Supplementary Material for: Exploring the Performance of Multifactor Dimensionality Reduction in Large Scale SNP Studies and in the Presence of Genetic Heterogeneity among Epistatic Disease Models

Background/Aims: In genetic studies of complex disease a consideration for the investigator is detection of joint effects. The Multifactor Dimensionality Reduction (MDR) algorithm searches for these effects with an exhaustive approach. Previously unknown aspects of MDR performance were the power to detect interactive effects given large numbers of non-model loci or varying degrees of heterogeneity among multiple epistatic disease models. Methods: To address the performance with many non-model loci, datasets of 500 cases and 500 controls with 100 to 10,000 SNPs were simulated for two-locus models, and one hundred 500-case/500-control datasets with 100 and 500 SNPs were simulated for three-locus models. Multiple levels of locus heterogeneity were simulated in several sample sizes. Results: These results show MDR is robust to locus heterogeneity when the definition of power is not as conservative as in previous simulation studies where all model loci were required to be found by the method. The results also indicate that MDR performance is related more strongly to broad-sense heritability than sample size and is not greatly affected by non-model loci. Conclusions: A study in which a population with high heritability estimates is sampled predisposes the MDR study to success more than a larger ascertainment in a population with smaller estimates.

背景与目的：在复杂疾病的遗传学研究中，研究者需重点考量联合效应的检测问题。多因子降维（Multifactor Dimensionality Reduction, MDR）算法通过穷举法搜寻此类效应。此前尚未明确的MDR性能维度包括：在存在大量非模型位点，或多个上位性疾病模型间存在不同程度异质性的情境下，检测交互效应的效能。方法：为探究存在大量非模型位点时的MDR性能，本研究针对双位点模型，模拟了包含100至10000个单核苷酸多态性（Single Nucleotide Polymorphism, SNP）、500例病例与500例对照的数据集；针对三位点模型，模拟了100组每组均含500例病例与500例对照、包含100和500个SNP位点的数据集。此外，本研究还在多种样本量下模拟了不同水平的位点异质性。结果：本研究结果显示，当效能定义未如既往模拟研究那般严苛（既往研究要求算法必须检出全部模型位点）时，MDR对位点异质性具有良好鲁棒性。此外，结果还表明，MDR的性能与广义遗传力的相关性显著强于样本量，且基本不受非模型位点的影响。结论：相较于在遗传力估计值较低的人群中开展更大规模的样本招募，在遗传力估计值较高的人群中进行采样的MDR研究更易获得成功。