Identifying Susceptibility Genes for Metabolic Syndrome

代谢综合征（MS）描述了胰岛素抵抗和代谢性CVD危险因素的聚集。鉴于这种情况造成的重大临床和公共卫生负担，进一步了解其遗传病因是重要的。最近在NHLBI家族心脏研究（FHS）中对MS的综合测量进行的基因组扫描发现，在240 cM处2号染色体上存在显著连锁（LOD=3.34，p=0.00004）。至少有14项与MS相关的表型的其他研究涉及2号染色体的这一相同的广泛区域。 连锁不平衡（LD）作图以鉴定影响MS易感性的基因。 将使用多种策略来鉴定、表征和确认该区域的MS基因。将对来自150个FHS家系的1122名受试者中的16个候选基因进行单核苷酸多态性（SNP）基因分型，这些候选基因按生物学功能（平均密度为1/10 kb）进行优先级排序，这些受试者对连锁峰有贡献。对于这些候选基因以外的区域，将以平均密度1/30 kb对SNP进行分型。国家的最先进的方法将被用来模拟模式的LD和确定重组热点。将使用基于家族的方法来测试个体SNP和多位点单倍型与MS复合测量之间的关联。在初步结果的基础上，选定的区域和候选基因将被额外的SNP饱和，以识别致病变异。为了证实最令人信服的发现，SNPs或单倍型与复合MS测量之间的关联将在从FHS随机选择的无关受试者（n=750）的独立样本中进行测试。此外，还将在淋巴母细胞系、前脂肪细胞组织和脑样本中检测相关SNP对基因表达的影响。鉴定影响MS的基因不仅将进一步理解解释异常聚集的病因学途径，而且还可能提供筛查和预防的新策略。

The metabolic syndrome (MS) describes the clustering of insulin resistance and metabolic CVD risk factors. Given the substantial clinical and public health burden imposed by this condition, further understanding of its genetic etiology is important. A recent genome scans for a composite measure of the MS in the NHLBI Family Heart Study (FHS) found significant linkage on chromosome 2 at 240 cM (LOD=3.34, p=0.00004). This same broad region of chromosome 2 has been implicated by at least 14 other studies for phenotypes related to the MS. The overall goal of this 3-year project is to characterize a 19.5 Mb region on chromosome 2q35-2q37 using linkage disequilibrium (LD) mapping to identify genes influencing susceptibility to the MS. Multiple strategies will be used to identify, characterize, and confirm MS genes in this region. Single nucleotide polymorphisms (SNPs) will be genotyped in 16 candidate genes prioritized by biological function (average density 1 per 10 kb) in 1122 subjects from the 150 FHS pedigrees contributing to the linkage peak. For regions outside these candidate genes, SNPs will be typed an average density 1 per 30 kb. State-of the-art methods will be used to model patterns of LD and identify recombination hotspots. Family-based methods will be used to test associations between individual SNPs and multilocus haplotypes and the MS composite measure. Building on initial results, selected regions and candidate genes will be saturated with additional SNPs in an effort to identify causal variants. To confirm the most compelling findings, associations between SNPs or haplotypes and the composite MS measure will be tested in an independent sample of randomly selected unrelated subjects (n=750) from FHS. In addition, the effects of implicated SNPs on gene expression will be tested in lymphoblast cell lines, preadipocyte tissue, and brain samples. Identification of genes influencing the MS will not only further the understanding of etiologic pathways that explain the clustering of abnormalities, but also may offer novel strategies for screening and prevention.