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@ARTICLE{Dossus:169139,
      author       = {L. Dossus and E. Kouloura and C. Biessy and V. Viallon and
                      A. P. Siskos and N. Dimou and S. Rinaldi and M. A. Merritt
                      and N. Allen and R. Fortner$^*$ and R. Kaaks$^*$ and E.
                      Weiderpass and I. T. Gram and J. A. Rothwell and L. Lécuyer
                      and G. Severi and M. B. Schulze and T. H. Nøst and M.
                      Crous-Bou and M.-J. Sánchez and P. Amiano and S. M.
                      Colorado-Yohar and A. B. Gurrea and J. A. Schmidt and D.
                      Palli and C. Agnoli and R. Tumino and C. Sacerdote and A.
                      Mattiello and R. Vermeulen and A. K. Heath and S.
                      Christakoudi and K. K. Tsilidis and R. C. Travis and M. J.
                      Gunter and H. C. Keun},
      title        = {{P}rospective analysis of circulating metabolites and
                      endometrial cancer risk.},
      journal      = {Gynecologic oncology},
      volume       = {162},
      number       = {2},
      issn         = {0090-8258},
      address      = {Amsterdam [u.a.]},
      publisher    = {Elsevier},
      reportid     = {DKFZ-2021-01281},
      pages        = {475-481},
      year         = {2021},
      note         = {2021 Aug;162(2):475-481},
      abstract     = {Endometrial cancer is strongly associated with obesity and
                      dysregulation of metabolic factors such as estrogen and
                      insulin signaling are causal risk factors for this
                      malignancy. To identify additional novel metabolic pathways
                      associated with endometrial cancer we performed metabolomic
                      analyses on pre-diagnostic plasma samples from 853
                      case-control pairs from the European Prospective
                      Investigation into Cancer and Nutrition (EPIC).A total of
                      129 metabolites (acylcarnitines, amino acids, biogenic
                      amines, glycerophospholipids, hexoses, and sphingolipids)
                      were measured by liquid chromatography-mass spectrometry.
                      Conditional logistic regression estimated the associations
                      of metabolites with endometrial cancer risk. An analysis
                      focusing on clusters of metabolites using the bootstrap
                      lasso method was also employed.After adjustment for body
                      mass index, sphingomyelin [SM] C18:0 was positively (OR1SD:
                      1.18, $95\%$ CI: 1.05-1.33), and glycine, serine, and free
                      carnitine (C0) were inversely (OR1SD: 0.89, $95\%$ CI:
                      0.80-0.99; OR1SD: 0.89, $95\%$ CI: 0.79-1.00 and OR1SD:
                      0.91, $95\%$ CI: 0.81-1.00, respectively) associated with
                      endometrial cancer risk. Serine, C0 and two sphingomyelins
                      were selected by the lasso method in $>90\%$ of the
                      bootstrap samples. The ratio of esterified to free carnitine
                      (OR1SD: 1.14, $95\%$ CI: 1.02-1.28) and that of short chain
                      to free acylcarnitines (OR1SD: 1.12, $95\%$ CI: 1.00-1.25)
                      were positively associated with endometrial cancer risk.
                      Further adjustment for C-peptide or other endometrial cancer
                      risk factors only minimally altered the results.These
                      findings suggest that variation in levels of glycine,
                      serine, SM C18:0 and free carnitine may represent specific
                      pathways linked to endometrial cancer development. If
                      causal, these pathways may offer novel targets for
                      endometrial cancer prevention.},
      keywords     = {Amino acids (Other) / Endometrial cancer (Other) / Lipids
                      (Other) / Metabolomics (Other) / Obesity (Other)},
      cin          = {C020},
      ddc          = {610},
      cid          = {I:(DE-He78)C020-20160331},
      pnm          = {313 - Krebsrisikofaktoren und Prävention (POF4-313)},
      pid          = {G:(DE-HGF)POF4-313},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:34099314},
      doi          = {10.1016/j.ygyno.2021.06.001},
      url          = {https://inrepo02.dkfz.de/record/169139},
}