加入共變數於三元體資料分析以估計疾病基因位置

Abstract

Case-parent trio design常被用在遺傳流行病學研究中，相較於其他的傳統方法，例如：affected-sib-pair (ASP) sign，case-parent trio design更適合應用在罕見疾病。Liang 等人在2001年時根據case-parent trio design提出一種疾病基因相關定位的方法，他們利用偏好傳遞統計量(expected preferential-transmission statistic)估計疾病基因的位置。相較於傳統的TDT方法，他們指出，這個方法不但較有效力，且可以應用於更廣泛的資料。此外，除了利用假設檢定去尋找疾病基因的位置，這個方法還能對疾病基因位點，提供準確的估計值及其相對應的標準差，以對這疾病位置作推論。因為許多複雜的疾病是由基因和環境因素的交互作用所造成，因此，加入這些基因或環境因素於三元體的資料分析，應能對疾病基因位點，做更精準的定位。在本研究中，我們用case-parent trios 的資料，分別利用有母數和無母數的方法，將相關的共變數併入模型中，以幫助我們估計疾病基因的位置。模擬結果和兔唇資料分析均顯示，估計疾病基因位置時，加入共變數，會使得估計值更有效率。

Case-parant trio design is commonly used in genetic epidemiological family studies. It is more suitable for rare disorders than other conventional designs for family studies, such as affected-sib-pair (ASP) designs. Liang et al. (2001b) proposed a multipoint linkage disequilibrium (LD) mapping approach to localize disease genes based on a preferential-transmission statistic in the case-parent trio design. They found that their approach was more powerful and could accommodate a wider variety of data than the conventional TDT approach. In addition, instead of conducting hypothesis testing to search for a disease locus, it provided a precise estimate for a postulated disease locus along with its standard error, so that one can make inference for the disease locus. Most complex diseases involve both genetic and environmental components, incorporating genetic or environmental factors into the LD mapping may be helpful in localizing the disease locus. We therefore incorporated trait-related covariates into the LD mapping to estimate the disease locus through parametric and nonparametric models in the case-parent trio design in the present study. Simulation studies and the example of oral cleft study both suggested that incorporating covariates into the LD mapping approach helps a great deal to improve efficiency in localizing the disease locus.