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Interactions between folate intake and genetic predictors of gene expression levels associated with colorectal cancer risk.
Haas, Cameron B; Su, Yu-Ru; Petersen, Paneen; Wang, Xiaoliang; Bien, Stephanie A; Lin, Yi; Albanes, Demetrius; Weinstein, Stephanie J; Jenkins, Mark A; Figueiredo, Jane C; Newcomb, Polly A; Casey, Graham; Le Marchand, Loic; Campbell, Peter T; Moreno, Victor; Potter, John D; Sakoda, Lori C; Slattery, Martha L; Chan, Andrew T; Li, Li; Giles, Graham G; Milne, Roger L; Gruber, Stephen B; Rennert, Gad; Woods, Michael O; Gallinger, Steven J; Berndt, Sonja; Hayes, Richard B; Huang, Wen-Yi; Wolk, Alicja; White, Emily; Nan, Hongmei; Nassir, Rami; Lindor, Noralane M; Lewinger, Juan P; Kim, Andre E; Conti, David; Gauderman, W James; Buchanan, Daniel D; Peters, Ulrike; Hsu, Li.
Affiliation
  • Haas CB; Department of Epidemiology, University of Washington, Seattle, WA, USA. cameron.b.haas@gmail.com.
  • Su YR; Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, WA, USA. cameron.b.haas@gmail.com.
  • Petersen P; Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, WA, USA.
  • Wang X; Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, WA, USA.
  • Bien SA; Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, WA, USA.
  • Lin Y; Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, WA, USA.
  • Albanes D; Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, WA, USA.
  • Weinstein SJ; Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
  • Jenkins MA; Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
  • Figueiredo JC; Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, VIC, Australia.
  • Newcomb PA; Department of Medicine, Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
  • Casey G; Department of Preventive Medicine and USC Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
  • Le Marchand L; Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, WA, USA.
  • Campbell PT; School of Public Health, University of Washington, Seattle, WA, USA.
  • Moreno V; Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA.
  • Potter JD; University of Hawaii Cancer Center, Honolulu, HI, USA.
  • Sakoda LC; Behavioral and Epidemiology Research Group, American Cancer Society, Atlanta, GA, USA.
  • Slattery ML; Oncology Data Analytics Program, Catalan Institute of Oncology-IDIBELL, L'Hospitalet de Llobregat, Barcelona, Spain.
  • Chan AT; CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain.
  • Li L; Department of Clinical Sciences, Faculty of Medicine, University of Barcelona, Barcelona, Spain.
  • Giles GG; ONCOBEL Program, Bellvitge Biomedical Research Institute (IDIBELL), L'Hospitalet de Llobregat, Barcelona, Spain.
  • Milne RL; Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, WA, USA.
  • Gruber SB; Center for Public Health Research, Massey University, Wellington, New Zealand.
  • Rennert G; Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, WA, USA.
  • Woods MO; Division of Research, Kaiser Permanente Northern California, Oakland, CA, USA.
  • Gallinger SJ; Department of Internal Medicine, University of Utah, Salt Lake City, UT, USA.
  • Berndt S; Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
  • Hayes RB; Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
  • Huang WY; Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
  • Wolk A; Broad Institute of Harvard and MIT, Cambridge, MA, USA.
  • White E; Department of Family Medicine, University of Virginia, Charlottesville, VA, USA.
  • Nan H; Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, VIC, Australia.
  • Nassir R; Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, VIC, Australia.
  • Lindor NM; Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, VIC, Australia.
  • Lewinger JP; Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, VIC, Australia.
  • Kim AE; Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, VIC, Australia.
  • Conti D; Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, VIC, Australia.
  • Gauderman WJ; Department of Preventive Medicine and USC Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
  • Buchanan DD; Department of Community Medicine and Epidemiology, Lady Davis Carmel Medical Center, Haifa, Israel.
  • Peters U; Ruth and Bruce Rappaport Faculty of Medicine, Technion-Israel Institute of Technology, Haifa, Israel.
  • Hsu L; Clalit National Cancer Control Center, Haifa, Israel.
Sci Rep ; 12(1): 18852, 2022 11 07.
Article in En | MEDLINE | ID: mdl-36344807
ABSTRACT
Observational studies have shown higher folate consumption to be associated with lower risk of colorectal cancer (CRC). Understanding whether and how genetic risk factors interact with folate could further elucidate the underlying mechanism. Aggregating functionally relevant genetic variants in set-based variant testing has higher power to detect gene-environment (G × E) interactions and may provide information on the underlying biological pathway. We investigated interactions between folate consumption and predicted gene expression on colorectal cancer risk across the genome. We used variant weights from the PrediXcan models of colon tissue-specific gene expression as a priori variant information for a set-based G × E approach. We harmonized total folate intake (mcg/day) based on dietary intake and supplemental use across cohort and case-control studies and calculated sex and study specific quantiles. Analyses were performed using a mixed effects score tests for interactions between folate and genetically predicted expression of 4839 genes with available genetically predicted expression. We pooled results across 23 studies for a total of 13,498 cases with colorectal tumors and 13,918 controls of European ancestry. We used a false discovery rate of 0.2 to identify genes with suggestive evidence of an interaction. We found suggestive evidence of interaction with folate intake on CRC risk for genes including glutathione S-Transferase Alpha 1 (GSTA1; p = 4.3E-4), Tonsuko Like, DNA Repair Protein (TONSL; p = 4.3E-4), and Aspartylglucosaminidase (AGA p = 4.5E-4). We identified three genes involved in preventing or repairing DNA damage that may interact with folate consumption to alter CRC risk. Glutathione is an antioxidant, preventing cellular damage and is a downstream metabolite of homocysteine and metabolized by GSTA1. TONSL is part of a complex that functions in the recovery of double strand breaks and AGA plays a role in lysosomal breakdown of glycoprotein.
Subject(s)

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Colorectal Neoplasms / Folic Acid Type of study: Etiology_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limits: Humans Language: En Journal: Sci Rep Year: 2022 Document type: Article Affiliation country: Estados Unidos

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Colorectal Neoplasms / Folic Acid Type of study: Etiology_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limits: Humans Language: En Journal: Sci Rep Year: 2022 Document type: Article Affiliation country: Estados Unidos
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