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  • Review Article
  • Published:

Measuring selection in contemporary human populations

Nature Reviews Genetics volume 11, pages 611–622 (2010)Cite this article

Subjects

An Erratum to this article was published on 30 November 2010

This article has been updated

Key Points

  • We can estimate selection on traits using a measure of fitness, reliable measurements of multiple traits and the phenotypic and genetic correlations among these traits.

  • This information is available for contemporary human populations in more than 19 existing databases that cover from approximately 1,000 to more than 8 million individuals.

  • A trait under selection to decrease could respond positively, negatively or not at all, depending on the quantitative contributions of phenotypic and genetic correlations.

  • To account for traits that change with age and are influenced by the environment, traits can be expressed relative to those of other individuals of similar age and environment.

  • Phenotypic evolution can be expressed in terms of phenotypic (P) and genetic (G) variance–covariances matrices and a vector of selection gradients, β.

  • Most human traits have measurable heritability and will respond to selection if they are not constrained by phenotypic and genetic correlations with other traits.

  • Traits directly related to lifetime reproductive success tend to have lower heritabilities than traits that have a less direct relationship to fitness.

  • Selection is acting in some human populations to reduce age at first reproduction, to increase age at menopause in females and to reduce total blood cholesterol.

  • A major unresolved issue is how to deal with cultural evolution and gene–culture co-evolution.

  • One next step will be to determine whether phenotypic changes are tracked by changes in the allele frequencies of the genes associated with the traits.

Abstract

Are humans currently evolving? This question can be answered using data on lifetime reproductive success, multiple traits and genetic variation and covariation in those traits. Such data are available in existing long-term, multigeneration studies — both clinical and epidemiological — but they have not yet been widely used to address contemporary human evolution. Here we review methods to predict evolutionary change and attempts to measure selection and inheritance in humans. We also assemble examples of long-term studies in which additional measurements of evolution could be made. The evidence strongly suggests that we are evolving and that our nature is dynamic, not static.

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Figure 1: Heritabilities (h2) of human traits.

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Change history

  • 10 August 2010

    In the version of this article initially published online, the e-mail address for Sean G. Byars was incorrect. This has now been corrected in all versions of the article.

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Acknowledgements

D.R.G. thanks C. Lee for hospitality and facilities. The authors thank the National Evolutionary Synthesis Center for supporting their collaboration and B.P. Stearns for detailed, constructive comments.

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Authors and Affiliations

  1. Department of Ecology and Evolutionary Biology, Yale University, New Haven, 06520-8102, Connecticut, USA

    Stephen C. Stearns & Sean G. Byars

  2. Department of Biology, Copenhagen University, Universitetsparken 15, DK-2100, Copenhagen, Denmark

    Sean G. Byars

  3. Department of Pathology, Brigham and Women's Hospital, 221 Longwood Avenue, Boston, 02115, Massachusetts, USA

    Diddahally R. Govindaraju

  4. Population Studies Center, University of Pennsylvania, Philadelphia, 19104-6299, Pennsylvania, USA

    Douglas Ewbank

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  1. Stephen C. Stearns
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  3. Diddahally R. Govindaraju
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  4. Douglas Ewbank
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FURTHER INFORMATION

Stephen C. Stearns' homepage

Atherosclerosis Risk in Communities Study (ARIC)

Coronary Artery Risk Development in Young Adults (CARDIA)

Danish National Board of Health

Finnish National Institute for Health and Welfare

Framingham Heart Study

Honolulu Heart Program

Jackson Heart Study

MERLIN

Norwegian Board of Health

Nurses' Health Study

Rotterdam Study

SOLAR

Statistics Iceland

Statistics Norway

Statistics Sweden

Swedish National Health Board

VCE

Wisconsin Longitudinal Study

Women's Health Study

Glossary

Longitudinal study

An observational study in which individuals are followed for a long period of time, often many decades, and in which the same traits are measured repeatedly.

Pleiotropy

The action of a single gene on two or more distinct phenotypic characters.

Linkage disequilibrium

A measure of whether alleles at two loci coexist in a population in a nonrandom fashion; one common cause is that the loci are neighbours on the same chromosome and therefore do not recombine.

Directional selection

Natural selection that favours values of a quantitative trait at one extreme of the population distribution. In positive directional selection, natural selection favours values of a quantitative trait at the upper extreme of the population distribution.

Generalized additive model

A statistical model that blends properties of generalized linear models with additive models (parametric or non-parametric) and is often used to estimate smoothing functions for scatter plots.

Heritability

The proportion of the total phenotypic variation in a trait that can be attributed to genetic effects.

Selection differential

The average superiority of the selected parents; it is expressed as the mean phenotypic value of the individuals selected as parents and expressed as a deviation from the population mean.

Additive genetic variance

The part of the total genetic variation that is due to the main (or additive) effects of alleles on a phenotype. The additive variance determines the response to selection.

Narrow-sense heritability

The proportion of phenotypic variation that can be accounted for by additive genetic effects. By contrast, broad-sense heritability includes effects of interactions among genes that are caused by dominance and epistasis.

Quadratic regression

A quadratic regression estimates the parameters of an equation for a parabola that best fits the data. Here it is incorporated in a larger model that also has linear elements.

Stabilizing selection

Natural selection that favours intermediate values of a quantitative trait.

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Stearns, S., Byars, S., Govindaraju, D. et al. Measuring selection in contemporary human populations. Nat Rev Genet 11, 611–622 (2010). https://doi.org/10.1038/nrg2831

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