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Epidemiology of 40 blood biomarkers of one-carbon metabolism, vitamin status, inflammation, and renal and endothelial function among cancer-free older adults.
Zahed, Hana; Johansson, Mattias; Ueland, Per M; Midttun, Øivind; Milne, Roger L; Giles, Graham G; Manjer, Jonas; Sandsveden, Malte; Langhammer, Arnulf; Sørgjerd, Elin Pettersen; Grankvist, Kjell; Johansson, Mikael; Freedman, Neal D; Huang, Wen-Yi; Chen, Chu; Prentice, Ross; Stevens, Victoria L; Wang, Ying; Le Marchand, Loic; Wilkens, Lynne R; Weinstein, Stephanie J; Albanes, Demetrius; Cai, Qiuyin; Blot, William J; Arslan, Alan A; Zeleniuch-Jacquotte, Anne; Shu, Xiao-Ou; Zheng, Wei; Yuan, Jian-Min; Koh, Woon-Puay; Visvanathan, Kala; Sesso, Howard D; Zhang, Xuehong; Gaziano, J Michael; Fanidi, Anouar; Muller, David; Brennan, Paul; Guida, Florence; Robbins, Hilary A.
Affiliation
  • Zahed H; Genomic Epidemiology Branch, International Agency for Research on Cancer, 150 cours Albert Thomas, 69008, Lyon, France.
  • Johansson M; Genomic Epidemiology Branch, International Agency for Research on Cancer, 150 cours Albert Thomas, 69008, Lyon, France.
  • Ueland PM; Department of Clinical Science, University of Bergen, Bergen, Norway.
  • Midttun Ø; Bevital AS, Bergen, Norway.
  • Milne RL; Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Australia.
  • Giles GG; Centre for Epidemiology and Biostatistics, School of Population and Global Health, The University of Melbourne, Melbourne, Australia.
  • Manjer J; Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Melbourne, Australia.
  • Sandsveden M; Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Australia.
  • Langhammer A; Centre for Epidemiology and Biostatistics, School of Population and Global Health, The University of Melbourne, Melbourne, Australia.
  • Sørgjerd EP; Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Melbourne, Australia.
  • Grankvist K; Department of Surgery, Skane University Hospital, Malmö, Sweden.
  • Johansson M; Lund University, Malmö, Sweden.
  • Freedman ND; Department of Clinical Sciences Malmo, Lund University, Malmö, Sweden.
  • Huang WY; Department of Public Health and Nursing, Hunt Research Centre, Norwegian University of Science and Technology, Levanger, Norway.
  • Chen C; Levanger Hospital, Nord-Trøndelag Hospital Trust, Levanger, Norway.
  • Prentice R; Department of Public Health and Nursing, NTNU, Hunt Research Centre, Norwegian University of Science and Technology, Levanger, Norway.
  • Stevens VL; Department of Endocrinology, St. Olavs Hospital, Trondheim University Hospital, Levanger, Norway.
  • Wang Y; Department of Medical Biosciences, Umea University, Umeå, Sweden.
  • Le Marchand L; Department of Radiation Sciences, Oncology, Umea University, Umeå, Sweden.
  • Wilkens LR; Metabolic Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA.
  • Weinstein SJ; Metabolic Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA.
  • Albanes D; Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, USA.
  • Cai Q; Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, USA.
  • Blot WJ; American Cancer Society, Atlanta, USA.
  • Arslan AA; American Cancer Society, Atlanta, USA.
  • Zeleniuch-Jacquotte A; University of Hawai'i Cancer Center, University of Hawai'i at Manoa, Honolulu, USA.
  • Shu XO; University of Hawai'i Cancer Center, University of Hawai'i at Manoa, Honolulu, USA.
  • Zheng W; Metabolic Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA.
  • Yuan JM; Metabolic Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA.
  • Koh WP; Vanderbilt University Medical Center, Nashville, USA.
  • Visvanathan K; Vanderbilt University Medical Center, Nashville, USA.
  • Sesso HD; Department of Obstetrics and Gynecology, NYU Langone Health, New York, NY, USA.
  • Zhang X; Department of Population Health, NYU Langone Health, New York, NY, USA.
  • Gaziano JM; Perlmutter Comprehensive Cancer Center, NYU Langone Health, New York, NY, USA.
  • Fanidi A; Department of Population Health, NYU Langone Health, New York, NY, USA.
  • Muller D; Perlmutter Comprehensive Cancer Center, NYU Langone Health, New York, NY, USA.
  • Brennan P; Vanderbilt University Medical Center, Nashville, USA.
  • Guida F; Vanderbilt University Medical Center, Nashville, USA.
  • Robbins HA; University of Pittsburgh Medical Center, Pittsburgh, USA.
Sci Rep ; 11(1): 13805, 2021 07 05.
Article in En | MEDLINE | ID: mdl-34226613
Imbalances of blood biomarkers are associated with disease, and biomarkers may also vary non-pathologically across population groups. We described variation in concentrations of biomarkers of one-carbon metabolism, vitamin status, inflammation including tryptophan metabolism, and endothelial and renal function among cancer-free older adults. We analyzed 5167 cancer-free controls aged 40-80 years from 20 cohorts in the Lung Cancer Cohort Consortium (LC3). Centralized biochemical analyses of 40 biomarkers in plasma or serum were performed. We fit multivariable linear mixed effects models to quantify variation in standardized biomarker log-concentrations across four factors: age, sex, smoking status, and body mass index (BMI). Differences in most biomarkers across most factors were small, with 93% (186/200) of analyses showing an estimated difference lower than 0.25 standard-deviations, although most were statistically significant due to large sample size. The largest difference was for creatinine by sex, which was - 0.91 standard-deviations lower in women than men (95%CI - 0.98; - 0.84). The largest difference by age was for total cysteine (0.40 standard-deviation increase per 10-year increase, 95%CI 0.36; 0.43), and by BMI was for C-reactive protein (0.38 standard-deviation increase per 5-kg/m2 increase, 95%CI 0.34; 0.41). For 31 of 40 markers, the mean difference between current and never smokers was larger than between former and never smokers. A statistically significant (p < 0.05) association with time since smoking cessation was observed for 8 markers, including C-reactive protein, kynurenine, choline, and total homocysteine. We conclude that most blood biomarkers show small variations across demographic characteristics. Patterns by smoking status point to normalization of multiple physiological processes after smoking cessation.
Subject(s)

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Carbon / Biomarkers / Inflammation / Kidney Type of study: Prognostic_studies / Screening_studies Limits: Aged / Aged80 / Female / Humans / Male / Middle aged Language: En Journal: Sci Rep Year: 2021 Type: Article Affiliation country: France

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Carbon / Biomarkers / Inflammation / Kidney Type of study: Prognostic_studies / Screening_studies Limits: Aged / Aged80 / Female / Humans / Male / Middle aged Language: En Journal: Sci Rep Year: 2021 Type: Article Affiliation country: France