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Grant Details

Grant Number: 5R01CA201407-04 Interpret this number
Primary Investigator: Peters, Ulrike
Organization: Fred Hutchinson Cancer Research Center
Project Title: Using Functional Genomics to Inform Gene Environment Interactions for Colorectal Cancer
Fiscal Year: 2019
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Abstract

PROJECT SUMMARY/ABSTRACT Colorectal cancer (CRC) is a complex disease with both genetic (G) and environmental (E) risk factors contributing to susceptibility. Genome-wide GxE interaction scans (GWIS) can help identify novel susceptibility loci and biologically meaningful GxE interactions that point to new carcinogenic mechanisms. Limited statistical power remains a primary concern in GxE analyses. To maximize the statistical power in a GWIS, it is essential to have the largest possible sample size by pooling resources across studies. In this project, we will combine the resources of three existing CRC consortia (approximately 53,600 cases and 52,400 controls of European descent): the Colorectal Cancer Family Registry (CCFR), the Colorectal Cancer Transdisciplinary (CORECT) Study, and the Genetics and Epidemiology of Colorectal Cancer Consortium (GECCO) for interaction testing with 8 environmental and lifestyle factors: alcohol, calcium, folate, hormone replacement therapy (HRT), non- steroidal anti-inflammatory drugs (NSAIDs), red meat, processed meat, and smoking. To improve statistical power and enhance our ability to discover true GxE associations, we will as part of Aim 1 incorporate functional genomics data in two forms: (1) enhancer/promoter profiles derived from ChIPseq and DNase I hypersensitive sites (DHS) data publicly available from Roadmap or from our own experiments in normal colon tissue; and (2) our newly generated RNA-Seq results from normal colon biopsies with detailed environmental and lifestyle risk factor information, and gene expression measured in normal human 3D colon organoids (“mini guts”) in response to environmental exposures. In Aim 2 we will use our novel statistical methods that can incorporate the CR and E-specific functional genomics data generated in Aim 1 to discover new GxE interaction for CRC with rare and common single nucleotide variants (down to MAF 0.1%) in up to 53,600 cases and 52,400 controls. To narrow in on the underlying causal variant(s) for any identified novel GxE interaction, we will conduct fine-mapping analyses using a trans-ethnic meta-analysis (23,500 non-European and 106,000 European). To follow-up on identified significant GxE interactions, we will functionally validate our strongest GxE interactions (including previously published findings) to provide support for the novel GxE interactions such as knock down in CRC cell lines and normal human 3D colon epithelial organoids. Our large and well-characterized study population, combined with our experienced research team, and integration of functional genomics data into our novel statistical methods provide opportunities to better understand how genetic and environmental risk factors, combined, contribute to individual risk of CRC. Discovering GxE interactions will provide insight into the underlying mechanisms that drive gene-CRC associations impacted by established environmental risk factors. Since genetic profiles are fixed, modifying environmental exposures to alter deleterious effects of alleles remains an important preventive strategy.

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Publications

Incorporating Participant and Clinical Feedback into a Community-Based Participatory Research Study of Colorectal Cancer Among Alaska Native People.
Authors: Nash S.H. , Greenley R. , Dietz-Chavez D. , Vindigni S. , Harrison T. , Peters U. , Redwood D. .
Source: Journal of community health, 2020 Aug; 45(4), p. 803-811.
PMID: 32144608
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Functional informed genome-wide interaction analysis of body mass index, diabetes and colorectal cancer risk.
Authors: Xia Z. , Su Y.R. , Petersen P. , Qi L. , Kim A.E. , Figueiredo J.C. , Lin Y. , Nan H. , Sakoda L.C. , Albanes D. , et al. .
Source: Cancer medicine, 2020 May; 9(10), p. 3563-3573.
EPub date: 2020-03-24.
PMID: 32207560
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Association of body mass index with colorectal cancer risk by genome-wide variants.
Authors: Campbell P.T. , Lin Y. , Bien S.A. , Figueiredo J.C. , Harrison T.A. , Guinter M.J. , Berndt S.I. , Brenner H. , Chan A.T. , Chang-Claude J. , et al. .
Source: Journal of the National Cancer Institute, 2020-04-23; , .
EPub date: 2020-04-23.
PMID: 32324875
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Mendelian Randomization of Circulating Polyunsaturated Fatty Acids and Colorectal Cancer Risk.
Authors: Khankari N.K. , Banbury B.L. , Borges M.C. , Haycock P. , Albanes D. , Arndt V. , Berndt S.I. , Bézieau S. , Brenner H. , Campbell P.T. , et al. .
Source: Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology, 2020 Apr; 29(4), p. 860-870.
EPub date: 2020-02-12.
PMID: 32051193
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Circulating Levels of Insulin-like Growth Factor 1 and Insulin-like Growth Factor Binding Protein 3 Associate With Risk of Colorectal Cancer Based on Serologic and Mendelian Randomization Analyses.
Authors: Murphy N. , Carreras-Torres R. , Song M. , Chan A.T. , Martin R.M. , Papadimitriou N. , Dimou N. , Tsilidis K.K. , Banbury B. , Bradbury K.E. , et al. .
Source: Gastroenterology, 2020 04; 158(5), p. 1300-1312.e20.
EPub date: 2019-12-27.
PMID: 31884074
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Cumulative Burden of Colorectal Cancer-Associated Genetic Variants Is More Strongly Associated With Early-Onset vs Late-Onset Cancer.
Authors: Archambault A.N. , Su Y.R. , Jeon J. , Thomas M. , Lin Y. , Conti D.V. , Win A.K. , Sakoda L.C. , Lansdorp-Vogelaar I. , Peterse E.F.P. , et al. .
Source: Gastroenterology, 2020 04; 158(5), p. 1274-1286.e12.
EPub date: 2019-12-19.
PMID: 31866242
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Identification of Novel Loci and New Risk Variant in Known Loci for Colorectal Cancer Risk in East Asians.
Authors: Lu Y. , Kweon S.S. , Cai Q. , Tanikawa C. , Shu X.O. , Jia W.H. , Xiang Y.B. , Huyghe J.R. , Harrison T.A. , Kim J. , et al. .
Source: Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology, 2020 02; 29(2), p. 477-486.
EPub date: 2019-12-11.
PMID: 31826910
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Meta-analysis of 16 studies of the association of alcohol with colorectal cancer.
Authors: McNabb S. , Harrison T.A. , Albanes D. , Berndt S.I. , Brenner H. , Caan B.J. , Campbell P.T. , Cao Y. , Chang-Claude J. , Chan A. , et al. .
Source: International journal of cancer, 2020-02-01; 146(3), p. 861-873.
EPub date: 2019-06-07.
PMID: 31037736
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Physical activity and risks of breast and colorectal cancer: a Mendelian randomisation analysis.
Authors: Papadimitriou N. , Dimou N. , Tsilidis K.K. , Banbury B. , Martin R.M. , Lewis S.J. , Kazmi N. , Robinson T.M. , Albanes D. , Aleksandrova K. , et al. .
Source: Nature communications, 2020-01-30; 11(1), p. 597.
EPub date: 2020-01-30.
PMID: 32001714
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Modeling the effect of prolonged ethanol exposure on global gene expression and chromatin accessibility in normal 3D colon organoids.
Authors: Devall M. , Jennelle L.T. , Bryant J. , Bien S. , Peters U. , Powell S. , Casey G. .
Source: PloS one, 2020; 15(1), p. e0227116.
EPub date: 2020-01-17.
PMID: 31951625
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Genetic overlap between autoimmune diseases and non-Hodgkin lymphoma subtypes.
Authors: Din L. , Sheikh M. , Kosaraju N. , Smedby K.E. , Bernatsky S. , Berndt S.I. , Skibola C.F. , Nieters A. , Wang S. , McKay J.D. , et al. .
Source: Genetic epidemiology, 2019 10; 43(7), p. 844-863.
EPub date: 2019-08-13.
PMID: 31407831
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Correction to: Genetic variant predictors of gene expression provide new insight into risk of colorectal cancer.
Authors: Bien S.A. , Su Y.R. , Conti D.V. , Harrison T.A. , Qu C. , Guo X. , Lu Y. , Albanes D. , Auer P.L. , Banbury B.L. , et al. .
Source: Human genetics, 2019 Jul; 138(7), p. 789-791.
PMID: 31254090
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Moving from one to many: insights from the growing list of pleiotropic cancer risk genes.
Authors: Bien S.A. , Peters U. .
Source: British journal of cancer, 2019 06; 120(12), p. 1087-1089.
EPub date: 2019-05-21.
PMID: 31110328
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Mendelian randomization analysis of C-reactive protein on colorectal cancer risk.
Authors: Wang X. , Dai J.Y. , Albanes D. , Arndt V. , Berndt S.I. , Bézieau S. , Brenner H. , Buchanan D.D. , Butterbach K. , Caan B. , et al. .
Source: International journal of epidemiology, 2019-06-01; 48(3), p. 767-780.
PMID: 30476131
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Genetic variant predictors of gene expression provide new insight into risk of colorectal cancer.
Authors: Bien S.A. , Su Y.R. , Conti D.V. , Harrison T.A. , Qu C. , Guo X. , Lu Y. , Albanes D. , Auer P.L. , Banbury B.L. , et al. .
Source: Human genetics, 2019 Apr; 138(4), p. 307-326.
EPub date: 2019-02-28.
PMID: 30820706
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A Unified Model for the Analysis of Gene-Environment Interaction.
Authors: Gauderman W.J. , Kim A. , Conti D.V. , Morrison J. , Thomas D.C. , Vora H. , Lewinger J.P. .
Source: American journal of epidemiology, 2019-04-01; 188(4), p. 760-767.
PMID: 30649161
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Using Bayes model averaging to leverage both gene main effects and G ×  E interactions to identify genomic regions in genome-wide association studies.
Authors: Moss L.C. , Gauderman W.J. , Lewinger J.P. , Conti D.V. .
Source: Genetic epidemiology, 2019 03; 43(2), p. 150-165.
EPub date: 2018-11-19.
PMID: 30456811
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Shared heritability and functional enrichment across six solid cancers.
Authors: Jiang X. , Finucane H.K. , Schumacher F.R. , Schmit S.L. , Tyrer J.P. , Han Y. , Michailidou K. , Lesseur C. , Kuchenbaecker K.B. , Dennis J. , et al. .
Source: Nature communications, 2019-01-25; 10(1), p. 431.
EPub date: 2019-01-25.
PMID: 30683880
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Combined effect of modifiable and non-modifiable risk factors for colorectal cancer risk in a pooled analysis of 11 population-based studies.
Authors: Wang X. , O'Connell K. , Jeon J. , Song M. , Hunter D. , Hoffmeister M. , Lin Y. , Berndt S. , Brenner H. , Chan A.T. , et al. .
Source: BMJ open gastroenterology, 2019; 6(1), p. e000339.
EPub date: 2019-12-02.
PMID: 31875139
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Discovery of common and rare genetic risk variants for colorectal cancer.
Authors: Huyghe J.R. , Bien S.A. , Harrison T.A. , Kang H.M. , Chen S. , Schmit S.L. , Conti D.V. , Qu C. , Jeon J. , Edlund C.K. , et al. .
Source: Nature genetics, 2019 01; 51(1), p. 76-87.
EPub date: 2018-12-03.
PMID: 30510241
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Current Challenges and New Opportunities for Gene-Environment Interaction Studies of Complex Diseases.
Authors: McAllister K. , Mechanic L.E. , Amos C. , Aschard H. , Blair I.A. , Chatterjee N. , Conti D. , Gauderman W.J. , Hsu L. , Hutter C.M. , et al. .
Source: American journal of epidemiology, 2017-10-01; 186(7), p. 753-761.
PMID: 28978193
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Update on the State of the Science for Analytical Methods for Gene-Environment Interactions.
Authors: Gauderman W.J. , Mukherjee B. , Aschard H. , Hsu L. , Lewinger J.P. , Patel C.J. , Witte J.S. , Amos C. , Tai C.G. , Conti D. , et al. .
Source: American journal of epidemiology, 2017-10-01; 186(7), p. 762-770.
PMID: 28978192
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Incorporation of Biological Knowledge Into the Study of Gene-Environment Interactions.
Authors: Ritchie M.D. , Davis J.R. , Aschard H. , Battle A. , Conti D. , Du M. , Eskin E. , Fallin M.D. , Hsu L. , Kraft P. , et al. .
Source: American journal of epidemiology, 2017-10-01; 186(7), p. 771-777.
PMID: 28978191
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Lessons Learned From Past Gene-Environment Interaction Successes.
Authors: Ritz B.R. , Chatterjee N. , Garcia-Closas M. , Gauderman W.J. , Pierce B.L. , Kraft P. , Tanner C.M. , Mechanic L.E. , McAllister K. .
Source: American journal of epidemiology, 2017-10-01; 186(7), p. 778-786.
PMID: 28978190
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Developing an Epidemiologic Study to Investigate Risk Factors for Colorectal Cancer Among Alaska Native People.
Authors: Nash S.H. , Peters U. , Redwood D. .
Source: Journal of public health management and practice : JPHMP, 2019 Sep/Oct; 25 Suppl 5, Tribal Epidemiology Centers: Advancing Public Health in Indian Country for Over 20 Years, p. S54-S60.
PMID: 31348191
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