A QTL genome scan of the metabolic syndrome and its component traits

A QTL genome scan of the metabolic syndrome and its component traits
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DOI:
10.1186/1471-2156-4-s1-s96
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发表时间:
2003-12-31
期刊:
影响因子:
2.9
通讯作者:
Santangelo, SL
Santangelo, SL
中科院分区:
生物学3区
文献类型:
--
作者:
McQueen, MB;Bertram, L;Santangelo, SL

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背景:由于高血压、血脂水平改变、肥胖和糖尿病经常同时发生,因此有时将它们统称为代谢综合征。虽然对每种代谢综合征特征进行了许多单独的研究,但很少有研究尝试在数量性状连锁或关联分析中将它们组合起来(即作为一个复合变量)进行分析。我们使用弗雷明汉心脏研究的基因型和表型数据对代谢综合征背后的数量性状基因座进行全基因组扫描。结果:所有协变量调整和年龄和性别标准化的个体性状以及复合代谢综合征性状的遗传力估计值都相当高(0.39-0.62),并且复合性状 是最高的,达到 0.61。根据 Lander 和 Kruglyak 的标准,复合性状没有产生具有暗示性连锁的区域,尽管个体性状有几个值得注意的区域,其中一些在复合变量中也被观察到。结论:尽管复合代谢综合征性状变量具有高遗传力,但并没有增加检测或定位该样本中连锁峰的能力。然而,这种结合相关个体特征的策略和相关方法值得进一步研究,特别是在具有复杂因果路径的环境中。
Background: Because high blood pressure, altered lipid levels, obesity, and diabetes so frequently occur together, they are sometimes collectively referred to as the metabolic syndrome. While there have been many studies of each metabolic syndrome trait separately, few studies have attempted to analyze them combined, i.e., as one composite variable, in quantitative trait linkage or association analysis. We used genotype and phenotype data from the Framingham Heart Study to perform a full-genome scan for quantitative trait loci underlying the metabolic syndrome.Results: Heritability estimates for all of the covariate-adjusted and age- and gender-standardized individual traits, and the composite metabolic syndrome trait, were all fairly high (0.39-0.62), and the composite trait was among the highest at 0.61. The composite trait yielded no regions with suggestive linkage by Lander and Kruglyak's criteria, although there were several noteworthy regions for individual traits, some of which were also observed for the composite variable.Conclusion: Despite its high heritability, the composite metabolic syndrome trait variable did not increase the power to detect or localize linkage peaks in this sample. However, this strategy and related methods of combining correlated individual traits deserve further investigation, particularly in settings with complex causal pathways.