Genome Wide Association Studies (GWAS) to Identify Candidate Obesity Susceptibility Genes in a Carefully Phenotyped, Metabolically Healthy Population of Obese White Adults
试验速览
- 阶段
- 不适用
- 状态
- 已完成
- 入组人数
- 81
- 主要终点
- number of SNPs associated with high BMI
研究概览
简要总结
This is a GWAS pilot study that aims to identified possible candidate genes associate to obesity by exploring single nucleotide polymorphism (SNP) in a small group of obese , metabolically healthy white adults, matched with lean, white adults , metabolically healthy. The investigators hypothesize that the careful phenotyping of the subject sand matching with increase the power to find SNP significantly associate with obesity (as defined by BMI).
详细描述
Between 60%-70% of the risk of obesity appears to be heritable. Unfortunately, the exact genes involved have been difficult to identify. New technologies now exist to help researchers discover obesity susceptibility genes. One of these technologies is the Affymetrix Genome-Wide Human SNP (single nucleotide polymorphism) Array 6.0 chips. SNPs are individual base pair differences in genes of different individuals, and they are the main source of human genetic diversity. The "chips" are thumbnail-size silicon surfaces that contain copies of hundreds of thousands of SNPs of the human genome (in this case around 900,000). SNP chips allow researchers to screen thousands of genes in a single experiment and compare genes of subjects with a particular disease or condition with unaffected control subjects. The investigators study utilizes SNP chips to compare the genetic profiles of obese subjects (N = 20, body mass index > 35 kg/m2) without common obesity-related co-morbidities such as diabetes mellitus or hypertension with well matched, lean controls (N = 20, body mass index 18-25 kg/m2). This is a pilot study intended to explore the following: 1) possible associations between obesity and previously unidentified obesity susceptibility genes; 2) associations between known obesity genes and obesity risk in subjects without obesity-related metabolic co-morbidities; and 3) how well our genetic data conform to other studies in similar populations as a way of assessing if the investigators have identified a representative cohort of obese subjects.
研究设计
- 研究类型
- Interventional
- 分配方式
- Non Randomized
- 干预模型
- Parallel
- 主要目的
- Diagnostic
- 盲法
- None
入排标准
- 年龄范围
- 40 Years 至 80 Years（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 是
入选标准
- •- Adults 40 year old or older
- •Caucasian males or females
- •BMI ≥ 35 kg/m² or history of BMI ≥ 35 kg/m², or BMi less than 25 kg/m2
- •No current or past use of glucose lowering drugs
- •No current or past medical history of diabetes mellitus
- •No current or past medical history of established coronary artery disease (angina, myocardial infraction, abnormal cardiac stress test)
- •No current or past medical history of or treatment for thyroid disorders
- •No current or past use of lipid lowering drugs or diagnosis of a lipid disorder
- •No current or past medical history of or treatment for hypertension
- •Subject's willingness to provide the study investigators with a copy of their medical records or give permission to the study investigators to access the following specific medical information:
- •Fasting plasma glucose (less than 100 mg/dL/5.6 mmol/L)
- •HDL-C cholesterol (more than 40 mg/dL /1.03 mmol/L)
- •Total cholesterol (less than 239 mg/dL/ 6.18mmol/L)
- •LDL cholesterol (less than 159 mg/dL/4.11 mmol/L)
排除标准
- •- Known monogenic forms of obesity
- •Polycystic ovary disease (in women)
- •Malabsorptive or maldigestive syndromes (Celiac disease, Crohn's Disease, inflammatory bowel disease, etc.)
- •Anorexia nervosa or bulimia
结局指标
主要结局
number of SNPs associated with high BMI
时间窗: baseline
Using GWAS to identify candidate genes associate with obesity (high BMI) in a carefully phenotyped white adults with obesity (as defined by BMI), metabolically healthy, matched with lean, white adults metabolically healthy.
次要结局
未报告次要终点
研究者
Doina Kulick, MD
Associate Professor of Medicine
University of Nevada, Reno