Harnessing the information contained within genome-wide association studies to improve individual prediction of complex disease risk
Abstract
The current paradigm within genetic diagnostics is to test individuals only at loci known to affect risk of complex disease-yet the technology exists to genotype an individual at thousands of loci across the genome. We investigated whether information from genome-wide association studies could be harnessed to improve discrimination of complex disease affection status. We employed genome-wide data from the Wellcome Trust Case Control Consortium to test this hypothesis. Each disease cohort together with the same set of controls were split into two samples-a 'Training Set', where thousands of SNPs that might predispose to disease risk were identified and a 'Prediction Set', where the discriminatory ability of these SNPs was assessed. Genome-wide scores consisting of, for example, the total number of risk alleles an individual carries was calculated for each individual in the prediction set. Case-control status was regressed on this score and the area under the receiver operator characteristic curve (AUC) estimated. In most cases, a liberal inclusion of SNPs in the genome-wide score improved AUC compared with a more stringent selection of top SNPs, but did not perform as well as selection based upon established variants. The addition of genome-wide scores to known variant information produced only a limited increase in discriminative accuracy but was most effective for bipolar disorder, coronary heart disease and type II diabetes. We conclude that this small increase in discriminative accuracy is unlikely to be of diagnostic or predictive utility at the present time.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Development of robust polygenic scores for several common diseases has been catalysed by more precise per-variant effect estimates from larger GWAS, improved algorithms, and large-scale biobanks.
“The development of robust polygenic scores for several common diseases has been catalysed by more precise per-variant effect estimates from larger GWAS datasets, improved algorithms for combining information across millions of single-nucleotide polymorphisms, and large-scale biobanks that support score validation69,146,147.”
From A brief history of human disease genetics (2020) · cites this paper as [147]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
PLINK: a tool set for whole-genome association and population-based linkage analyses.
Purcell, S., Neale, B., Todd-Brown, K., Thomas, L., Ferreira, M. A. R., Bender, D., Maller, J., Sklar, P., de Bakker, P. I. W., Daly, M. J., et al. (2007) · The American Journal of Human Genetics · doi:10.1086/519795 · Cited by 34,089 · see citing works
The meaning and use of the area under a receiver operating characteristic (ROC) curve.
Hanley, J. A., & McNeil, B. J. (1982) · Radiology · doi:10.1148/radiology.143.1.7063747 · Cited by 21,856 · see citing works
Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls
The Wellcome Trust Case Control Consortium, Management Committee, Burton, P. R., Clayton, D. G., Cardon, L. R., Craddock, N., Deloukas, P., Duncanson, A., Kwiatkowski, D. P., McCarthy, M. I., et al. (2007) · Nature · doi:10.1038/nature05911 · Cited by 9,442 · see citing works
Self-citationThe Wellcome Trust Case Control Consortium, U.K.
Mossman, K. (2008) · Scientific American · doi:10.1038/scientificamerican0108-42a · Cited by 2,714 · see citing works
A vision for the future of genomics research
Collins, F. S., Green, E. D., Guttmacher, A. E., Guyer, M. S., & on behalf of the US National Human Genome Research Institute (2003) · Nature · doi:10.1038/nature01626 · Cited by 1,752 · see citing works
Personal genomes: The case of the missing heritability
Maher, B. (2008) · Nature · doi:10.1038/456018a · Cited by 1,737 · see citing works
Genetic Mapping in Human Disease
Altshuler, D., Daly, M. J., & Lander, E. S. (2008) · Science · doi:10.1126/science.1156409 · Cited by 1,452 · see citing works
Polygenic susceptibility to breast cancer and implications for prevention
Pharoah, P. D. P., Antoniou, A. C., Bobrow, M., Zimmern, R. L., Easton, D. F., & Ponder, B. A. J. (2002) · Nature Genetics · doi:10.1038/ng853 · Cited by 898 · see citing works
Implications of the Human Genome Project for Medical Science
Collins, F. S. (2001) · JAMA · doi:10.1001/jama.285.5.540 · Cited by 842 · see citing works
Prediction of individual genetic risk to disease from genome-wide association studiesPreprint
Wray, N. R., Goddard, M. E., & Visscher, P. M. (2007) · Genome Research · doi:10.1101/gr.6665407 · Cited by 714 · see citing works
Self-citationMaller, J., George, S., Purcell, S., Fagerness, J., Altshuler, D., Daly, M. J., & Seddon, J. M. (2006) · Nature Genetics · doi:10.1038/ng1873 · Cited by 599 · see citing works
Will Genetics Revolutionize Medicine?
Holtzman, N. A., & Marteau, T. M. (2000) · New England Journal of Medicine · doi:10.1056/nejm200007133430213 · Cited by 409 · see citing works
Predictive testing for complex diseases using multiple genes: Fact or fiction?
Janssens, A. C. J. W., Aulchenko, Y. S., Elefante, S., Borsboom, G., Steyerberg, E. W., & van Duijn, C. M. (2006) · Genetics in Medicine · doi:10.1097/01.gim.0000229689.18263.f4 · Cited by 232 · see citing works
Prediction of individual genetic risk of complex disease
Wray, N. R., Goddard, M. E., & Visscher, P. M. (2008) · Current Opinion in Genetics & Development · doi:10.1016/j.gde.2008.07.006 · Cited by 165 · see citing works
Self-citationImproving the Prediction of Complex Diseases by Testing for Multiple Disease-Susceptibility Genes
Yang, Q., Khoury, M. J., Botto, L. D., Friedman, J. M., & Flanders, W. D. (2003) · The American Journal of Human Genetics · doi:10.1086/367923 · Cited by 156 · see citing works
Misconceptions about the use of genetic tests in populations
Vineis, P., Schulte, P. A., & McMichael, A. J. (2001) · The Lancet · doi:10.1016/s0140-6736(00)04136-2 · Cited by 156 · see citing works
Janssens, A. C. J. W., Moonesinghe, R., Yang, Q., Steyerberg, E. W., van Duijn, C. M., & Khoury, M. J. (2007) · Genetics in Medicine · doi:10.1097/gim.0b013e31812eece0 · Cited by 151 · see citing works
Schizophrenia genetics: the search for a hard lead
Sullivan, P. F. (2008) · Current Opinion in Psychiatry · doi:10.1097/yco.0b013e3282f4efde · Cited by 32 · see citing works
Genetic screening and counseling
Norton, M. E. (2008) · Current Opinion in Obstetrics & Gynecology · doi:10.1097/gco.0b013e3282f73230 · Cited by 30 · see citing works
Genetic Testing in Clinical Practice
Lamberts, S. W. J., & Uitterlinden, A. G. (2008) · Annual Review of Medicine · doi:10.1146/annurev.med.60.103007.132540 · Cited by 27 · see citing works
Valle, D. L. (2004) · The American Journal of Human Genetics · doi:10.1086/382790 · Cited by 21 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
10 Years of GWAS Discovery: Biology, Function, and Translation
Visscher, P. M., Wray, N. R., Zhang, Q., Sklar, P., McCarthy, M. I., Brown, M. A., & Yang, J. (2017) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2017.06.005 · Cited by 3,719 · see citing works
Self-citationPower and predictive accuracy of polygenic risk scores
Dudbridge, F. (2013) · PLoS Genetics · doi:10.1371/journal.pgen.1003348 · Cited by 1,509 · see citing works
“The use of a mass of markers across the whole genome has been explored, but to date has not yielded a noticeable improvement in discrimination [14,19].”
BackgroundMethodInfluentialModeling Linkage Disequilibrium Increases Accuracy of Polygenic Risk Scores
Vilhjálmsson, B. J., Yang, J., Finucane, H. K., Gusev, A., Lindström, S., Ripke, S., Genovese, G., Loh, P.-R., Bhatia, G., Do, R., et al. (2015) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2015.09.001 · Cited by 1,303 · see citing works
Self-citationEvaluating the potential role of pleiotropy in Mendelian randomization studies
Hemani, G., Bowden, J., & Davey Smith, G. (2018) · Human Molecular Genetics · doi:10.1093/hmg/ddy163 · Cited by 1,496 · see citing works
Human Demographic History Impacts Genetic Risk Prediction across Diverse Populations
Martin, A. R., Gignoux, C. R., Walters, R. K., Wojcik, G. L., Neale, B. M., Gravel, S., Daly, M. J., Bustamante, C. D., & Kenny, E. E. (2017) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2017.03.004 · Cited by 1,391 · see citing works
Collider scope: when selection bias can substantially influence observed associations
Munafò, M. R., Tilling, K., Taylor, A. E., Evans, D. M., & Davey Smith, G. (2018) · International Journal of Epidemiology · doi:10.1093/ije/dyx206 · Cited by 813 · see citing works
Self-citationA brief history of human disease genetics
Claussnitzer, M., Cho, J. H., Collins, R., Cox, N. J., Dermitzakis, E. T., Hurles, M. E., Kathiresan, S., Kenny, E. E., Lindgren, C. M., MacArthur, D. G., et al. (2020) · Nature · doi:10.1038/s41586-019-1879-7 · Cited by 697 · see citing works
Identification of IL6R and chromosome 11q13.5 as risk loci for asthma
Ferreira, M. A., Matheson, M. C., Duffy, D. L., Marks, G. B., Hui, J., Le Souëf, P., Danoy, P., Baltic, S., Nyholt, D. R., Jenkins, M., et al. (2011) · The Lancet · doi:10.1016/s0140-6736(11)60874-x · Cited by 381 · see citing works
Self-citationZhang, Y., Qi, G., Park, J.-H., & Chatterjee, N. (2018) · Nature Genetics · doi:10.1038/s41588-018-0193-x · Cited by 288 · see citing works
Hints of hidden heritability in GWAS
Gibson, G. (2010) · Nature Genetics · doi:10.1038/ng0710-558 · Cited by 281 · see citing works
Identification of Pathways for Bipolar Disorder: A Meta-analysis
Nurnberger, J. I., Koller, D. L., Jung, J., Edenberg, H. J., Foroud, T., Guella, I., Vawter, M. P., & Kelsoe, J. R. (2014) · JAMA Psychiatry · doi:10.1001/jamapsychiatry.2014.176 · Cited by 234 · see citing works
When Optimism Hurts: Inflated Predictions in Psychiatric Neuroimaging
Whelan, R., & Garavan, H. (2014) · Biological Psychiatry · doi:10.1016/j.biopsych.2013.05.014 · Cited by 209 · see citing works
Richmond, R. C., Davey Smith, G., Ness, A. R., den Hoed, M., McMahon, G., & Timpson, N. J. (2014) · PLoS Medicine · doi:10.1371/journal.pmed.1001618 · Cited by 167 · see citing works
Multilocus Genetic Risk Scores for Coronary Heart Disease Prediction
Ganna, A., Magnusson, P. K. E., Pedersen, N. L., de Faire, U., Reilly, M., Ärnlöv, J., Sundström, J., Hamsten, A., & Ingelsson, E. (2013) · Arteriosclerosis, Thrombosis, and Vascular Biology · doi:10.1161/atvbaha.113.301218 · Cited by 156 · see citing works
Statistical methods to detect pleiotropy in human complex traits
Hackinger, S., & Zeggini, E. (2017) · Open Biology · doi:10.1098/rsob.170125 · Cited by 143 · see citing works
The pursuit of susceptibility genes for Alzheimer's disease: progress and prospects
Sleegers, K., Lambert, J.-C., Bertram, L., Cruts, M., Amouyel, P., & Van Broeckhoven, C. (2010) · Trends in Genetics · doi:10.1016/j.tig.2009.12.004 · Cited by 129 · see citing works
Stergiakouli, E., Martin, J., Hamshere, M. L., Langley, K., Evans, D. M., St Pourcain, B., Timpson, N. J., Owen, M. J., O'Donovan, M., Thapar, A., et al. (2015) · Journal of the American Academy of Child & Adolescent Psychiatry · doi:10.1016/j.jaac.2015.01.010 · Cited by 94 · see citing works
Self-citationMinică, C. C., Dolan, C. V., Boomsma, D. I., de Geus, E., & Neale, M. C. (2018) · Behavior Genetics · doi:10.1007/s10519-018-9904-4 · Cited by 80 · see citing works
DeepRisk: a deep learning approach for genome-wide assessment of common disease risk
Peng, J., Bao, Z., Li, J., Han, R., Wang, Y., Han, L., Peng, J., Wang, T., Hao, J., Wei, Z., et al. (2024) · Fundamental Research · doi:10.1016/j.fmre.2024.02.015 · Cited by 15 · see citing works
- Authors
- Evans, D. M., Visscher, P. M., & Wray, N. R.
- Affiliations
- University of Bristol (GB)
- QIMR Berghofer Medical Research Institute (AU)
- Corresponding author
- Evans, David M.
- Venue
- Human Molecular Genetics
- Publisher
- Oxford University Press (OUP)
- Published
- 2009-06-24
- Volume
- 18
- Issue
- 18
- Pages
- 3525-3531
- ISSN
- 0964-6906 (ISSN-L)
- 1460-2083
- OpenAlex
- W2121514846
- Cited by
- 297
- References
- 21
- Citations by year
- 2026: 1 · 2025: 8 · 2024: 6 · 2023: 7 · 2022: 11 · 2021: 13 · 2020: 16 · 2019: 24 · 2018: 20 · 2017: 23 · 2016: 21 · 2015: 26 · 2014: 27 · 2013: 25 · 2012: 29
- FWCI
- 13.37
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Human Molecular Genetics (publishedVersion)
- PubMed (publishedVersion)
- Bristol Research (University of Bristol) (submittedVersion)
- Funders
- Wellcome Trust
- Medical Research Council (G0800582)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Mapping and Diversity in Plants and Animals
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic and phenotypic traits in livestock
- Keywords
- genome-wide association study, single nucleotide polymorphisms, bipolar disorder, coronary artery disease, type 2 diabetes, genetic diagnosis, Wellcome Trust Case Control Consortium
- MeSH terms
- Genetic Testing, Humans, Risk Factors, Genome, Human, Computational Biology, Polymorphism, Single Nucleotide, Genome-Wide Association Study
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
