公共衛生學院: 流行病學與預防醫學研究所指導教授: 李文宗蘇翊善Su, Yi-ShanYi-ShanSu2017-03-032018-06-292017-03-032018-06-292015http://ntur.lib.ntu.edu.tw//handle/246246/273829在基因環境獨立的假設下，未知或未測量的環境因子，不論其為何，皆不會干擾基因本身的效應。這使得許多研究者因此以為不同環境暴露下基因效應的異質性，即表示基因環境交互作用的存在─儘管仍有其他環境因子未被校正。本研究中，作者推導出在基因環境獨立假設下的交互作用誤差公式，進行電腦模擬，並用實例進行示範。結果顯示，即使感興趣的基因，與研究中及任何其他未測量的環境因子間皆未有交互作用，仍然可能會造成基因環境交互作用的假象。因此，我們建議研究者在進行基因相關研究時，應儘可能量測並且控制所有和疾病有強烈相關的環境因子─不論是獨立的危險因子、中介因子或是干擾因子。Background: Under the assumption of gene-environment independence,unknown/unmeasured environmental factors, irrespective of what they may be, can notconfound the genetic effects. This has led many people to believe that genetic heterogeneity across different levels of the studied environmental exposure should only mean gene-environment interaction—even though other environmental factors are not adjusted for. Methods: In this study, the authors derive formula for bias and conduct computer simulations under the gene-environment independence assumption. They use a real data example to demonstrate the methodologies. Results: They show that apparent gene-environment interaction can and will arise, even if the gene of interest is not associated with, and is not interacting with, the environmental factor under study and any other unmeasured environmental factor. Conclusions: It is recommended to measure and control as far as possible all strong environmental factors in genetic association studies, be they independent risk factors, mediators, or confounders.2117735 bytesapplication/pdf論文公開時間: 2016/8/26論文使用權限: 同意有償授權(權利金給回饋本人)基因環境交互作用干擾作用不可摺疊性相對勝算比gene–environment interactionconfoundingnon-collapsibilityodds ratiothesis10.6342/NTU201600988http://ntur.lib.ntu.edu.tw/bitstream/246246/273829/1/ntu-104-R01849040-1.pdf