title: Serum biomarkers of habitual coffee consumption may provide insight into the mechanism underlying the association between coffee consumption and colorectal cancer.
abstract: BACKGROUND
  Coffee intake may be inversely associated with colorectal cancer; however, previous studies have been inconsistent. Serum coffee metabolites are integrated exposure measures that may clarify associations with cancer and elucidate underlying mechanisms.
  
  
  OBJECTIVE
  Our aims were 2-fold as follows: 1) to identify serum metabolites associated with coffee intake and 2) to examine these metabolites in relation to colorectal cancer.
  
  
  METHODS
  In a nested case-control study of 251 colorectal cancer cases and 247 matched control subjects from the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial, we conducted untargeted metabolomics analyses of baseline serum by using ultrahigh-performance liquid-phase chromatography-tandem mass spectrometry and gas chromatography-mass spectrometry. Usual coffee intake was self-reported in a food-frequency questionnaire. We used partial Pearson correlations and linear regression to identify serum metabolites associated with coffee intake and conditional logistic regression to evaluate associations between coffee metabolites and colorectal cancer.
  
  
  RESULTS
  After Bonferroni correction for multiple comparisons (P = 0.05 ÷ 657 metabolites), 29 serum metabolites were positively correlated with coffee intake (partial correlation coefficients: 0.18-0.61; P < 7.61 × 10(-5)); serum metabolites most highly correlated with coffee intake (partial correlation coefficients >0.40) included trigonelline (N'-methylnicotinate), quinate, and 7 unknown metabolites. Of 29 serum metabolites, 8 metabolites were directly related to caffeine metabolism, and 3 of these metabolites, theophylline (OR for 90th compared with 10th percentiles: 0.44; 95% CI: 0.25, 0.79; P-linear trend = 0.006), caffeine (OR for 90th compared with 10th percentiles: 0.56; 95% CI: 0.35, 0.89; P-linear trend = 0.015), and paraxanthine (OR for 90th compared with 10th percentiles: 0.58; 95% CI: 0.36, 0.94; P-linear trend = 0.027), were inversely associated with colorectal cancer.
  
  
  CONCLUSIONS
  Serum metabolites can distinguish coffee drinkers from nondrinkers; some caffeine-related metabolites were inversely associated with colorectal cancer and should be studied further to clarify the role of coffee in the cause of colorectal cancer. The Prostate, Lung, Colorectal, and Ovarian trial was registered at clinicaltrials.gov as NCT00002540.
authors.affiliation: From the Nutritional Epidemiology Branch (KAG, EL, SCM, QX, NDF, and RS), the Biostatistics Branch (JNS), and the Occupational and Environmental Epidemiology Branch (W-YH), Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Department of Health and Human Services, Bethesda, MD; the Innovation Center for Biomedical Informatics and Department of Oncology, Georgetown University Medical Center, Washington, DC (SMB); Information Management Services Inc., Silver Spring, MD (XX); and the Department of Epidemiology and Biostatistics, School of Public Health, Faculty of Medicine, Imperial College London, St. Mary's Campus, Norfolk Place, London, United Kingdom (AJC).
authors.forename: Kristin A
authors.initials: KA
authors.lastname: Guertin
authors.affiliation: From the Nutritional Epidemiology Branch (KAG, EL, SCM, QX, NDF, and RS), the Biostatistics Branch (JNS), and the Occupational and Environmental Epidemiology Branch (W-YH), Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Department of Health and Human Services, Bethesda, MD; the Innovation Center for Biomedical Informatics and Department of Oncology, Georgetown University Medical Center, Washington, DC (SMB); Information Management Services Inc., Silver Spring, MD (XX); and the Department of Epidemiology and Biostatistics, School of Public Health, Faculty of Medicine, Imperial College London, St. Mary's Campus, Norfolk Place, London, United Kingdom (AJC).
authors.forename: Erikka
authors.initials: E
authors.lastname: Loftfield
authors.affiliation: From the Nutritional Epidemiology Branch (KAG, EL, SCM, QX, NDF, and RS), the Biostatistics Branch (JNS), and the Occupational and Environmental Epidemiology Branch (W-YH), Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Department of Health and Human Services, Bethesda, MD; the Innovation Center for Biomedical Informatics and Department of Oncology, Georgetown University Medical Center, Washington, DC (SMB); Information Management Services Inc., Silver Spring, MD (XX); and the Department of Epidemiology and Biostatistics, School of Public Health, Faculty of Medicine, Imperial College London, St. Mary's Campus, Norfolk Place, London, United Kingdom (AJC).
authors.forename: Simina M
authors.initials: SM
authors.lastname: Boca
authors.affiliation: From the Nutritional Epidemiology Branch (KAG, EL, SCM, QX, NDF, and RS), the Biostatistics Branch (JNS), and the Occupational and Environmental Epidemiology Branch (W-YH), Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Department of Health and Human Services, Bethesda, MD; the Innovation Center for Biomedical Informatics and Department of Oncology, Georgetown University Medical Center, Washington, DC (SMB); Information Management Services Inc., Silver Spring, MD (XX); and the Department of Epidemiology and Biostatistics, School of Public Health, Faculty of Medicine, Imperial College London, St. Mary's Campus, Norfolk Place, London, United Kingdom (AJC).
authors.forename: Joshua N
authors.initials: JN
authors.lastname: Sampson
authors.affiliation: From the Nutritional Epidemiology Branch (KAG, EL, SCM, QX, NDF, and RS), the Biostatistics Branch (JNS), and the Occupational and Environmental Epidemiology Branch (W-YH), Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Department of Health and Human Services, Bethesda, MD; the Innovation Center for Biomedical Informatics and Department of Oncology, Georgetown University Medical Center, Washington, DC (SMB); Information Management Services Inc., Silver Spring, MD (XX); and the Department of Epidemiology and Biostatistics, School of Public Health, Faculty of Medicine, Imperial College London, St. Mary's Campus, Norfolk Place, London, United Kingdom (AJC).
authors.forename: Steven C
authors.initials: SC
authors.lastname: Moore
authors.affiliation: From the Nutritional Epidemiology Branch (KAG, EL, SCM, QX, NDF, and RS), the Biostatistics Branch (JNS), and the Occupational and Environmental Epidemiology Branch (W-YH), Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Department of Health and Human Services, Bethesda, MD; the Innovation Center for Biomedical Informatics and Department of Oncology, Georgetown University Medical Center, Washington, DC (SMB); Information Management Services Inc., Silver Spring, MD (XX); and the Department of Epidemiology and Biostatistics, School of Public Health, Faculty of Medicine, Imperial College London, St. Mary's Campus, Norfolk Place, London, United Kingdom (AJC).
authors.forename: Qian
authors.initials: Q
authors.lastname: Xiao
authors.affiliation: From the Nutritional Epidemiology Branch (KAG, EL, SCM, QX, NDF, and RS), the Biostatistics Branch (JNS), and the Occupational and Environmental Epidemiology Branch (W-YH), Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Department of Health and Human Services, Bethesda, MD; the Innovation Center for Biomedical Informatics and Department of Oncology, Georgetown University Medical Center, Washington, DC (SMB); Information Management Services Inc., Silver Spring, MD (XX); and the Department of Epidemiology and Biostatistics, School of Public Health, Faculty of Medicine, Imperial College London, St. Mary's Campus, Norfolk Place, London, United Kingdom (AJC).
authors.forename: Wen-Yi
authors.initials: WY
authors.lastname: Huang
authors.affiliation: From the Nutritional Epidemiology Branch (KAG, EL, SCM, QX, NDF, and RS), the Biostatistics Branch (JNS), and the Occupational and Environmental Epidemiology Branch (W-YH), Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Department of Health and Human Services, Bethesda, MD; the Innovation Center for Biomedical Informatics and Department of Oncology, Georgetown University Medical Center, Washington, DC (SMB); Information Management Services Inc., Silver Spring, MD (XX); and the Department of Epidemiology and Biostatistics, School of Public Health, Faculty of Medicine, Imperial College London, St. Mary's Campus, Norfolk Place, London, United Kingdom (AJC).
authors.forename: Xiaoqin
authors.initials: X
authors.lastname: Xiong
authors.affiliation: From the Nutritional Epidemiology Branch (KAG, EL, SCM, QX, NDF, and RS), the Biostatistics Branch (JNS), and the Occupational and Environmental Epidemiology Branch (W-YH), Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Department of Health and Human Services, Bethesda, MD; the Innovation Center for Biomedical Informatics and Department of Oncology, Georgetown University Medical Center, Washington, DC (SMB); Information Management Services Inc., Silver Spring, MD (XX); and the Department of Epidemiology and Biostatistics, School of Public Health, Faculty of Medicine, Imperial College London, St. Mary's Campus, Norfolk Place, London, United Kingdom (AJC).
authors.forename: Neal D
authors.initials: ND
authors.lastname: Freedman
authors.affiliation: From the Nutritional Epidemiology Branch (KAG, EL, SCM, QX, NDF, and RS), the Biostatistics Branch (JNS), and the Occupational and Environmental Epidemiology Branch (W-YH), Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Department of Health and Human Services, Bethesda, MD; the Innovation Center for Biomedical Informatics and Department of Oncology, Georgetown University Medical Center, Washington, DC (SMB); Information Management Services Inc., Silver Spring, MD (XX); and the Department of Epidemiology and Biostatistics, School of Public Health, Faculty of Medicine, Imperial College London, St. Mary's Campus, Norfolk Place, London, United Kingdom (AJC).
authors.forename: Amanda J
authors.initials: AJ
authors.lastname: Cross
authors.affiliation: From the Nutritional Epidemiology Branch (KAG, EL, SCM, QX, NDF, and RS), the Biostatistics Branch (JNS), and the Occupational and Environmental Epidemiology Branch (W-YH), Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Department of Health and Human Services, Bethesda, MD; the Innovation Center for Biomedical Informatics and Department of Oncology, Georgetown University Medical Center, Washington, DC (SMB); Information Management Services Inc., Silver Spring, MD (XX); and the Department of Epidemiology and Biostatistics, School of Public Health, Faculty of Medicine, Imperial College London, St. Mary's Campus, Norfolk Place, London, United Kingdom (AJC).
authors.forename: Rashmi
authors.initials: R
authors.lastname: Sinha
mesh_terms: D000368:Aged; D015415:Biomarkers / Q000097:blood*; D016022:Case-Control Studies; D003069:Coffee; D015179:Colorectal Neoplasms / Q000517:prevention & control*; D005247:Feeding Behavior; D008401:Gas Chromatography-Mass Spectrometry; D006801:Humans; D016015:Logistic Models; D055432:Metabolomics; D008875:Middle Aged; D016032:Randomized Controlled Trials as Topic; D012307:Risk Factors
chemical_list: D015415:Biomarkers; D003069:Coffee
keywords: coffee; colorectal cancer; dietary intake; metabolites; metabolomics