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Cited by 336Genetic Associations and EpidemiologyGenetic and phenotypic traits in livestockGenetic Mapping and Diversity in Plants and Animals

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The Genetic Interpretation of Area under the ROC Curve in Genomic Profiling

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Wray, Naomi R., Yang, Jian, Goddard, Michael E., Visscher, Peter M.·2010·PLoS Genetics
DOI 10.1371/journal.pgen.1000864PMC PMC2829056
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Abstract

Genome-wide association studies in human populations have facilitated the creation of genomic profiles which combine the effects of many associated genetic variants to predict risk of disease. The area under the receiver operator characteristic (ROC) curve is a well established measure for determining the efficacy of tests in correctly classifying diseased and non-diseased individuals. We use quantitative genetics theory to provide insight into the genetic interpretation of the area under the ROC curve (AUC) when the test classifier is a predictor of genetic risk. Even when the proportion of genetic variance explained by the test is 100%, there is a maximum value for AUC that depends on the genetic epidemiology of the disease, i.e. either the sibling recurrence risk or heritability and disease prevalence. We derive an equation relating maximum AUC to heritability and disease prevalence. The expression can be reversed to calculate the proportion of genetic variance explained given AUC, disease prevalence, and heritability. We use published estimates of disease prevalence and sibling recurrence risk for 17 complex genetic diseases to calculate the proportion of genetic variance that a test must explain to achieve AUC = 0.75; this varied from 0.10 to 0.74. We provide a genetic interpretation of AUC for use with predictors of genetic risk based on genomic profiles. We provide a strategy to estimate proportion of genetic variance explained on the liability scale from estimates of AUC, disease prevalence, and heritability (or sibling recurrence risk) available as an online calculator.

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Figure 1 The dependence of maximum AUC (AUCmax) from a genomic profile on heritability and disese prevalence. (A,B) Probability of disease versus genetic liability. (C,D) ROC curve [46].
Figure 1 The dependence of maximum AUC (AUCmax) from a genomic profile on heritability and disese prevalence. (A,B) Probability of disease versus genetic liability. (C,D) ROC curve [46].CC BY · PubMed Central
Figure 2 Relationship between maximum AUC (AUCmax) from a genomic profile and heritability on the liability scale . For different disease prevalences (A–D) from simulation (dashed line) and from equation 3 (solid line).
Figure 2 Relationship between maximum AUC (AUCmax) from a genomic profile and heritability on the liability scale . For different disease prevalences (A–D) from simulation (dashed line) and from equation 3 (solid line).CC BY · PubMed Central
Figure 3 The relationship between maximum AUC (AUCmax) from a genomic profile and heritability on the liability scale (dashed line) or heritability on the observed scale (solid line), for disease prevalences in order from top left, K = 0.001, 0.01, 0.1, 0.3.
Figure 3 The relationship between maximum AUC (AUCmax) from a genomic profile and heritability on the liability scale (dashed line) or heritability on the observed scale (solid line), for disease prevalences in order from top left, K = 0.001, 0.01, 0.1, 0.3.CC BY · PubMed Central

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Research works printed but not linked: 1

  1. M McGue, 1983, The transmission of schizophrenia under a multifactorial threshold model., American Journal of Human Genetics, 35, 1161

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Metadata

Authors
Wray, N. R., Yang, J., Goddard, M. E., & Visscher, P. M.
Affiliations
  • QIMR Berghofer Medical Research Institute (AU)
  • The University of Melbourne (AU)
Corresponding author
Wray, Naomi R.
ORCID
Venue
PLoS Genetics
Publisher
Public Library of Science (PLoS)
Published
2010-02-26
Volume
6
Issue
2
Pages
e1000864
ISSN
  • 1553-7390 (ISSN-L)
  • 1553-7404
DOI
10.1371/journal.pgen.1000864
PMC
PMC2829056
OpenAlex
W1990700240
Cited by
334
References
52
Citations by year
2026: 11 · 2025: 16 · 2024: 9 · 2023: 16 · 2022: 13 · 2021: 26 · 2020: 27 · 2019: 28 · 2018: 14 · 2017: 24 · 2016: 14 · 2015: 19 · 2014: 30 · 2013: 22 · 2012: 34
FWCI
15.45
Type
journal article
Language
en
Open access
Licence
Locations
  • PLoS Genetics (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • Figshare (submittedVersion, cc-by)
  • Minerva Access (University of Melbourne) (submittedVersion, cc-by)
Funders
  • Medical Research Council
  • Australian Research Council (DP0770096)
  • National Health and Medical Research Council (496688, 442915, DP0770096, 389892)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic and phenotypic traits in livestock
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Mapping and Diversity in Plants and Animals
Keywords
area under the ROC curve, genomic profiling, genetic risk prediction, heritability, disease prevalence, sibling recurrence risk, liability scale, complex genetic disorders, genome-wide association study, genetic epidemiology
MeSH terms
Aged, 80 and over, Disease, Humans, Macular Degeneration, ROC Curve, Genome, Human, Prevalence, Area Under Curve, Gene Expression Profiling, Inheritance Patterns

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