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
{"title":"测试多个遗传标记与多项式性状关联的新方法。","authors":"Soonil Kwon, Mark O Goodarzi, Kent D Taylor, Jinrui Cui, Y-D Ida Chen, Jerome I Rotter, Willa Hsueh, Xiuqing Guo","doi":"","DOIUrl":null,"url":null,"abstract":"<p><p>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.</p>","PeriodicalId":87345,"journal":{"name":"Proceedings. American Statistical Association. Annual Meeting","volume":"2010 ","pages":"3971-3979"},"PeriodicalIF":0.0000,"publicationDate":"2010-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4439253/pdf/nihms681398.pdf","citationCount":"0","resultStr":"{\"title\":\"A novel method for testing association of multiple genetic markers with a multinomial trait.\",\"authors\":\"Soonil Kwon, Mark O Goodarzi, Kent D Taylor, Jinrui Cui, Y-D Ida Chen, Jerome I Rotter, Willa Hsueh, Xiuqing Guo\",\"doi\":\"\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>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.</p>\",\"PeriodicalId\":87345,\"journal\":{\"name\":\"Proceedings. American Statistical Association. Annual Meeting\",\"volume\":\"2010 \",\"pages\":\"3971-3979\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4439253/pdf/nihms681398.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings. American Statistical Association. Annual Meeting\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings. American Statistical Association. Annual Meeting","FirstCategoryId":"1085","ListUrlMain":"","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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。

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

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

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

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.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信