Review Article | Published:

Validating therapeutic targets through human genetics

Nature Reviews Drug Discovery volume 12, pages 581594 (2013) | Download Citation

Abstract

More than 90% of the compounds that enter clinical trials fail to demonstrate sufficient safety and efficacy to gain regulatory approval. Most of this failure is due to the limited predictive value of preclinical models of disease, and our continued ignorance regarding the consequences of perturbing specific targets over long periods of time in humans. 'Experiments of nature' — naturally occurring mutations in humans that affect the activity of a particular protein target or targets — can be used to estimate the probable efficacy and toxicity of a drug targeting such proteins, as well as to establish causal rather than reactive relationships between targets and outcomes. Here, we describe the concept of dose–response curves derived from experiments of nature, with an emphasis on human genetics as a valuable tool to prioritize molecular targets in drug development. We discuss empirical examples of drug–gene pairs that support the role of human genetics in testing therapeutic hypotheses at the stage of target validation, provide objective criteria to prioritize genetic findings for future drug discovery efforts and highlight the limitations of a target validation approach that is anchored in human genetics.

Key points

  • Existing preclinical models have a limited ability to test 'therapeutic hypotheses'; that is, whether perturbing a target in a given manner would benefit patients and have minimal toxicity.

  • 'Experiments of nature', including human genetics, provide an estimate of dose–response curves at the time of target validation.

  • There is an increasing number of studies in the literature demonstrating that genes with a series of disease-associated alleles represent promising drug targets.

  • Here, we provide objective criteria to help prioritize research on the most promising targets and ultimately nominate a gene product as the target for a drug development programme.

  • We highlight important limitations of human genetics in target validation, including a commentary on the genetic architecture of common diseases.

  • We also discuss the role of genome-wide association studies (GWASs) and large-scale sequencing projects in drug discovery, emphasizing the importance of precompetitive collaborations that make clinical and genetic data available in a responsible manner.

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Acknowledgements

The authors thank S. Kathiresan for his assistance in providing critical comments on the manuscript.

Author information

Affiliations

  1. Division of Rheumatology, Immunology and Allergy, Brigham And Women's Hospital, Boston, Massachusetts 02115, USA.

    • Robert M. Plenge
  2. Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA.

    • Robert M. Plenge
    • , Edward M. Scolnick
    •  & David Altshuler
  3. Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA.

    • Edward M. Scolnick
  4. Department of Molecular Biology and Diabetes Unit, Massachusetts General Hospital, Boston, Massachusetts 02114, USA.

    • David Altshuler
  5. Department of Genetics and Medicine, Harvard Medical School, Boston, Massachusetts 02115, USA.

    • David Altshuler

Authors

  1. Search for Robert M. Plenge in:

  2. Search for Edward M. Scolnick in:

  3. Search for David Altshuler in:

Competing interests

D.A. is on the Board of Directors for Vertex Pharmaceuticals. R.M.P. and E.M.S. declare no competing interests.

Corresponding author

Correspondence to Robert M. Plenge.

Glossary

Preclinical models

Any of a broad range of approaches to support the therapeutic hypothesis before a drug is tested in a clinical trial.

Therapeutic hypothesis

The hypothesis that perturbing a target in a given manner leads to patient benefit (efficacy with minimal toxicity).

Target validation

The process of gathering information about a potential drug target prior to initiating a screen to find biological or chemical modulators of the target of interest.

First-in-class drug

A drug that is the first to target a new biological mechanism of action.

Alleles

DNA sequence variations between two chromosomes (for example, one maternal chromosome and one paternal chromosome).

'Experiments of nature'

Naturally occurring human conditions or states that modulate a biological target with a reproducible effect on human physiology; in the context of drug discovery, these experiments mimic the effect of therapeutic modulation of the target.

Inherited DNA variation

A variation in DNA sequence that is passed from the parent to the offspring according to the rules of Mendelian segregation.

Causal alleles

DNA variants that are responsible for influencing a clinical phenotype.

Complex traits

Diseases that do not segregate within families according to obvious rules; the underlying genetic cause is often highly polygenic and substantially influenced by environmental and stochastic factors.

Genetic architecture

The underlying genetic basis for a phenotypic trait; variables include: the number of causal genes (monogenic, oligogenic or polygenic); the population frequency of causal alleles (common, low-frequency or rare); and the effect size of the causal alleles (small effect reflecting low penetrance, or large effect reflecting high penetrance).

Genetic locus

A location or region of the genome; the boundaries of a locus can be defined by linkage disequilibrium blocks or other factors.

Functional alleles

Alleles to which a biological function can be ascribed; examples include differential gene expression or mRNA splicing, or differences in protein-coding sequence.

Function–phenotype dose–response curves

An assessment of the effect of modulating the function of a target on a biological phenotype in a way that mirrors the traditional dose–response curves of drug efficacy and toxicity from clinical trials.

Causal gene

A gene that, when perturbed by a mutation, leads to a clinical phenotype.

Genome-wide association studies

(GWASs). Comprehensive testing of genetic variants in a collection of individuals to see whether any variant is associated with a trait; contemporary GWASs are limited to testing common variants, although newer technologies allow the testing of low-frequency variants.

Single nucleotide polymorphisms

(SNPs). DNA sequence variations that occur when a single nucleotide — A, T, C or G — differs between paired chromosomes.

Linkage disequilibrium

A non-random correlation of alleles at a locus (or region) of the genome, such that some combinations of alleles in a population are observed more frequently than would be expected by chance; the extent of linkage disequilibrium can be measured by the square of the correlation coefficient (r2); non-random recombination across the genome during the course of human history results in blocks of linkage disequilibrium (often containing multiple genes).

Mendelian diseases

Diseases that segregate faithfully within a family according to Mendel's laws; for a given family, the underlying genetic cause is generally a single mutation that is rare in the general population and highly penetrant in family members who inherit the mutation.

Spectrum of alleles

Somewhat arbitrary thresholds for the frequency of alleles observed in the general population; 'common alleles' are those that are observed in >5% of the general population; 'low-frequency alleles' are those that are observed in 0.1–5% of the general population; and 'rare alleles' are private to families; in practical terms, alleles that are common or low-frequency can be catalogued in a reference population (for example, the International HapMap Project) to facilitate testing in another population (for example, patients), whereas rare alleles must be discovered and tested in the same individuals.

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