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Gene–environment interactions in human diseases

Nature Reviews Genetics volume 6, pages 287–298 (2005)Cite this article

Key Points

  • Complex diseases are thought to involve the interaction between environmental and lifestyle factors, and inherited susceptibility.

  • The increasing number of disease-associated alleles of both high and low penetrance that have been described allows us to assess whether allele penetrance is modified by environmental factors.

  • There are many models that describe the precise nature of the risks associated with combinations of genetic and environmental risk factors. This introduces an additional element of multiple comparisons into the already large matrix of potential genetic and environmental risk factors.

  • All the main epidemiological study designs can be used to detect gene–environment interactions. The optimal study design depends on the interaction that is being examined.

  • The sample sizes that are required to detect gene–environment or gene–gene interactions are much larger than those necessary to detect genetic or environmental factors in isolation.

  • Many studies that have been carried out do not have adequate sample sizes to address gene–environment interactions.

  • Creating common databases of results, and pooling results across consortia could mitigate the problem of sample size. Pre-planned pooling of results will be more efficient than post-hoc pooling, as the increasing use of haplotype-tagging SNPs might mean that different research groups choose different gene variants.

  • Finding the common variants associated with risk of common diseases will be just the beginning of applying knowledge of gene variation to human disease. Dissecting the interaction of genes with environment will be necessary to assess their public-health and clinical relevance, and will present many challenges.

Abstract

Studies of gene–environment interactions aim to describe how genetic and environmental factors jointly influence the risk of developing a human disease. Gene–environment interactions can be described by using several models, which take into account the various ways in which genetic effects can be modified by environmental exposures, the number of levels of these exposures and the model on which the genetic effects are based. Choice of study design, sample size and genotyping technology influence the analysis and interpretation of observed gene–environment interactions. Current systems for reporting epidemiological studies make it difficult to assess whether the observed interactions are reproducible, so suggestions are made for improvements in this area.

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Figure 1: Models of gene–environment interactions.
Figure 2: Number of cases needed to detect a range of multiplicative interactions, according to allele prevalence.

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Acknowledgements

I thank my colleagues at the Harvard School of Public Health and the Channing Laboratory for helpful discussions, and P. Kraft for reviewing the manuscript.

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Authors and Affiliations

  1. Department of Epidemiology, Program in Molecular and Genetic Epidemiology, Harvard School of Public Health, 677 Huntington Avenue, Boston, 02115, Massachusetts, USA

    David J. Hunter

  2. Channing Laboratory, Brigham and Women's Hospital, Boston, 02115, Massachusetts, USA

    David J. Hunter

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Related links

Related links

DATABASES

Entrez

APOE4

BRCA1

CCR5

NAT2

OMIM

Alzheimer disease

multiple sclerosis

Parkinson disease

phenylketonuria

sickle-cell anaemia

xeroderma pigmentosum

FURTHER INFORMATION

GeneSNPs

Human Genome Project

National Cancer Institute Breast and Prostate Cancer and Hormone-Related Gene Variants Cohort Consortium

National Cancer Institute Cancer Genome Anatomy Project SNP500Cancer Database

UK Biobank

US National Institute of Environmental Health Sciences Environmental Genome Project

Glossary

PHARMACOGENETICS

The study of drug responses that are related to inherited genetic differences.

EPIDEMIOLOGY

A discipline that seeks to explain the extent to which factors that people are exposed to (environmental or genetic) influence their risk of disease, by means of population-based investigations.

CANDIDATE-GENE STUDIES

Studies of specific genes in which variation might influence the risk of a specific disease, usually because the gene is part of a biological pathway that is plausibly related to the disease.

BIOMARKER

A molecular marker of a biological function or external exposure.

ASSOCIATION STUDY

An approach to gene mapping that looks for associations between a particular phenotype and allelic variation in a population.

PRIOR PROBABILITY

An attempt to distinguish between more likely and less likely interactions on the basis of knowledge of biological mechanisms, before an interaction is observed.

VARIANCE

A statistic that quantifies the dispersion of data about the mean. In quantitative genetics, the phenotypic variance (Vp) is the observed variation of a trait in a population. Vp can be partitioned into components, owing to genetic variance (Vg), environmental variance (Ve) and gene–environment correlations and interactions.

PENETRANCE

The frequency with which individuals that carry a given gene variant will show the manifestations associated with that variant. If penetrance of a disease allele is 100% then all individuals carrying that allele will express the associated disorder.

POPULATION STRATIFICATION

The presence of multiple subgroups with different allele frequencies within a population. The different underlying allele frequencies in sampled subgroups might be independent of the disease within each group, and they can lead to erroneous conclusions of linkage disequilibrium or disease relevance.

HAPLOTYPE-TAGGING SNP

One of a small subset of SNPs that is needed to uniquely identify a complete haplotype.

LINKAGE DISEQUILIBRIUM

(LD). A measure of whether alleles at two loci co-exist in a population in a non-random fashion. Alleles that are in LD are found together on the same haplotype more often than would be expected by chance.

SYSTEMS BIOLOGY

The study of the complex interactions that occur at all levels of biological information — from whole-genome sequence interactions to developmental and biochemical networks — and their functional relationship to the phenotypes of organisms.

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Hunter, D. Gene–environment interactions in human diseases. Nat Rev Genet 6, 287–298 (2005). https://doi.org/10.1038/nrg1578

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