Difference between revisions of "GIANT consortium"

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= [[Data Release]] =
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= Data Release =
  
We are releasing the summary data from our 2010 meta-analyses of GWA data, in order to enable other researchers to examine particular variants or loci for their evidence of association with anthropometric traits. The files include p-values and direction of effect at over 2 million directly genotyped or imputed single nucleotide polymorphisms (SNPs). To prevent the possibility of identification of individuals from these summary results, we are not releasing allele frequency data from our samples. A manuscript describing the rationale for releasing association data but not frequency data is in preparation.
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We are releasing the summary data from our meta-analyses of GWAS data, in order to enable other researchers to examine particular variants or loci for their evidence of association with anthropometric traits. The files include p-values and direction of effect at over 2 million directly genotyped or imputed single nucleotide polymorphisms (SNPs). To prevent the possibility of identification of individuals from these summary results, we are not releasing allele frequency data from our samples.
  
 
=== [[GIANT consortium data files|Click here to access the '''Summarized Genome-Wide Meta-analysis data files]]''' ===
 
=== [[GIANT consortium data files|Click here to access the '''Summarized Genome-Wide Meta-analysis data files]]''' ===
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= Selected Recent Publications =
 
= Selected Recent Publications =
  
*Locke AE*, Kahali B*, Berndt SI*, Justice AE*, Pers TH*, Day FR, Powell C, Vedantam S, Buchkovich ML, Yang J, Croteau-Chonka DC, Esko T et al. (2015) Genetic studies of body mass index yield new insights for obesity biology. Nature In press.  
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*[https://pubmed.ncbi.nlm.nih.gov/36224396/ Yengo L, Vedantam S, Marouli E, et al.] (2022). A saturated map of common genetic variants associated with human height. Nature <strong>610</strong>, 704-712.
  
*Shungin D*, Winkler TW*, Croteau-Chonka DC*, Ferreira T*, Locke AE*, Magi R*, Strawbridge R, Pers TH, Fischer K, Justice AE, Workalemahu T, Wu JM, et al. (2015) New genetic loci link adipocyte and insulin biology to body fat distribution. Nature In press.
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*[https://https://pubmed.ncbi.nlm.nih.gov/30239722/ Pulit SL et al.] (2019). Meta-analysis of genome-wide association studies for body fat distribution in 694,649 individuals of European ancestry. Nature <strong>28</strong>, 166-174.
  
*http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&amp;db=PubMed&amp;dopt=Citation&amp;list_uids=25282103 Wood AR, Esko T, Yang J, Vedantam S, Pers TH, Gustafsson S et al.] (2014). Defining the role of common variation in the genomic and biological architecture of adult human height (2014). Nature Genetics. <strong>46</strong>, 1173-86.
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*[https://pubmed.ncbi.nlm.nih.gov/30124842/ Yengo L, Sidorenko J, Kemper KE, Zheng Z, Wood AR, Weedon MN, Frayling TM, Hirschhorn J, Yang J, Visscher PM; GIANT Consortium] (2018). Meta-analysis of genome-wide association studies for height and body mass index in ∼700000 individuals of European ancestry. Hum  Mol Genet <strong>27</strong>, 3641-3649.
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*[https://pubmed.ncbi.nlm.nih.gov/27876822/ Ried JS et al.] (2016). A principal component meta-analysis on multiple anthropometric traits identifies novel loci for body shape. Nature Commun <strong>23</strong>, 13357.
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*[https://www.ncbi.nlm.nih.gov/pubmed/25673413 Locke AE, Kahali B, Berndt SI, Justice AE, Pers TH, Day FR, Powell C, Vedantam S, Buchkovich ML, Yang J, Croteau-Chonka DC, Esko T et al.] (2015). Genetic studies of body mass index yield new insights for obesity biology. Nature <strong>518</strong>, 197-206.
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*[https://www.ncbi.nlm.nih.gov/pubmed/25673412 Shungin D, Winkler TW, Croteau-Chonka DC, Ferreira T, Locke AE, Magi R, Strawbridge R, Pers TH, Fischer K, Justice AE, Workalemahu T, Wu JM, et al.] (2015). New genetic loci link adipose and insulin biology to body fat distribution. Nature <strong>518</strong>, 187-196.
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*[http://www.ncbi.nlm.nih.gov/pubmed/25282103?dopt=Citation Wood AR, Esko T, Yang J, Vedantam S, Pers TH, Gustafsson S, Chu AY, Estrada K, Luan J, Kutalik Z, et al.] (2014). Defining the role of common variation in the genomic and biological architecture of adult human height (2014). Nature Genetics <strong>46</strong>, 1173-86.
  
 
*[http://www.ncbi.nlm.nih.gov/pubmed/23563607?dopt=Citation Berndt SI, Gustafsson S, Mägi R, Ganna A, Wheeler E, Feitosa MF, Justice AE, Monda KL, Croteau-Chonka DC, Day FR, et al.] (2013). Genome-wide meta-analysis identifies 11 new loci for anthropometric traits and provides insights into genetic architecture. Nature Genetics <strong>45</strong>, 501-512.
 
*[http://www.ncbi.nlm.nih.gov/pubmed/23563607?dopt=Citation Berndt SI, Gustafsson S, Mägi R, Ganna A, Wheeler E, Feitosa MF, Justice AE, Monda KL, Croteau-Chonka DC, Day FR, et al.] (2013). Genome-wide meta-analysis identifies 11 new loci for anthropometric traits and provides insights into genetic architecture. Nature Genetics <strong>45</strong>, 501-512.

Latest revision as of 16:28, 20 January 2024

GIANT: Genetic Investigation of ANthropometric Traits

The Genetic Investigation of ANthropometric Traits (GIANT) consortium is an international collaboration that seeks to identify genetic loci that modulate human body size and shape, including height and measures of obesity. The GIANT consortium is a collaboration between investigators from many different groups, institutions, countries, and studies, and the results represent their combined efforts. The primary approach has been meta-analysis of genome-wide association data and other large-scale genetic data sets. Anthropometric traits that have been studied by GIANT include body mass index (BMI), height, and traits related to waist circumference (such as waist-hip ratio adjusted for BMI, or WHRadjBMI). Thus far, the GIANT consortium has identified common genetic variants at hundreds of loci that are associated with anthropometric traits.


Data Release

We are releasing the summary data from our meta-analyses of GWAS data, in order to enable other researchers to examine particular variants or loci for their evidence of association with anthropometric traits. The files include p-values and direction of effect at over 2 million directly genotyped or imputed single nucleotide polymorphisms (SNPs). To prevent the possibility of identification of individuals from these summary results, we are not releasing allele frequency data from our samples.

Click here to access the Summarized Genome-Wide Meta-analysis data files

Click here to create regional association plots from GIANT data using LocusZoom

Then select "Plot Using Published GWAS Results"


Selected Recent Publications

  • Pulit SL et al. (2019). Meta-analysis of genome-wide association studies for body fat distribution in 694,649 individuals of European ancestry. Nature 28, 166-174.
  • Ried JS et al. (2016). A principal component meta-analysis on multiple anthropometric traits identifies novel loci for body shape. Nature Commun 23, 13357.

Participating Cohorts and Research Groups

A growing list of collaborating cohorts and groups may be found here.