Gout is a chronic disease caused by the deposit of monosodium urate (MSU) crystals in body tissues secondary to hyperuricemia. Patients with gout suffer severe attacks of acute joint pain. As the disease progresses, the joint pain becomes chronic and associated with disabling and deformative manifestations called tophus. This disease is strongly associated with several comorbidities such as cardiovascular disease and chronic kidney failure. Gout is a very common disease, which is affecting 0.9% of the adult population in France and nearly 4% of the North-American population. Data from New Zealand show a particularly high prevalence of gout among Polynesians (minority populations in New Zealand and other islands of the South Pacific) that would be explained by genetic susceptibility and frequently interrelated metabolic diseases. Data on the Polynesian population in New Caledonia suggest prevalence figures close to 7% and prevalence in French Polynesia is assumed to be higher. International genomic studies of gout and hyperuricaemia have identified alleles associated with the occurrence of gout. The aim is to focus on families with several gouty members (numerous in French Polynesia, and geographically clustered) in order to enable the study of individuals with monogenic gout or with a low number of variants (= cases) determining in the occurrence of gout, as well as a non-gouty family member (= controls). Dual-energy CT scan (DECT) allows identification and quantification of UMS crystal deposits in the tissue. The volume of crystals correlates not only with the inflammatory activity of the disease but also with the comorbidities that complicate it. Dual-energy scanning has shown the presence of UMS crystals in some hyperuricemic individuals, which could help to identify those individuals most at risk of developing the disease as they already have the stigma of sub-clinical inflammatory activity.
Study Type
INTERVENTIONAL
Allocation
NON_RANDOMIZED
Purpose
OTHER
Masking
NONE
Enrollment
33
* Clinical phenotypic assessment and neurosensory measures * Biological, genetic and metabolomic evaluation * Questionnaires (quality of life, gout, life habit, comorbidities) * Morphological evaluation by Dual-energy CT scan
Centre Hospitalier de Polynésie Française
Papeete, Ville de Pirae, French Polynesia
Multiple correlation between genetic variants and clinical presentation
Genome-wide association study (GWAS) aims at identifying genetic variants (genotype) that associated with specific traits (phenotype). The link between the genetic variants and the stage of the disease will be sought using a bivariate analysis: Chi-2 tests or Fisher's exact tests in case of small numbers will be implemented
Time frame: 4 months
Multiple correlation between disease stage, comorbidities, environmental and metabolomics data
The link between variants will be stablish using a multivariate logistic regression model.- The comorbidities analysed are the following: initial uraemia, glomerular filtration rate (GFR), hypertension, chronic heart failure, diabetes, obesity (BMI \> 30), obliterative arterial disease of the lower limbs, history of myocardial infarction, history of cerebrovascular accident \- The environmental data analysed were as follows: habitus data (alcohol consumption, soft drinks, physical activity)
Time frame: 4 months
Multiple correlation between severity of gout, its impact (pain, disease impact, and quality of life), presence of certain genetic variants, metabolomic changes and comorbidities
The link between variants will be stablish using a multivariate logistic regression model. Quality of life will be assessed by the EuroQol questionnaire; perception of hyperuricemia-related illness by the Brief Hyperuricemia Perceptions Questionnaire (BIPQ); body and foot pain in the previous week by a VAS out of 100; activity limitations by the Health Assessment Questionnaire (HAQ-II); foot pain and disability by the Manchester Foot Pain and Disability Index (MFPDI).
Time frame: 4 months
Multiple correlation between genetic variants, comorbidities, environmental factors, presence of gout
The link between variants will be stablish using a multivariate logistic regression model. Health status will be assessed by the following elements: * Perceived health status: good (modalities "very good" and "good") / bad ("average", "bad" and "very bad") * Total number of visits to a health professional in the last 12 monthsThe presence of gout will be determined using a calculation combining and weighting different responses to the questionnaires. The diagnosis of gout is retained if the patient meets the 2015 ACR/EULAR criteria for diagnostic classification of gout.
Time frame: 4 months
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