Mutational load analysis of unrelated individuals.
Mutational load analysis of unrelated individuals.
复制标题
DOI：
10.1186/1753-6561-5-s9-s55
复制
发表时间：
2011-11-29
期刊：
影响因子：
--
通讯作者：
McQueen, Matthew B
中科院分区：
文献类型：
--
作者：
Howrigan, Daniel P;Simonson, Matthew A;McQueen, Matthew B
进化遗传模型预测，基因组中罕见有害突变的累积效应--称为突变负荷--增加了对复杂疾病的易感性。为了检验突变负荷假设，我们采用了两层方法：评估全外显子组次要等位基因负荷负荷的影响，然后进行单个基因筛查。对于我们的初步分析，我们检查了各种次要等位基因频率（MAF）阈值和加权方案，以检查次要等位基因负荷对情感状态的总体影响。我们发现次要等位基因负荷和情感状态之间存在一致的关联，但这种效应在罕见和/或功能性单核苷酸多态性（SNP）中并没有显著增加。我们的后续分析考虑了单个基因中的次要等位基因负荷，以确定是否只有一个或几个基因驱动了整体效应。检查我们最重要的结果-MAF < 2.4%的非同义SNP的次要等位基因负荷-我们在Bonferroni校正多重测试后没有检测到显著相关的基因。在去除中度显著性基因（p < 0.05）后，稀有非同义等位基因负荷的总体效应仍然显著。总的来说，我们没有发现明确的支持突变负荷负担的影响状态;然而，这些结果最终取决于遗传分析研讨会17模拟的性质，并受到其限制。
Evolutionary genetic models predict that the cumulative effect of rare deleterious mutations across the genome-known as mutational load burden-increases the susceptibility to complex disease. To test the mutational load burden hypothesis, we adopted a two-tiered approach: assessing the impact of whole-exome minor allele load burden and then conducting individual-gene screening. For our primary analysis, we examined various minor allele frequency (MAF) thresholds and weighting schemes to examine the overall effect of minor allele load on affection status. We found a consistent association between minor allele load and affection status, but this effect did not markedly increase within rare and/or functional single-nucleotide polymorphisms (SNPs). Our follow-up analysis considered minor allele load in individual genes to see whether only one or a few genes were driving the overall effect. Examining our most significant result-minor allele load of nonsynonymous SNPs with MAF < 2.4%-we detected no significantly associated genes after Bonferroni correction for multiple testing. After moderately significant genes (p < 0.05) were removed, the overall effect of rare nonsynonymous allele load remained significant. Overall, we did not find clear support for mutational load burden on affection status; however, these results are ultimately dependent on and limited by the nature of the Genetic Analysis Workshop 17 simulation.