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Functional informed genome-wide interaction analysis of body mass index, diabetes and colorectal cancer risk.
Xia, Zhiyu; Su, Yu-Ru; Petersen, Paneen; Qi, Lihong; Kim, Andre E; Figueiredo, Jane C; Lin, Yi; Nan, Hongmei; Sakoda, Lori C; Albanes, Demetrius; Berndt, Sonja I; Bézieau, Stéphane; Bien, Stephanie; Buchanan, Daniel D; Casey, Graham; Chan, Andrew T; Conti, David V; Drew, David A; Gallinger, Steven J; Gauderman, W James; Giles, Graham G; Gruber, Stephen B; Gunter, Marc J; Hoffmeister, Michael; Jenkins, Mark A; Joshi, Amit D; Le Marchand, Loic; Lewinger, Juan P; Li, Li; Lindor, Noralane M; Moreno, Victor; Murphy, Neil; Nassir, Rami; Newcomb, Polly A; Ogino, Shuji; Rennert, Gad; Song, Mingyang; Wang, Xiaoliang; Wolk, Alicja; Woods, Michael O; Brenner, Hermann; White, Emily; Slattery, Martha L; Giovannucci, Edward L; Chang-Claude, Jenny; Pharoah, Paul D P; Hsu, Li; Campbell, Peter T; Peters, Ulrike.
Afiliação
  • Xia Z; Department of Epidemiology, University of Washington, Seattle, WA, USA.
  • Su YR; Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA.
  • Petersen P; Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA.
  • Qi L; Department of Public Health Sciences, University of California Davis, Davis, CA, USA.
  • Kim AE; Department of Preventive Medicine &, USC Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
  • Figueiredo JC; Department of Preventive Medicine &, USC Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
  • Lin Y; Department of Medicine, Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
  • Nan H; Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA.
  • Sakoda LC; Department of Epidemiology, Richard M. Fairbanks School of Public Health, Indiana University, Indianapolis, IN, USA.
  • Albanes D; Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA.
  • Berndt SI; Division of Research, Kaiser Permanente Northern California, Oakland, CA, USA.
  • Bézieau S; Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
  • Bien S; Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
  • Buchanan DD; Service de Génétique Médicale, Centre Hospitalier Universitaire (CHU) Nantes, Nantes, France.
  • Casey G; Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA.
  • Chan AT; Colorectal Oncogenomics Group, Department of Clinical Pathology, The University of Melbourne, Parkville, Victoria, Australia.
  • Conti DV; University of Melbourne Centre for Cancer Research, Victorian Comprehensive Cancer Centre, Parkville, Victoria, Australia.
  • Drew DA; Genetic Medicine and Family Cancer Clinic, The Royal Melbourne Hospital, Parkville, Victoria, Australia.
  • Gallinger SJ; Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA.
  • Gauderman WJ; Division of Gastroenterology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
  • Giles GG; Channing Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
  • Gruber SB; Clinical and Translational Epidemiology Unit, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
  • Gunter MJ; Broad Institute of Harvard and MIT, Cambridge, MA, USA.
  • Hoffmeister M; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Harvard University, Boston, MA, USA.
  • Jenkins MA; Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Harvard University, Boston, MA, USA.
  • Joshi AD; Department of Preventive Medicine &, USC Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
  • Le Marchand L; Division of Gastroenterology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
  • Lewinger JP; Clinical and Translational Epidemiology Unit, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
  • Li L; Lunenfeld Tanenbaum Research Institute, Mount Sinai Hospital, University of Toronto, Toronto, Ontario, Canada.
  • Lindor NM; Department of Preventive Medicine &, USC Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
  • Moreno V; Cancer Epidemiology Division, Melbourne, Victoria, Australia.
  • Murphy N; Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Victoria, Australia.
  • Nassir R; Department of Preventive Medicine &, USC Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
  • Newcomb PA; Section of Nutrition and Metabolism, International Agency for Research on Cancer, Lyon, France.
  • Ogino S; Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany.
  • Rennert G; Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Victoria, Australia.
  • Song M; Clinical and Translational Epidemiology Unit, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
  • Wang X; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Harvard University, Boston, MA, USA.
  • Wolk A; University of Hawaii Cancer Center, Honolulu, HI, USA.
  • Woods MO; Department of Preventive Medicine &, USC Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
  • Brenner H; Department of Family Medicine, University of Virginia, Charlottesville, VA, USA.
  • White E; Department of Health Science Research, Mayo Clinic, Scottsdale, AZ, USA.
  • Slattery ML; Oncology Data Analytics Program, Catalan Institute of Oncology-IDIBELL, L'Hospitalet de Llobregat, Barcelona, Spain.
  • Giovannucci EL; CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain.
  • Chang-Claude J; Department of Clinical Sciences, Faculty of Medicine, University of Barcelona, Barcelona, Spain.
  • Pharoah PDP; ONCOBEL Program, Bellvitge Biomedical Research Institute (IDIBELL), L'Hospitalet de Llobregat, Barcelona, Spain.
  • Hsu L; Section of Nutrition and Metabolism, International Agency for Research on Cancer, Lyon, France.
  • Campbell PT; Department of Pathology, School of Medicine, Umm Al-Qura University, Makkah, Saudi Arabia.
  • Peters U; Department of Epidemiology, University of Washington, Seattle, WA, USA.
Cancer Med ; 9(10): 3563-3573, 2020 May.
Artigo em Inglês | MEDLINE | ID: mdl-32207560
ABSTRACT

BACKGROUND:

Body mass index (BMI) and diabetes are established risk factors for colorectal cancer (CRC), likely through perturbations in metabolic traits (e.g. insulin resistance and glucose homeostasis). Identification of interactions between variation in genes and these metabolic risk factors may identify novel biologic insights into CRC etiology.

METHODS:

To improve statistical power and interpretation for gene-environment interaction (G × E) testing, we tested genetic variants that regulate expression of a gene together for interaction with BMI (kg/m2 ) and diabetes on CRC risk among 26 017 cases and 20 692 controls. Each variant was weighted based on PrediXcan analysis of gene expression data from colon tissue generated in the Genotype-Tissue Expression Project for all genes with heritability ≥1%. We used a mixed-effects model to jointly measure the G × E interaction in a gene by partitioning the interactions into the predicted gene expression levels (fixed effects), and residual G × E effects (random effects). G × BMI analyses were stratified by sex as BMI-CRC associations differ by sex. We used false discovery rates to account for multiple comparisons and reported all results with FDR <0.2.

RESULTS:

Among 4839 genes tested, genetically predicted expressions of FOXA1 (P = 3.15 × 10-5 ), PSMC5 (P = 4.51 × 10-4 ) and CD33 (P = 2.71 × 10-4 ) modified the association of BMI on CRC risk for men; KIAA0753 (P = 2.29 × 10-5 ) and SCN1B (P = 2.76 × 10-4 ) modified the association of BMI on CRC risk for women; and PTPN2 modified the association between diabetes and CRC risk in both sexes (P = 2.31 × 10-5 ).

CONCLUSIONS:

Aggregating G × E interactions and incorporating functional information, we discovered novel genes that may interact with BMI and diabetes on CRC risk.
Texto completo: Disponível Coleções: Bases de dados internacionais Base de dados: MEDLINE Tipo de estudo: Estudo de etiologia / Estudo observacional / Estudo prognóstico / Fatores de risco Idioma: Inglês Revista: Cancer Med Ano de publicação: 2020 Tipo de documento: Artigo País de afiliação: Estados Unidos

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Texto completo: Disponível Coleções: Bases de dados internacionais Base de dados: MEDLINE Tipo de estudo: Estudo de etiologia / Estudo observacional / Estudo prognóstico / Fatores de risco Idioma: Inglês Revista: Cancer Med Ano de publicação: 2020 Tipo de documento: Artigo País de afiliação: Estados Unidos
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