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Evaluating the heritability explained by known susceptibility variants: a survey of ten complex diseases
Abstract
Recently, an increasing number of susceptibility variants have been identified for complex diseases. At the same time, the concern of "missing heritability" has also emerged. There is however no unified way to assess the heritability explained by individual genetic variants for binary outcomes. A systemic and quantitative assessment of the degree of "missing heritability" for complex diseases is lacking. In this study, we measure the variance in liability explained by individual variants, which can be directly interpreted as the locus-specific heritability. The method is extended to deal with haplotypes, multi-allelic markers, multi-locus genotypes, and markers in linkage disequilibrium. Methods to estimate the standard error and confidence interval are proposed. To assess our current level of understanding of the genetic basis of complex diseases, we conducted a survey of 10 diseases, evaluating the total variance explained by the known variants. The diseases under evaluation included Alzheimer's disease, bipolar disorder, breast cancer, coronary artery disease, Crohn's disease, prostate cancer, schizophrenia, systemic lupus erythematosus (SLE), type 1 diabetes and type 2 diabetes. The median total variance explained across the 10 diseases was 9.81%, while the median variance explained per associated SNP was around 0.25%. Our results suggest that a substantial proportion of heritability remains unexplained for the diseases under study. Programs to implement the methodologies described in this paper are available at http://sites.google.com/site/honcheongso/software/varexp.
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“Using a model that assumes an underlying normally distributed but unobserved disease risk score or liability49, the nineteen loci described here account for between 10% (if AMD prevalence is close to 1%) and 30% (if AMD prevalence is closer to 10%) of the variability in disease risk (corresponding to 15–65% of the total genetic contribution to AMD).”
From Seven new loci associated with age-related macular degeneration (2013) · cites this paper as [49]
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Cites
An Introduction to the Bootstrap
Efron, B., & Tibshirani, R. J. (1994) · doi:10.1201/9780429246593 · Cited by 40,500
An Introduction to the Bootstrap
Efron, B., & Tibshirani, R. J. (1993) · doi:10.1007/978-1-4899-4541-9 · Cited by 21,230
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
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
Common polygenic variation contributes to risk of schizophrenia and bipolar disorder
The International Schizophrenia Consortium (2009) · Nature · doi:10.1038/nature08185 · Cited by 4,821
Hindorff, L. A., Sethupathy, P., Junkins, H. A., Ramos, E. M., Mehta, J. P., Collins, F. S., & Manolio, T. A. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0903103106 · Cited by 4,013
Better Bootstrap Confidence Intervals
Efron, B. (1987) · Journal of the American Statistical Association · doi:10.1080/01621459.1987.10478410 · Cited by 3,462
The Wellcome Trust Case Control Consortium, U.K.
Mossman, K. (2008) · Scientific American · doi:10.1038/scientificamerican0108-42a · Cited by 2,714
Genome-wide association defines more than 30 distinct susceptibility loci for Crohn's disease
the NIDDK IBD Genetics Consortium, Barrett, J. C., the Belgian-French IBD Consortium, the Wellcome Trust Case Control Consortium, Hansoul, S., Nicolae, D. L., Cho, J. H., Duerr, R. H., Rioux, J. D., Brant, S. R., et al. (2008) · Nature Genetics · doi:10.1038/ng.175 · Cited by 2,593
Systematic meta-analyses of Alzheimer disease genetic association studies: the AlzGene database
Bertram, L., McQueen, M. B., Mullin, K., Blacker, D., & Tanzi, R. E. (2007) · Nature Genetics · doi:10.1038/ng1934 · Cited by 1,857
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Hohman, T. J., Bush, W. S., Jiang, L., Brown-Gentry, K. D., Torstenson, E. S., Dudek, S. M., Mukherjee, S., Naj, A., Kunkle, B. W., Ritchie, M. D., et al. (2016) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2015.10.031 · Cited by 52
Harris, S. E., Davies, G., Luciano, M., Payton, A., Fox, H. C., Haggarty, P., Ollier, W., Horan, M. A., Porteous, D. J., Starr, J. M., et al. (2014) · Journal of Alzheimer s Disease · doi:10.3233/jad-131058 · Cited by 49
Dand, N., Mucha, S., Tsoi, L. C., Mahil, S. K., Stuart, P. E., Arnold, A., Baurecht, H., Burden, A. D., Duffin, K. C., Chandran, V., et al. (2017) · Human Molecular Genetics · doi:10.1093/hmg/ddx328 · Cited by 54
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So, H., & Sham, P. C. (2017) · Scientific Reports · doi:10.1038/srep41262 · Cited by 49
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Feenstra, B., Geller, F., Krogh, C., Hollegaard, M. V., Gørtz, S., Boyd, H. A., Murray, J. C., HOUGAARD, D. M., & Melbye, M. (2012) · Nature Genetics · doi:10.1038/ng.1067 · Cited by 43
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Wenderfer, S. E., & Eldin, K. W. (2018) · Pediatric Clinics of North America · doi:10.1016/j.pcl.2018.08.007 · Cited by 43
Kharazmi, E., Scherer, D., Boekstegers, F., Liang, Q., Sundquist, K., Sundquist, J., Fallah, M., & Bermejo, J. L. (2023) · Gastroenterology · doi:10.1053/j.gastro.2023.03.227 · Cited by 43
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Qi, G., & Chatterjee, N. (2018) · PLoS Genetics · doi:10.1371/journal.pgen.1007549 · Cited by 38
So, H., & Sham, P. C. (2010) · PLoS Genetics · doi:10.1371/journal.pgen.1001230 · Cited by 39
Self-citationCruchaga, C., Chakraverty, S., Mayo, K., Vallania, F., Mitra, R. D., Faber, K. M., Williamson, J., Bird, T., Diaz-Arrastia, R. R., Foroud, T., et al. (2012) · PLoS ONE · doi:10.1371/annotation/c92e16da-7733-421d-b063-1db19488daa6 · Cited by 40
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Ke, X. (2012) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2012.05.020 · Cited by 40
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Yang, S., Hong, M., Oh, H., Low, H.-Q., Jung, S., Ahn, S., Kim, Y., Baek, J., Lee, C. H., Kim, E., et al. (2016) · Gastroenterology · doi:10.1053/j.gastro.2016.08.025 · Cited by 37
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Märtens, K., Hallin, J., Warringer, J., Liti, G., & Parts, L. (2016) · Nature Communications · doi:10.1038/ncomms11512 · Cited by 38
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Chen, H., Petty, L. E., Sha, J., Zhao, Y., Kuzma, A. B., Valladares, O., Bush, W. S., Naj, A. C., Gamazon, E. R., & Below, J. E. (2021) · Translational Psychiatry · doi:10.1038/s41398-021-01677-0 · Cited by 36
Zhang, J., Zhang, Y., Yang, J., Zhang, L., Sun, L., Pan, H., Hirankarn, N., Ying, D., Zeng, S., Lee, T. L., et al. (2013) · Human Molecular Genetics · doi:10.1093/hmg/ddt424 · Cited by 35
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Gjesing, A. P., Ekstrøm, C. T., Eiberg, H., Urhammer, S. A., Holst, J. J., Pedersen, O. B., & Hansen, T. F. (2012) · Diabetologia · doi:10.1007/s00125-012-2484-6 · Cited by 32
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Zhen, Q., Yang, Z., Wang, W., Li, B., Bai, M., Wu, J., Ge, H., Dong, Z., Shen, J., Tang, H., et al. (2019) · Journal of Investigative Dermatology · doi:10.1016/j.jid.2019.03.1157 · Cited by 31
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Wang, P., Qin, W., Wang, P., Huang, Y., Liu, Y., Zhang, R., Li, S., Yang, Q., Wang, X., Chen, F., et al. (2018) · Scientific Reports · doi:10.1038/s41598-018-21611-7 · Cited by 25
Ishikawa, T., Masuda, T., Hachiya, T., Dina, C., Simonet, F., Nagata, Y., Tanck, M. W. T., Sonehara, K., Glinge, C., Tadros, R., et al. (2024) · European Heart Journal · doi:10.1093/eurheartj/ehae251 · Cited by 24
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Zhang, B., Chen, M.-Y., Shen, Y.-J., Zhuo, X.-B., Gao, P. H., Zhou, F.-S., Liang, B., Zu, J., Zhang, Q., Suleman, S., et al. (2018) · Cancer Research · doi:10.1158/0008-5472.can-17-1721 · Cited by 21
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Gal, G., Goral, A., Murad, H., Gross, R., Pugachova, I., Barchana, M., Kohn, R., & Levav, I. (2012) · Schizophrenia Research · doi:10.1016/j.schres.2012.04.018 · Cited by 21
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Versmissen, J., Oosterveer, D. M., Yazdanpanah, M., Dehghan, A., Hólm, H., Erdman, J., Aulchenko, Y. S., Þorleifsson, G., Schunkert, H., Huijgen, R., et al. (2014) · European Journal of Human Genetics · doi:10.1038/ejhg.2014.101 · Cited by 17
Oliynyk, R. T. (2019) · PeerJ · doi:10.7717/peerj.7168 · Cited by 15
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So, H., Yip, B. H. K., & Sham, P. C. (2010) · PLoS ONE · doi:10.1371/journal.pone.0013898 · Cited by 15
Self-citationAlonso‐Perez, E., Suarez-Gestal, M., Calaza, M., Blanco, F. J., Suárez, A., Santos, M. J., Papasteriades, C. A., Carreira, P. E., Pullmann, R., Ordi‐Ros, J., et al. (2014) · Arthritis Research & Therapy · doi:10.1186/ar4585 · Cited by 15
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Self-citationCaliebe, A., Harder, M., Schuett, R., Krawczak, M., Nebel, A., & von Wurmb‐Schwark, N. (2015) · European Journal of Human Genetics · doi:10.1038/ejhg.2015.167 · Cited by 14
Liu, L., Yin, X., Wen, L., Yang, C., Sheng, Y., Lin, Y., Zhu, Z., Shen, C., Shi, Y., Zheng, Y., et al. (2016) · G3 Genes Genomes Genetics · doi:10.1534/g3.116.027326 · Cited by 14
Torres, D., Bermejo, J. L., Mesa, K. G., Gilbert, M. B., Briceño, I., Pohl‐Zeidler, S., Silos, R. G., Boekstegers, F., Plass, C., & Hamann, U. (2018) · International Journal of Cancer · doi:10.1002/ijc.32023 · Cited by 15
Defining the Genetic Architecture of Alzheimer's Disease: Where Next?
Sims, R., & Williams, J. H. (2015) · Neurodegenerative Diseases · doi:10.1159/000440841 · Cited by 13
Sušak, H., Serra, L., Demidov, G. M., Rabionet, R., Domènech, L., Bosio, M., Muyas, F., Estivill, X., Escaramís, G., & Ossowski, S. (2021) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1007784 · Cited by 13
Self-reported walking pace, polygenic risk scores and risk of coronary artery disease in UK biobank.
Zaccardi, F., Timmins, I., Goldney, J., Dudbridge, F., Dempsey, P., Davies, M., Khunti, K., & Yates, T. (2022) · NMCD. Nutrition Metabolism and Cardiovascular Diseases · doi:10.1016/j.numecd.2022.08.021 · Cited by 12
Genome-wide fine-mapping improves identification of causal variants
Wu, Y., Zheng, Z., Thibaut, L., Lin, T., Feng, Q., Cheng, H., Yengo, L., Goddard, M. E., Wray, N. R., Visscher, P. M., et al. (2026) · Nature Genetics · doi:10.1038/s41588-026-02549-3 · Cited by 23
Kitazawa, M., Ohnuma, T., Takebayashi, Y., Shibata, N., Baba, H., Ohi, K., Yasuda, Y., Nakamura, Y., Aleksić, B., Yoshimi, A., et al. (2012) · American Journal of Medical Genetics Part B Neuropsychiatric Genetics · doi:10.1002/ajmg.b.32049 · Cited by 11
Gim, J., Kim, W., Kwak, S. H., Choi, H., Park, C., Park, K. S., Kwon, S., Park, T., & Won, S. (2017) · Genetics · doi:10.1534/genetics.117.300283 · Cited by 12
Copy number variation of scavenger-receptor cysteine-rich domains within DMBT1 and Crohn’s disease
Polley, S., Prescott, N. J., Nimmo, E. R., Veal, C., Vind, I., Munkholm, P. S., Fode, P., Mansfield, J. C., Andersen, P. S., Satsangi, J. J., et al. (2016) · European Journal of Human Genetics · doi:10.1038/ejhg.2015.280 · Cited by 10
Hwang, L., Cuéllar-Partida, G., Yengo, L., Zeng, J., Toivonen, J., Arvas, M., Beaumont, R. N., Freathy, R. M., Moen, G.-H., Warrington, N. M., et al. (2024) · Nature Communications · doi:10.1038/s41467-024-53495-9 · Cited by 9
Nishino, J., Kochi, Y., Shigemizu, D., Kato, M., Ikari, K., Ochi, H., Noma, H., Matsui, K., Morizono, T., Boroevich, K. A., et al. (2018) · Frontiers in Genetics · doi:10.3389/fgene.2018.00115 · Cited by 11
Predictors of metabolic syndrome in first manic episode
Kesebir, S., Erdinç, B., & Tarhan, N. (2016) · Asian Journal of Psychiatry · doi:10.1016/j.ajp.2016.10.014 · Cited by 11
Svishcheva, G. R. (2019) · Scientific Reports · doi:10.1038/s41598-019-41827-5 · Cited by 10
Novo, I., López‐Cortegano, E., & Caballero, A. (2021) · Human Genetics · doi:10.1007/s00439-021-02308-w · Cited by 9
Assessment of research models for testing gene–environment interactions
Inselman, A. L., Hansen, D. K., Lee, H.-Y., Nakamura, N., Ning, B., Monteiro, J. P., Varma, V., & Kaput, J. (2011) · European Journal of Pharmacology · doi:10.1016/j.ejphar.2011.05.084 · Cited by 9
Lee, H., Oh, H., Yang, S., Baek, J., Jung, S., Hong, M., Kim, K. M., Shin, H. D., Kim, K. J., Park, S. H., et al. (2017) · Journal of Crohn s and Colitis · doi:10.1093/ecco-jcc/jjx023 · Cited by 9
MiRNA Profiles in Lymphoblastoid Cell Lines of Finnish Prostate Cancer Families
Fischer, D., Wahlfors, T., Mattila, H., Oja, H., Tammela, T. L. J., & Schleutker, J. (2015) · PLoS ONE · doi:10.1371/journal.pone.0127427 · Cited by 8
Epigenetics of Metabolic Syndrome as a Mood Disorder
Kesebir, S. (2018) · Journal of Clinical Medicine Research · doi:10.14740/jocmr3389w · Cited by 14
Diabetes mellitus, glycemic traits, and cerebrovascular disease: a Mendelian randomization studyPreprint
Georgakis, M. K., Harshfield, E. L., Malik, R., Franceschini, N., Langenberg, C., Wareham, N. J., Markus, H. S., & Dichgans, M. (2019) · medRxiv · doi:10.1101/2019.12.27.19015834 · Cited by 9
Metadata
- Authors
- So, H.-C., Gui, A. H. S., Cherny, S. S., & Sham, P. C.
- Affiliations
- University of Hong Kong (HK)
- Corresponding author
- Sham, Pak C.
- Venue
- Genetic Epidemiology
- Publisher
- Wiley
- Published
- 2011-03-03
- Volume
- 35
- Issue
- 5
- Pages
- 310-317
- ISSN
- 0741-0395 (ISSN-L)
- OpenAlex
- W2128416240
- Cited by
- 289
- References
- 32
- Citations by year
- 2026: 3 · 2025: 4 · 2024: 5 · 2023: 9 · 2022: 16 · 2021: 14 · 2020: 9 · 2019: 19 · 2018: 22 · 2017: 26 · 2016: 23 · 2015: 26 · 2014: 32 · 2013: 29 · 2012: 40
- FWCI
- 22.18
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Genetic Epidemiology (publishedVersion)
- PubMed (publishedVersion)
- The HKU Scholars Hub (University of Hong Kong) (submittedVersion)
- Funders
- Wellcome Trust
- Croucher Foundation
- 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
- missing heritability, complex diseases, single nucleotide polymorphisms, haplotypes, linkage disequilibrium, multilocus genotypes, genetic risk variants, Alzheimer's disease, bipolar disorder, breast cancer, coronary artery disease, Crohn's disease, prostate cancer, schizophrenia, systemic lupus erythematosus, type 1 diabetes, type 2 diabetes
- MeSH terms
- Alleles, Female, Genetic Markers, Genotype, Haplotypes, Humans, Male, Models, Genetic, Genetic Variation, Models, Statistical, Linkage Disequilibrium, Statistics, Nonparametric, Genetic Predisposition to Disease, Genome-Wide Association Study
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