Genetic Epidemiology of Body Mass Index, Adiposity and Weight Gain

描述(申请人提供)：肥胖是美国和世界范围内发病率和死亡率的主要原因。识别增加肥胖易感性的基因将通过提供有关肥胖症的发展和治疗的基本生物学和临床数据，并通过建议高危个人具体的生活方式变化来影响公共健康。肥胖是一种复杂的疾病，有明确的遗传和环境风险因素，但导致这种风险增加的实际基因很少，肥胖症发生的潜在机制仍然不清楚。我们广泛的长期目标是识别增加对体重指数、肥胖症和体重增加的易感性的遗传变异，并表征这些遗传变异与行为因素之间的相互作用。作为宿务纵向健康和营养调查(CLHNS)的一部分，我们建议对过去22年收集了详细的人体测量、环境、饮食和体力活动数据的菲律宾妇女进行大样本研究。在目前的应用中，我们建议使用选定的基因对CLHNS女性的体重指数、肥胖和体重增加的数量和纵向特征进行遗传分析。我们将根据功能数据、与小鼠肥胖相关的顺式作用表达数量性状基因座以及在其他人类群体中存在关联的先前证据来选择和优先选择基因。在高通量基因分型、单核苷酸多态(SNP)发现和单倍型图谱(HapMap)构建方面的最新技术进步提供了前所未有的工具，使得能够比以前更彻底地分析选定的基因。我们建议对720个选定基因中的12,000个SNP进行深入的关联分析，方法是评估1896名女性中常见的和可能的功能SNPs样本集。我们将评估体重增加的纵向指标的关联性，并评估遗传变异、饮食结构和体力活动指标之间的相互作用。有希望的关联将在其他大型队列研究中进行评估，以确定最可能的易感变异。我们坚信，对遗传因素及其相互作用的详细研究是确定有针对性的肥胖预防策略和治疗方法的关键一步。

DESCRIPTION (provided by applicant): Obesity is a major cause of morbidity and mortality in the USA and worldwide. Identification of genes increasing susceptibility to obesity would impact public health by providing basic biological and clinical data about development and treatment of obesity and by advising specific lifestyle changes in at-risk individuals. Obesity is a complex disease with clear genetic and environmental risk factors, however few actual genes leading to this increased risk have been identified and the underlying mechanisms by which obesity develops remain obscure. Our broad long-term objectives are to identify genetic variants increasing susceptibility to body mass index, adiposity, and weight gain and to characterize the interactions between these genetic variants and behavioral factors. We propose to study a large sample of Filipino women for which detailed anthropometric, environmental, diet and physical activity data have been collected for the past 22 years as part of the Cebu Longitudinal Health and Nutrition Survey (CLHNS). In the current application, we propose genetic analysis of the quantitative and longitudinal traits of body mass index, adiposity, and weight gain using selected genes in the CLHNS women. We will select and prioritize genes based on functional data, cis-acting expression quantitative trait loci correlated with obesity in mice, and prior evidence of association in other human populations. Recent technical advances in high-throughput genotyping, single nucleotide polymorphism (SNP) discovery and haplotype map (HapMap) construction provide unprecedented tools enabling more thorough analysis of selected genes than was previously possible. We propose to perform in- depth association analysis of 12,000 SNPs in 720 selected genes by evaluating common and likely functional SNPs in a large, well-characterized sample set of 1896 women. We will evaluate association with longitudinal measures of weight gain and we will evaluate interactions between genetic variants, diet composition and physical activity measures. Promising associations will be evaluated in other large cohort studies, to identify the most likely susceptibility variants. We strongly believe that a detailed study of genetic factors and their interactions is an essential step to identifying targeted obesity prevention strategies and treatments.