Case-controls studies are popular epidemiological designs for detecting gene-environment interactions in the etiology of complex diseases, where the genetic susceptibility and environmental exposures may often be reasonably assumed independent in the source population. Various papers have presented analytical methods exploiting gene-environment independence to achieve better efficiency, all of which require either a rare disease assumption or a distributional assumption on the genetic variables. We relax both assumptions. We construct a semiparametric estimator in case-control studies exploiting gene-environment independence, while the distributions of genetic susceptibility and environmental exposures are both unspecified and the disease rate is assumed unknown and is not required to be close to zero. The resulting estimator is semiparametric efficient and its superiority over prospective logistic regression, the usual analysis in case-control studies, is demonstrated in various numerical illustrations.

中文翻译：

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基因环境独立模型病例对照研究中的半参数有效估计器

病例对照研究是流行的流行病学设计，用于检测复杂疾病病因学中的基因 - 环境相互作用，其中遗传易感性和环境暴露通常可以合理地假设独立于源人群。各种论文提出了利用基因-环境独立性来实现更高效率的分析方法，所有这些都需要对罕见疾病的假设或对遗传变量的分布假设。我们放宽了这两个假设。我们在利用基因-环境独立性的病例对照研究中构建了一个半参数估计量，而遗传易感性和环境暴露的分布均未指定，假设发病率未知，不需要接近于零。