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Stepwise approach to SNP-set analysis illustrated with the Metabochip and colorectal cancer in Japanese Americans of the Multiethnic Cohort

机译:逐步接近SNP-Set分析,并在不同种族的群组中的MetaboChip和结肠直肠癌中显示出来的分析

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Common variants have explained less than the amount of heritability expected for complex diseases, which has led to interest in less-common variants and more powerful approaches to the analysis of whole-genome scans. Because of low frequency (low statistical power), less-common variants are best analyzed using SNP-set methods such as gene-set or pathway-based analyses. However, there is as yet no clear consensus regarding how to focus in on potential risk variants following set-based analyses. We used a stepwise, telescoping approach to analyze common- and rare-variant data from the Illumina Metabochip array to assess genomic association with colorectal cancer (CRC) in the Japanese sub-population of the Multiethnic Cohort (676 cases, 7180 controls). We started with pathway analysis of SNPs that are in genes and pathways having known mechanistic roles in colorectal cancer, then focused on genes within the pathways that evidenced association with CRC, and finally assessed individual SNPs within the genes that evidenced association. Pathway SNPs downloaded from the dbSNP database were cross-matched with Metabochip SNPs and analyzed using the logistic kernel machine regression approach (logistic SNP-set kernel-machine association test, or sequence kernel association test; SKAT) and related methods. The TGF-β and WNT pathways were associated with all CRC, and the WNT pathway was associated with colon cancer. Individual genes demonstrating the strongest associations were TGFBR2 in the TGF-β pathway and SMAD7 (which is involved in both the TGF-β and WNT pathways). As partial validation of our approach, a known CRC risk variant in SMAD7 (in both the TGF-β and WNT pathways: rs11874392) was associated with CRC risk in our data. We also detected two novel candidate CRC risk variants (rs13075948 and rs17025857) in TGFBR2, a gene known to be associated with CRC risk. A stepwise, telescoping approach identified some potentially novel risk variants associated with colorectal cancer, so it may be a useful method for following up on results of set-based SNP analyses. Further work is required to assess the statistical characteristics of the approach, and additional applications should aid in better clarifying its utility.
机译:常见的变体已经解释了复杂疾病预期的遗传性的量,这导致了对较常见的变种以及对全基因组扫描分析的更强大的方法感兴趣。由于低频(低统计功率),使用SNP集合方法(如基于基于途径)的SNP集合方法最佳地分析了较少常见的变体。但是,关于如何关注基于集合的分析后的潜在风险变量,尚未明确的共识。我们使用逐步,伸缩方法来分析来自Illumina Metabochip阵列的常见和稀有变体数据,以评估日本多民族群组中的结肠直肠癌(CRC)的基因组关联(676例,7180例,控制)。我们开始伴随着在基因和途径中的SNP途径分析,该途径在结肠直肠癌中具有已知的机械作用,然后重点关注途径内的基因,其显着与CRC联系,最后评估了显着的基因内的个体SNP。从DBSNP数据库下载的途径SNP与MetaboChip SNP交叉匹配,并使用Logistic内核机回归方法(Logistic SNP-Set Kernel-Machinaify测试或序列核关联测试; SKAT)和相关方法进行分析。 TGF-β和WNT途径与所有CRC相关,WNT途径与结肠癌有关。表现出最强的关联的个体基因是TGF-β途径和Smad7中的TGFBR2(参与TGF-β和WNT途径)。作为我们方法的局部验证,SMAD7中已知的CRC风险变量(在TGF-β和WNT路径中:RS11874392)与我们的数据中的CRC风险相关。我们还在TGFBR2中检测到两种新候选CRC风险变量(RS13075948和RS17025857),该基因已知与CRC风险相关。逐步,伸缩方法鉴定了与结直肠癌相关的一些可能的新风险变体,因此可以是用于跟进基于SEN的SNP分析结果的有用方法。需要进一步的工作来评估方法的统计特征,另外的申请应该有助于更好地澄清其实用程序。

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