Circulating Metabolic Biomarkers of Screen-Detected Prostate Cancer in the ProtecT Study.
Circulating Metabolic Biomarkers of Screen-Detected Prostate Cancer in the ProtecT Study.
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DOI：
10.1158/1055-9965.epi-18-0079
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发表时间：
2019-01
期刊：
影响因子：
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通讯作者：
PRACTICAL consortium
中科院分区：
文献类型：
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作者：
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
循环代谢物和前列腺癌之间的关联是否是因果关系尚不清楚。我们报告了代谢物和前列腺癌的最大研究（2，291例病例和2，661例对照），并使用双样本孟德尔随机化（MR）评估前列腺癌-代谢物关联子集的因果关系。该研究的病例对照部分在9个英国中心进行，年龄在50-69岁之间的男性在前列腺检测癌症和治疗（ProtecT）试验中接受前列腺特异性抗原（PSA）筛查。两个数据源用于评估因果关系：24，925名参与者的代谢物全基因组关联研究（GWAS）和44，825例前列腺癌病例和27，904例对照组中的GWAS，该研究属于研究基因组中癌症相关改变（PRACTICAL）联盟。35种代谢物与前列腺癌密切相关（p <0.0014，多重检验阈值）。这些问题分为四类：i）脂质和脂蛋白亚类特征（总胆固醇和比率、胆固醇酯和比率、游离胆固醇和比率、磷脂和比率以及甘油三酯比率）; ii）脂肪酸和比率; iii）氨基酸; iv）和体液平衡。14种顶级代谢物由遗传变量代理，但MR表明这些不是因果关系。我们确定了35种与前列腺癌存在相关的循环代谢物，但没有发现14种可用MR检测的因果关系的证据。因此，14种MR检测的代谢物在前列腺癌风险中不太可能具有机械重要性。代谢组提供了一组有希望的生物标志物，可以帮助前列腺癌分类。
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). 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. 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. 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. The metabolome provides a promising set of biomarkers that may aid prostate cancer classification.