Xue Yuan, Ding Juan, Wang Jinjuan, Zhang Sanguo, Pan Dongdong
School of Mathematical Sciences, University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China.
J Genet. 2020;99.
The sum of squared score (SSU) and sequence kernel association test (SKAT) are the two good alternative tests for genetic association studies in case-control data. Both SSU and SKAT are derived through assuming a dose-response model between the risk of disease and genotypes. However, in practice, the real genetic mode of inheritance is impossible to know. Thus, these two tests might losepower substantially as shown in simulation results when the genetic model is misspecified. Here, to make both the tests suitable in broad situations, we propose two-phase SSU (tpSSU) and two-phase SKAT (tpSKAT), where the Hardy-Weinberg equilibrium test is adopted to choose the genetic model in the first phase and the SSU and SKAT are constructed corresponding to the selected genetic model in the second phase. We found that both tpSSU and tpSKAT outperformed the original SSU and SKAT in most of our simulation scenarios. Byapplying tpSSU and tpSKAT to the study of type 2 diabetes data, we successfully identified some genes that have direct effects on obesity. Besides, we also detected the significant chromosomal region 10q21.22 in GAW16 rheumatoid arthritis dataset, with P<106. These findings suggest that tpSSU and tpSKAT can be effective in identifying genetic variants for complex diseases in case-control association studies.
平方得分总和检验（SSU）和序列核关联检验（SKAT）是病例对照数据基因关联研究中两种不错的替代检验方法。SSU和SKAT都是通过假设疾病风险与基因型之间存在剂量反应模型推导出来的。然而，在实际中，真实的遗传遗传模式是不可能知道的。因此，当遗传模型设定错误时，如模拟结果所示，这两种检验可能会大幅丧失检验效能。在此，为使这两种检验在广泛情况下都适用，我们提出了两阶段SSU（tpSSU）和两阶段SKAT（tpSKAT），其中在第一阶段采用哈迪-温伯格平衡检验来选择遗传模型，在第二阶段根据所选遗传模型构建SSU和SKAT。我们发现，在我们的大多数模拟场景中，tpSSU和tpSKAT都优于原始的SSU和SKAT。通过将tpSSU和tpSKAT应用于2型糖尿病数据的研究，我们成功鉴定出了一些对肥胖有直接影响的基因。此外，我们还在GAW16类风湿性关节炎数据集中检测到了显著的染色体区域10q21.22，P<10^-6。这些发现表明，tpSSU和tpSKAT在病例对照关联研究中可有效识别复杂疾病的遗传变异。
