The blood metabolome of incident kidney cancer: A case-control study nested within the MetKid consortium

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  • Florence Guida, Genomic Epidemiology Branch, Frankrig
  • Vanessa Y Tan, MRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom., Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK., Storbritannien
  • Laura J Corbin, MRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom., Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK., Storbritannien
  • Karl Smith-Byrne, Genomic Epidemiology Branch, Frankrig
  • Karine Alcala, Genomic Epidemiology Branch, Frankrig
  • Claudia Langenberg, MRC Epidemiology Unit, University of Cambridge, Cambridge, U.K., Storbritannien
  • Isobel D Stewart, MRC Epidemiology Unit, University of Cambridge, Cambridge, U.K., Storbritannien
  • Adam S Butterworth, British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, British Heart Foundation Centre of Research Excellence, University of Cambridge, Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, The National Institute for Health Research Blood and Transplant Unit (NIHR BTRU) in Donor Health and Genomics, University of Cambridge, Cambridge, UK., Storbritannien
  • Praveen Surendran, British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, British Heart Foundation Centre of Research Excellence, University of Cambridge, Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Rutherford Fund Fellow, Department of Public Health and Primary Care, University of Cambridge, Storbritannien
  • David Achaintre, Nutrition and Metabolism Branch, Frankrig
  • Jerzy Adamski, Institute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Neuherberg, Institute of Biochemistry, Faculty of Medicine, University of Ljubljana, Chair of Experimental Genetics, School of Life Science, Weihenstephan, Technische Universität München, Freising, Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Tyskland
  • Pilar Amiano Exezarreta, Biodonostia Health Research Institute, Spanien
  • Manuela M Bergmann, German Institute of Human Nutrition Potsdam-Rehbrücke, Tyskland
  • Caroline J Bull, MRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom., Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK., School of Cellular and Molecular Medicine, University of Bristol, Bristol, United Kingdom., Bristol Renal, Translational Health Sciences, Bristol Medical School, University of Bristol, Storbritannien
  • Christina C Dahm
  • Audrey Gicquiau, Nutrition and Metabolism Branch, Frankrig
  • Graham G Giles, Cancer Epidemiology & Intelligence Division, Cancer Council of Victoria, 615 St Kilda Road, Melbourne, VIC, 3004, Australia., Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville Victoria, 3010, Australia., Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Australien
  • Marc J Gunter, Nutrition and Metabolism Branch, International Agency for Research on Cancer (IARC-WHO), Lyon, France.
  • ,
  • Toomas Haller, Estonian Genome Center, Institute of Genomics, University of Tartu, Tartu, Estonia., Estland
  • Arnulf Langhammer, Norwegian University for Science and Technology (NTNU), Nord-Trøndelag Hospital Trust, Norge
  • Tricia L Larose, Genomic Epidemiology Branch, HUNT Research Centre, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Levanger, Department of Community Medicine and Global Health, Institute of Health and Society, Faculty of Medicine, University of Oslo, Frankrig
  • Börje Ljungberg, University of Umeå, Umeå, Sweden., Sverige
  • Andres Metspalu, Estonian Genome Centre, Institute of Genomics, University of Tartu, 51010, Tartu, Estonia., Estland
  • Roger L Milne, Cancer Epidemiology & Intelligence Division, Cancer Council of Victoria, 615 St Kilda Road, Melbourne, VIC, 3004, Australia., Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville Victoria, 3010, Australia., Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Australien
  • David C Muller, Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK., Storbritannien
  • Therese H Nøst, Department of Community Medicine, Faculty of Health Sciences, UiT The Arctic University of Norway, Tromsø, Norge
  • Elin Pettersen Sørgjerd, Norwegian University for Science and Technology (NTNU), Norge
  • Cornelia Prehn, Metabolomics and Proteomics Core (MPC), Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Neuherberg, Tyskland
  • Elio Riboli, Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK., Storbritannien
  • Sabina Rinaldi, Nutrition and Metabolism Branch, Frankrig
  • Joseph A Rothwell, Université Paris-Saclay, UVSQ, Inserm, Gustave Roussy, Équipe "Exposome et Hérédité", CESP UMR1018, Inserm, Villejuif, Frankrig
  • Augustin Scalbert, Nutrition and Metabolism Branch, Frankrig
  • Julie A Schmidt, Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, England., Storbritannien
  • Gianluca Severi, Université Paris-Saclay, UVSQ, Inserm, Gustave Roussy, Équipe "Exposome et Hérédité", CESP UMR1018, Inserm, Villejuif, Department of Statistics, Computer Science and Applications "G Parenti" (DISIA), University of Florence, Storbritannien
  • Sabina Sieri, Epidemiology and Prevention Unit, Milan, Italy., Italien
  • Roel Vermeulen, Institute for Risk Assessment Sciences (IRAS), Utrecht University, Holland
  • Emma E Vincent, MRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom., Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK., School of Cellular and Molecular Medicine, University of Bristol, Bristol, United Kingdom., Bristol Renal, Translational Health Sciences, Bristol Medical School, University of Bristol, Storbritannien
  • Melanie Waldenberger, Research Unit Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Neuherberg, Tyskland
  • Nicholas J Timpson, MRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom., Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK., Storbritannien
  • Mattias Johansson, Genomic Epidemiology Branch, Frankrig

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.

OriginalsprogEngelsk
Artikelnummere1003786
TidsskriftPLOS Medicine
Vol/bind18
Nummer9
Antal sider26
ISSN1549-1277
DOI
StatusE-pub ahead of print - 20 sep. 2021

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