遺傳學中穩定表現型的統計驗證及推論

Abstract

在生物學上，「穩定表現型」(endophenotype)和疾病有著相同的遺傳路徑，但穩定表現型卻比診斷上的表現型(phenotype)更為接近其相關的基因，這也顯示穩定表現型在複雜疾病上基因研究的重要性。在這個計劃裡，我們將提出一個統計方法，用以定義及驗證穩定表現型的存在與否。這個統計方法，將借用一個臨床試驗中驗證替代變數(surrogate endpoint)的概念。我們並將針對穩定表現型的驗證，發展相關操作上的指標。我們將透過模擬研究，提供這些指標相關意義。同時，也提供這些指標的信賴區間，藉此執行統計檢定和統計推論。除外，透過信賴區間和模擬的結果，建構一些準則，以幫助我們找尋有用的穩定表現型。

Endophenotypes, which involve the same biological pathways as diseases but presumably are closer to the relevant gene action than diagnostic phenotypes, have emerged as an important concept in the genetic studies of complex diseases. In this project, we propose to develop a formal statistical methodology for validating endophenotypes. The proposed method was motivated by the conditioning strategy used for surrogate endpoints commonly seen in clinical research. Indices such as proportion of heritability explained, adjusted association and relative heritability are used as operational criteria of validation. Besides, we will provide relevant confidence intervals for these indices for making statistical inferences. Using these confidence intervals, we will construct some criteria to help us search a useful endophenotype. Usefulness of the proposed methods will be demonstrated through computer simulations.