000168680 001__ 168680 000168680 005__ 20240229133612.0 000168680 0247_ $$2doi$$a10.1186/s12916-021-01970-1 000168680 0247_ $$2pmid$$apmid:33926456 000168680 0247_ $$2pmc$$apmc:PMC8086283 000168680 0247_ $$2altmetric$$aaltmetric:105023102 000168680 037__ $$aDKFZ-2021-00988 000168680 041__ $$aEnglish 000168680 082__ $$a610 000168680 1001_ $$aKliemann, Nathalie$$b0 000168680 245__ $$aMetabolic signatures of greater body size and their associations with risk of colorectal and endometrial cancers in the European Prospective Investigation into Cancer and Nutrition. 000168680 260__ $$aHeidelberg [u.a.]$$bSpringer$$c2021 000168680 3367_ $$2DRIVER$$aarticle 000168680 3367_ $$2DataCite$$aOutput Types/Journal article 000168680 3367_ $$0PUB:(DE-HGF)16$$2PUB:(DE-HGF)$$aJournal Article$$bjournal$$mjournal$$s1620224451_355 000168680 3367_ $$2BibTeX$$aARTICLE 000168680 3367_ $$2ORCID$$aJOURNAL_ARTICLE 000168680 3367_ $$00$$2EndNote$$aJournal Article 000168680 520__ $$aThe mechanisms underlying the obesity-cancer relationship are incompletely understood. This study aimed to characterise metabolic signatures of greater body size and to investigate their association with two obesity-related malignancies, endometrial and colorectal cancers, and with weight loss within the context of an intervention study.Targeted mass spectrometry metabolomics data from 4326 participants enrolled in the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort and 17 individuals from a single-arm pilot weight loss intervention (Intercept) were used in this analysis. Metabolic signatures of body size were first determined in discovery (N = 3029) and replication (N = 1297) sets among EPIC participants by testing the associations between 129 metabolites and body mass index (BMI), waist circumference (WC), and waist-to-hip ratio (WHR) using linear regression models followed by partial least squares analyses. Conditional logistic regression models assessed the associations between the metabolic signatures with endometrial (N = 635 cases and 648 controls) and colorectal (N = 423 cases and 423 controls) cancer risk using nested case-control studies in EPIC. Pearson correlation between changes in the metabolic signatures and weight loss was tested among Intercept participants.After adjustment for multiple comparisons, greater BMI, WC, and WHR were associated with higher levels of valine, isoleucine, glutamate, PC aa C38:3, and PC aa C38:4 and with lower levels of asparagine, glutamine, glycine, serine, lysoPC C17:0, lysoPC C18:1, lysoPC C18:2, PC aa C42:0, PC ae C34:3, PC ae C40:5, and PC ae C42:5. The metabolic signature of BMI (OR1-sd 1.50, 95% CI 1.30-1.74), WC (OR1-sd 1.46, 95% CI 1.27-1.69), and WHR (OR1-sd 1.54, 95% CI 1.33-1.79) were each associated with endometrial cancer risk. Risk of colorectal cancer was positively associated with the metabolic signature of WHR (OR1-sd: 1.26, 95% CI 1.07-1.49). In the Intercept study, a positive correlation was observed between weight loss and changes in the metabolic signatures of BMI (r = 0.5, 95% CI 0.06-0.94, p = 0.03), WC (r = 0.5, 95% CI 0.05-0.94, p = 0.03), and WHR (r = 0.6, 95% CI 0.32-0.87, p = 0.01).Obesity is associated with a distinct metabolic signature comprising changes in levels of specific amino acids and lipids which is positively associated with both colorectal and endometrial cancer and is potentially reversible following weight loss. 000168680 536__ $$0G:(DE-HGF)POF4-313$$a313 - Krebsrisikofaktoren und Prävention (POF4-313)$$cPOF4-313$$fPOF IV$$x0 000168680 588__ $$aDataset connected to CrossRef, PubMed, , Journals: inrepo01.inet.dkfz-heidelberg.de 000168680 650_7 $$2Other$$aCancer 000168680 650_7 $$2Other$$aMetabolomics 000168680 650_7 $$2Other$$aObesity 000168680 650_7 $$2Other$$aWeight loss 000168680 7001_ $$aViallon, Vivian$$b1 000168680 7001_ $$aMurphy, Neil$$b2 000168680 7001_ $$aBeeken, Rebecca J$$b3 000168680 7001_ $$aRothwell, Joseph A$$b4 000168680 7001_ $$aRinaldi, Sabina$$b5 000168680 7001_ $$aAssi, Nada$$b6 000168680 7001_ $$avan Roekel, Eline H$$b7 000168680 7001_ $$aSchmidt, Julie A$$b8 000168680 7001_ $$aBorch, Kristin Benjaminsen$$b9 000168680 7001_ $$aAgnoli, Claudia$$b10 000168680 7001_ $$aRosendahl, Ann H$$b11 000168680 7001_ $$aSartor, Hanna$$b12 000168680 7001_ $$aHuerta, José María$$b13 000168680 7001_ $$aTjønneland, Anne$$b14 000168680 7001_ $$aHalkjær, Jytte$$b15 000168680 7001_ $$aBueno-de-Mesquita, Bas$$b16 000168680 7001_ $$aGicquiau, Audrey$$b17 000168680 7001_ $$aAchaintre, David$$b18 000168680 7001_ $$aAleksandrova, Krasimira$$b19 000168680 7001_ $$aSchulze, Matthias B$$b20 000168680 7001_ $$aHeath, Alicia K$$b21 000168680 7001_ $$aTsilidis, Konstantinos K$$b22 000168680 7001_ $$aMasala, Giovanna$$b23 000168680 7001_ $$aPanico, Salvatore$$b24 000168680 7001_ $$0P:(DE-He78)4b2dc91c9d1ac33a1c0e0777d0c1697a$$aKaaks, Rudolf$$b25$$udkfz 000168680 7001_ $$0P:(DE-He78)74a6af8347ec5cbd4b77e562e10ca1f2$$aFortner, Renée T$$b26$$udkfz 000168680 7001_ $$aVan Guelpen, Bethany$$b27 000168680 7001_ $$aDossus, Laure$$b28 000168680 7001_ $$aScalbert, Augustin$$b29 000168680 7001_ $$aKeun, Hector C$$b30 000168680 7001_ $$aTravis, Ruth C$$b31 000168680 7001_ $$aJenab, Mazda$$b32 000168680 7001_ $$aJohansson, Mattias$$b33 000168680 7001_ $$aFerrari, Pietro$$b34 000168680 7001_ $$aGunter, Marc J$$b35 000168680 773__ $$0PERI:(DE-600)2131669-7$$a10.1186/s12916-021-01970-1$$gVol. 19, no. 1, p. 101$$n1$$p101$$tBMC medicine$$v19$$x1741-7015$$y2021 000168680 909CO $$ooai:inrepo02.dkfz.de:168680$$pVDB 000168680 9101_ $$0I:(DE-588b)2036810-0$$6P:(DE-He78)4b2dc91c9d1ac33a1c0e0777d0c1697a$$aDeutsches Krebsforschungszentrum$$b25$$kDKFZ 000168680 9101_ $$0I:(DE-588b)2036810-0$$6P:(DE-He78)74a6af8347ec5cbd4b77e562e10ca1f2$$aDeutsches Krebsforschungszentrum$$b26$$kDKFZ 000168680 9130_ $$0G:(DE-HGF)POF3-313$$1G:(DE-HGF)POF3-310$$2G:(DE-HGF)POF3-300$$3G:(DE-HGF)POF3$$4G:(DE-HGF)POF$$aDE-HGF$$bGesundheit$$lKrebsforschung$$vCancer risk factors and prevention$$x0 000168680 9131_ $$0G:(DE-HGF)POF4-313$$1G:(DE-HGF)POF4-310$$2G:(DE-HGF)POF4-300$$3G:(DE-HGF)POF4$$4G:(DE-HGF)POF$$aDE-HGF$$bGesundheit$$lKrebsforschung$$vKrebsrisikofaktoren und Prävention$$x0 000168680 9141_ $$y2021 000168680 915__ $$0StatID:(DE-HGF)0100$$2StatID$$aJCR$$bBMC MED : 2019$$d2021-01-29 000168680 915__ $$0StatID:(DE-HGF)0200$$2StatID$$aDBCoverage$$bSCOPUS$$d2021-01-29 000168680 915__ $$0StatID:(DE-HGF)0300$$2StatID$$aDBCoverage$$bMedline$$d2021-01-29 000168680 915__ $$0StatID:(DE-HGF)0320$$2StatID$$aDBCoverage$$bPubMed Central$$d2021-01-29 000168680 915__ $$0StatID:(DE-HGF)0501$$2StatID$$aDBCoverage$$bDOAJ Seal$$d2021-01-29 000168680 915__ $$0StatID:(DE-HGF)0500$$2StatID$$aDBCoverage$$bDOAJ$$d2021-01-29 000168680 915__ $$0StatID:(DE-HGF)0030$$2StatID$$aPeer Review$$bDOAJ : Open peer review$$d2021-01-29 000168680 915__ $$0LIC:(DE-HGF)CCBYNV$$2V:(DE-HGF)$$aCreative Commons Attribution CC BY (No Version)$$bDOAJ$$d2021-01-29 000168680 915__ $$0StatID:(DE-HGF)0600$$2StatID$$aDBCoverage$$bEbsco Academic Search$$d2021-01-29 000168680 915__ $$0StatID:(DE-HGF)0030$$2StatID$$aPeer Review$$bASC$$d2021-01-29 000168680 915__ $$0StatID:(DE-HGF)0199$$2StatID$$aDBCoverage$$bClarivate Analytics Master Journal List$$d2021-01-29 000168680 915__ $$0StatID:(DE-HGF)0160$$2StatID$$aDBCoverage$$bEssential Science Indicators$$d2021-01-29 000168680 915__ $$0StatID:(DE-HGF)1050$$2StatID$$aDBCoverage$$bBIOSIS Previews$$d2021-01-29 000168680 915__ $$0StatID:(DE-HGF)1110$$2StatID$$aDBCoverage$$bCurrent Contents - 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