Lupo Philip J, Mitchell Laura E, Canfield Mark A, Shaw Gary M, Olshan Andrew F, Finnell Richard H, Zhu Huiping
Department of Pediatrics, Section of Hematology-Oncology, Baylor College of Medicine, Houston, TX, USA.
Human Genetics Center, Division of Epidemiology, Human Genetics and Environmental Sciences, University of Texas School of Public Health, Houston, TX, USA.
Mol Genet Metab. 2014 Jan;111(1):46-51. doi: 10.1016/j.ymgme.2013.11.004. Epub 2013 Nov 18.
Single-gene analyses indicate that maternal genes associated with metabolic conditions (e.g., obesity) may influence the risk of neural tube defects (NTDs). However, to our knowledge, there have been no assessments of maternal-fetal metabolic gene-gene interactions and NTDs. We investigated 23 single nucleotide polymorphisms among 7 maternal metabolic genes (ADRB3, ENPP1, FTO, LEP, PPARG, PPARGC1A, and TCF7L2) and 2 fetal metabolic genes (SLC2A2 and UCP2). Samples were obtained from 737 NTD case-parent triads included in the National Birth Defects Prevention Study for birth years 1999-2007. We used a 2-step approach to evaluate maternal-fetal gene-gene interactions. First, a case-only approach was applied to screen all potential maternal and fetal interactions (n = 76), as this design provides greater power in the assessment of gene-gene interactions compared to other approaches. Specifically, ordinal logistic regression was used to calculate the odds ratio (OR) and 95% confidence interval (CI) for each maternal-fetal gene-gene interaction, assuming a log-additive model of inheritance. Due to the number of comparisons, we calculated a corrected p-value (q-value) using the false discovery rate. Second, we confirmed all statistically significant interactions (q < 0.05) using a log-linear approach among case-parent triads. In step 1, there were 5 maternal-fetal gene-gene interactions with q < 0.05. The "top hit" was an interaction between maternal ENPP1 rs1044498 and fetal SLC2A2 rs6785233 (interaction OR = 3.65, 95% CI: 2.32-5.74, p = 2.09×10(-8), q=0.001), which was confirmed in step 2 (p = 0.00004). Our findings suggest that maternal metabolic genes associated with hyperglycemia and insulin resistance and fetal metabolic genes involved in glucose homeostasis may interact to increase the risk of NTDs.
单基因分析表明,与代谢状况(如肥胖)相关的母体基因可能会影响神经管缺陷(NTDs)的风险。然而,据我们所知,尚未有对母胎代谢基因-基因相互作用与神经管缺陷的评估。我们研究了7个母体代谢基因(ADRB3、ENPP1、FTO、LEP、PPARG、PPARGC1A和TCF7L2)和2个胎儿代谢基因(SLC2A2和UCP2)中的23个单核苷酸多态性。样本取自1999 - 2007年出生年份纳入国家出生缺陷预防研究的737个神经管缺陷病例-父母三联体。我们采用两步法来评估母胎基因-基因相互作用。首先,应用病例对照法筛选所有潜在的母体和胎儿相互作用(n = 76),因为与其他方法相比,这种设计在评估基因-基因相互作用时具有更大的效力。具体而言,采用有序逻辑回归计算每个母胎基因-基因相互作用的比值比(OR)和95%置信区间(CI),假设遗传的对数相加模型。由于比较次数较多,我们使用错误发现率计算校正p值(q值)。其次,我们在病例-父母三联体中使用对数线性方法确认所有具有统计学意义的相互作用(q < 0.05)。在第一步中,有5个母胎基因-基因相互作用的q < 0.05。“最显著的”是母体ENPP1 rs1044498与胎儿SLC