Circulating Metabolic Biomarkers of Screen-Detected Prostate Cancer in the ProtecT Study.

Author(s): Adams CD,  Richmond R,  Ferreira DLS,  Spiller W,  Tan V,  Zheng J,  Würtz P,  Donovan J,  Hamdy F,  Neal D,  Lane JA,  Smith GD,  Relton C,  Eeles RA,  Haiman CA,  Kote-Jarai Z,  Schumacher FR,  Olama AAA,  Benlloch S,  Muir K,  Berndt SI,  Conti DV,  Wiklund F,  Chanock SJ,  Gapstur S,  Stevens VL,  Tangen CM,  Batra J,  Clements JA,  Gronberg H,  Pashayan N,  Schleutker J,  Albanes D,  Wolk A,  West CML,  Mucci LA,  Cancel-Tassin G,  Koutros S,  Sorensen KD,  Maehle L,  Travis RC,  Hamilton RJ,  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,  De Ruyck K,  Razack A,  Newcomb LF,  Lessel D,  Kaneva RP,  Usmani N,  Claessens F,  Townsend PA,  Dominguez MG,  Roobol MJ,  Menegaux F,  Khaw KT,  Cannon-Albright LA,  Pandha H,  Thibodeau SN,  Martin RM,  PRACTICAL consortium

Journal: Cancer Epidemiol Biomarkers Prev

Date: 2019 Jan

Major Program(s) or Research Group(s): NCORP

PubMed ID: 30352818

PMC ID: PMC6746173

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.