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Association of Polygenic Risk Scores for Multiple Cancers in a Phenome-wide Study: Results from The Michigan Genomics Initiative.
Fritsche, Lars G; Gruber, Stephen B; Wu, Zhenke; Schmidt, Ellen M; Zawistowski, Matthew; Moser, Stephanie E; Blanc, Victoria M; Brummett, Chad M; Kheterpal, Sachin; Abecasis, Gonçalo R; Mukherjee, Bhramar.
Afiliação
  • Fritsche LG; Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA; Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA; K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Norw
  • Gruber SB; USC Norris Comprehensive Cancer Center, Los Angeles, CA 90033, USA.
  • Wu Z; Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA; Michigan Institute for Data Science, University of Michigan, Ann Arbor, MI 48109, USA.
  • Schmidt EM; Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA.
  • Zawistowski M; Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA; Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA.
  • Moser SE; Division of Pain Medicine, Department of Anesthesiology, University of Michigan Medical School, Ann Arbor, MI 48109, USA.
  • Blanc VM; Central Biorepository, University of Michigan Medical School, Ann Arbor, MI 48109, USA.
  • Brummett CM; Division of Pain Medicine, Department of Anesthesiology, University of Michigan Medical School, Ann Arbor, MI 48109, USA; Institute for Healthcare Policy and Innovation, University of Michigan, Ann Arbor, MI 48109, USA.
  • Kheterpal S; Division of Pain Medicine, Department of Anesthesiology, University of Michigan Medical School, Ann Arbor, MI 48109, USA; Institute for Healthcare Policy and Innovation, University of Michigan, Ann Arbor, MI 48109, USA.
  • Abecasis GR; Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA; Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA.
  • Mukherjee B; Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA; Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA; Michigan Institute for Data Science, University of Michigan, Ann Arbor, MI 48109, USA; Dep
Am J Hum Genet ; 102(6): 1048-1061, 2018 06 07.
Article em En | MEDLINE | ID: mdl-29779563
ABSTRACT
Health systems are stewards of patient electronic health record (EHR) data with extraordinarily rich depth and breadth, reflecting thousands of diagnoses and exposures. Measures of genomic variation integrated with EHRs offer a potential strategy to accurately stratify patients for risk profiling and discover new relationships between diagnoses and genomes. The objective of this study was to evaluate whether polygenic risk scores (PRS) for common cancers are associated with multiple phenotypes in a phenome-wide association study (PheWAS) conducted in 28,260 unrelated, genotyped patients of recent European ancestry who consented to participate in the Michigan Genomics Initiative, a longitudinal biorepository effort within Michigan Medicine. PRS for 12 cancer traits were calculated using summary statistics from the NHGRI-EBI catalog. A total of 1,711 synthetic case-control studies was used for PheWAS analyses. There were 13,490 (47.7%) patients with at least one cancer diagnosis in this study sample. PRS exhibited strong association for several cancer traits they were designed for, including female breast cancer, prostate cancer, melanoma, basal cell carcinoma, squamous cell carcinoma, and thyroid cancer. Phenome-wide significant associations were observed between PRS and many non-cancer diagnoses. To differentiate PRS associations driven by the primary trait from associations arising through shared genetic risk profiles, the idea of "exclusion PRS PheWAS" was introduced. Further analysis of temporal order of the diagnoses improved our understanding of these secondary associations. This comprehensive PheWAS used PRS instead of a single variant.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Herança Multifatorial / Genômica / Estudos de Associação Genética / Neoplasias Tipo de estudo: Diagnostic_studies / Etiology_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Female / Humans / Male / Middle aged Idioma: En Ano de publicação: 2018 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Herança Multifatorial / Genômica / Estudos de Associação Genética / Neoplasias Tipo de estudo: Diagnostic_studies / Etiology_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Female / Humans / Male / Middle aged Idioma: En Ano de publicação: 2018 Tipo de documento: Article