Landscape of Gout in French Polynesia. (METABOGOUT)

January 6, 2026 updated by: Lille Catholic University

FENUA-METABOGOUT : Genetic Landscape of Gout, Inflammation and Metabolic Diseases in French Polynesia.

The aim of this research is to characterise the genetic and molecular landscape of gout, inflammation and metabolic diseases, as well as the associated molecular, anthropomorphic and pathological characteristics.

Study Overview

Detailed Description

Recent work by the GHICL has highlighted the imminent public health problem represented by gout and hyperuricaemia in French Polynesia, with gout affecting around 15% and hyperuricaemia 71.6% of the adult population.

Hyperuricaemia is defined as a serum urate level above the saturation point, leading to its crystallisation under biological conditions. It is generally accepted that hyperuricaemia (HU) begins at 6.0 mg/dL (360 µmol/L).

The best-known consequence of hyperuricaemia is the development of gout, which results from the inflammatory response to the presence of monosodium urate (MSU) crystals in and around the joints. The factors modulating the deposition of MSU crystals in HU are poorly understood and a potential genetic contribution is unknown. It is known that the inflammatory response to the presence of MSU crystal deposits causing gout flares is mediated by activation of the NLRP33 inflammasome, but there is significant variability in this inflammatory response within the same individual (irregular recurrence of flares), and between individuals. The exceptionally high prevalence of HU that have been identified in French Polynesia represents a major health burden, as hyperuricaemia and gout are associated with many other cardiometabolic diseases.

For example, hyperuricaemia, BMI and type 2 diabetes are all associated with the risk of gout. The association between gout and cardiovascular events is also well known, and is thought to be mediated by a persistent inflammatory state. These data are particularly relevant in the context of French Polynesia where, in addition to high rates of gout and HU, a prevalence of obesity of over 40% (BMI >30kg/m2) and a prevalence of diabetes (based on HBA1c measurements) of over 13% was previously identified by the same team.

This last point is particularly striking as the prevalence of diabetes based on self-reported diagnosis was only 7%, indicating that many people are probably undiagnosed and therefore untreated. A better understanding not only of the mechanism and causal link between these conditions and risk factors, but also of the genetic basis of the disease, could lead to the development of therapies and to the improvement in diagnosis. This is particularly crucial in French Polynesia, where hyperuricaemia and its pathological effects on cardiometabolic health affect a large proportion of the adult population.

Here a multi-pronged approach to take advantage of a previous study named 'TOPATA' (NCT04812886) performed previously in French Polynesia, is proposed. The idea is to expand the existing cohort, in order to identify the genetic effectors contributing to the high rates of metabolic diseases previously observed, and to track the longitudinal impacts of HU.

Study Type

Observational

Enrollment (Estimated)

2750

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Contact

Study Contact Backup

Study Locations

      • Faa'a, French Polynesia, 98702
        • Recruiting
        • Medical Office Dr Antoine Scuiller
        • Contact:
      • Papeete, French Polynesia, 98713
      • Papeete, French Polynesia, 98714
        • Recruiting
        • Medical Office Dr Voradeth Nouanesengsy
        • Contact:
      • Pirae, French Polynesia, 98716
        • Not yet recruiting
        • CH de Polynesie Française Papeete
        • Contact:
      • Pirae, French Polynesia, 98716
        • Recruiting
        • Medical Office Dr Nanethida Nouanesengsy
        • Contact:
      • Pirae, French Polynesia, 98716
        • Recruiting
        • Medical Office Dr Raphael Habib
        • Contact:

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Adult
  • Older Adult

Accepts Healthy Volunteers

Yes

Sampling Method

Non-Probability Sample

Study Population

General population group: Participants will be recruited by general practitioners or study nurses during consultations in community-based practices. The objective is to include a representative general population sample, with no specific reason for consultation required or excluded.

Gout group: Patients will be recruited at the Rheumatology Clinic of the Taaone Hospital Center (CHT) in Papeete when presenting with gout symptoms, either tophaceous gout or an acute flare within the previous 48 hours.

2021 follow-up group: Participants from the TOPATA study conducted in 2021 will be recontacted by telephone to assess willingness to participate, followed by an in-person inclusion visit. Only individuals currently living in Tahiti will be contacted. Nurses will be responsible for recruitment, biological sample collection, physical measurements, and questionnaire administration.

Description

Inclusion Criteria:

All participants:

  • Age between 18 and 75 years old inclusive
  • Signature of informed consent
  • Fasting for the collection of biological samples
  • Declared Polynesian ancestry
  • Affiliated to a social security scheme

General population group :

  • Not having participated to the 2021 TOPATA study
  • Visiting a general practitioner (for whatever reason)

Gout Group :

  • Managed at the rheumatology clinic of the Taaone Hospital Centre (CHT) in Papeete by Dr Baptiste Gérard.

Tophaceous gout sub-group:

  • Present with tophaceous gout.

Gout crisis subgroup:

  • Be within 48 hours of the onset of a gout attack
  • Agree to return 1 week after inclusion for the second blood and urine sample.

    2021 follow-up group:

  • To have been included in the TOPATA study in 2021
  • Have taken the genetic and biological samples that generated the genetic and serum urate data for the 2021 study
  • Have hyperuricaemia without signs of gout OR without hyperuricaemia or gout at the time of inclusion in TOPATA

Exclusion Criteria:

All participants :

  • Refusal or inability to understand or give consent
  • Physical inability to follow and respect the protocol
  • 1st degree relative*,
  • Person under guardianship or trusteeship
  • Pregnant or breast-feeding woman

    * If several relatives from the same household are eligible to participate, only one person may be included in the study. The choice is left to the discretion of the investigator or the first person met. However, both members of a couple (e.g. husband and wife) may participate.

  • General population group :
  • Unable to return for sampling if required.
  • Gout group :
  • Person wearing a knee prosthesis
  • People suffering from other inflammatory rheumatic diseases

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

Cohorts and Interventions

Group / Cohort
Intervention / Treatment
General Population Group
Patients aged between 18 and 75 years old who did not take part in the TOPATA study in 2021 and who visit their general practitioner for a consultation (for whatever reason)
Collection of sociodemographic data, collection of treatment data, standard and clinical ophthalmological examination, physical and biological measurements, clinical characteristics specific to chronic and metabolic diseases, questionnaires (gout questionnaire, health assessment questionnaire (HAQ-II), EuroQol (EQ)-5D-5L, joint pain, state of health, diet and physical activity, access to care, addictions, sleep quality, pain scale (EVA), personal and family history) will be performed.
Collection of blood and urine samples for genetic, biochemical, omics, and biobank analyses, in order to characterize cardiometabolic health markers will be performed.
Gout Group

Patients aged between 18 and 75 years old who are treated at the rheumatology clinic of the Taaone Hospital Centre (CHT) in Papeete by Dr Baptiste Gérard.

  • There is a tophaceous gout subgroup: patients with tophaceous gout.
  • And a gout attack subgroup: patients presenting with a gout crisis.
Collection of sociodemographic data, collection of treatment data, standard and clinical ophthalmological examination, physical and biological measurements, clinical characteristics specific to chronic and metabolic diseases, questionnaires (gout questionnaire, health assessment questionnaire (HAQ-II), EuroQol (EQ)-5D-5L, joint pain, state of health, diet and physical activity, access to care, addictions, sleep quality, pain scale (EVA), personal and family history) will be performed.
Collection of blood and urine samples for genetic, biochemical, omics, and biobank analyses, in order to characterize cardiometabolic health markers will be performed.
Follow-up group 2021

Patients aged between 18 and 75 years old who were included in the TOPATA study in 2021 and for whom genetic and biological samples during the 2021 study were taken.

Patients must have had hyperuricaemia without signs of gout OR without hyperuricaemia or gout at the time of inclusion in the 2021 TOPATA study.

Collection of sociodemographic data, collection of treatment data, standard and clinical ophthalmological examination, physical and biological measurements, clinical characteristics specific to chronic and metabolic diseases, questionnaires (gout questionnaire, health assessment questionnaire (HAQ-II), EuroQol (EQ)-5D-5L, joint pain, state of health, diet and physical activity, access to care, addictions, sleep quality, pain scale (EVA), personal and family history) will be performed.
Collection of blood and urine samples for genetic, biochemical, omics, and biobank analyses, in order to characterize cardiometabolic health markers will be performed.

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
GWAS-identified associations between population-enriched genetic variants and health-related traits
Time Frame: 12 month
Effect estimates (odds ratios or beta coefficients) for statistically significant associations between population-enriched genetic variants and predefined health-related traits identified through GWAS.
12 month

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Multiple correlation between gout, hyperuricemia, type 2 diabetes and obesity
Time Frame: 12 month
Anthropometric and biological characteristics of gout, hyperuricemia, type 2 diabetes, and obesity will be assessed, and comorbidity associations analyzed using multivariate logistic regression. Measurements will include waist and hip circumferences, blood pressure, muscle properties by myotonometry, lower-limb strength via chair stand test, and handgrip strength. Blood analyses will assess lipid profile, liver function, inflammation, renal function and metabolism, glucose metabolism, and complete blood count. Urine analyses will also be performed.
12 month
Incidence rate of gout or HU in French Polynesia between 2021 and 2025
Time Frame: 4 years
Incidence rate of gout or HU in French Polynesia between 2021 and 2025 in a sample of participants in the 2021 cohort with asymptomatic HU and no gout.
4 years
Proportion of each type of urate-lowering therapy prescribed annually between 2019 and 2025
Time Frame: 4 years
Breakdown of types of THU prescribed between 2019 and 2025 based on the database of healthcare claims submitted to the Caisse de Prévoyance Sociale (CPS)
4 years
Incidence of major adverse cardiovascular events (MACE) in patients with gout, diabetes, or obesity
Time Frame: 12 month
Occurrence of MACE related to gout, diabetes or obesity on the Healthcare Claims Database (HCD).
12 month
Determinants of progression from asymptomatic hyperuricemia (in 2021) to gout (in 2025)
Time Frame: 4 years
Factors influencing the transition from asymptomatic HU to gout will be sought among demographic, anthropomorphic and biological characteristics, comorbidities, current treatments, genetic profiles, gene expression, proteomic profiles and metabolomic profiles.
4 years
Multiple correlation between metabolic changes and disease evolution
Time Frame: 12 month
Severe gout is defined by subcutaneous tophi. Clinical characteristics will be assessed, including disease features (age at onset, duration), topography (affected joints, mono-/polyarticular and axial involvement), number, duration, and severity of flares, serum uric acid, and presence, number, and size of tophi. Treatment history and response (urate-lowering therapy, flare management), comorbidities (cardiovascular disease, chronic kidney disease, metabolic syndrome, diabetes, obesity, hypertension), and lifestyle factors (diet, alcohol, physical activity) will also be recorded. Molecular and biological characterization will include genetic, transcriptomic, proteomic, and metabolomic analyses to identify biomarkers associated with disease severity and progression.
12 month
Multiple correlation between molecular, clinical features and gout severity
Time Frame: 12 month
Severe gout is defined by subcutaneous tophi. Clinical characteristics will be evaluated, including disease features (age at onset, duration), topography (affected joints, mono-/polyarticular and axial involvement), number, duration, and severity of flares, serum uric acid, and presence, number, and size of tophi. Treatment history and response (urate-lowering therapy, flare management), comorbidities (cardiovascular disease, chronic kidney disease, metabolic syndrome, diabetes, obesity, hypertension), and lifestyle factors (diet, alcohol, physical activity) will also be recorded. Molecular and biological characterization will include genetic, transcriptomic, proteomic, and metabolomic analyses to identify biomarkers linked to disease severity and progression.
12 month
Multiple correlation between gout attacks, clinical manifestations, gene expression, proteomic, and metabolomic profiles.
Time Frame: 12 month
Gout attack characteristics will be investigated, including attack location (affected joints, mono- or polyarticular), pain intensity (VAS or NRS), and inflammatory parameters (CRP, ESR if available, leukocyte count and differential). Synovial fluid analysis will include total and differential cell counts and presence of monosodium urate crystals. Triggering factors (diet, alcohol, trauma, infection, medications), associated acute conditions (infection, surgery, cardiovascular events), and flare duration and severity will be recorded. Treatments and clinical response will also be documented. Molecular characterization will include genetic analyses (urate transport and inflammation variants), gene expression, proteomic profiling of blood and synovial fluid, and metabolomic analyses of serum, urine, and synovial fluid to identify biomarkers of acute flares.
12 month
Change in clinical and molecular characteristics of acute gout flares between baseline and 1-week visit
Time Frame: one week
Composite assessment of acute gout flares including clinical characteristics (attack location, mono- or polyarticular involvement, pain intensity measured by VAS or NRS, inflammatory markers [CRP, ESR if available, leukocyte count and differential]), synovial fluid findings (total and differential cell counts and presence of monosodium urate crystals), triggering factors and associated acute conditions, flare duration and severity, treatments administered and clinical response, and molecular biomarkers identified through genetic analyses, gene expression profiling, proteomic analyses, and metabolomic profiling of blood, urine, and synovial fluid.
one week

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Collaborators

Investigators

  • Principal Investigator: Tristan Pascart, Professor, GHICL

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

September 2, 2025

Primary Completion (Estimated)

September 1, 2027

Study Completion (Estimated)

September 1, 2027

Study Registration Dates

First Submitted

October 1, 2025

First Submitted That Met QC Criteria

January 6, 2026

First Posted (Actual)

January 15, 2026

Study Record Updates

Last Update Posted (Actual)

January 15, 2026

Last Update Submitted That Met QC Criteria

January 6, 2026

Last Verified

January 1, 2026

More Information

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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