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Shifting Paradigm of Association Studies: Value of Rare Single-Nucleotide Polymorphisms
Open accessAbstract
Currently, single-nucleotide polymorphisms (SNPs) with minor allele frequency (MAF) of >5% are preferentially used in case-control association studies of common human diseases. Recent technological developments enable inexpensive and accurate genotyping of a large number of SNPs in thousands of cases and controls, which can provide adequate statistical power to analyze SNPs with MAF <5%. Our purpose was to determine whether evaluating rare SNPs in case-control association studies could help identify causal SNPs for common diseases. We suggest that slightly deleterious SNPs (sdSNPs) subjected to weak purifying selection are major players in genetic control of susceptibility to common diseases. We compared the distribution of MAFs of synonymous SNPs with that of nonsynonymous SNPs (1) predicted to be benign, (2) predicted to be possibly damaging, and (3) predicted to be probably damaging by PolyPhen. Our sources of data were the International HapMap Project, ENCODE, and the SeattleSNPs project. We found that the MAF distribution of possibly and probably damaging SNPs was shifted toward rare SNPs compared with the MAF distribution of benign and synonymous SNPs that are not likely to be functional. We also found an inverse relationship between MAF and the proportion of nsSNPs predicted to be protein disturbing. On the basis of this relationship, we estimated the joint probability that a SNP is functional and would be detected as significant in a case-control study. Our analysis suggests that including rare SNPs in genotyping platforms will advance identification of causal SNPs in case-control association studies, particularly as sample sizes increase.
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“First, it has been argued that population phenomena, such as the recent expansion of the human population, are likely to have resulted in a large number of segregating, functionally-relevant, rare variants that mediate phenotypic variation.14, 15”
From Statistical analysis strategies for association studies involving rare variants (2010) · cites this paper as [14]
In the citing paper
“There are many reasons to believe that multiple rare variants, both within the same gene and across different genes, collectively influence the expression and prevalence of traits and diseases in the population at large.”
From Statistical analysis strategies for association studies involving rare variants (2010) · cites this paper as [14]
In the citing paper
“This strategy is highly problematic given, for example, the poor power that such statistical tests have to detect small rare variant frequency differences between diagnostic or phenotypic groups (figures 1A and 1B).14, 28, 29”
From Statistical analysis strategies for association studies involving rare variants (2010) · cites this paper as [14]
In the citing paper
“Irrespective of how one might define ‘rare variant’ (which, although we have adopted the convention <1% frequency, might range from <0.1% to <0.01% depending on the context13) it is essential to recognize that such variants likely contribute to phenotypic expression in conjunction with, or over-and-above, common variants.”
From Statistical analysis strategies for association studies involving rare variants (2010) · cites this paper as [14]
In the citing paper
“Association analyses involving rare variants are not as straightforward as analyses involving common variations since the power to detect an association between a single rare variant is low in even very large samples (Figure 1).14, 28, 29”
From Statistical analysis strategies for association studies involving rare variants (2010) · cites this paper as [14]
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Metadata
- Authors
- Gorlov, I. P., Gorlova, O. Y., Sunyaev, S. R., Spitz, M. R., & Amos, C. I.
- Affiliations
- The University of Texas MD Anderson Cancer Center (US)
- Brigham and Women's Hospital (US)
- Corresponding author
- Amos, Christopher I.
- Venue
- The American Journal of Human Genetics
- Publisher
- Elsevier BV
- Published
- 2008-01
- Volume
- 82
- Issue
- 1
- Pages
- 100-112
- ISSN
- 0002-9297 (ISSN-L)
- PMC
- PMC2253956
- OpenAlex
- W2097349182
- Cited by
- 338
- References
- 68
- Citations by year
- 2026: 2 · 2025: 3 · 2024: 9 · 2023: 9 · 2022: 7 · 2021: 10 · 2020: 16 · 2019: 10 · 2018: 7 · 2017: 10 · 2016: 15 · 2015: 17 · 2014: 28 · 2013: 27 · 2012: 41
- FWCI
- 24.19
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- The American Journal of Human Genetics (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Institutes of Health
- National Cancer Institute (P01CA034936, P01 CA 34936-14A1)
- National Institute of Environmental Health Sciences (ES-09912, R01ES009912)
- 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 › Forensic and Genetic Research
- Keywords
- minor allele frequency, case-control association, non-synonymous SNPs, synonymous SNPs, PolyPhen, purifying selection, disease susceptibility, genotyping platforms
- MeSH terms
- Gene Frequency, Genetics, Population, Humans, Genome, Human, Case-Control Studies, Genetic Predisposition to Disease, Mutation, Missense, Polymorphism, Single Nucleotide
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