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A Metabolomics Analysis of Adiposity and Advanced Prostate Cancer Risk in the Health Professionals Follow-Up Study.
Dickerman, Barbra A; Ebot, Ericka M; Healy, Brian C; Wilson, Kathryn M; Eliassen, A Heather; Ascherio, Alberto; Pernar, Claire H; Zeleznik, Oana A; Vander Heiden, Matthew G; Clish, Clary B; Giovannucci, Edward; Mucci, Lorelei A.
Afiliação
  • Dickerman BA; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA.
  • Ebot EM; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA.
  • Healy BC; Department of Neurology, Harvard Medical School, Boston, MA 02115, USA.
  • Wilson KM; Partners Multiple Sclerosis Center, Brigham and Women's Hospital, Boston, MA 02115, USA.
  • Eliassen AH; Biostatistics Center, Massachusetts General Hospital, Boston, MA 02114, USA.
  • Ascherio A; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA.
  • Pernar CH; Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02115, USA.
  • Zeleznik OA; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA.
  • Vander Heiden MG; Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02115, USA.
  • Clish CB; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA.
  • Giovannucci E; Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02115, USA.
  • Mucci LA; Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA.
Metabolites ; 10(3)2020 Mar 10.
Article em En | MEDLINE | ID: mdl-32164144
Obesity is associated with a higher risk of advanced prostate cancer, but men with the same body mass index (BMI) may differ in their underlying metabolic health. Using metabolomics data from nested case-control studies in the Health Professionals Follow-Up Study, we calculated Pearson correlations between 165 circulating metabolites and three adiposity measures (BMI, waist circumference, and derived fat mass from a validated prediction equation) to identify adiposity-associated metabolites. We used Lasso to further select metabolites for prediction models of adiposity measures, which we used to calculate metabolic scores representing metabolic obesity. In an independent set of 212 advanced prostate cancer cases (T3b/T4/N1/M1 or lethal during follow-up) and 212 controls, we used logistic regression to evaluate the associations between adiposity measures and metabolic scores with risk of advanced disease. All adiposity measures were associated with higher blood levels of carnitines (Pearson r range, 0.16 to 0.18) and lower levels of glutamine (r = -0.19) and glycine (r, -0.29 to -0.20), in addition to alterations in various lipids. No adiposity measure or metabolic score was associated with risk of advanced prostate cancer (e.g., odds ratio for a 5 kg/m2 increase in BMI 0.96 (95% CI: 0.73, 1.27) and BMI metabolic score 1.18 (95% CI: 0.57, 2.48)). BMI, waist circumference, and derived fat mass were associated with a broad range of metabolic alterations. Neither adiposity nor metabolic scores were associated with risk of advanced prostate cancer.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Etiology_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Idioma: En Revista: Metabolites Ano de publicação: 2020 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Etiology_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Idioma: En Revista: Metabolites Ano de publicação: 2020 Tipo de documento: Article País de afiliação: Estados Unidos