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

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.

Grant Number: 5R35GM124881-08
NIH Institute/Center: NIH
Principal Investigator: Julien Ayroles