Opinion | Published:

Common disorders are quantitative traits

Nature Reviews Genetics volume 10, pages 872878 (2009) | Download Citation

  • A Corrigendum to this article was published on 09 November 2009

This article has been updated

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.

Access optionsAccess options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

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.

References

  1. 1.

    The correlation between relatives on the supposition of Mendelian inheritance. Trans. R. Soc. Edinb. 52, 399–433 (1918).

  2. 2.

    Progress and challenges in genome-wide association studies in humans. Nature 456, 728–731 (2008).

  3. 3.

    The Wellcome Trust Case Control Consortium. Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls. Nature 447, 661–678 (2007).

  4. 4.

    Personal genomes: the case of the missing heritability. Nature 456, 18–21 (2008).

  5. 5.

    & Introduction to Quantitative Genetics (Longman, Harlow, 1996).

  6. 6.

    The road to genome-wide association studies. Nature Rev. Genet. 9, 314–318 (2008).

  7. 7.

    et al. Genome-wide association studies for complex traits: consensus, uncertainty and challenges. Nature Rev. Genet. 9, 356–369 (2008).

  8. 8.

    , & The genetics of quantitative traits: challenges and prospects. Nature Rev. Genet. 10, 565–577 (2009).

  9. 9.

    et al. Genetic variant near IRS1 is associated with type 2 diabetes, insulin resistance and hyperinsulinemia. Nature Genet. 41, 1110–1115 (2009).

  10. 10.

    et al. A polymorphism within the G6PC2 gene is associated with fasting plasma glucose levels. Science 320, 1085–1088 (2008).

  11. 11.

    et al. Genetic loci associated with C-reactive protein levels and risk of coronary heart disease. JAMA 302, 37–48 (2009).

  12. 12.

    Inflammatory bowel disease. N. Engl. J. Med. 347, 417–429 (2002).

  13. 13.

    New links to the pathogenesis of Crohn disease provided by genome-wide association scans. Nature Rev. Genet. 9, 9–14 (2008).

  14. 14.

    , , & Nod-like proteins in immunity, inflammation and disease. Nature Immunol. 7, 1250–1257 (2006).

  15. 15.

    et al. Gene–environment interaction modulated by allelic heterogeneity in inflammatory diseases. Proc. Natl Acad. Sci. USA 100, 3455–3460 (2003).

  16. 16.

    et al. A frameshift mutation in NOD2 associated with susceptibility to Crohn's disease. Nature 411, 603–606 (2001).

  17. 17.

    IL-23: a master regulator in Crohn disease. Nature Med. 13, 26–28 (2007).

  18. 18.

    & Unravelling the pathogenesis of inflammatory bowel disease. Nature 448, 427–434 (2007).

  19. 19.

    et al. Genome-wide association study identifies new susceptibility loci for Crohn disease and implicates autophagy in disease pathogenesis. Nature Genet. 39, 596–604 (2007).

  20. 20.

    , , & Human IRGM induces autophagy to eliminate intracellular mycobacteria. Science 313, 1438–1441 (2006).

  21. 21.

    , , , & Differential effects of NOD2 variants on Crohn's disease risk and phenotype in diverse populations: a metaanalysis. Am. J. Gastroenterol. 99, 2393–2404 (2004).

  22. 22.

    et al. IL23R variation determines susceptibility but not disease phenotype in inflammatory bowel disease. Gastroenterology 132, 1657–1664 (2007).

  23. 23.

    & The emerging landscape of breast cancer susceptibility. Nature Genet. 40, 17–22 (2008).

  24. 24.

    et al. Genome-wide association defines more than 30 distinct susceptibility loci for Crohn's disease. Nature Genet. 40, 955–962 (2008).

  25. 25.

    et al. The human disease network. Proc. Natl Acad. Sci. USA 104, 8685–8690 (2007).

  26. 26.

    , & Prediction of individual genetic risk of complex disease. Curr. Opin. Genet. Dev. 18, 257–263 (2008).

  27. 27.

    et al. Polygenic susceptibility to breast cancer and implications for prevention. Nature Genet. 31, 33–36 (2002).

  28. 28.

    , , , & An epidemiologic assessment of genomic profiling for measuring susceptibility to common diseases and targeting interventions. Genet. Med. 6, 38–47 (2004).

  29. 29.

    , , , & A behavioural genomic analysis of DNA markers associated with general cognitive ability in 7-year-olds. J. Child Psychol. Psychiatry 46, 1097–1107 (2005).

  30. 30.

    et al. Prediction of coronary heart disease risk using a genetic risk score: the Atherosclerosis Risk in Communities Study. Am. J. Epidemiol. 166, 28–35 (2007).

  31. 31.

    The International Schizophrenia Consortium. Common polygenic variation contributes to risk of schizophrenia and bipolar disorder. Nature 460, 748–752 (2009).

  32. 32.

    et al. Association between common variation in 120 candidate genes and breast cancer risk. PLoS Genet. 3, e42 (2007).

  33. 33.

    et al. Five common gene variants identify elevated genetic risk for coronary heart disease. Genet. Med. 9, 682–689 (2007).

  34. 34.

    et al. Common variation in three genes, including a noncoding variant in CFH, strongly influences risk of age-related macular degeneration. Nature Genet. 38, 1055–1059 (2006).

  35. 35.

    , , , & Proof of principle of potential clinical utility of multiple SNP analysis for prediction of recurrent venous thrombosis. J. Thromb. Haemost. 6, 751–754 (2008).

  36. 36.

    et al. Genetic prediction of future type 2 diabetes. PLoS Med. 2, e345 (2005).

  37. 37.

    The evolution of personality variation in humans and other animals. Am. Psychol. 61, 622–631 (2006).

  38. 38.

    Systems biology: a brief overview. Science 295, 1662–1664 (2002).

  39. 39.

    et al. Genome-wide strategies for discovering genetic influences on cognition and cognitive disorders: methodological considerations. Cogn. Neuropsychiatry 14, 391–418 (2009).

  40. 40.

    et al. Internet cognitive testing of large samples needed in genetic research. Twin Res. Hum. Genet. 10, 554–563 (2007).

  41. 41.

    et al. Phenomics: the systematic study of phenotypes on a genome-wide scale. Neuroscience 164, 30–42 (2009).

  42. 42.

    & The human phenome project. Nature Genet. 34, 15–21 (2003).

  43. 43.

    , & The genetic contribution to non-syndromic human obesity. Nature Rev. Genet. 10, 431–442 (2009).

  44. 44.

    et al. Clinical utility as a criterion for revising psychiatric diagnoses. Am. J. Psychiatry 161, 946–954 (2004).

  45. 45.

    The Psychiatric GWAS Consortium Steering Committee. A framework for interpreting genome-wide association studies of psychiatric disorders. Mol. Psychiatry 14, 10–17 (2009).

  46. 46.

    , , , & Evidence based medicine: what it is and what it isn't. BMJ 312, 71–72 (1996).

  47. 47.

    , & Rose's Strategy of Preventive Medicine (Oxford Univ. Press, 2008).

  48. 48.

    et al. A common variant in the FTO gene is associated with body mass index and predisposes to childhood and adult obesity. Science 316, 889–894 (2007).

  49. 49.

    , et al. A genome-wide association study identifies novel risk loci for type 2 diabetes. Nature 445, 881–885 (2007).

Download references

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.

Author information

Affiliations

  1. Robert Plomin, Claire M. A. Haworth and Oliver S. P. Davis are at the Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, King's College London, London SE5 8AF, UK.

    • Robert Plomin
    • , Claire M. A. Haworth
    •  & Oliver S. P. Davis

Authors

  1. Search for Robert Plomin in:

  2. Search for Claire M. A. Haworth in:

  3. Search for Oliver S. P. Davis in:

Corresponding author

Correspondence to Robert Plomin.

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

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

The co-occurrence of two or more disorders or diseases in an individual.

Covariance

A statistic that indicates the extent to which two variables are related and vary together.

Crohn's disease

Characterized by chronic intestinal inflammation, which leads to diarrhoea, bleeding, severe abdominal pain and weight loss.

Effect size

The proportion of individual differences for a trait in the population that are accounted for by a particular factor.

Genome-wide association research

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

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

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

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

The effect of a single gene on multiple phenotypes.

Population cohort study

A longitudinal study of individuals who are representative of the general population and who are often recruited by their year of birth.

Power

The probability that a statistical test will reject the null hypothesis when the alternative hypothesis is true.

Quantitative genetics

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

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

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

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

A measure of the dispersal of phenotypic scores around the mean.

Web-based testing

Administering online questionnaires and tests using the internet, which allows access to large and geographically diverse samples.

About this article

Publication history

Published

DOI

https://doi.org/10.1038/nrg2670

Further reading