A path to personalized phenotypic prediction: unlocking the context-dependency of allelic effects

项目总结 当今我们许多最繁重的健康负担是由复杂且鲜为人知的相互作用所驱动的 一个人的基因构成和他或她的环境之间的关系。换句话说，基因变异可能 使个人在面对环境扰动时具有生理敏感度或韧性。 我们的现代环境与塑造人类的祖先选择压力严重背道而驰 随着进化时间的推移，基因变异引发了一个问题，即我们的 基因组和现代生活是困扰现代社会的非传染病的罪魁祸首。这 被称为进化错配假说的概念已经成为进化医学的中心原则 并对我们如何研究、管理和治疗一长串条件思维具有潜在的深远影响 来自与我们现代环境不匹配的基因组。然而，这一假设很难解释。 在实践中进行强有力的测试，也许部分原因是我们没有完全理解其背后的机制基础 这种现象。在错配模型下，我们预计基因变异是中性的或有益的 过去的环境在现代环境中会导致疾病；换句话说，我们预计会出现这种情况 不匹配会产生“基因与环境”(GxE)的相互作用，从而对健康产生一些遗传效应 都依赖于环境。我的实验室的目标是促进我们对一些人是如何以及为什么 比其他人对环境应激源更敏感，并确定 这个变种。我的团队的工作清楚地证明了GxE对表型变异的贡献是 普遍存在，而且普遍被低估了。我们现在想要超越对差异的解释 由GxE解释，并从机理上理解这些相互作用如何形成表型变异 并引发疾病风险。在接下来的5年里，我的实验室的一个主要主题将是利用进化不匹配作为 一个研究GxE的镜头。我们的目标是了解：(1)是什么使特定的基因组区域对其敏感 环境背景？(2)人口进化史在这一过程中扮演什么角色？(3)为什么以及如何 有些人似乎比其他人对环境扰动更敏感？我们特别是 对研究一类仅由环境变化才能揭示的遗传效应感兴趣 “隐秘的遗传变异”)。理解这类变种如何驱动的机制基础 表型变异是我的研究项目的主要目标之一。技术的进步推动了 个人基因组学的兴起和精准医学的前景。然而，要释放这种潜力，我们必须 首先，了解每个个体独特的环境和遗传相互作用如何导致变异 在复杂的特征中。这是本应用程序的主要目标，也是我的研究项目--我的工作--的重点 利用这些工具来解决与等位基因效应的上下文依赖相关的问题， 进化的镜头。我们使用果蝇和人类作为模型来进行这项工作。

PROJECT SUMMARY Many of our most onerous health burdens today are driven by complex and poorly understood interactions between a person’s genetic makeup and his or her environment. In other words, genetic variation may predispose individuals toward physiological sensitivity or resilience in the face of environmental perturbations. Our modern environments are deeply diverged from the ancestral selective pressures that have shaped human genetic variation through evolutionary time, raising the question of how much the “mismatch” between our genomes and modern life is responsible for the non-communicable diseases that plague modern societies. This concept, known as the evolutionary mismatch hypothesis, has become a central tenet of evolutionary medicine and has potentially profound implications for how we study, manage, and treat a long list of conditions thought to arise from genomes mismatched to our modern environments. However, this hypothesis has been difficult to robustly test in practice, perhaps in part because we do not fully understand the mechanistic basis underlying this phenomenon. Under a mismatch model, we would expect genetic variation that was neutral or beneficial in past environments to become disease-causing in modern environments; in other words, we would expect this mismatch to generate “genotype-by-environment” (GxE) interactions, such that some genetic effects on health are environmentally dependent. My lab’s goal is to advance our understanding of how and why some individuals are more sensitive to environmental stressors than others, and to identify the molecular and genetic drivers of this variation. Work in my group has clearly established that the contribution of GxE to phenotypic variation is pervasive and it is generally underestimated. We now want to move beyond accounting for the variance explained by GxE and gain a mechanistic understanding of how these interactions shape phenotypic variation and drive disease risk. Over the next 5 years, a major theme of my lab will be to use evolutionary mismatch as a lens to study GxE. We aim to understand: (1) What makes a specific genomic region sensitive to its environmental context? (2) What role does population evolutionary history play in this process? (3) Why and how some individuals appear to be more sensitive than others to environmental perturbation? We are particularly interested in studying a class of genetic effects that are only revealed by environmental change (also known as “cryptic genetic variation”). Understanding the mechanistic underpinnings of how this class of variants drive phenotypic variation is one of the major goals of my research program. Technological advances have fueled the ascent of personal genomics and the promise of precision medicine. However, to unlock this potential, we must first understand how the environmental and genetic interactions unique to each individual contribute to variation in complex traits. This is the primary goal of this application and the focus of my research program – my work leverages these tools to address questions related to the context-dependency of allelic effects using a powerful, evolutionary lens. We conduct this work using both Drosophila and humans as a model.