Suppr超能文献

生物特征与发育的基因-环境相互作用:回顾与展望。

Biometric and developmental gene-environment interactions: looking back, moving forward.

作者信息

Tabery James

机构信息

Department of Philosophy, University of Utah, Salt Lake City, UT 84112, USA.

出版信息

Dev Psychopathol. 2007 Fall;19(4):961-76. doi: 10.1017/S0954579407000478.

Abstract

A history of research on gene-environment interaction (G x E) is provided in this article, revealing the fact that there have actually been two distinct concepts of G x E since the very origins of this research. R. A. Fisher introduced what I call the biometric concept of G x E (G x EB), whereas Lancelot Hogben introduced what I call the developmental concept of G x E (G x ED). Much of the subsequent history of research on G x E has largely consisted of the separate legacies of these separate concepts, along with the (sometimes acrimonious) disputes that have arisen time and again when employers of each have argued over the appropriate way to conceptualize the phenomenon. With this history in place, more recent attempts to distinguish between different concepts of G x E are considered, paying particular attention to the commonly made distinction between "statistical interaction" and "interactionism," and Michael Rutter's distinction between statistical interaction and "the biological concept of interaction." I argue that the history of the separate legacies of G x EB and G x ED better supports Rutter's analysis of the situation and that this analysis best paves the way for an integrative relationship between the various scientists investigating the place of G x E in the etiology of complex traits.

摘要

本文介绍了基因-环境相互作用(G×E)的研究历史,揭示了自该研究起源以来,实际上存在两种截然不同的G×E概念这一事实。R. A. 费希尔引入了我所称的G×E的生物统计学概念(G×EB),而兰斯洛特·霍格本引入了我所称的G×E的发育概念(G×ED)。G×E研究的后续历史很大程度上包括了这些不同概念各自的传承,以及每当各自的使用者就该现象的恰当概念化方式展开争论时反复出现的(有时很激烈的)争议。基于这段历史,本文考虑了近期区分不同G×E概念的尝试,特别关注了常被提及的“统计相互作用”与“相互作用论”之间的区别,以及迈克尔·鲁特对统计相互作用和“相互作用的生物学概念”的区分。我认为,G×EB和G×ED各自传承的历史更好地支持了鲁特对这种情况的分析,并且这种分析最有助于为研究G×E在复杂性状病因学中地位的不同科学家之间建立整合关系铺平道路。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验