测试多个遗传标记与多项式性状关联的新方法。

Soonil Kwon, Mark O Goodarzi, Kent D Taylor, Jinrui Cui, Y-D Ida Chen, Jerome I Rotter, Willa Hsueh, Xiuqing Guo
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引用次数: 0

摘要

我们利用最大似然估计和置换方法,开发了一种具有奇异值分解的多项式概率模型,用于同时测试大量单核苷酸多态性(SNPs)。我们通过模拟验证了该方法。我们模拟了 1000 个 SNPs,其中包括 9 个与疾病状态相关的 SNPs,并成功鉴定了 9 个 SNPs 中的 8 个。应用该方法对墨西哥裔美国人样本中的 32 个基因进行了研究,通过糖耐量受损 (IGT) 或空腹血糖受损 (IFG) 来寻找与糖尿病前期的关联,我们发现了 3 个基因(SORCS1、我们发现 3 个基因(SORCS1、AMPD1、PPAR)同时与 IGT 和 IFG 相关,5 个基因(AMPD2、PRKAA2、C5、TCF7L2、ITR)仅与 IGT 机制相关,6 个基因(CAPN10、IL4、NOS3、CD14、GCG、SORT1)仅与 IFG 机制相关。这些数据表明,IGT 和 IFG 可能通过不同的遗传决定因素表明了糖尿病前期的不同生理机制。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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A novel method for testing association of multiple genetic markers with a multinomial trait.

We developed a multinomial probit model with singular value decomposition for testing a large number of single nucleotide polymorphisms (SNPs) simultaneously, using maximum likelihood estimation and permutation. The method was validated by simulation. We simulated 1000 SNPs, including 9 associated with disease states, and 8 of the 9 were successfully identified. Applying the method to study 32 genes in our Mexican-American samples for association with prediabetes through either impaired glucose tolerance (IGT) or impaired fasting glucose (IFG), we found 3 genes (SORCS1, AMPD1, PPAR) associated with both IGT and IFG, while 5 genes (AMPD2, PRKAA2, C5, TCF7L2, ITR) with the IGT mechanism only and 6 genes (CAPN10, IL4,NOS3, CD14, GCG, SORT1) with the IFG mechanism only. These data suggest that IGT and IFG may indicate different physiological mechanism to prediabetes, via different genetic determinants.

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