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Searching for missing heritability: Designing rare variant association studies
Open accessAbstract
Significance: Discovering the genetic basis of common diseases, such as diabetes, heart disease, and schizophrenia, is a key goal in biomedicine. Genomic studies have revealed thousands of common genetic variants underlying disease, but these variants explain only a portion of the heritability. Rare variants are also likely to play an important role, but few examples are known thus far, and initial discovery efforts with small sample sizes have had only limited success. In this paper, we describe an analytical framework for the design of rare variant association studies of disease. It provides guidance with respect to sample size, as well as the roles of selection, disruptive and missense alleles, gene-specific allele frequency thresholds, isolated populations, gene sets, and coding vs. noncoding regions.
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“However, the analysis of URVs has had limited success in delivering individual gene discovery in schizophrenia because of power limitations, with only a single gene, SETD1A, identified as robustly associated 13,18 .”
From Exome sequencing identifies rare coding variants in 10 genes which confer substantial risk for schizophrenia (2020) · cites this paper as [13]
In the citing paper
“The most natural grouping for rare variants is within a gene, based on predicted functional consequence or evidence for deleteriousness 13,14 .”
From Exome sequencing identifies rare coding variants in 10 genes which confer substantial risk for schizophrenia (2020) · cites this paper as [13]
In the citing paper
“Theory predicts that the forces of natural selection will tend to keep large effect risk variants at much lower frequencies in the population, especially in disorders such as schizophrenia that are associated with reduced fecundity 13 .”
From Exome sequencing identifies rare coding variants in 10 genes which confer substantial risk for schizophrenia (2020) · cites this paper as [13]
In the citing paper
“Because individuals affected with schizophrenia have fewer offspring, purifying selection is expected to prevent high-risk alleles from reaching even modest allele frequencies6.”
From Increased burden of ultra-rare protein-altering variants among 4,877 individuals with schizophrenia (2016) · cites this paper as [6]
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A method and server for predicting damaging missense mutations.
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Self-citationFinding 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
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
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
Biological, clinical and population relevance of 95 loci for blood lipids
Teslovich, T. M., Musunuru, K., Smith, A. V., Edmondson, A. C., Stylianou, I. M., Koseki, M., Pirruccello, J. P., Ripatti, S., Chasman, D. I., Willer, C. J., et al. (2010) · Nature · doi:10.1038/nature09270 · Cited by 3,487
Self-citationSequence Variations in PCSK9, Low LDL, and Protection against Coronary Heart Disease
Cohen, J. C., Boerwinkle, E., Mosley, T. H., & Hobbs, H. H. (2006) · New England Journal of Medicine · doi:10.1056/nejmoa054013 · Cited by 3,181
THE NUMBER OF ALLELES THAT CAN BE MAINTAINED IN A FINITE POPULATION
Kimura, M., & Crow, J. F. (1964) · Genetics · doi:10.1093/genetics/49.4.725 · Cited by 2,621
Rare-Variant Association Testing for Sequencing Data with the Sequence Kernel Association Test
Wu, M. C., Lee, S., Cai, T., Li, Y., Boehnke, M., & Lin, X. (2011) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2011.05.029 · Cited by 2,373
Sporadic autism exomes reveal a highly interconnected protein network of de novo mutations
O’Roak, B. J., Vives, L., Girirajan, S., Karakoc, E., Krumm, N., Coe, B. P., Levy, R., Ko, A., Lee, C., Smith, J. D., et al. (2012) · Nature · doi:10.1038/nature10989 · Cited by 2,165 · cited 2×
“For example, CHD8 was associated with autism with mental retardation (prevalence < 1/300) (52) based on the observation of de novo disruptive mutations in 3 of 1,078 cases (53, 54).”
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The Ensembl Variant Effect Predictor
McLaren, W., Gil, L., Hunt, S. E., Riat, H. S., Ritchie, G. R. S., Thormann, A., Flicek, P., & Cunningham, F. (2016) · Genome Biology · doi:10.1186/s13059-016-0974-4 · Cited by 8,099
FinnGen provides genetic insights from a well-phenotyped isolated population
Kurki, M. I., Karjalainen, J., Palta, P., Sipilä, T. P., Kristiansson, K., Donner, K. M., Reeve, M. P., Laivuori, H., Aavikko, M., Kaunisto, M. A., et al. (2023) · Nature · doi:10.1038/s41586-022-05473-8 · Cited by 4,233
Self-citationGenetics of diabetes mellitus and diabetes complications
Cole, J. B., & Florez, J. C. (2020) · Nature Reviews Nephrology · doi:10.1038/s41581-020-0278-5 · Cited by 1,797
Fritsche, L. G., Igl, W., Bailey, J. N. C., Grassmann, F., Sengupta, S., Bragg-Gresham, J. L., Burdon, K. P., Hebbring, S. J., Wen, C., Gorski, M., et al. (2016) · Nature Genetics · doi:10.1038/ng.3448 · Cited by 1,544
Guidelines for investigating causality of sequence variants in human disease
MacArthur, D. G., Manolio, T. A., Dimmock, D. P., Rehm, H. L., Shendure, J., Abecasis, G. R., Adams, D. R., Altman, R. B., Antonarakis, S. E., Ashley, E. A., et al. (2014) · Nature · doi:10.1038/nature13127 · Cited by 1,224
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Metadata
- Authors
- 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.
- Affiliations
- Broad Institute (US)
- ORCID
- Venue
- Proceedings of the National Academy of Sciences
- Publisher
- National Academy of Sciences
- Published
- 2014-01-17
- Volume
- 111
- Issue
- 4
- Pages
- E455-64
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- PMC
- PMC3910587
- OpenAlex
- W1986818660
- Cited by
- 635
- References
- 65
- Citations by year
- 2026: 11 · 2025: 18 · 2024: 36 · 2023: 40 · 2022: 35 · 2021: 64 · 2020: 41 · 2019: 59 · 2018: 52 · 2017: 71 · 2016: 86 · 2015: 70 · 2014: 48
- FWCI
- 59.70
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Proceedings of the National Academy of Sciences (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- DSpace@MIT (Massachusetts Institute of Technology) (submittedVersion, cc-by-nc)
- Funders
- National Human Genome Research Institute (U54HG003067)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genomics and Rare Diseases
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Mapping and Diversity in Plants and Animals
- Keywords
- missing heritability, research design, sample size, isolated populations, gene set analysis, de novo mutations, selection coefficients, replication
- MeSH terms
- Gene Frequency, Humans, Mutation, Genetic Variation, Genetic Predisposition to Disease, Genome-Wide Association Study
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