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@ARTICLE{Xia:154193,
      author       = {Z. Xia and Y.-R. Su and P. Petersen and L. Qi and A. E. Kim
                      and }, , USC Norris Comprehensive Cancer Center, Keck School
                      of Medicine, University of Southern California, Los Angeles,
                      CA, USA. and J. C. Figueiredo and }, , USC Norris
                      Comprehensive Cancer Center, Keck School of Medicine,
                      University of Southern California, Los Angeles, CA, USA. |
                      Department of Medicine, Samuel Oschin Comprehensive Cancer
                      Institute, Cedars-Sinai Medical Center, Los Angeles, CA,
                      USA. and Y. Lin and H. Nan and L. C. Sakoda and D. Albanes
                      and S. I. Berndt and S. Bézieau and S. Bien and D. D.
                      Buchanan and G. Casey and A. T. Chan and D. V. Conti and },
                      , USC Norris Comprehensive Cancer Center, Keck School of
                      Medicine, University of Southern California, Los Angeles,
                      CA, USA. and D. A. Drew and S. J. Gallinger and W. J.
                      Gauderman and }, , USC Norris Comprehensive Cancer Center,
                      Keck School of Medicine, University of Southern California,
                      Los Angeles, CA, USA. and G. G. Giles and S. B. Gruber and
                      }, , USC Norris Comprehensive Cancer Center, Keck School of
                      Medicine, University of Southern California, Los Angeles,
                      CA, USA. and M. J. Gunter and M. Hoffmeister$^*$ and M. A.
                      Jenkins and A. D. Joshi and L. Le Marchand and J. P.
                      Lewinger and }, , USC Norris Comprehensive Cancer Center,
                      Keck School of Medicine, University of Southern California,
                      Los Angeles, CA, USA. and L. Li and N. M. Lindor and V.
                      Moreno and N. Murphy and R. Nassir and P. A. Newcomb and S.
                      Ogino and G. Rennert and M. Song and X. Wang and A. Wolk and
                      M. O. Woods and H. Brenner$^*$ and E. White and M. L.
                      Slattery and E. L. Giovannucci and J. Chang-Claude$^*$ and
                      P. D. P. Pharoah and L. Hsu and P. T. Campbell and U.
                      Peters},
      title        = {{F}unctional informed genome-wide interaction analysis of
                      body mass index, diabetes and colorectal cancer risk.},
      journal      = {Cancer medicine},
      volume       = {9},
      number       = {10},
      issn         = {2045-7634},
      address      = {Hoboken, NJ},
      publisher    = {Wiley},
      reportid     = {DKFZ-2020-00649},
      pages        = {3563-3573},
      year         = {2020},
      note         = {2020 May;9(10):3563-3573},
      abstract     = {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.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.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 ).Aggregating G × E interactions
                      and incorporating functional information, we discovered
                      novel genes that may interact with BMI and diabetes on CRC
                      risk.},
      cin          = {C070 / C120 / C020},
      ddc          = {610},
      cid          = {I:(DE-He78)C070-20160331 / I:(DE-He78)C120-20160331 /
                      I:(DE-He78)C020-20160331},
      pnm          = {313 - Cancer risk factors and prevention (POF3-313)},
      pid          = {G:(DE-HGF)POF3-313},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:32207560},
      doi          = {10.1002/cam4.2971},
      url          = {https://inrepo02.dkfz.de/record/154193},
}