The DOI matches its Crossref record; 32 of the 32 references it cites were found in a registry or an index.
Distribution of allele frequencies and effect sizes and their interrelationships for common genetic susceptibility variants
Open accessAbstract
Recent discoveries of hundreds of common susceptibility SNPs from genome-wide association studies provide a unique opportunity to examine population genetic models for complex traits. In this report, we investigate distributions of various population genetic parameters and their interrelationships using estimates of allele frequencies and effect-size parameters for about 400 susceptibility SNPs across a spectrum of qualitative and quantitative traits. We calibrate our analysis by statistical power for detection of SNPs to account for overrepresentation of variants with larger effect sizes in currently known SNPs that are expected due to statistical power for discovery. Across all qualitative disease traits, minor alleles conferred “risk” more often than “protection.” Across all traits, an inverse relationship existed between “regression effects” and allele frequencies. Both of these trends were remarkably strong for type I diabetes, a trait that is most likely to be influenced by selection, but were modest for other traits such as human height or late-onset diseases such as type II diabetes and cancers. Across all traits, the estimated effect-size distribution suggested the existence of increasingly large numbers of susceptibility SNPs with decreasingly small effects. For most traits, the set of SNPs with intermediate minor allele frequencies (5–20%) contained an unusually small number of susceptibility loci and explained a relatively small fraction of heritability compared with what would be expected from the distribution of SNPs in the general population. These trends could have several implications for future studies of common and uncommon variants.
Overview
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
Verification
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?
In the citing paper
“analyses of the distribution of risk allele frequencies across 8 traits argues that if anything minor allele frequencies are skewed to be greater than 0.2, providing strong empirical evidence that rare alleles are not alone responsible53.”
From Rare and common variants: twenty arguments (2012) · cites this paper as [53]
In the citing paper
“No-one doubts that some fraction of the total risk for any complex disease is due to rare alleles, but these studies argue that it is not the majority.”
From Rare and common variants: twenty arguments (2012) · cites this paper as [53]
In the citing paper
“In several instances where SNP-wise GWAS has uncovered few loci, this approach has provided clear evidence for polygenic risk, but it must be recognized that the high variance in estimation of effects results in noisy scores that, although highly significant in the replication sample, only capture over an order of magnitude less of the variance and are far from predictive.”
From Rare and common variants: twenty arguments (2012) · cites this paper as [53]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
The genetical theory of natural selection
Fisher, R. A. (1930) · doi:10.5962/bhl.title.27468 · Cited by 17,617
The Neutral Theory of Molecular Evolution
Kimura, M. (1979) · Scientific American · doi:10.1038/scientificamerican1179-98 · Cited by 7,687
The Neutral Theory of Molecular Evolution
Kimura, M. (1983) · Cambridge University Press eBooks · doi:10.1017/cbo9780511623486 · Cited by 6,300
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
Common 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
A generalization of sampling without replacement from a finite universe
Horvitz, D. G., & Thompson, D. J. (1952) · Journal of the American Statistical Association · doi:10.1080/01621459.1952.10483446 · Cited by 4,293
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
A Generalization of Sampling Without Replacement From a Finite Universe
Horvitz, D. G., & Thompson, D. J. (1952) · Journal of the American Statistical Association · doi:10.2307/2280784 · Cited by 3,011
Franke, A., McGovern, D. P. B., Barrett, J. C., Wang, K., Radford-Smith, G. L., Ahmad, T., Lees, C. W., Balschun, T., Lee, J., Roberts, R., et al. (2010) · Nature Genetics · doi:10.1038/ng.717 · Cited by 2,520
Hundreds of variants clustered in genomic loci and biological pathways affect human height
Lango Allen, H., Estrada, K., Lettre, G., Berndt, S. I., Weedon, M. N., Rivadeneira, F., Willer, C. J., Jackson, A. U., Vedantam, S., Raychaudhuri, S., et al. (2010) · Nature · doi:10.1038/nature09410 · Cited by 1,945
Self-citationTwelve 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
The Type 1 Diabetes Genetics Consortium, Barrett, J. C., Clayton, D. G., Concannon, P., Akolkar, B., Cooper, J. D., Erlich, H. A., Julier, C., Morahan, G., Nerup, J., et al. (2009) · Nature Genetics · doi:10.1038/ng.381 · Cited by 1,746
Are Rare Variants Responsible for Susceptibility to Complex Diseases?
Pritchard, J. K. (2001) · The American Journal of Human Genetics · doi:10.1086/321272 · Cited by 1,197
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
THE POPULATION GENETICS OF ADAPTATION: THE DISTRIBUTION OF FACTORS FIXED DURING ADAPTIVE EVOLUTION
Orr, H. A. (1998) · Evolution · doi:10.1111/j.1558-5646.1998.tb01823.x · Cited by 896
Genome-wide association study identifies five susceptibility loci for glioma
Shete, S. S., Hosking, F. J., Robertson, L. B., Dobbins, S. E., Sanson, M., Malmer, B., Simon, M., Marie, Y., Boisselier, B., Delattre, J., et al. (2009) · Nature Genetics · doi:10.1038/ng.407 · Cited by 795
Genome-wide association study identifies five new breast cancer susceptibility loci
The Breast Cancer Susceptibility Collaboration (UK), Turnbull, C., Ahmed, S., Morrison, J., Pernet, D., Renwick, A., Maranian, M., Seal, S., Ghoussaini, M., Hines, S., et al. (2010) · Nature Genetics · doi:10.1038/ng.586 · Cited by 687
Park, J.-H., Wacholder, S., Gail, M. H., Peters, U., Jacobs, K. B., Chanock, S. J., & Chatterjee, N. (2010) · Nature Genetics · doi:10.1038/ng.610 · Cited by 678
Self-citationPetersen, G. M., Amundadottir, L. T., Fuchs, C. S., Kraft, P. L., Stolzenberg‐Solomon, R. Z., Jacobs, K. B., Arslan, A. A., Bueno-de-Mesquita, H. B., Gallinger, S., Gross, M. D., et al. (2010) · Nature Genetics · doi:10.1038/ng.522 · Cited by 598
Self-citationStudy, C. (2008) · Nature Genetics · doi:10.1038/ng.262 · Cited by 556
Epidemiologic studies utilizing surveys: accounting for the sampling design.
Korn, E. L., & Graubard, B. I. (1991) · American Journal of Public Health · doi:10.2105/ajph.81.9.1166 · Cited by 485
Rothman, N., García‐Closas, M., Chatterjee, N., Malats, N., Wu, X., Figueroa, J. D., Real, F. X., Berg, D. V. D., Matullo, G., Baris, D., et al. (2010) · Nature Genetics · doi:10.1038/ng.687 · Cited by 471
Self-citationEeles, R. A., Collaborators, T. U. P. S., Kote‐Jarai, Z., Olama, A. A. A., Giles, G. G., Guy, M., Severi, G., Muir, K. R., Hopper, J. L., Henderson, B. E., et al. (2009) · Nature Genetics · doi:10.1038/ng.450 · Cited by 417
Self-citationPaajanen, T. A., Oksala, N., Kuukasjärvi, P., & Karhunen, P. J. (2010) · European Heart Journal · doi:10.1093/eurheartj/ehq155 · Cited by 336
Eyre‐Walker, A. (2010) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0906182107 · Cited by 230
Lifestyle factors and primary glioma and meningioma tumours in the Million Women Study cohort
Collaborators, F. T. M. W. S., Benson, V. S., Pirie, K. L., Green, J., Casabonne, D., & Beral, V. (2008) · British Journal of Cancer · doi:10.1038/sj.bjc.6604445 · Cited by 199
Theories of adaptation: what they do and don?t say
Orr, H. A. (2005) · Genetica · doi:10.1007/s10709-004-2702-3 · Cited by 119
Theories of adaptation: what they do and don’t say
Orr, H. A. (2005) · Springer eBooks · doi:10.1007/1-4020-3836-4_2 · Cited by 110
Height, Body Mass Index, and Physical Activity in Relation to Glioma Risk
Moore, S. C., Rajaraman, P., Dubrow, R., Darefsky, A. S., Koebnick, C., Hollenbeck, A. R., Schatzkin, A. G., & Leitzmann, M. F. (2009) · Cancer Research · doi:10.1158/0008-5472.can-09-1669 · Cited by 105
The Distribution of Gene Frequencies in Populations of Polyploids
Wright, S. (1938) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.24.9.372 · Cited by 70
Estimating Odds Ratios in Genome Scans: An Approximate Conditional Likelihood Approach
Ghosh, A., Zou, F., & Wright, F. A. (2008) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2008.03.002 · Cited by 66
Tallness is associated with risk of testicular cancer: evidence for the nutrition hypothesis
for German Testicular Cancer Study Group, Dieckmann, K.-P., Hartmann, J. T., Claßen, J., Lüdde, R., Diederichs, M., & Pichlmeier, U. (2008) · British Journal of Cancer · doi:10.1038/sj.bjc.6604695 · Cited by 32
Flagged first, then by citations
Cited by
Sorted by citations
Rare and common variants: twenty arguments
Gibson, G. (2012) · Nature Reviews Genetics · doi:10.1038/nrg3118 · Cited by 1,278
The UK10K project identifies rare variants in health and disease
The UK10K Consortium, Writing group, Walter, K., Min, J. L., Huang, J., Crooks, L., Memari, Y., McCarthy, S., Perry, J. R. B., Xu, C., et al. (2015) · Nature · doi:10.1038/nature14962 · Cited by 1,040
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 719
Comprehensive genotyping of the USA national maize inbred seed bank
Romay, M. C., Millard, M. J., Glaubitz, J. C., Peiffer, J. A., Swarts, K., Casstevens, T. M., Elshire, R. J., Acharya, C. B., Mitchell, S. E., Flint-Garcia, S. A., et al. (2013) · Genome biology · doi:10.1186/gb-2013-14-6-r55 · Cited by 563
Diversity and scale: Genetic architecture of 2068 traits in the VA Million Veteran Program
Verma, A., Huffman, J. E., Rodriguez, A., Conery, M., Liu, M., Ho, Y.-L., Kim, Y., Heise, D. A., Guare, L., Panickan, V. A., et al. (2024) · Science · doi:10.1126/science.adj1182 · Cited by 463
Self-citation
Metadata
- Authors
- Park, J.-H., Gail, M. H., Weinberg, C. R., Carroll, R. J., Chung, C. C., Wang, Z., Chanock, S. J., Fraumeni, J. F., & Chatterjee, N.
- Affiliations
- National Institutes of Health (US)
- Texas A&M University (US)
- ORCID
- Venue
- Proceedings of the National Academy of Sciences
- Publisher
- National Academy of Sciences
- Published
- 2011-10-14
- Volume
- 108
- Issue
- 44
- Pages
- 18026-18031
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- PMC
- PMC3207674
- OpenAlex
- W2074498980
- Cited by
- 280
- References
- 31
- Citations by year
- 2026: 10 · 2025: 14 · 2024: 21 · 2023: 23 · 2022: 16 · 2021: 26 · 2020: 21 · 2019: 22 · 2018: 22 · 2017: 24 · 2016: 13 · 2015: 17 · 2014: 19 · 2013: 22 · 2012: 9
- FWCI
- 9.84
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Proceedings of the National Academy of Sciences (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- OakTrust (Texas A&M University Libraries) (submittedVersion)
- UTS ePRESS (University of Technology Sydney) (submittedVersion)
- Funders
- National Institutes of Health (5r37ca057030-23)
- National Cancer Institute ((R37-CA057030), U01CA057030, R27-CA057030, R01CA057030)
- 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 › Forensic and Genetic Research
- Keywords
- allele frequency distribution, effect size distribution, genetic risk variants, single nucleotide polymorphisms, statistical power, minor allele frequency, regression effect, type 1 diabetes, type 2 diabetes, human height, cancer susceptibility, heritability, complex traits, population genetics, natural selection
- MeSH terms
- Calibration, Gene Frequency, Humans, Genetic Variation, Polymorphism, Single Nucleotide
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
