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

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 an...

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Autores principales: Guida, 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, 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, Börje, Metspalu, Andres, Milne, Roger L., Muller, David C., Nøst, Therese H., Pettersen Sørgjerd, Elin, 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
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8496779/
https://www.ncbi.nlm.nih.gov/pubmed/34543281
http://dx.doi.org/10.1371/journal.pmed.1003786
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author Guida, 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, 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, Börje
Metspalu, Andres
Milne, Roger L.
Muller, David C.
Nøst, Therese H.
Pettersen Sørgjerd, Elin
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
author_facet Guida, 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, 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, Börje
Metspalu, Andres
Milne, Roger L.
Muller, David C.
Nøst, Therese H.
Pettersen Sørgjerd, Elin
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
author_sort Guida, Florence
collection PubMed
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 [ß(BMI)] 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 (ß(BMI): 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.
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spelling pubmed-84967792021-10-08 The blood metabolome of incident kidney cancer: A case–control study nested within the MetKid consortium Guida, 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, 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, Börje Metspalu, Andres Milne, Roger L. Muller, David C. Nøst, Therese H. Pettersen Sørgjerd, Elin 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 PLoS Med Research Article 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 [ß(BMI)] 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 (ß(BMI): 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. Public Library of Science 2021-09-20 /pmc/articles/PMC8496779/ /pubmed/34543281 http://dx.doi.org/10.1371/journal.pmed.1003786 Text en © 2021 Guida et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Guida, 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, 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, Börje
Metspalu, Andres
Milne, Roger L.
Muller, David C.
Nøst, Therese H.
Pettersen Sørgjerd, Elin
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
The blood metabolome of incident kidney cancer: A case–control study nested within the MetKid consortium
title The blood metabolome of incident kidney cancer: A case–control study nested within the MetKid consortium
title_full The blood metabolome of incident kidney cancer: A case–control study nested within the MetKid consortium
title_fullStr The blood metabolome of incident kidney cancer: A case–control study nested within the MetKid consortium
title_full_unstemmed The blood metabolome of incident kidney cancer: A case–control study nested within the MetKid consortium
title_short The blood metabolome of incident kidney cancer: A case–control study nested within the MetKid consortium
title_sort blood metabolome of incident kidney cancer: a case–control study nested within the metkid consortium
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8496779/
https://www.ncbi.nlm.nih.gov/pubmed/34543281
http://dx.doi.org/10.1371/journal.pmed.1003786
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