Circulating metabolic biomarkers of screen-detected prostate cancer in the ProtecT study

Charleen D. Adams, Rebecca Richmond, Diana L. Santos Ferreira, Wes Spiller, Vanessa Tan, Jie Zheng, Peter Würtz, Jenny Donovan, Freddie Hamdy, David Neal, J. Athene Lane, George Davey Smith, Caroline Relton, Rosalind A. Eeles, Christopher A. Haiman, ZSofia Kote-Jarai, Fredrick R. Schumacher, Ali Amin Al Olama, Sara Benlloch, Kenneth MuirSonja I. Berndt, David V. Conti, Fredrik Wiklund, Stephen J. Chanock, Susan Gapstur, Victoria L. Stevens, Catherine M. Tangen, Jyotsna Batra, Judith A. Clements, Henrik Gronberg, Nora Pashayan, Johanna Schleutker, Demetrius Albanes, Alicja Wolk, Catharine M.L. West, Lorelei A. Mucci, Géraldine Cancel-Tassin, Stella Koutros, Karina Dalsgaard Sorensen, Lovise Maehle, Ruth C. Travis, Robert J. Hamilton, Sue Ann Ingles, Barry S. Rosenstein, Yong Jie Lu, Graham G. Giles, Adam S. Kibel, Ana Vega, Manolis Kogevinas, Kathryn L. Penney, Jong Y. Park, Janet L. Stanford, Cezary Cybulski, Børge G. Nordestgaard, Hermann Brenner, Christiane Maier, Jeri Kim, Esther M. John, Manuel R. Teixeira, Susan L. Neuhausen, Kim De Ruyck, Azad Razack, Lisa F. Newcomb, Davor Lessel, Radka P. Kaneva, Nawaid Usmani, Frank Claessens, Paul A. Townsend, Manuela Gago Dominguez, Monique J. Roobol, Florence Menegaux, Kay Tee Khaw, Lisa A. Cannon-Albright, Hardev Pandha, Stephen N. Thibodeau, on behalf of the PRACTICAL consortium, Richard M. Martin

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6 Citations (Scopus)

Abstract

Background: Whether associations between circulating metabolites and prostate cancer are causal is unknown. We report on the largest study of metabolites and prostate cancer (2,291 cases and 2,661 controls) and appraise causality for a subset of the prostate cancer–metabolite associations using two-sample Mendelian randomization (MR). Methods: The case–control portion of the study was conducted in nine UK centers with men ages 50–69 years who underwent prostate-specific antigen screening for prostate cancer within the Prostate Testing for Cancer and Treatment (ProtecT) trial. Two data sources were used to appraise causality: a genome-wide association study (GWAS) of metabolites in 24,925 participants and a GWAS of prostate cancer in 44,825 cases and 27,904 controls within the Association Group to Investigate Cancer Associated Alterations in the Genome (PRACTICAL) consortium. Results: Thirty-five metabolites were strongly associated with prostate cancer (P < 0.0014, multiple-testing threshold). These fell into four classes: (i) lipids and lipoprotein subclass characteristics (total cholesterol and ratios, cholesterol esters and ratios, free cholesterol and ratios, phospholipids and ratios, and triglyceride ratios); (ii) fatty acids and ratios; (iii) amino acids; (iv) and fluid balance. Fourteen top metabolites were proxied by genetic variables, but MR indicated these were not causal. Conclusions: We identified 35 circulating metabolites associated with prostate cancer presence, but found no evidence of causality for those 14 testable with MR. Thus, the 14 MR-tested metabolites are unlikely to be mechanistically important in prostate cancer risk. Impact: The metabolome provides a promising set of biomarkers that may aid prostate cancer classification.

Original languageEnglish
Pages (from-to)208-216
Number of pages9
JournalCancer Epidemiology, Biomarkers & Prevention
Volume28
Issue number1
DOIs
Publication statusPublished - Jan 2019
Externally publishedYes

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