Circulating Metabolic Biomarkers of Screen-Detected Prostate Cancer in the ProtecT Study
Authors
Adams, CRichmond, RC
Santos Ferreira, DL
Spiller, W
Tan, VY
Zheng, J
Wurtz, P
Donovan, JL
Hamdy, FC
Neal, DE
Lane, JA
Davey, SG
Relton, CL
Eeles, RA
Henderson, BE
Haiman, CA
Kote-Jarai, Z
Schumacher, FR
Amin, Al, OA
Benlloch, S
Muir, K
Berndt, SI
Conti, DV
Wiklund, F
Chanock, SJ
Gapstur, SM
Stevens, VL
Tangen, CM
Batra, J
Clements, JA
Gronberg, H
Pashayan, N
Schleutker, J
Albanes, D
Wolk, A
West, Catharine M L
Mucci, LA
Cancel-Tassin, G
Koutros, S
Sorensen, KD
Maehle, L
Travis, RC
Hamilton, R
Ingles, SA
Rosenstein, BS
Lu, YJ
Giles, GG
Kibel, AS
Vega, A
Kogevinas, M
Penney, KL
Park, JY
Stanford, JL
Cybulski, C
Nordestgaard, BG
Brenner, H
Maier, C
Kim, J
John, EM
Teixeira, MR
Neuhausen, SL
DeRuyck, K
Razack, A
Newcomb, LF
Lessel, D
Kaneva, RP
Usmani, N
Claessens, F
Townsend, P
Gago, DM
Roobol, MJ
Menegaux, F
Khaw, KT
Cannon-Albright, LA
Pandha, H
Thibodeau, SN
Martin, RM
Affiliation
City of Hope MRC Integrative Epidemiology Unit, University of BristolIssue Date
2018
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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). MATERIALS AND METHODS: The case-control portion of the study was conducted in nine UK centres with men aged 50-69 years who underwent prostate-specific antigen (PSA) 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.Citation
Adams C, Richmond RC, Santos Ferreira DL, Spiller W, Tan VY, Zheng J, et al. Circulating Metabolic Biomarkers of Screen-Detected Prostate Cancer in the ProtecT Study. Cancer Epidemiology Biomarkers & Prevention. 2018 Oct 23;cebp.0079.2018.Journal
Cancer Epidemiol Biomarkers PrevDOI
10.1158/1055-9965.EPI-18-0079PubMed ID
30352818Additional Links
https://dx.doi.org/10.1158/1055-9965.EPI-18-0079Type
ArticleLanguage
enae974a485f413a2113503eed53cd6c53
10.1158/1055-9965.EPI-18-0079
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