State Key Laboratory of Integrated Services Networks, Xidian University, Xi'an, Shaanxi, China.
PLoS One. 2022 Oct 12;17(10):e0275929. doi: 10.1371/journal.pone.0275929. eCollection 2022.
Previous studies have suggested that gene-environment interactions (GEIs) between a common variant and an environmental factor can influence multiple correlated phenotypes simultaneously, that is, GEI pleiotropy, and that analyzing multiple phenotypes jointly is more powerful than analyzing phenotypes separately by using single-phenotype GEI tests. Methods to test the GEI for rare variants with multiple phenotypes are, however, lacking. In our work, we model the correlation among the GEI effects of a variant on multiple quantitative phenotypes through four kernels and propose four multiphenotype GEI tests for rare variants, which are a test with a homogeneous kernel (Hom-GEI), a test with a heterogeneous kernel (Het-GEI), a test with a projection phenotype kernel (PPK-GEI) and a test with a linear phenotype kernel (LPK-GEI). Through numerical simulations, we show that correlation among phenotypes can enhance the statistical power except for LPK-GEI, which simply combines statistics from single-phenotype GEI tests and ignores the phenotypic correlations. Among almost all considered scenarios, Het-GEI and PPK-GEI are more powerful than Hom-GEI and LPK-GEI. We apply Het-GEI and PPK-GEI in the genome-wide GEI analysis of systolic blood pressure (SBP) and diastolic blood pressure (DBP) in the UK Biobank. We analyze 18,101 genes and find that LEUTX is associated with SBP and DBP (p = 2.20×10-6) through its interaction with hemoglobin. The single-phenotype GEI test and our multiphenotype GEI tests Het-GEI and PPK-GEI are also used to evaluate the gene-hemoglobin interactions for 22 genes that were previously reported to be associated with SBP or DBP in a meta-analysis of genetic main effects. MYO1C shows nominal significance (p < 0.05) by the Het-GEI test. NOS3 shows nominal significance in DBP and MYO1C in both SBP and DBP by the single-phenotype GEI test.
先前的研究表明，常见变异体与环境因素之间的基因-环境相互作用（GEI）可以同时影响多个相关表型，即 GEI 多效性，并且联合分析多个表型比使用单表型 GEI 测试分别分析表型更有效。然而，用于测试具有多种表型的稀有变体的 GEI 的方法却缺乏。在我们的工作中，我们通过四个核来模拟变异体对多个定量表型的 GEI 效应之间的相关性，并为稀有变体提出了四种多表型 GEI 测试，分别是具有同质核的测试（Hom-GEI）、具有异质核的测试（Het-GEI）、具有投影表型核的测试（PPK-GEI）和具有线性表型核的测试（LPK-GEI）。通过数值模拟，我们表明，表型之间的相关性除了 LPK-GEI 之外，都可以提高统计功效，LPK-GEI 只是简单地结合了单表型 GEI 测试的统计数据，忽略了表型相关性。在几乎所有考虑的情况下，Het-GEI 和 PPK-GEI 比 Hom-GEI 和 LPK-GEI 更有效。我们在 UK Biobank 中对收缩压（SBP）和舒张压（DBP）的全基因组 GEI 分析中应用了 Het-GEI 和 PPK-GEI。我们分析了 18101 个基因，发现 LEUTX 通过与血红蛋白的相互作用与 SBP 和 DBP 相关（p = 2.20×10-6）。单表型 GEI 测试和我们的多表型 GEI 测试 Het-GEI 和 PPK-GEI 也用于评估在对遗传主效应的荟萃分析中先前报道与 SBP 或 DBP 相关的 22 个基因与血红蛋白的相互作用。Het-GEI 测试显示 MYO1C 具有名义显著性（p < 0.05）。单表型 GEI 测试显示 NOS3 在 DBP 中具有名义显著性，在 SBP 和 DBP 中 MYO1C 具有名义显著性。
