Please use this identifier to cite or link to this item: https://doi.org/10.1371/journal.pmed.1003786
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dc.titleThe blood metabolome of incident kidney cancer: A case-control study nested within the MetKid consortium
dc.contributor.authorGuida, Florence
dc.contributor.authorTan, Vanessa Y.
dc.contributor.authorCorbin, Laura J.
dc.contributor.authorSmith-Byrne, Karl
dc.contributor.authorAlcala, Karine
dc.contributor.authorLangenberg, Claudia
dc.contributor.authorStewart, Isobel D.
dc.contributor.authorButterworth, Adam S.
dc.contributor.authorSurendran, Praveen
dc.contributor.authorAchaintre, David
dc.contributor.authorAdamski, Jerzy
dc.contributor.authorAmiano Exezarreta, Pilar
dc.contributor.authorBergmann, Manuela M.
dc.contributor.authorBull, Caroline J.
dc.contributor.authorDahm, Christina C.
dc.contributor.authorGicquiau, Audrey
dc.contributor.authorGiles, Graham G.
dc.contributor.authorGunter, Marc J.
dc.contributor.authorHaller, Toomas
dc.contributor.authorLanghammer, Arnulf
dc.contributor.authorLarose, Tricia L.
dc.contributor.authorLjungberg, Boerje
dc.contributor.authorMetspalu, Andres
dc.contributor.authorMilne, Roger L.
dc.contributor.authorMuller, David C.
dc.contributor.authorNøst, Therese H.
dc.contributor.authorSørgjerd, Elin Pettersen
dc.contributor.authorPrehn, Cornelia
dc.contributor.authorRiboli, Elio
dc.contributor.authorRinaldi, Sabina
dc.contributor.authorRothwell, Joseph A.
dc.contributor.authorScalbert, Augustin
dc.contributor.authorSchmidt, Julie A.
dc.contributor.authorSeveri, Gianluca
dc.contributor.authorSieri, Sabina
dc.contributor.authorVermeulen, Roel
dc.contributor.authorVincent, Emma E.
dc.contributor.authorWaldenberger, Melanie
dc.contributor.authorTimpson, Nicholas J.
dc.contributor.authorJohansson, Mattias
dc.date.accessioned2022-10-11T07:53:45Z
dc.date.available2022-10-11T07:53:45Z
dc.date.issued2021-09-20
dc.identifier.citationGuida, Florence, Tan, Vanessa Y., Corbin, Laura J., Smith-Byrne, Karl, Alcala, Karine, Langenberg, Claudia, Stewart, Isobel D., Butterworth, Adam S., Surendran, Praveen, Achaintre, David, Adamski, Jerzy, Amiano Exezarreta, Pilar, Bergmann, Manuela M., Bull, Caroline J., Dahm, Christina C., Gicquiau, Audrey, Giles, Graham G., Gunter, Marc J., Haller, Toomas, Langhammer, Arnulf, Larose, Tricia L., Ljungberg, Boerje, Metspalu, Andres, Milne, Roger L., Muller, David C., Nøst, Therese H., Sørgjerd, Elin Pettersen, Prehn, Cornelia, Riboli, Elio, Rinaldi, Sabina, Rothwell, Joseph A., Scalbert, Augustin, Schmidt, Julie A., Severi, Gianluca, Sieri, Sabina, Vermeulen, Roel, Vincent, Emma E., Waldenberger, Melanie, Timpson, Nicholas J., Johansson, Mattias (2021-09-20). The blood metabolome of incident kidney cancer: A case-control study nested within the MetKid consortium. PLoS Medicine 18 (9) : e1003786. ScholarBank@NUS Repository. https://doi.org/10.1371/journal.pmed.1003786
dc.identifier.issn1549-1277
dc.identifier.urihttps://scholarbank.nus.edu.sg/handle/10635/232022
dc.description.abstractBackground Excess bodyweight and related metabolic perturbations have : been implicated in kidney cancer aetiology, but the specific molecular mechanisms underlying these relationships are poorly understood. In this study, we sought to identify circulating metabolites that predispose kidney cancer and to evaluate the extent to which they are influenced by body mass index (BMI). Methods and findings We assessed the association between circulating levels of 1,416 metabolites and incident kidney cancer using pre-diagnostic blood samples from up to 1,305 kidney cancer case-control pairs from 5 prospective cohort studies. Cases were diagnosed on average 8 years after blood collection. We found 25 metabolites robustly associated with kidney cancer risk. In particular, 14 glycerophospholipids (GPLs) were inversely associated with risk, including 8 phosphatidylcholines (PCs) and 2 plasmalogens. The PC with the strongest association was PC ae C34:3 with an odds ratio (OR) for 1 standard deviation (SD) increment of 0.75 (95% confidence interval [CI]: 0.68 to 0.83, p = 2.6 × 10−8). In contrast, 4 amino acids, including glutamate (OR for 1 SD = 1.39, 95% CI: 1.20 to 1.60, p = 1.6 × 10−5), were positively associated with risk. Adjusting for BMI partly attenuated the risk association for some -but not all-metabolites, whereas other known risk factors of kidney cancer, such as smoking and alcohol consumption, had minimal impact on the observed associations. A mendelian randomisation (MR) analysis of the influence of BMI on the blood metabolome highlighted that some metabolites associated with kidney cancer risk are influenced by BMI. Specifically, elevated BMI appeared to decrease levels of several GPLs that were also found inversely associated with kidney cancer risk (e.g., −0.17 SD change [ßBMI] in 1-(1-enyl-palmitoyl)-2-linoleoyl-GPC (P-16:0/18:2) levels per SD change in BMI, p = 3.4 × 10−5). BMI was also associated with increased levels of glutamate (ßBMI: 0.12, p = 1.5 × 10−3). While our results were robust across the participating studies, they were limited to study participants of European descent, and it will, therefore, be important to evaluate if our findings can be generalised to populations with different genetic backgrounds. Conclusions This study suggests a potentially important role of the blood metabolome in kidney cancer aetiology by highlighting a wide range of metabolites associated with the risk of developing kidney cancer and the extent to which changes in levels of these metabolites are driven by BMI-the principal modifiable risk factor of kidney cancer. © 2021 Guida et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
dc.publisherPublic Library of Science
dc.rightsAttribution 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.sourceScopus OA2021
dc.typeArticle
dc.contributor.departmentBIOCHEMISTRY
dc.description.doi10.1371/journal.pmed.1003786
dc.description.sourcetitlePLoS Medicine
dc.description.volume18
dc.description.issue9
dc.description.pagee1003786
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