Measuring missing heritability: Inferring the contribution of common variants
Open accessAbstract
Significance: Studies have identified thousands of common genetic variants associated with hundreds of diseases. Yet, these common variants typically account for a minority of the heritability, a problem known as “missing heritability.” Geneticists recently proposed indirect methods for estimating the total heritability attributable to common variants, including those whose effects are too small to allow identification in current studies. Here, we show that these methods seriously underestimate the true heritability when applied to case–control studies of disease. We describe a method that provides unbiased estimates. Applying it to six diseases, we estimate that common variants explain an average of 60% of the heritability for these diseases. The framework also may be applied to case–control studies, extreme-phenotype studies, and other settings.
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?
For most common diseases, polygenic inheritance involving many common variants of small effect plays a greater role than rare monogenic mutations.
“For most common diseases, polygenic inheritance, involving many common genetic variants of small effect, plays a greater role than rare monogenic mutations.2–5”
From Genome-wide polygenic scores for common diseases identify individuals with risk equivalent to monogenic mutations (2018) · cites this paper as [4]
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
Principal components analysis corrects for stratification in genome-wide association studies
Price, A. L., Patterson, N. J., Plenge, R. M., Weinblatt, M. E., Shadick, N. A., & Reich, D. (2006) · Nature Genetics · doi:10.1038/ng1847 · Cited by 10,248 · 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
Finding the missing heritability of complex diseases
Manolio, T. A., Collins, F. S., Cox, N. J., Goldstein, D. B., Hindorff, L. A., Hunter, D. J., McCarthy, M. I., Ramos, E. M., Cardon, L. R., Chakravarti, A., et al. (2009) · Nature · doi:10.1038/nature08494 · Cited by 8,336 · see citing works
GCTA: a tool for genome-wide complex trait analysis
Yang, J., Lee, S. H., Goddard, M. E., & Visscher, P. M. (2011) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2010.11.011 · Cited by 8,279 · see citing works
Population Structure and Eigenanalysis
Patterson, N., Price, A. L., & Reich, D. (2006) · PLoS Genetics · doi:10.1371/journal.pgen.0020190 · Cited by 5,280 · see citing works
Mapping mendelian factors underlying quantitative traits using RFLP linkage maps.
Lander, E. S., & Botstein, D. (1989) · Genetics · doi:10.1093/genetics/121.1.185 · Cited by 5,236 · see citing works
Self-citationCommon SNPs explain a large proportion of the heritability for human height
Yang, J., Benyamin, B., McEvoy, B. P., Gordon, S., Henders, A. K., Nyholt, D. R., Madden, P. A., Heath, A. C., Martin, N. G., Montgomery, G. W., et al. (2010) · Nature Genetics · doi:10.1038/ng.608 · Cited by 4,446 · see citing works
The NHGRI GWAS Catalog, a curated resource of SNP-trait associations
Welter, D., MacArthur, J., Morales, J., Burdett, T., Hall, P., Junkins, H., Klemm, A., Flicek, P., Manolio, T., Hindorff, L., et al. (2014) · Nucleic Acids Research · doi:10.1093/nar/gkt1229 · Cited by 2,707 · see citing works
Twelve type 2 diabetes susceptibility loci identified through large-scale association analysis
The MAGIC investigators, Voight, B. F., The GIANT Consortium, Scott, L. J., Steinthorsdottir, V., Morris, A. P., Dina, C., Welch, R. P., Zeggini, E., Huth, C., et al. (2010) · Nature Genetics · doi:10.1038/ng.609 · Cited by 1,761 · 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
The mystery of missing heritability: Genetic interactions create phantom heritability
Zuk, O., Hechter, E., Sunyaev, S. R., & Lander, E. S. (2012) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1119675109 · Cited by 1,542 · see citing works
Self-citationGenome-wide association analysis identifies 13 new risk loci for schizophrenia
Multicenter Genetic Studies of Schizophrenia Consortium, Ripke, S., Psychosis Endophenotypes International Consortium, Wellcome Trust Case Control Consortium 2, O'Dushlaine, C., Chambert, K., Moran, J. L., Kähler, A. K., Akterin, S., Bergen, S. E., et al. (2013) · Nature Genetics · doi:10.1038/ng.2742 · Cited by 1,496 · see citing works
Regression Towards Mediocrity in Hereditary Stature.
Galton, F. (1886) · The Journal of the Anthropological Institute of Great Britain and Ireland · doi:10.2307/2841583 · Cited by 1,474 · see citing works
The investigation of linkage between a quantitative trait and a marker locus
Haseman, J. K., & Elston, R. C. (1972) · Behavior Genetics · doi:10.1007/bf01066731 · Cited by 1,367 · see citing works
Myocardial Infarction Genetics Consortium (2009) · Nature Genetics · doi:10.1038/ng.327 · Cited by 1,088 · see citing works
Logistic Disease Incidence Models and Case-Control Studies
Prentice, R. L., & Pyke, R. (1979) · Biometrika · doi:10.1093/biomet/66.3.403 · Cited by 1,086 · see citing works
Estimating Missing Heritability for Disease from Genome-wide Association Studies
Lee, S. H., Wray, N. R., Goddard, M. E., & Visscher, P. M. (2011) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2011.02.002 · Cited by 1,064 · see citing works
Advantages and pitfalls in the application of mixed-model association methods
Yang, J., Zaitlen, N. A., Goddard, M. E., Visscher, P. M., & Price, A. L. (2014) · Nature Genetics · doi:10.1038/ng.2876 · Cited by 981 · see citing works
HERITABILITY OF THRESHOLD CHARACTERS
Dempster, E. R., & Lerner, I. M. (1950) · Genetics · doi:10.1093/genetics/35.2.212 · Cited by 848 · see citing works
Genome-wide association analysis identifies 20 loci that influence adult height
Initiative, D. G., Weedon, M. N., The Wellcome Trust Case Control Consortium, Cambridge GEM Consortium, Lango, H., Lindgren, C. M., Wallace, C., Evans, D. M., Mangino, M., Freathy, R. M., et al. (2008) · Nature Genetics · doi:10.1038/ng.121 · Cited by 826 · see citing works
Polygenic Modeling with Bayesian Sparse Linear Mixed Models
Zhou, X., Carbonetto, P. S., & Stephens, M. (2013) · PLoS Genetics · doi:10.1371/journal.pgen.1003264 · Cited by 801 · see citing works
Improved Heritability Estimation from Genome-wide SNPs
Speed, D., Hemani, G., Johnson, M. R., & Balding, D. J. (2012) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2012.10.010 · Cited by 700 · see citing works
Many sequence variants affecting diversity of adult human height
Gudbjartsson, D. F., Walters, G. B., Þorleifsson, G., Stefánsson, H., Halldórsson, B. V., Zusmanovich, P., Sulem, P., Thorlacius, S., Gylfason, A., Steinberg, S., et al. (2008) · Nature Genetics · doi:10.1038/ng.122 · Cited by 666 · see citing works
Searching for missing heritability: Designing rare variant association studies
Zuk, O., Schaffner, S. F., Samocha, K., Do, R., Hechter, E., Kathiresan, S., Daly, M. J., Neale, B. M., Sunyaev, S. R., & Lander, E. S. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1322563111 · Cited by 635 · see citing works
Self-citationVisscher, P. M., Medland, S. E., Ferreira, M. A. R., Morley, K. I., Zhu, G., Cornes, B. K., Montgomery, G. W., & Martin, N. G. (2006) · PLoS Genetics · doi:10.1371/journal.pgen.0020041 · Cited by 613 · see citing works
Spencer, C. C. A., Su, Z., Donnelly, P., & Marchini, J. (2009) · PLoS Genetics · doi:10.1371/journal.pgen.1000477 · Cited by 606 · see citing works
Identification of ten loci associated with height highlights new biological pathways in human growth
Initiative, T. D. G., Lettre, G., FUSION, KORA, The Prostate, L. C. A. O. C. S. T., Study, T. N. H., SardiNIA, Jackson, A., Gieger, C., Schumacher, F. R., et al. (2008) · Nature Genetics · doi:10.1038/ng.125 · Cited by 583 · see citing works
Estimating the proportion of variation in susceptibility to schizophrenia captured by common SNPs
The Schizophrenia Psychiatric Genome-Wide Association Study Consortium (PGC-SCZ), Lee, S. H., The International Schizophrenia Consortium (ISC), The Molecular Genetics of Schizophrenia Collaboration (MGS), DeCandia, T. R., Ripke, S., Yang, J., Sullivan, P. F., Goddard, M. E., Keller, M. C., et al. (2012) · Nature Genetics · doi:10.1038/ng.1108 · Cited by 579 · see citing works
The Australia and New Zealand Multiple Sclerosis Genetics Consortium (ANZgene) (2009) · Nature Genetics · doi:10.1038/ng.396 · Cited by 550 · see citing works
Assessing the role of HLA-linked and unlinked determinants of disease.
RISCH, N. J. (1987) · PubMed · Cited by 542 · see citing works
Do, C. B., Tung, J. Y., Dorfman, E., Kiefer, A. K., Drabant, E. M., Francke, U., Mountain, J. L., Goldman, S. M., Tanner, C. M., Langston, J. W., et al. (2011) · PLoS Genetics · doi:10.1371/journal.pgen.1002141 · Cited by 515 · see citing works
Sizing up human height variation
Visscher, P. M. (2008) · Nature Genetics · doi:10.1038/ng0508-489 · Cited by 461 · see citing works
Guan, Y., & Stephens, M. (2011) · The Annals of Applied Statistics · doi:10.1214/11-aoas455 · Cited by 362 · see citing works
Paşaniuc, B., & Zaitlen, N. (2013) · eScholarship (California Digital Library) · Cited by 362 · see citing works
Zhang, Z., Ober, U., Erbe, M., Zhang, H., Gao, N., He, J., Li, J., & Simianer, H. (2014) · PLoS ONE · doi:10.1371/journal.pone.0093017 · Cited by 243 · see citing works
Lee, S. H., Harold, D., Nyholt, D. R., ANZGene Consortium, International Endogene Consortium, the Genetic and Environmental Risk for Alzheimer's disease (GERAD1) Consortium, Goddard, M. E., Zondervan, K. T., Williams, J., Montgomery, G. W., et al. (2013) · Human Molecular Genetics · doi:10.1093/hmg/dds491 · Cited by 217 · see citing works
Wei, Z., Wang, K., Qu, H., Zhang, H., Bradfield, J. P., Kim, C., Frackleton, E., Hou, C., Glessner, J., Chiavacci, R. M., et al. (2009) · PLoS Genetics · doi:10.1371/journal.pgen.1000678 · Cited by 207 · see citing works
Chen, G. (2014) · Frontiers in Genetics · doi:10.3389/fgene.2014.00107 · Cited by 65 · see citing works
Accurate estimation of heritability in genome wide studies using random effects models
Golan, D., & Rosset, S. (2011) · Bioinformatics · doi:10.1093/bioinformatics/btr219 · Cited by 28 · see citing works
Self-citationResnick, H. E., Rodríguez, B. L., Havlik, R. J., Ferrucci, L., Foley, D. J., Curb, J. D., & Harris, T. B. (2000) · Genetic Epidemiology · doi:10.1002/1098-2272(200007)19:1 · Cited by 25 · see citing works
Burton, P. R. (2002) · Genetic Epidemiology · doi:10.1002/gepi.10206 · Cited by 25 · see citing works
Watson, C. T., Disanto, G., Breden, F. J., Giovannoni, G., & Ramagopalan, S. V. (2012) · Scientific Reports · doi:10.1038/srep00770 · Cited by 20 · see citing works
Refining genetically inferred relationships using treelet covariance smoothing
Crossett, A., Lee, A. B., Klei, L., Devlin, B., & Roeder, K. (2013) · The Annals of Applied Statistics · doi:10.1214/12-aoas598 · Cited by 9 · see citing works
REFINING GENETICALLY INFERRED RELATIONSHIPS USING TREELET COVARIANCE SMOOTHING 1
Crossett, A., Lee, A. B., Klei, L., Devlin, B., & Roeder, K. (2012) · Cited by 8 · see citing works
Flagged first, then by citations
Research works printed but not linked: 1
- Elston RC, Buxbaum S, Jacobs KB, Olson JM (2000) Haseman and Elston revisited. Genet Epidemiol 19(1):1-17.
Cited by
Sorted by citations
Khera, A. V., Chaffin, M., Aragam, K. G., Haas, M. E., Roselli, C., Choi, S. H., Natarajan, P., Lander, E. S., Lubitz, S. A., Ellinor, P. T., et al. (2018) · Nature Genetics · doi:10.1038/s41588-018-0183-z · Cited by 2,953 · see citing works
Self-citationGenome-wide association studies
Uffelmann, E., Huang, Q. Q., Munung, N. S., de Vries, J., Okada, Y., Martin, A. R., Martin, H. C., Lappalainen, T., & Posthuma, D. (2021) · Nature Reviews Methods Primers · doi:10.1038/s43586-021-00056-9 · Cited by 1,849 · see citing works
Polygenic Prediction of Weight and Obesity Trajectories from Birth to Adulthood
Khera, A. V., Chaffin, M., Wade, K. H., Zahid, S., Brancale, J., Xia, R., Distefano, M., Senol-Cosar, O., Haas, M. E., Bick, A., et al. (2019) · Cell · doi:10.1016/j.cell.2019.03.028 · Cited by 789 · see citing works
Self-citationSchizophrenia Working Group of the Psychiatric Genomics Consortium, Loh, P.-R., Bhatia, G., Gusev, A., Finucane, H. K., Bulik-Sullivan, B. K., Pollack, S. J., de Candia, T. R., Lee, S. H., Wray, N. R., et al. (2015) · Nature Genetics · doi:10.1038/ng.3431 · Cited by 449 · see citing works
Contrasting the Genetic Architecture of 30 Complex Traits from Summary Association Data
Shi, H., Kichaev, G., & Pasaniuc, B. (2016) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2016.05.013 · Cited by 387 · see citing works
Minimal phenotyping yields genome-wide association signals of low specificity for major depression
MDD Working Group of the Psychiatric Genomics Consortium, Cai, N., Revez, J. A., Adams, M. J., Andlauer, T. F. M., Breen, G., Byrne, E. M., Clarke, T.-K., Forstner, A. J., Grabe, H. J., et al. (2020) · Nature Genetics · doi:10.1038/s41588-020-0594-5 · Cited by 344 · see citing works
Khera, A. V., Chaffin, M., Zekavat, S. M., Collins, R. L., Roselli, C., Natarajan, P., Lichtman, J. H., D’Onofrio, G., Mattera, J., Dreyer, R., et al. (2019) · Circulation · doi:10.1161/circulationaha.118.035658 · Cited by 315 · 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
Psychosis in Alzheimer disease—mechanisms, genetics and therapeutic opportunities
Ismail, Z., Creese, B., Aarsland, D., Kales, H. C., Lyketsos, C. G., Sweet, R. A., & Ballard, C. (2022) · Nature Reviews Neurology · doi:10.1038/s41582-021-00597-3 · Cited by 189 · see citing works
Schoech, A. P., Jordan, D. M., Loh, P.-R., Gazal, S., O’Connor, L. J., Balick, D. J., Palamara, P. F., Finucane, H. K., Sunyaev, S. R., & Price, A. L. (2019) · Nature Communications · doi:10.1038/s41467-019-08424-6 · Cited by 157 · see citing works
Genetic correlates of phenotypic heterogeneity in autism
Warrier, V., Zhang, X., Reed, P., Havdahl, A., Moore, T. M., Cliquet, F., Leblond, C. S., Rolland, T., Rosengren, A., LEAP, E.-A., et al. (2022) · Nature Genetics · doi:10.1038/s41588-022-01072-5 · Cited by 152 · see citing works
Accurate estimation of SNP-heritability from biobank-scale data irrespective of genetic architecture
Hou, K., Burch, K. S., Majumdar, A., Shi, H., Mancuso, N., Wu, Y., Sankararaman, S., & Pasaniuc, B. (2019) · Nature Genetics · doi:10.1038/s41588-019-0465-0 · Cited by 91 · see citing works
Efficient variance components analysis across millions of genomes
Pazokitoroudi, A., Wu, Y., Burch, K. S., Hou, K., Zhou, A., Pasaniuc, B., & Sankararaman, S. (2020) · Nature Communications · doi:10.1038/s41467-020-17576-9 · Cited by 55 · see citing works
Peyrot, W. J., Boomsma, D. I., Penninx, B. W. J. H., & Wray, N. R. (2016) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2015.12.017 · Cited by 42 · see citing works
Tesfaye, M., Jaholkowski, P., Hindley, G. F. L., Shadrin, A. A., Rahman, Z., Bahrami, S., Lin, A., Holen, B., Parker, N., Cheng, W., et al. (2023) · Genome Medicine · doi:10.1186/s13073-023-01212-4 · Cited by 46 · see citing works
Clinical neuroscience of addiction: what clinical psychologists need to know and why
Ray, L. A., & Grodin, E. N. (2021) · Annual Review of Clinical Psychology · doi:10.1146/annurev-clinpsy-081219-114309 · Cited by 18 · see citing works
- Authors
- Golan, D., Lander, E. S., & Rosset, S.
- Affiliations
- Tel Aviv University (IL)
- Broad Institute (US)
- Venue
- Proceedings of the National Academy of Sciences
- Publisher
- National Academy of Sciences
- Published
- 2014-11-24
- Volume
- 111
- Issue
- 49
- Pages
- E5272-81
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- PMC
- PMC4267399
- OpenAlex
- W2146415150
- Cited by
- 288
- References
- 44
- Citations by year
- 2026: 15 · 2025: 12 · 2024: 15 · 2023: 19 · 2022: 31 · 2021: 29 · 2020: 34 · 2019: 34 · 2018: 32 · 2017: 23 · 2016: 22 · 2015: 22
- FWCI
- 14.49
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Proceedings of the National Academy of Sciences (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- DSpace@MIT (Massachusetts Institute of Technology) (submittedVersion, cc-by-nc)
- Funders
- HHS | National Institutes of Health (NIH) (HG003067)
- 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
- missing heritability, common genetic variants, heritability estimation, restricted maximum likelihood, Haseman-Elston regression, case-control study, disease heritability, sample size, population structure
- MeSH terms
- Alleles, Computer Simulation, Gene Frequency, Genotype, Humans, Models, Genetic, Phenotype, Regression Analysis, Research Design, Genetic Variation, Models, Statistical, Case-Control Studies, Polymorphism, Single Nucleotide, Genomics, Genetic Diseases, Inborn, Genome-Wide Association Study, Genetic Association Studies
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
