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GWASeq: targeted re-sequencing follow up to GWAS.
Salomon, Matthew P; Li, Wai Lok Sibon; Edlund, Christopher K; Morrison, John; Fortini, Barbara K; Win, Aung Ko; Conti, David V; Thomas, Duncan C; Duggan, David; Buchanan, Daniel D; Jenkins, Mark A; Hopper, John L; Gallinger, Steven; Le Marchand, Loïc; Newcomb, Polly A; Casey, Graham; Marjoram, Paul.
Afiliação
  • Salomon MP; Department of Preventive Medicine, Keck School of Medicine of the University of Southern California, Los Angeles, CA, USA. Matthew.Salomon@providence.org.
  • Li WL; Department of Molecular Oncology, John Wayne Cancer Institute at Providence Saint John's Health Center, Santa Monica, CA, USA. Matthew.Salomon@providence.org.
  • Edlund CK; Department of Preventive Medicine, Keck School of Medicine of the University of Southern California, Los Angeles, CA, USA. sibon.li@gmail.com.
  • Morrison J; Department of Preventive Medicine, Keck School of Medicine of the University of Southern California, Los Angeles, CA, USA. cedlund@usc.edu.
  • Fortini BK; Department of Preventive Medicine, Keck School of Medicine of the University of Southern California, Los Angeles, CA, USA. jmorr@usc.edu.
  • Win AK; Department of Preventive Medicine, Keck School of Medicine of the University of Southern California, Los Angeles, CA, USA. fortini@usc.edu.
  • Conti DV; Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, Melbourne, VIC, Australia. awin@unimelb.edu.au.
  • Thomas DC; Department of Preventive Medicine, Keck School of Medicine of the University of Southern California, Los Angeles, CA, USA. dconti@med.usc.edu.
  • Duggan D; Department of Preventive Medicine, Keck School of Medicine of the University of Southern California, Los Angeles, CA, USA. dthomas@usc.edu.
  • Buchanan DD; Translational Genomics Research Institute, Phoenix, AZ, USA. dduggan@tgen.org.
  • Jenkins MA; Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, Melbourne, VIC, Australia. daniel.buchanan@unimelb.edu.au.
  • Hopper JL; Oncogenomics Group, Genetic Epidemiology Laboratory, Department of Pathology, The University of Melbourne, Parkville, Melbourne, VIC, Australia. daniel.buchanan@unimelb.edu.au.
  • Gallinger S; Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, Melbourne, VIC, Australia. m.jenkins@unimelb.edu.au.
  • Le Marchand L; Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, Melbourne, VIC, Australia. j.hopper@unimelb.edu.au.
  • Newcomb PA; Samuel Lunenfeld Research Institute, Mount Sinai Hospital, Toronto, ON, Canada. steven.gallinger@uhn.ca.
  • Casey G; University of Hawaii Cancer Center, Honolulu, HI, USA. loic@cc.hawaii.edu.
  • Marjoram P; Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA. pnewcomb@fhcrc.org.
BMC Genomics ; 17: 176, 2016 Mar 03.
Article em En | MEDLINE | ID: mdl-26940994
ABSTRACT

BACKGROUND:

For the last decade the conceptual framework of the Genome-Wide Association Study (GWAS) has dominated the investigation of human disease and other complex traits. While GWAS have been successful in identifying a large number of variants associated with various phenotypes, the overall amount of heritability explained by these variants remains small. This raises the question of how best to follow up on a GWAS, localize causal variants accounting for GWAS hits, and as a consequence explain more of the so-called "missing" heritability. Advances in high throughput sequencing technologies now allow for the efficient and cost-effective collection of vast amounts of fine-scale genomic data to complement GWAS.

RESULTS:

We investigate these issues using a colon cancer dataset. After QC, our data consisted of 1993 cases, 899 controls. Using marginal tests of associations, we identify 10 variants distributed among six targeted regions that are significantly associated with colorectal cancer, with eight of the variants being novel to this study. Additionally, we perform so-called 'SNP-set' tests of association and identify two sets of variants that implicate both common and rare variants in the etiology of colorectal cancer.

CONCLUSIONS:

Here we present a large-scale targeted re-sequencing resource focusing on genomic regions implicated in colorectal cancer susceptibility previously identified in several GWAS, which aims to 1) provide fine-scale targeted sequencing data for fine-mapping and 2) provide data resources to address methodological questions regarding the design of sequencing-based follow-up studies to GWAS. Additionally, we show that this strategy successfully identifies novel variants associated with colorectal cancer susceptibility and can implicate both common and rare variants.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Análise de Sequência de DNA / Estudo de Associação Genômica Ampla / Sequenciamento de Nucleotídeos em Larga Escala Tipo de estudo: Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Ano de publicação: 2016 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Análise de Sequência de DNA / Estudo de Associação Genômica Ampla / Sequenciamento de Nucleotídeos em Larga Escala Tipo de estudo: Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Ano de publicação: 2016 Tipo de documento: Article