metabolic alterations in response to diet quality. Here, we used 1 H NMR spectroscopy in a multicountry study in European children (1147 children from 6 different cohorts) and identified a common panel of 4 urinary metabolites (hippurate, N -methylnicotinic acid, urea, and sucrose) that was predictive of Mediterranean diet adherence (KIDMED) and ultra-processed food consumption and also had higher capacity in discriminating children’s diet quality than that of established sociodemographic determinants. Further, we showed that the identified metabolite panel also reflected the associations of these diet quality indicators with C-peptide, a stable and accurate marker of insulin resistance and future risk of metabolic disease. This methodology enables objective assessment of dietary patterns in European child populations, complementary to traditional questionary methods, and can be used in future studies to evaluate diet quality. Moreover, this knowledge can provide mechanistic evidence of common biological pathways that characterize healthy and unhealthy dietary patterns, and diet-related molecular alterations that could associate to metabolic disease.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.415

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
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 head0.030
GPT teacher head0.303
Teacher spread0.273 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations21
Published2022
Admission routes1
Has abstractyes

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