scispace - formally typeset
Search or ask a question
Topic

Single-nucleotide polymorphism

About: Single-nucleotide polymorphism is a research topic. Over the lifetime, 40159 publications have been published within this topic receiving 1197524 citations. The topic is also known as: single nucleotide variation & single nucleotide polymorphism.


Papers
More filters
Journal ArticleDOI
Paul Burton1, David Clayton2, Lon R. Cardon, Nicholas John Craddock3  +192 moreInstitutions (4)
07 Jun 2007-Nature
TL;DR: This study has demonstrated that careful use of a shared control group represents a safe and effective approach to GWA analyses of multiple disease phenotypes; generated a genome-wide genotype database for future studies of common diseases in the British population; and shown that, provided individuals with non-European ancestry are excluded, the extent of population stratification in theBritish population is generally modest.
Abstract: There is increasing evidence that genome-wide association ( GWA) studies represent a powerful approach to the identification of genes involved in common human diseases. We describe a joint GWA study ( using the Affymetrix GeneChip 500K Mapping Array Set) undertaken in the British population, which has examined similar to 2,000 individuals for each of 7 major diseases and a shared set of similar to 3,000 controls. Case-control comparisons identified 24 independent association signals at P < 5 X 10(-7): 1 in bipolar disorder, 1 in coronary artery disease, 9 in Crohn's disease, 3 in rheumatoid arthritis, 7 in type 1 diabetes and 3 in type 2 diabetes. On the basis of prior findings and replication studies thus-far completed, almost all of these signals reflect genuine susceptibility effects. We observed association at many previously identified loci, and found compelling evidence that some loci confer risk for more than one of the diseases studied. Across all diseases, we identified a large number of further signals ( including 58 loci with single-point P values between 10(-5) and 5 X 10(-7)) likely to yield additional susceptibility loci. The importance of appropriately large samples was confirmed by the modest effect sizes observed at most loci identified. This study thus represents a thorough validation of the GWA approach. It has also demonstrated that careful use of a shared control group represents a safe and effective approach to GWA analyses of multiple disease phenotypes; has generated a genome-wide genotype database for future studies of common diseases in the British population; and shown that, provided individuals with non-European ancestry are excluded, the extent of population stratification in the British population is generally modest. Our findings offer new avenues for exploring the pathophysiology of these important disorders. We anticipate that our data, results and software, which will be widely available to other investigators, will provide a powerful resource for human genetics research.

9,244 citations

Journal ArticleDOI
18 Oct 2007-Nature
TL;DR: The Phase II HapMap is described, which characterizes over 3.1 million human single nucleotide polymorphisms genotyped in 270 individuals from four geographically diverse populations and includes 25–35% of common SNP variation in the populations surveyed, and increased differentiation at non-synonymous, compared to synonymous, SNPs is demonstrated.
Abstract: We describe the Phase II HapMap, which characterizes over 3.1 million human single nucleotide polymorphisms (SNPs) genotyped in 270 individuals from four geographically diverse populations and includes 25-35% of common SNP variation in the populations surveyed. The map is estimated to capture untyped common variation with an average maximum r2 of between 0.9 and 0.96 depending on population. We demonstrate that the current generation of commercial genome-wide genotyping products captures common Phase II SNPs with an average maximum r2 of up to 0.8 in African and up to 0.95 in non-African populations, and that potential gains in power in association studies can be obtained through imputation. These data also reveal novel aspects of the structure of linkage disequilibrium. We show that 10-30% of pairs of individuals within a population share at least one region of extended genetic identity arising from recent ancestry and that up to 1% of all common variants are untaggable, primarily because they lie within recombination hotspots. We show that recombination rates vary systematically around genes and between genes of different function. Finally, we demonstrate increased differentiation at non-synonymous, compared to synonymous, SNPs, resulting from systematic differences in the strength or efficacy of natural selection between populations.

4,565 citations

Journal ArticleDOI
TL;DR: An online catalog of SNP-trait associations from published genome-wide association studies for use in investigating genomic characteristics of trait/disease-associated SNPs (TASs) is developed, well-suited to guide future investigations of the role of common variants in complex disease etiology.
Abstract: We have developed an online catalog of SNP-trait associations from published genome-wide association studies for use in investigating genomic characteristics of trait/disease-associated SNPs (TASs). Reported TASs were common [median risk allele frequency 36%, interquartile range (IQR) 21%−53%] and were associated with modest effect sizes [median odds ratio (OR) 1.33, IQR 1.20–1.61]. Among 20 genomic annotation sets, reported TASs were significantly overrepresented only in nonsynonymous sites [OR = 3.9 (2.2−7.0), p = 3.5 × 10−7] and 5kb-promoter regions [OR = 2.3 (1.5−3.6), p = 3 × 10−4] compared to SNPs randomly selected from genotyping arrays. Although 88% of TASs were intronic (45%) or intergenic (43%), TASs were not overrepresented in introns and were significantly depleted in intergenic regions [OR = 0.44 (0.34−0.58), p = 2.0 × 10−9]. Only slightly more TASs than expected by chance were predicted to be in regions under positive selection [OR = 1.3 (0.8−2.1), p = 0.2]. This new online resource, together with bioinformatic predictions of the underlying functionality at trait/disease-associated loci, is well-suited to guide future investigations of the role of common variants in complex disease etiology.

4,041 citations

Journal ArticleDOI
TL;DR: In addition to the APOE locus (encoding apolipoprotein E), 19 loci reached genome-wide significance (P < 5 × 10−8) in the combined stage 1 and stage 2 analysis, of which 11 are newly associated with Alzheimer's disease.
Abstract: Eleven susceptibility loci for late-onset Alzheimer's disease (LOAD) were identified by previous studies; however, a large portion of the genetic risk for this disease remains unexplained. We conducted a large, two-stage meta-analysis of genome-wide association studies (GWAS) in individuals of European ancestry. In stage 1, we used genotyped and imputed data (7,055,881 SNPs) to perform meta-analysis on 4 previously published GWAS data sets consisting of 17,008 Alzheimer's disease cases and 37,154 controls. In stage 2, 11,632 SNPs were genotyped and tested for association in an independent set of 8,572 Alzheimer's disease cases and 11,312 controls. In addition to the APOE locus (encoding apolipoprotein E), 19 loci reached genome-wide significance (P < 5 × 10−8) in the combined stage 1 and stage 2 analysis, of which 11 are newly associated with Alzheimer's disease.

3,726 citations

Journal ArticleDOI
Denise Harold1, Richard Abraham2, Paul Hollingworth2, Rebecca Sims2, Amy Gerrish2, Marian L. Hamshere3, Jaspreet Singh Pahwa2, Valentina Moskvina2, Kimberley Dowzell2, Amy L. Williams2, Nicola L. Jones2, Charlene Thomas2, Alexandra Stretton2, Angharad R. Morgan2, Simon Lovestone4, John Powell5, Petroula Proitsi5, Michelle K. Lupton5, Carol Brayne6, David C. Rubinsztein7, Michael Gill6, Brian A. Lawlor6, Aoibhinn Lynch6, Kevin Morgan8, Kristelle Brown8, Peter Passmore9, David Craig9, Bernadette McGuinness9, Stephen Todd9, Clive Holmes10, David M. A. Mann11, A. David Smith12, Seth Love3, Patrick G. Kehoe3, John Hardy, Simon Mead13, Nick C. Fox13, Martin N. Rossor13, John Collinge13, Wolfgang Maier14, Frank Jessen14, Britta Schürmann14, Hendrik van den Bussche15, Isabella Heuser16, Johannes Kornhuber17, Jens Wiltfang18, Martin Dichgans19, Lutz Frölich20, Harald Hampel21, Harald Hampel19, Michael Hüll22, Dan Rujescu19, Alison Goate23, John S. K. Kauwe24, Carlos Cruchaga23, Petra Nowotny23, John C. Morris23, Kevin Mayo23, Kristel Sleegers25, Karolien Bettens25, Sebastiaan Engelborghs25, Peter Paul De Deyn25, Christine Van Broeckhoven25, Gill Livingston26, Nicholas Bass26, Hugh Gurling26, Andrew McQuillin26, Rhian Gwilliam27, Panagiotis Deloukas27, Ammar Al-Chalabi28, Christopher Shaw28, Magda Tsolaki29, Andrew B. Singleton30, Rita Guerreiro30, Thomas W. Mühleisen14, Markus M. Nöthen14, Susanne Moebus18, Karl-Heinz Jöckel18, Norman Klopp, H-Erich Wichmann19, Minerva M. Carrasquillo31, V. Shane Pankratz31, Steven G. Younkin31, Peter Holmans2, Michael Conlon O'Donovan2, Michael John Owen2, Julie Williams2 
TL;DR: A two-stage genome-wide association study of Alzheimer's disease involving over 16,000 individuals, the most powerful AD GWAS to date, produced compelling evidence for association with Alzheimer's Disease in the combined dataset.
Abstract: We undertook a two-stage genome-wide association study (GWAS) of Alzheimer's disease (AD) involving over 16,000 individuals, the most powerful AD GWAS to date. In stage 1 (3,941 cases and 7,848 controls), we replicated the established association with the apolipoprotein E (APOE) locus (most significant SNP, rs2075650, P = 1.8 10-157) and observed genome-wide significant association with SNPs at two loci not previously associated with the disease: at the CLU (also known as APOJ) gene (rs11136000, P = 1.4 10-9) and 5' to the PICALM gene (rs3851179, P = 1.9 10-8). These associations were replicated in stage 2 (2,023 cases and 2,340 controls), producing compelling evidence for association with Alzheimer's disease in the combined dataset (rs11136000, P = 8.5 10-10, odds ratio = 0.86; rs3851179, P = 1.3 10-9, odds ratio = 0.86).

2,956 citations


Network Information
Related Topics (5)
Gene
211.7K papers, 10.3M citations
92% related
Gene expression
113.3K papers, 5.5M citations
90% related
Regulation of gene expression
85.4K papers, 5.8M citations
86% related
Transcription factor
82.8K papers, 5.4M citations
85% related
Signal transduction
122.6K papers, 8.2M citations
84% related
Performance
Metrics
No. of papers in the topic in previous years
YearPapers
20241
20233,206
20225,744
20211,693
20201,834
20191,914