Your browser doesn't support javascript.
loading
No large-effect low-frequency coding variation found for myocardial infarction.
Holmen, Oddgeir L; Zhang, He; Zhou, Wei; Schmidt, Ellen; Hovelson, Daniel H; Langhammer, Arnulf; Løchen, Maja-Lisa; Ganesh, Santhi K; Mathiesen, Ellisiv B; Vatten, Lars; Platou, Carl; Wilsgaard, Tom; Chen, Jin; Skorpen, Frank; Dalen, Håvard; Boehnke, Michael; Abecasis, Goncalo R; Njølstad, Inger; Hveem, Kristian; Willer, Cristen J.
Afiliação
  • Holmen OL; HUNT Research Centre, Department of Public Health and General Practice, Norwegian University of Science and Technology, 7600 Levanger, Norway St. Olav Hospital, Trondheim University Hospital, Trondheim, Norway.
  • Zhang H; Department of Internal Medicine, Division of Cardiology.
  • Zhou W; Department of Internal Medicine, Division of Cardiology.
  • Schmidt E; Department of Internal Medicine, Division of Cardiology, Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA.
  • Hovelson DH; Department of Internal Medicine, Division of Cardiology, Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA.
  • Langhammer A; HUNT Research Centre, Department of Public Health and General Practice, Norwegian University of Science and Technology, 7600 Levanger, Norway.
  • Løchen ML; Epidemiology of Chronic Diseases Research Group, Department of Community Medicine, Faculty of Health Sciences.
  • Ganesh SK; Department of Internal Medicine, Division of Cardiology.
  • Mathiesen EB; Brain and Circulation Research Group, Department of Clinical Medicine, Faculty of Health Sciences, UiT The Arctic University of Norway, 9037 Tromsø, Norway Department of Neurology and Neurophysiology, University Hospital of North Norway, 9037 Tromsø, Norway.
  • Vatten L; Department of Public Health.
  • Platou C; HUNT Research Centre, Department of Public Health and General Practice, Norwegian University of Science and Technology, 7600 Levanger, Norway.
  • Wilsgaard T; Epidemiology of Chronic Diseases Research Group, Department of Community Medicine, Faculty of Health Sciences.
  • Chen J; Department of Internal Medicine, Division of Cardiology.
  • Skorpen F; Department of Laboratory Medicine, Children's and Women's Health Faculty of Medicine.
  • Dalen H; Medical Imaging Laboratory for Innovative Future Healthcare, Lab and Department of Circulation and Medical Imaging, Norwegian University of Science and Technology, 7030 Trondheim, Norway Department of Medicine, Levanger Hospital, Nord-Trøndelag Health Trust, 7600 Levanger, Norway.
  • Boehnke M; Center for Statistical Genetics, Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA.
  • Abecasis GR; Center for Statistical Genetics, Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA.
  • Njølstad I; Epidemiology of Chronic Diseases Research Group, Department of Community Medicine, Faculty of Health Sciences.
  • Hveem K; HUNT Research Centre, Department of Public Health and General Practice, Norwegian University of Science and Technology, 7600 Levanger, Norway Department of Medicine, Levanger Hospital, Nord-Trøndelag Health Trust, 7600 Levanger, Norway.
  • Willer CJ; Department of Internal Medicine, Division of Cardiology, Department of Human Genetics, University of Michigan Medical School, Ann Arbor, MI 48109, USA Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA cristen@umich.edu.
Hum Mol Genet ; 23(17): 4721-8, 2014 Sep 01.
Article em En | MEDLINE | ID: mdl-24728188
ABSTRACT
Genome-wide association studies have identified variants, primarily common, that are associated with coronary artery disease or myocardial infarction (MI), but have not tested the majority of the low frequency and rare variation in the genome. We explored the hypothesis that previously untested low frequency (1-5% minor allele frequency) and rare (<1% minor allele frequency) coding variants are associated with MI. We genotyped 2906 MI cases and 6738 non-MI controls from Norway using the Illumina HumanExome Beadchip, allowing for direct genotyping of 85 972 polymorphic coding variants as well as 48 known GWAS SNPs. We followed-up 34 coding variants in an additional 2350 MI cases and 2318 controls from Norway. We evaluated exome array coverage in a subset of these samples using whole exome sequencing (N = 151). The exome array provided successful genotyping for an estimated 72.5% of Norwegian loss-of-function or missense variants with frequency >1% and 66.2% of variants <1% frequency observed more than once. Despite 80% power in the two-stage study (N = 14 312) to detect association with low-frequency variants with high effect sizes [odds ratio (OR) >1.86 and >1.36 for 1 and 5% frequency, respectively], we did not identify any novel genes or single variants that reached significance. This suggests that low-frequency coding variants with large effect sizes (OR >2) may not exist for MI. Larger sample sizes may identify coding variants with more moderate effects.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Variação Genética / Fases de Leitura Aberta / Predisposição Genética para Doença / Infarto do Miocárdio Tipo de estudo: Etiology_studies / Prognostic_studies / Risk_factors_studies Limite: Female / Humans / Male Idioma: En Ano de publicação: 2014 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Variação Genética / Fases de Leitura Aberta / Predisposição Genética para Doença / Infarto do Miocárdio Tipo de estudo: Etiology_studies / Prognostic_studies / Risk_factors_studies Limite: Female / Humans / Male Idioma: En Ano de publicação: 2014 Tipo de documento: Article