The blood metabolome of incident kidney cancer: A case–control study nested within the MetKid consortium
Creators: name: Guida, Florence
name: Tan, Vanessa Y.
name: Corbin, Laura J.
name: Smith-Byrne, Karl
name: Alcala, Karine
name: Langenberg, Claudia
name: Stewart, Isobel D.
name: Butterworth, Adam S.
name: Surendran, Praveen
name: Achaintre, David
name: Adamski, Jerzy
name: Amiano, Pilar
name: Bergmann, Manuela M.
name: Bull, Caroline J.
name: Dahm, Christina C.
name: Gicquiau, Audrey
name: Giles, Graham G.
name: Gunter, Marc J.
name: Haller, Toomas
name: Langhammer, Arnulf
name: Larose, Tricia L.
name: Ljungberg, Börje
name: Metspalu, Andres
name: Milne, Roger L.
name: Muller, David C.
name: Nøst, Therese H.
name: Pettersen Sørgjerd, Elin
name: Prehn, Cornelia
name: Riboli, Elio
name: Rinaldi, Sabina
name: Rothwell, Joseph A.
name: Scalbert, Augustin
name: Schmidt, Julie A.
name: Severi, Gianluca
name: Sieri, Sabina
name: Vermeulen, Roel
name: Vincent, Emma E.
name: Waldenberger, Melanie
name: Timpson, Nicholas J.
name: Johansson, Mattias
Publisher: name: Apollo - University of Cambridge Repository
Year: 2021
Subjects: Research Article
Biology and life sciences
Medicine and health sciences
Research and analysis methods

description: Background: 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.