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The virtuous cycle of human genetics and mouse models in drug discovery


Ongoing studies in many species seek to understand the origins, architecture and consequences of phenotypic variation under normal and dysfunctional conditions, with the aim of identifying targets for intervention that can prevent, stabilize or reverse disease. Some suggest that only humans are appropriate for studying these questions and argue that candidate drug targets identified in mouse models are largely unreliable. Here, we review the vast evidence showing that mouse models continue to make fundamental contributions to our understanding of genetic principles, pathogenic mechanisms and therapeutic modalities. We propose a virtuous cycle in which the power of observational studies and natural experiments in humans are closely integrated with the rigour of true experiments in model organisms.

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The authors thank R. Balling, B. Beutler, M. B. Sleiman, S. Brown, M. Bucan, M. Buttini, T. Chavakis, A. Economides, M. A. Handel, P. Jha, N. Katsanis, B. Knowles, G. Kollias, J. Lambris, E. Leiter, H. Li, K. Lloyd, J. Noebels, S. Robertson, D. Solter, P. Treuting, E. Williams and H. Zoghbi for suggesting papers that highlight important discoveries in mouse models or helping with figure suggestions. The authors also thank J. Riordan for contributing a draft paragraph about the merits of mouse models and J. Wecker for critically reading a draft of the manuscript.

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Correspondence to Joseph H. Nadeau or Johan Auwerx.

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J.A. is a scientific adviser to Astellas, Amazentis and TES pharma.

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Complex traits

Biological features that depend on multiple genes and environmental conditions and often involve interactions among genes, environment and age.

Model organisms

Organisms that are amenable to experimental studies and for which rich genetic, genomic, phenotyping and analytical resources have been developed.

Gene–gene interactions

(GxG, also known as epistasis). The signal for GxGs is non-additivity where their combined action is more (or less) than the simple summation of their separate phenotypic effects.

Gene–age interactions

(GxA). In many cases, phenotypes depend not only on genes and environment but also on stage of life.

Gene–environment interactions

(GxE). The signal for GxEs is non-additivity where their combined action is more (or less) than the simple summation of their separate phenotypic effects.

Genetic modifiers

Genetic variants in one gene (the modifier gene) that affect the phenotype associated with another gene (the target gene). In many cases, the target is the phenotype associated with a naturally occurring or an engineered single-gene variant. In other cases, the phenotype target is a multigenic trait where the action of one or more underlying genes depends on the action of a modifier gene. Modifier genes are examples of gene–gene interactions.


The phenotypic variation that arises independent of the genetic variants in study subjects. Epigenetic effects can result from chemical modifications (methylation) of nucleic acids (DNA or RNA) or of associated proteins (histone modifications). RNAs and proteins can also induce and transmit epigenetic information. Such changes arise during development to control differentiation as cells transition from totipotency to specialization. In addition to changes within generations, epigenetic changes can be inherited to affect phenotypes in later generations.


The collection of commensal microorganisms (including bacteria, fungi and species) that live in or on organisms. The relation between host and their microbiome is usually symbiotic — their survival and functionality are interdependent.


The cellular mitochondrial content.


A primary goal of genetic research is establishing the molecular mechanisms and systems properties that connect genotype and phenotype.

Personalized medicine

Can also be referred to as precision medicine. A medical practice where health care and disease treatments are based on the individual’s genetic constitution.

Forward genetics

An approach that begins with a phenotype of interest and searches for its genetic basis.

Reverse genetics

An approach that seeks to learn about gene function by examining phenotypic consequences of spontaneous, engineered and naturally occurring genetic variants.

Quantitative trait loci

(QTLs). The genetic variants that control phenotypic variation. These sometimes have independent genetic effects and other times depend on gene–gene, gene–environment and gene–age effects.

Mendelian traits

When a single gene contributes to phenotypic variation.

Polygenic traits

When two or more genes contribute to phenotypic variation.

Systems biology

A biological approach that studies higher-order organismal forms and functions that emerge from multilayered molecular and physical features and their interactions.

Systems genetics

A field that seeks to reveal the relations between genotype and phenotype and thereby account for both high-order and emergent organismal properties by integrated studies at the molecular, cellular and physiological levels.

Comparative models

Analyses of genetic and phenotypic variation in humans and in at least one model organism. Reliable results depend on a clear understanding of the biological similarities and differences between the species being compared.

Genetic reference populations

These are genetically defined strains that can be scored for phenotypes of interest. Usually, they support genome-wide surveys to test for genotype–phenotype relations. Examples for mice include inbred strains, recombinant inbred strains and chromosome substitution strains.

Genome-wide association studies

(GWAS). Tests for statistical evidence for preferential co-occurrence of genetic and phenotypic variants across populations and environments. Positive results argue that the tested genetic marker accounts for a statistically significant portion of the total phenotypic variance and that genetic variants near the marker contribute functionally to phenotypic variation in the trait of interest.


(LOF). LOF variants reduce functionality or loss of phenotypes. These terms apply to specific variants and phenotypes; a given variant could result in the gain of one phenotype and in the loss of another.

Gene mapping

A mapping approach that encompasses two kinds of activities. The first involves using linkage analysis in segregating crosses, in families and in natural populations to establish the location of genes in the genome. Availability of largely complete genome sequences has mostly supplanted this activity. The second involves determining the genomic location of genetic variants that control phenotypic variants (quantitative trait loci), that is, forward genetics.

Genetic engineering

An approach that involves intentional changes in DNA sequences to test its effects on traits of interest. Often, engineering involves embryonic stem cells, induced pluripotent stem cells and early embryos so that phenotypic consequences can be assessed in intact organisms or in related cells and tissues derived from engineered pluripotent cells.


An approach that involves tests to determine whether similar results would be obtained with the same study designs, materials, reagents, analytical methods and protocols.


A principle that involves tests to determine whether similar results are found in different populations and environments and with different study designs and assay protocols.

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Nadeau, J.H., Auwerx, J. The virtuous cycle of human genetics and mouse models in drug discovery. Nat Rev Drug Discov 18, 255–272 (2019).

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