Circulating Metabolic Biomarkers of Screen-Detected Prostate Cancer in the ProtecT Study.
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Date
2019-01-01Author
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, Y-J
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, K-T
Cannon-Albright, LA
Pandha, H
Thibodeau, SN
Martin, RM
PRACTICAL consortium,
Type
Journal Article
Metadata
Show full item recordAbstract
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.
Collections
Subject
PRACTICAL consortium
Humans
Prostatic Neoplasms
Cholesterol
Prostate-Specific Antigen
Triglycerides
Phospholipids
Case-Control Studies
Aged
Middle Aged
Male
Genome-Wide Association Study
Metabolome
Mendelian Randomization Analysis
Biomarkers, Tumor
United Kingdom
Research team
Oncogenetics
Language
eng
Date accepted
2018-10-15
License start date
2019-01
Citation
Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology, 2019, 28 (1), pp. 208 - 216
Publisher
AMER ASSOC CANCER RESEARCH