BMC Medicine (Apr 2021)

Metabolic signatures of greater body size and their associations with risk of colorectal and endometrial cancers in the European Prospective Investigation into Cancer and Nutrition

  • Nathalie Kliemann,
  • Vivian Viallon,
  • Neil Murphy,
  • Rebecca J. Beeken,
  • Joseph A. Rothwell,
  • Sabina Rinaldi,
  • Nada Assi,
  • Eline H. van Roekel,
  • Julie A. Schmidt,
  • Kristin Benjaminsen Borch,
  • Claudia Agnoli,
  • Ann H. Rosendahl,
  • Hanna Sartor,
  • José María Huerta,
  • Anne Tjønneland,
  • Jytte Halkjær,
  • Bas Bueno-de-Mesquita,
  • Audrey Gicquiau,
  • David Achaintre,
  • Krasimira Aleksandrova,
  • Matthias B. Schulze,
  • Alicia K. Heath,
  • Konstantinos K. Tsilidis,
  • Giovanna Masala,
  • Salvatore Panico,
  • Rudolf Kaaks,
  • Renée T. Fortner,
  • Bethany Van Guelpen,
  • Laure Dossus,
  • Augustin Scalbert,
  • Hector C. Keun,
  • Ruth C. Travis,
  • Mazda Jenab,
  • Mattias Johansson,
  • Pietro Ferrari,
  • Marc J. Gunter

DOI
https://doi.org/10.1186/s12916-021-01970-1
Journal volume & issue
Vol. 19, no. 1
pp. 1 – 14

Abstract

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Abstract Background The mechanisms underlying the obesity-cancer relationship are incompletely understood. This study aimed to characterise metabolic signatures of greater body size and to investigate their association with two obesity-related malignancies, endometrial and colorectal cancers, and with weight loss within the context of an intervention study. Methods Targeted mass spectrometry metabolomics data from 4326 participants enrolled in the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort and 17 individuals from a single-arm pilot weight loss intervention (Intercept) were used in this analysis. Metabolic signatures of body size were first determined in discovery (N = 3029) and replication (N = 1297) sets among EPIC participants by testing the associations between 129 metabolites and body mass index (BMI), waist circumference (WC), and waist-to-hip ratio (WHR) using linear regression models followed by partial least squares analyses. Conditional logistic regression models assessed the associations between the metabolic signatures with endometrial (N = 635 cases and 648 controls) and colorectal (N = 423 cases and 423 controls) cancer risk using nested case-control studies in EPIC. Pearson correlation between changes in the metabolic signatures and weight loss was tested among Intercept participants. Results After adjustment for multiple comparisons, greater BMI, WC, and WHR were associated with higher levels of valine, isoleucine, glutamate, PC aa C38:3, and PC aa C38:4 and with lower levels of asparagine, glutamine, glycine, serine, lysoPC C17:0, lysoPC C18:1, lysoPC C18:2, PC aa C42:0, PC ae C34:3, PC ae C40:5, and PC ae C42:5. The metabolic signature of BMI (OR1-sd 1.50, 95% CI 1.30–1.74), WC (OR1-sd 1.46, 95% CI 1.27–1.69), and WHR (OR1-sd 1.54, 95% CI 1.33–1.79) were each associated with endometrial cancer risk. Risk of colorectal cancer was positively associated with the metabolic signature of WHR (OR1-sd: 1.26, 95% CI 1.07–1.49). In the Intercept study, a positive correlation was observed between weight loss and changes in the metabolic signatures of BMI (r = 0.5, 95% CI 0.06–0.94, p = 0.03), WC (r = 0.5, 95% CI 0.05–0.94, p = 0.03), and WHR (r = 0.6, 95% CI 0.32–0.87, p = 0.01). Conclusions Obesity is associated with a distinct metabolic signature comprising changes in levels of specific amino acids and lipids which is positively associated with both colorectal and endometrial cancer and is potentially reversible following weight loss.

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