Abstract
After drifting apart for 100 years, the two worlds of genetics — quantitative genetics and molecular genetics — are finally coming together in genome-wide association (GWA) research, which shows that the heritability of complex traits and common disorders is due to multiple genes of small effect size. We highlight a polygenic framework, supported by recent GWA research, in which qualitative disorders can be interpreted simply as being the extremes of quantitative dimensions. Research that focuses on quantitative traits — including the low and high ends of normal distributions — could have far-reaching implications for the diagnosis, treatment and prevention of the problematic extremes of these traits.
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Change history
06 November 2009
An incorrect version of this article was previously published online (publication date 27 October 2009). In the second paragraph of the 'Identifying quantitative mechanisms' section in this article, the history of genome-wide association (GWA) studies for type 2 diabetes was incorrectly described and a key reference was omitted. The corrected paragraph is shown below. The authors apologize for this error. For some traits, such as type 2 diabetes (T2D), a quantitative approach has already been embraced, with striking results9. Although the first T2D GWA studies were case–control studies (REF. 49, and subsequently other studies, for example, REF. 3), a wave of follow-up studies have focused on quantitative traits that are related to T2D, including levels of fasting glucose10 and C-reactive protein11, and glucose tolerance9. These studies are leading to refinements in the definition of T2D. Reference 49 has now been added to the reference list.
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Acknowledgements
The preparation of this paper was supported in part by grants from the UK Medical Research Council (G050079), the Wellcome Trust (WT084728) and the US National Institute of Child Health and Human Development (HD44454). C.M.A.H. is supported by a Medical Research Council/Economic and Social Research Council Interdisciplinary Fellowship (G0802681). O.S.P.D. is supported by a Sir Henry Wellcome Fellowship (WT088984). We thank C. G. Mathew for comments on an earlier draft.
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Glossary
- Autophagy
-
The degradation by a cell of its own components. In the immune response, autophagy removes intracellular bacteria and viruses, and enhances adaptive immunity.
- Case–control study
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Compares cases (a selected group of individuals, for example, those diagnosed with a disorder) with controls (a comparison group of individuals, for example, those who are not diagnosed with the disorder). Genome-wide association case–control studies test whether genetic marker allele frequencies differ between cases and controls.
- Comorbidity
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The co-occurrence of two or more disorders or diseases in an individual.
- Covariance
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A statistic that indicates the extent to which two variables are related and vary together.
- Crohn's disease
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Characterized by chronic intestinal inflammation, which leads to diarrhoea, bleeding, severe abdominal pain and weight loss.
- Effect size
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The proportion of individual differences for a trait in the population that are accounted for by a particular factor.
- Genome-wide association research
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A hypothesis-free genetic method that uses hundreds of thousands of DNA markers distributed throughout the chromosomes to identify alleles that are correlated with a trait.
- Heritability
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The proportion of phenotypic variance in a population that is due to genetic variation.
- Linear regression
-
A statistical method for testing and describing the linear relationship between variables. The regression coefficient describes the slope of the regression line and reflects the amount of variance of the dependent variable that is explained by variation of the independent variable.
- Logistic regression
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A statistical method for testing and describing the linear relationship between variables when the dependent variable is binary. It relates the log odds of the probability of an event to a linear combination of the predictor variables.
- Odds ratio
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A measurement of the effect size of an association for binary values. For example, in case–control studies, the odds ratio is calculated as the odds of an allele in cases divided by the odds of the allele in controls. An odds ratio of one indicates that there is no difference in allele frequency between cases and controls.
- Pleiotropy
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The effect of a single gene on multiple phenotypes.
- Population cohort study
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A longitudinal study of individuals who are representative of the general population and who are often recruited by their year of birth.
- Power
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The probability that a statistical test will reject the null hypothesis when the alternative hypothesis is true.
- Quantitative genetics
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A theory of multiple gene influences that, together with environmental variation, results in quantitative (continuous) distributions of phenotypes. Quantitative genetic methods, such as twin and adoption methods for human analysis, estimate genetic and environmental contributions to phenotypic variance and covariance in a population.
- Sensitivity
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The proportion of true positives that are accurately identified as such — for example, the percentage of cases that are diagnosed using a questionnaire. A sensitivity of 100% means that all cases are correctly identified.
- Specificity
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The proportion of true negatives that are classified as negatives. For example, a diagnostic test with specificity of 100% means that all healthy people have been identified as healthy.
- Trait
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A phenotype that differs between individuals in a species and shows some stability across time and situations. Disorders and diseases are qualitative (dichotomous) traits; quantitative traits are continuously distributed, usually as the bell-shaped curve called the normal distribution.
- Variance
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A measure of the dispersal of phenotypic scores around the mean.
- Web-based testing
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Administering online questionnaires and tests using the internet, which allows access to large and geographically diverse samples.
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Plomin, R., Haworth, C. & Davis, O. Common disorders are quantitative traits. Nat Rev Genet 10, 872–878 (2009). https://doi.org/10.1038/nrg2670
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DOI: https://doi.org/10.1038/nrg2670
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