Etheredge Analee J, Christensen Kaare, Del Junco Deborah, Murray Jeffrey C, Mitchell Laura E
Institute of Biosciences and Technology, Texas A&M University System Health Science Center, Houston, 77030, USA.
Birth Defects Res A Clin Mol Teratol. 2005 Aug;73(8):541-6. doi: 10.1002/bdra.20167.
Epidemiological investigations have begun to consider gene-environment (GE) interactions as potential risk factors for many diseases, including several different birth defects. However, traditional methodological approaches for the analysis of case-control data tend to have low power for detection of interaction effects. A log-linear approach that can impose the assumption that the genotype and exposure of interest occur independently in the population has been proposed as a potentially more powerful method for assessing GE interactions but has not been widely applied in the published literature.
The present analyses were undertaken to compare the results obtained when stratified analyses and a log-linear approach were used to assess potential GE interactions. The analyses were conducted using data from a population-based, case-control study conducted in Denmark and considered associations between nonsyndromic cleft lip with or without cleft palate (CL+/-P), infant genotype for variants of RAR-alpha, TGF-alpha, TGF-beta3, and MSX1, and maternal exposure to smoking, alcohol, and multivitamins.
Neither the stratified nor the log-linear analyses provided evidence that that risk of CL+/-P is influenced by any of the GE interactions that were evaluated, despite the potential increase in power offered by the latter approach. Further, the analyses highlight concerns regarding the power to reject the assumption of independence of the genetic and environmental factor of interest in the controls and related concerns regarding the validity of results obtained using the log-linear approach when the underlying assumption is violated.
The potential increase in power offered by the log-linear approach is offset by concerns regarding the validity of this approach when the independence assumption is violated.
流行病学调查已开始将基因-环境(GE)相互作用视为包括几种不同出生缺陷在内的许多疾病的潜在风险因素。然而,用于分析病例对照数据的传统方法在检测相互作用效应方面往往效能较低。一种对数线性方法被提出作为评估GE相互作用的潜在更有效方法,该方法可以假定感兴趣的基因型和暴露在人群中独立发生,但尚未在已发表的文献中广泛应用。
进行本分析以比较使用分层分析和对数线性方法评估潜在GE相互作用时获得的结果。分析使用了丹麦一项基于人群的病例对照研究的数据,并考虑了非综合征性唇裂伴或不伴腭裂(CL+/-P)、视黄酸受体α(RAR-α)、转化生长因子α(TGF-α)、转化生长因子β3(TGF-β3)和肌肉特异性同源盒基因1(MSX1)变体的婴儿基因型,以及母亲吸烟、饮酒和服用多种维生素的暴露情况之间的关联。
分层分析和对数线性分析均未提供证据表明所评估的任何GE相互作用会影响CL+/-P的风险,尽管后一种方法可能会提高效能。此外,分析突出了对在对照组中拒绝感兴趣的遗传和环境因素独立性假设的效能的担忧,以及当违反基本假设时使用对数线性方法获得的结果的有效性的相关担忧。
当独立性假设被违反时,对数线性方法所提供的潜在效能提高被对该方法有效性的担忧所抵消。