National Institute of Pathology (Indian Council of Medical Research) Safdarjung Hospital Campus, New Delhi, India.
PLoS One. 2011;6(12):e29431. doi: 10.1371/journal.pone.0029431. Epub 2011 Dec 19.
Complex disease such as cancer results from interactions of multiple genetic and environmental factors. Studying these factors singularly cannot explain the underlying pathogenetic mechanism of the disease. Multi-analytical approach, including logistic regression (LR), classification and regression tree (CART) and multifactor dimensionality reduction (MDR), was applied in 188 lung cancer cases and 290 controls to explore high order interactions among xenobiotic metabolizing genes and environmental risk factors. Smoking was identified as the predominant risk factor by all three analytical approaches. Individually, CYP1A12A polymorphism was significantly associated with increased lung cancer risk (OR = 1.69;95%CI = 1.11-2.59,p = 0.01), whereas EPHX1 Tyr113His and SULT1A1 Arg213His conferred reduced risk (OR = 0.40;95%CI = 0.25-0.65,p<0.001 and OR = 0.51;95%CI = 0.33-0.78,p = 0.002 respectively). In smokers, EPHX1 Tyr113His and SULT1A1 Arg213His polymorphisms reduced the risk of lung cancer, whereas CYP1A12A, CYP1A12C and GSTP1 Ile105Val imparted increased risk in non-smokers only. While exploring non-linear interactions through CART analysis, smokers carrying the combination of EPHX1 113TC (Tyr/His), SULT1A1 213GG (Arg/Arg) or AA (His/His) and GSTM1 null genotypes showed the highest risk for lung cancer (OR = 3.73;95%CI = 1.33-10.55,p = 0.006), whereas combined effect of CYP1A12A 6235CC or TC, SULT1A1 213GG (Arg/Arg) and betel quid chewing showed maximum risk in non-smokers (OR = 2.93;95%CI = 1.15-7.51,p = 0.01). MDR analysis identified two distinct predictor models for the risk of lung cancer in smokers (tobacco chewing, EPHX1 Tyr113His, and SULT1A1 Arg213His) and non-smokers (CYP1A12A, GSTP1 Ile105Val and SULT1A1 Arg213His) with testing balance accuracy (TBA) of 0.6436 and 0.6677 respectively. Interaction entropy interpretations of MDR results showed non-additive interactions of tobacco chewing with SULT1A1 Arg213His and EPHX1 Tyr113His in smokers and SULT1A1 Arg213His with GSTP1 Ile105Val and CYP1A12C in nonsmokers. These results identified distinct gene-gene and gene environment interactions in smokers and non-smokers, which confirms the importance of multifactorial interaction in risk assessment of lung cancer.
复杂疾病，如癌症，是由多种遗传和环境因素相互作用引起的。单独研究这些因素并不能解释疾病的潜在发病机制。本研究采用逻辑回归（LR）、分类和回归树（CART）以及多因子维度缩减（MDR）三种分析方法，对 188 例肺癌病例和 290 例对照进行了分析，探讨了外源物代谢基因和环境危险因素之间的高阶相互作用。三种分析方法均发现吸烟是主要的危险因素。单独来看，CYP1A12A 多态性与肺癌风险增加显著相关（OR=1.69；95%CI=1.11-2.59，p=0.01），而 EPHX1 Tyr113His 和 SULT1A1 Arg213His 则降低了风险（OR=0.40；95%CI=0.25-0.65，p<0.001 和 OR=0.51；95%CI=0.33-0.78，p=0.002）。在吸烟者中，EPHX1 Tyr113His 和 SULT1A1 Arg213His 多态性降低了肺癌的风险，而 CYP1A12A、CYP1A12C 和 GSTP1 Ile105Val 则仅在非吸烟者中增加了风险。通过 CART 分析探索非线性相互作用时发现，携带 EPHX1 113TC（Tyr/His）、SULT1A1 213GG（Arg/Arg）或 AA（His/His）和 GSTM1 缺失基因型的吸烟者患肺癌的风险最高（OR=3.73；95%CI=1.33-10.55，p=0.006），而 CYP1A12A 6235CC 或 TC、SULT1A1 213GG（Arg/Arg）和嚼槟榔的联合作用在非吸烟者中显示出最大的风险（OR=2.93；95%CI=1.15-7.51，p=0.01）。MDR 分析确定了吸烟者（吸烟、EPHX1 Tyr113His 和 SULT1A1 Arg213His）和非吸烟者（CYP1A12A、GSTP1 Ile105Val 和 SULT1A1 Arg213His）中肺癌风险的两个不同预测模型，其测试平衡准确性（TBA）分别为 0.6436 和 0.6677。MDR 结果的交互信息解释表明，在吸烟者中，吸烟与 SULT1A1 Arg213His 和 EPHX1 Tyr113His 之间存在非加性相互作用，在非吸烟者中，SULT1A1 Arg213His 与 GSTP1 Ile105Val 和 CYP1A12C 之间存在非加性相互作用。这些结果确定了吸烟者和非吸烟者中不同的基因-基因和基因-环境相互作用，证实了多因素相互作用在肺癌风险评估中的重要性。
