Tahiti-families: From Genetic to Phenotype Study of Polynesian Families of Gout Patients
试验速览
- 阶段
- 不适用
- 状态
- 已完成
- 发起方
- 入组人数
- 33
- 试验地点
- 2
- 主要终点
- Multiple correlation between genetic variants and clinical presentation
研究概览
简要总结
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.
研究设计
- 研究类型
- Interventional
- 分配方式
- Non Randomized
- 干预模型
- Parallel
- 主要目的
- Other
- 盲法
- None
入排标准
- 年龄范围
- 18 Years 至 80 Years(Adult, Older Adult)
- 性别
- All
- 接受健康志愿者
- 是
入选标准
- •Case group :
- •Gout patients
- •Polynesian origin
- •Aged 18 to 80 years
- •Agreeing to participate in the study
- •Having a 1st or 2nd degree relative who is also gouty and a 1st degree relative of the same generation and sex who is not gouty
- •Control group :
- •Non-gouty individuals who are 1st degree relatives of a gouty patient of the same generation and sex
- •Aged 18 to 80 years
- •Agreeing to participate in the study
排除标准
- •Pregnant women
- •Persons under guardianship, curatorship or other legal incapacity
- •Persons with a contraindication to Magnetic resonance imaging (MRI) examination
- •For non-gouty controls : current hyperuricemic treatment (Allopurinol, Febuxostat, Probenecid or Benzbromarone)
- •For gouty case : not participating in the TOPATA study (NCT04812886)
研究组 & 干预措施
Case group : gout patients
Epidemiological study
干预措施: Epidemiological study (Other)
Control group
Epidemiological study
干预措施: Epidemiological study (Other)
结局指标
主要结局
Multiple correlation between genetic variants and clinical presentation
时间窗: 4 months
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
次要结局
- Multiple correlation between severity of gout, its impact (pain, disease impact, and quality of life), presence of certain genetic variants, metabolomic changes and comorbidities(4 months)
- Multiple correlation between genetic variants, comorbidities, environmental factors, presence of gout(4 months)
- Multiple correlation between disease stage, comorbidities, environmental and metabolomics data(4 months)
