% IMPORTANT: The following is UTF-8 encoded.  This means that in the presence
% of non-ASCII characters, it will not work with BibTeX 0.99 or older.
% Instead, you should use an up-to-date BibTeX implementation like “bibtex8” or
% “biber”.

@ARTICLE{Stern:286375,
      author       = {M. C. Stern and J. Sanchez Mendez and A. E. Kim and M.
                      Obón-Santacana and F. Moratalla-Navarro and V. Martín and
                      V. Moreno and Y. Lin and S. A. Bien and C. Qu and Y.-R. Su
                      and E. White and T. A. Harrison and J. R. Huyghe and C. M.
                      Tangen and P. A. Newcomb and A. I. Phipps and C. E. Thomas
                      and E. S. Kawaguchi and J. P. Lewinger and J. L. Morrison
                      and D. V. Conti and J. Wang and D. C. Thomas and E. A. Platz
                      and K. Visvanathan and T. O. Keku and C. C. Newton and C. Y.
                      Um and A. Kundaje and A. Shcherbina and N. Murphy and M. J.
                      Gunter and N. Dimou and N. Papadimitriou and S. Bézieau and
                      F. J. van Duijnhoven and S. Männistö and G. Rennert and A.
                      Wolk and M. Hoffmeister$^*$ and H. Brenner$^*$ and J.
                      Chang-Claude$^*$ and Y. Tian and L. Le Marchand and M.
                      Cotterchio and K. K. Tsilidis and D. T. T. Bishop and Y. A.
                      Melaku and B. M. Lynch and D. D. Buchanan and C. M. Ulrich
                      and J. Ose and A. R. Peoples and A. J. Pellatt and L. Li and
                      M. A. Devall and P. T. Campbell and D. Albanes and S. J.
                      Weinstein and S. I. Berndt and S. B. Gruber and E.
                      Ruiz-Narvaez and M. Song and A. D. Joshi and D. A. Drew and
                      J. L. Petrick and A. T. Chan and M. Giannakis and U. Peters
                      and L. Hsu and W. J. Gauderman},
      title        = {{G}enome-wide gene-environment interaction analyses to
                      understand the relationship between red meat and processed
                      meat intake and colorectal cancer risk.},
      journal      = {Cancer epidemiology, biomarkers $\&$ prevention},
      volume       = {33},
      number       = {3},
      issn         = {1055-9965},
      address      = {Philadelphia, Pa.},
      publisher    = {AACR},
      reportid     = {DKFZ-2023-02778},
      pages        = {400-410},
      year         = {2024},
      note         = {2024 Mar 1;33(3):400-410},
      abstract     = {High red meat and/or processed meat consumption are
                      established colorectal cancer (CRC) risk factors. We
                      conducted a genome-wide gene-environment (GxE) interaction
                      analysis to identify genetic variants that may modify these
                      associations.A pooled sample of 29,842 CRC cases and 39,635
                      controls of European ancestry from 27 studies were included.
                      Quantiles for red meat and processed meat intake were
                      constructed from harmonized questionnaire data. Genotyping
                      arrays were imputed to the Haplotype Reference Consortium.
                      Two-step EDGE and joint tests of GxE interaction were
                      utilized in our genome-wide scan.Meta-analyses confirmed
                      positive associations between increased consumption of red
                      meat and processed meat with CRC risk (per quartile red meat
                      OR = 1.30; $95\%CI$ = 1.21-1.41; processed meat OR = 1.40;
                      $95\%CI$ = 1.20-1.63). Two significant genome-wide GxE
                      interactions for red meat consumption were found. Joint GxE
                      tests revealed the rs4871179 SNP in chromosome 8 (downstream
                      of HAS2); greater than median of consumption ORs = 1.38
                      $(95\%CI$ = 1.29-1.46), 1.20 $(95\%CI$ = 1.12 -1.27), and
                      1.07 $(95\%CI$ = 0.95 - 1.19) for CC, CG and GG,
                      respectively. The two-step EDGE method identified the
                      rs35352860 SNP in chromosome 18 (SMAD7 intron); greater than
                      median of consumption ORs = 1.18 $(95\%CI$ = 1.11-1.24),
                      1.35 $(95\%CI$ = 1.26-1.44), and 1.46 $(95\%CI$ = 1.26-1.69)
                      for CC, CT, and TT, respectively.We propose two novel
                      biomarkers that support the role of meat consumption with an
                      increased risk of CRC.The reported GxE interactions may
                      explain the increased risk of CRC in certain population
                      subgroups.},
      cin          = {C070 / C020 / HD01},
      ddc          = {610},
      cid          = {I:(DE-He78)C070-20160331 / I:(DE-He78)C020-20160331 /
                      I:(DE-He78)HD01-20160331},
      pnm          = {313 - Krebsrisikofaktoren und Prävention (POF4-313)},
      pid          = {G:(DE-HGF)POF4-313},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:38112776},
      doi          = {10.1158/1055-9965.EPI-23-0717},
      url          = {https://inrepo02.dkfz.de/record/286375},
}