Pre-diagnostic metabolite concentrations and prostate cancer risk in 1077 cases and 1077 matched controls in the European Prospective Investigation into ... View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2017-07-05

AUTHORS

Julie A. Schmidt, Georgina K. Fensom, Sabina Rinaldi, Augustin Scalbert, Paul N. Appleby, David Achaintre, Audrey Gicquiau, Marc J. Gunter, Pietro Ferrari, Rudolf Kaaks, Tilman Kühn, Anna Floegel, Heiner Boeing, Antonia Trichopoulou, Pagona Lagiou, Eleutherios Anifantis, Claudia Agnoli, Domenico Palli, Morena Trevisan, Rosario Tumino, H. Bas Bueno-de-Mesquita, Antonio Agudo, Nerea Larrañaga, Daniel Redondo-Sánchez, Aurelio Barricarte, José Maria Huerta, J. Ramón Quirós, Nick Wareham, Kay-Tee Khaw, Aurora Perez-Cornago, Mattias Johansson, Amanda J. Cross, Konstantinos K. Tsilidis, Elio Riboli, Timothy J. Key, Ruth C. Travis

ABSTRACT

BACKGROUND: Little is known about how pre-diagnostic metabolites in blood relate to risk of prostate cancer. We aimed to investigate the prospective association between plasma metabolite concentrations and risk of prostate cancer overall, and by time to diagnosis and tumour characteristics, and risk of death from prostate cancer. METHODS: In a case-control study nested in the European Prospective Investigation into Cancer and Nutrition, pre-diagnostic plasma concentrations of 122 metabolites (including acylcarnitines, amino acids, biogenic amines, glycerophospholipids, hexose and sphingolipids) were measured using targeted mass spectrometry (AbsoluteIDQ p180 Kit) and compared between 1077 prostate cancer cases and 1077 matched controls. Risk of prostate cancer associated with metabolite concentrations was estimated by multi-variable conditional logistic regression, and multiple testing was accounted for by using a false discovery rate controlling procedure. RESULTS: Seven metabolite concentrations, i.e. acylcarnitine C18:1, amino acids citrulline and trans-4-hydroxyproline, glycerophospholipids PC aa C28:1, PC ae C30:0 and PC ae C30:2, and sphingolipid SM (OH) C14:1, were associated with prostate cancer (p < 0.05), but none of the associations were statistically significant after controlling for multiple testing. Citrulline was associated with a decreased risk of prostate cancer (odds ratio (OR1SD) = 0.73; 95% confidence interval (CI) 0.62-0.86; p trend = 0.0002) in the first 5 years of follow-up after taking multiple testing into account, but not after longer follow-up; results for other metabolites did not vary by time to diagnosis. After controlling for multiple testing, 12 glycerophospholipids were inversely associated with advanced stage disease, with risk reduction up to 46% per standard deviation increase in concentration (OR1SD = 0.54; 95% CI 0.40-0.72; p trend = 0.00004 for PC aa C40:3). Death from prostate cancer was associated with higher concentrations of acylcarnitine C3, amino acids methionine and trans-4-hydroxyproline, biogenic amine ADMA, hexose and sphingolipid SM (OH) C14:1 and lower concentration of glycerophospholipid PC aa C42:4. CONCLUSIONS: Several metabolites, i.e. C18:1, citrulline, trans-4-hydroxyproline, three glycerophospholipids and SM (OH) C14:1, might be related to prostate cancer. Analyses by time to diagnosis indicated that citrulline may be a marker of subclinical prostate cancer, while other metabolites might be related to aetiology. Several glycerophospholipids were inversely related to advanced stage disease. More prospective data are needed to confirm these associations. More... »

PAGES

122

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  • Journal

    TITLE

    BMC Medicine

    ISSUE

    1

    VOLUME

    15

    Author Affiliations

  • Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, OX3 7LF UK
  • International Agency for Research on Cancer, 69372 Lyon, CEDEX 08 France
  • Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, W2 1PG UK
  • Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Foundation under Public Law, DE-69120 Heidelberg, Germany
  • Department of Epidemiology, German Institute of Human Nutrition (DIfE) Potsdam-Rehbrücke, DE-14558 Nuthetal, Germany
  • WHO Collaborating Center for Nutrition and Health, Unit of Nutritional Epidemiology and Nutrition in Public Health, Department of Hygiene, Epidemiology and Medical Statistics, School of Medicine, National and Kapodistrian University of Athens, GR-11527 Athens, Greece
  • Department of Epidemiology, Harvard T. H. Chan School of Public Health, 02115 Boston, Massachusetts USA
  • Hellenic Health Foundation, GR-11527 Athens, Greece
  • Epidemiology and Prevention Unit, Fondazione IRCCS Istituto Nazionale dei Tumori, Via Venezian, 1, 20133 Milano, Italy
  • Cancer Risk Factors and Life-Style Epidemiology Unit, Cancer Research and Prevention Institute – ISPO, 50134 Florence, Italy
  • CPO-Piemonte, 10126 Turin, Italy
  • Cancer Registry and Histopathology Unit, “Civic-M.P.Arezzo” Hospital, ASP 97100 Ragusa, Italy
  • Department for Determinants of Chronic Diseases (DCD), National Institute for Public Health and the Environment (RIVM), 3720 BA Bilthoven, The Netherlands
  • Unit of Nutrition and Cancer, Cancer Epidemiology Research Program, Catalan Institute of Oncology-IDIBELL, 08908 L’Hospitalet de Llobregat Barcelona, Spain
  • CIBER of Epidemiology and Public Health (CIBERESP), Madrid, Spain
  • Escuela Andaluza de Salud Pública, Instituto de Investigación Biosanitaria ibs.GRANADA, Hospitales Universitarios de Granada/Universidad de Granada, 18012 Granada, Spain
  • Navarra Institute for Health Research (IdiSNA) Pamplona, Pamplona, Spain
  • Department of Epidemiology, Murcia Regional Health Council, IMIB-Arrixaca, 30003 Murcia, Spain
  • Public Health Directorate, 33006 Asturias, Spain
  • MRC Epidemiology Unit, University of Cambridge, CB2 0SR Cambridge, UK
  • School of Clinical Medicine, University of Cambridge, CB2 2QQ Cambridge, UK
  • Department of Hygiene and Epidemiology, School of Medicine, University of Ioannina, 45110 Ioannina, Greece
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1186/s12916-017-0885-6

    DOI

    http://dx.doi.org/10.1186/s12916-017-0885-6

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1090255103

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/28676103


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        "description": "BACKGROUND: Little is known about how pre-diagnostic metabolites in blood relate to risk of prostate cancer. We aimed to investigate the prospective association between plasma metabolite concentrations and risk of prostate cancer overall, and by time to diagnosis and tumour characteristics, and risk of death from prostate cancer.\nMETHODS: In a case-control study nested in the European Prospective Investigation into Cancer and Nutrition, pre-diagnostic plasma concentrations of 122 metabolites (including acylcarnitines, amino acids, biogenic amines, glycerophospholipids, hexose and sphingolipids) were measured using targeted mass spectrometry (AbsoluteIDQ p180 Kit) and compared between 1077 prostate cancer cases and 1077 matched controls. Risk of prostate cancer associated with metabolite concentrations was estimated by multi-variable conditional logistic regression, and multiple testing was accounted for by using a false discovery rate controlling procedure.\nRESULTS: Seven metabolite concentrations, i.e. acylcarnitine C18:1, amino acids citrulline and trans-4-hydroxyproline, glycerophospholipids PC aa C28:1, PC ae C30:0 and PC ae C30:2, and sphingolipid SM (OH) C14:1, were associated with prostate cancer (p\u2009<\u20090.05), but none of the associations were statistically significant after controlling for multiple testing. Citrulline was associated with a decreased risk of prostate cancer (odds ratio (OR1SD)\u2009=\u20090.73; 95% confidence interval (CI) 0.62-0.86; p trend\u2009=\u20090.0002) in the first 5\u00a0years of follow-up after taking multiple testing into account, but not after longer follow-up; results for other metabolites did not vary by time to diagnosis. After controlling for multiple testing, 12 glycerophospholipids were inversely associated with advanced stage disease, with risk reduction up to 46% per standard deviation increase in concentration (OR1SD\u2009=\u20090.54; 95% CI 0.40-0.72; p trend\u2009=\u20090.00004 for PC aa C40:3). Death from prostate cancer was associated with higher concentrations of acylcarnitine C3, amino acids methionine and trans-4-hydroxyproline, biogenic amine ADMA, hexose and sphingolipid SM (OH) C14:1 and lower concentration of glycerophospholipid PC aa C42:4.\nCONCLUSIONS: Several metabolites, i.e. C18:1, citrulline, trans-4-hydroxyproline, three glycerophospholipids and SM (OH) C14:1, might be related to prostate cancer. Analyses by time to diagnosis indicated that citrulline may be a marker of subclinical prostate cancer, while other metabolites might be related to aetiology. Several glycerophospholipids were inversely related to advanced stage disease. More prospective data are needed to confirm these associations.", 
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    33 schema:description BACKGROUND: Little is known about how pre-diagnostic metabolites in blood relate to risk of prostate cancer. We aimed to investigate the prospective association between plasma metabolite concentrations and risk of prostate cancer overall, and by time to diagnosis and tumour characteristics, and risk of death from prostate cancer. METHODS: In a case-control study nested in the European Prospective Investigation into Cancer and Nutrition, pre-diagnostic plasma concentrations of 122 metabolites (including acylcarnitines, amino acids, biogenic amines, glycerophospholipids, hexose and sphingolipids) were measured using targeted mass spectrometry (AbsoluteIDQ p180 Kit) and compared between 1077 prostate cancer cases and 1077 matched controls. Risk of prostate cancer associated with metabolite concentrations was estimated by multi-variable conditional logistic regression, and multiple testing was accounted for by using a false discovery rate controlling procedure. RESULTS: Seven metabolite concentrations, i.e. acylcarnitine C18:1, amino acids citrulline and trans-4-hydroxyproline, glycerophospholipids PC aa C28:1, PC ae C30:0 and PC ae C30:2, and sphingolipid SM (OH) C14:1, were associated with prostate cancer (p &lt; 0.05), but none of the associations were statistically significant after controlling for multiple testing. Citrulline was associated with a decreased risk of prostate cancer (odds ratio (OR<sub>1SD</sub>) = 0.73; 95% confidence interval (CI) 0.62-0.86; p <sub>trend</sub> = 0.0002) in the first 5 years of follow-up after taking multiple testing into account, but not after longer follow-up; results for other metabolites did not vary by time to diagnosis. After controlling for multiple testing, 12 glycerophospholipids were inversely associated with advanced stage disease, with risk reduction up to 46% per standard deviation increase in concentration (OR<sub>1SD</sub> = 0.54; 95% CI 0.40-0.72; p <sub>trend</sub> = 0.00004 for PC aa C40:3). Death from prostate cancer was associated with higher concentrations of acylcarnitine C3, amino acids methionine and trans-4-hydroxyproline, biogenic amine ADMA, hexose and sphingolipid SM (OH) C14:1 and lower concentration of glycerophospholipid PC aa C42:4. CONCLUSIONS: Several metabolites, i.e. C18:1, citrulline, trans-4-hydroxyproline, three glycerophospholipids and SM (OH) C14:1, might be related to prostate cancer. Analyses by time to diagnosis indicated that citrulline may be a marker of subclinical prostate cancer, while other metabolites might be related to aetiology. Several glycerophospholipids were inversely related to advanced stage disease. More prospective data are needed to confirm these associations.
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