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Record W4409096485 · doi:10.2196/64894

Associations Among Diet, Health, Lifestyle, and Gut Microbiota Composition in the General French Population: Protocol for the Le French Gut – Le Microbiote Français Study

2025· article· en· W4409096485 on OpenAlexvenueno aff
Chloé Connan, Sébastien Fromentin, Mourad Benallaoua, Anne‐Sophie Alvarez, Nicolas Pons, Benoît Quinquis, Christian Morabito, Julie‐Anne Nazare, Elise Borezée, Florence Haimet, S. Dusko Ehrlich, Karine Valeille, Alexandre Cavezza, Hervé M. Blottière, Patrick Veiga, Mathieu Almeida, Joël Doré, Robert Benamouzig

Bibliographic record

VenueJMIR Research Protocols · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGut microbiota and health
Canadian institutionsnot available
FundersAgence Nationale de la Recherche
KeywordsPreprintFecesProtocol (science)MedicineTraditional medicineWorld Wide WebBiologyComputer scienceMicrobiologyAlternative medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Over the past 2 decades, the gut microbiota has emerged as a key player in human health, being involved in many different clinical contexts. Yet, many aspects of the relationship with its host are poorly documented. One obstacle is the substantial variability in wet-laboratory procedures and data processing implemented during gut microbiota studies, which poses a challenge of comparability and potential meta-analysis. OBJECTIVE: The study protocol described here aimed to better understand the relationship between health, dietary habits, and the observed heterogeneity of gut microbiota composition in the general population. "Le French Gut - Le microbiote français" aimed to collect, sequence, and analyze 100,000 fecal samples from French residents using a high-quality shotgun metagenomic pipeline, complemented with comprehensive health, lifestyle, and dietary metadata. METHODS: "Le French Gut - Le microbiote français" is a prospective, noninterventional French national study involving individuals, the creation of a biological collection (feces), and the exploitation of data from questionnaires and the National Health Data System (Système National des Données de Santé). This national study is open to all metropolitan French adult residents, excluding those who have undergone a colectomy or digestive stoma, or who have had a colonoscopy or taken antibiotics in the last 3 months. This is a home-based trial in which volunteers complete a questionnaire with insights about their health and habits, and in which stool samples are self-collected. Data analysis is structured into 6 work packages, each focusing on a specific aspect of the gut microbiome, including its composition and associations with lifestyle, quality of life, and health. RESULTS: This paper outlines the study protocol, with recruitment having started in September 2022 and expected to continue until the end of December 2025. As of January 2025, a total of 20,000 participants have been enrolled. The first scientific publications based on the data analysis are expected by mid-2025. CONCLUSIONS: "Le French Gut" aims to provide a reference database and new ecosystem tools for understanding the relationship between the gut microbiota, its host, and diet. We expect to be able to find new signatures or targets and promote the design of innovative preventive strategies, personalized nutrition, and precision medicine. TRIAL REGISTRATION: ClinicalTrials.gov NCT05758961; https://clinicaltrials.gov/study/NCT05758961. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/64894.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.014
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.022
Threshold uncertainty score0.074

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.014
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0020.002
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0220.004

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 head0.090
GPT teacher head0.504
Teacher spread0.414 · 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 source (direct Gemma or distilled Codex), not a consensus.

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

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

Citations3
Published2025
Admission routes1
Has abstractyes

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