Iles Mark M
Section of Epidemiology and Biostatistics, Cancer Research UK Clinical Centre, Leeds Institute of Molecular Medicine, University of Leeds, St James's University Hospital, Beckett Street, Leeds, LS9 7TF, UK.
Ann Hum Genet. 2010 Jul;74(4):375-9. doi: 10.1111/j.1469-1809.2010.00579.x.
When conducting a genetic association study, it has previously been observed that a multiplicative risk model tends to fit better at a disease-associated marker locus than at the ungenotyped causative locus. This suggests that, while overall risk decreases as linkage disequilibrium breaks down, non-multiplicative components are more affected. This effect is investigated here, in particular the practical consequences it has on testing for trait/marker associations and the estimation of mode of inheritance and risk once an associated locus has been found. The extreme significance levels required for genome-wide association studies define a restricted range of detectable allele frequencies and effect sizes. For such parameters there is little to be gained by using a test that models the correct mode of inheritance rather than the multiplicative; thus the Cochran-Armitage trend test, which assumes a multiplicative model, is preferable to a more general model as it uses fewer degrees of freedom. Equally when estimating risk, it is likely that a multiplicative risk model will provide a good fit to the data, regardless of the underlying mode of inheritance at the true susceptibility locus. This may lead to problems in interpreting risk estimates.
在进行基因关联研究时，之前已经观察到，与疾病相关的标记位点采用乘法风险模型往往比未分型的致病位点拟合得更好。这表明，虽然随着连锁不平衡的瓦解总体风险会降低，但非乘法成分受影响更大。本文对此效应进行了研究，特别是研究了其对性状/标记关联检验以及一旦发现相关位点后遗传方式和风险估计的实际影响。全基因组关联研究所需的极端显著水平定义了一个可检测等位基因频率和效应大小的受限范围。对于此类参数，使用能模拟正确遗传方式而非乘法模型的检验几乎没有什么好处；因此，假设乘法模型的 Cochr an - Armitage趋势检验比更通用的模型更可取，因为它使用的自由度更少。同样，在估计风险时，无论真实易感位点的潜在遗传方式如何，乘法风险模型很可能都能很好地拟合数据。这可能会在解释风险估计时导致问题。
