Diabesity Gene Discovery at Chromosome 6q23

描述(申请人提供)：2型糖尿病(T2 DM)和相关疾病是一个主要的健康问题，在大多数人类人口中患病率迅速上升。我们已经确定了一个染色体位置(6q23)，该位置与墨西哥裔美国人的“肥胖”表型密切相关。表型包括空腹血浆胰岛素和肥胖。这些发现最近在其他几个人群中得到了独立的复制。我们建议在一个大型墨西哥裔美国人队列中定位和鉴定位于6q23的一个或多个易感基因，该队列包括来自两个大规模人群研究(SAFADS/SAFGDS和VAGES)的2000名受试者。这是墨西哥裔美国人DNA和糖尿病基因发现表型数据的最大储存库，并提供了前所未有的基因定位能力。全基因组扫描已在SAFADS/SAFGDS中完成，不久将在VAGES中完成。我们将从公共和私人SNP数据库中选择单核苷酸多态(SNP)，这些SNP以高密度(每10kb 1个)覆盖连接区域。SNPs将定位在基因为中心的连锁峰区内，该连锁高峰区域负责99%的连锁证据。这些SNP将使用高通量程序进行基因分型，所产生的数据将用于测量连锁不平衡和定义区域内的单倍型结构。SNP基因分型将以一种新的成本最小化的三阶段策略进行，使用逐渐增大的数据集。我们将计算SNPs与糖尿病表型的关联，并根据关联的SNPs进行连锁分析，以定义包含解释所观察到的连锁的变异的基因座。确定的一个或多个目标基因内所有常见的以基因为中心的SNPs将被分型，并使用一种新的数量性状核苷酸(QTN)方法分析数据，该方法同时利用来自所有SNPs的信息来充分考虑关联。对最高概率基因(S)的严格验证将利用一系列统计和分子遗传学技术：(I)QTN和条件连锁分析；(Ii)基因/信使核糖核酸/蛋白质结构、功能和细胞位置的生物信息学分析和预测；以及(Iii)在设计补充性体内临床研究之前，使用DNA微阵列和定量RT-PCR在适当的细胞系中分析该基因的正常和变异形式的表达，以阐明病理生理机制。

DESCRIPTION (provided by applicant): Type 2 diabetes mellitus (T2DM) and related disorders are a major health problem and rapidly increasing in prevalence in most human populations. We have identified a chromosomal location (6q23) which is strongly linked to "diabesity" phenotypes in Mexican Americans. The phenotypes include fasting plasma insulin and obesity. These findings have recently been independently replicated in several other populations. We propose to localize and identify the susceptibility gene or genes located at 6q23 in a large Mexican American cohort comprising > 2,000 subjects from two large population studies (SAFADS/SAFGDS and VAGES). This is the largest repository of Mexican American DNAs and phenotypic data for diabetes gene discovery and provides unprecedented power to localize genes. Genome-wide scans are complete in SAFADS/SAFGDS and will soon be completed in VAGES. We will select single nucleotide polymorphisms (SNPs), from public and private SNP databases, which cover the linked region at high density (1 per 10 kb). The SNPs will be located gene-centrically within the linkage peak region responsible for > 99% of the evidence for linkage. These SNPs will be genotyped using high-throughput procedures, and the resulting data will be used to measure linkage disequilibrium and define haplotype structure within the region. SNP genotyping will be performed in a novel cost-minimizing three-phase strategy using progressively larger datasets. We will calculate association of SNPs with diabesity phenotypes and perform linkage analysis conditional on associated SNPs, to define loci which contain variants that account for the observed linkage. All common gene-centric SNPs within a defined target gene or genes will be genotyped and the data analyzed using a novel quantitative trait nucleotide (QTN) approach which utilizes the information from all SNPs simultaneously to fully account for association. Rigorous validation of the highest probability gene(s) will utilize a battery of statistical and molecular genetic techniques: (i) QTN and conditional linkage analyses; (ii) bioinformatic analysis and prediction of gene/mRNA/protein structure, function, and cellular location; and (iii) expression analyses of normal and variant forms of the gene using DNA microarrays and quantitative RT-PCR, in appropriate cell lines, under various nutritional and hormonal perturbations, to elucidate pathophysiological mechanisms, prior to the design of complementary in vivo clinical studies.