Scientific Reports (Jun 2021)

Prediagnostic circulating metabolites in female breast cancer cases with low and high mammographic breast density

  • Benedetta Bendinelli,
  • Alessia Vignoli,
  • Domenico Palli,
  • Melania Assedi,
  • Daniela Ambrogetti,
  • Claudio Luchinat,
  • Saverio Caini,
  • Calogero Saieva,
  • Paola Turano,
  • Giovanna Masala

DOI
https://doi.org/10.1038/s41598-021-92508-1
Journal volume & issue
Vol. 11, no. 1
pp. 1 – 11

Abstract

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Abstract Mammographic breast density (MBD) is a strong independent risk factor for breast cancer (BC). We designed a matched case–case study in the EPIC Florence cohort, to evaluate possible associations between the pre-diagnostic metabolomic profile and the risk of BC in high- versus low-MBD women who developed BC during the follow-up. A case–case design with 100 low-MBD (MBD ≤ 25%) and 100 high-MDB BC cases (MBD > 50%) was performed. Matching variables included age, year and type of mammographic examination. 1H NMR metabolomic spectra were available for 87 complete case–case sets. The conditional logistic analyses showed an inverse association between serum levels of alanine, leucine, tyrosine, valine, lactic acid, pyruvic acid, triglycerides lipid main fraction and 11 VLDL lipid subfractions and high-MBD cases. Acetic acid was directly associated with high-MBD cases. In models adjusted for confounding variables, tyrosine remained inversely associated with high-MBD cases while 3 VLDL subfractions of free cholesterol emerged as directly associated with high-MBD cases. A pathway analysis showed that the “phenylalanine, tyrosine and tryptophan pathway” emerged and persisted after applying the FDR procedure. The supervised OPLS-DA analysis revealed a slight but significant separation between high- and low-MBD cases. This case–case study suggested a possible role for pre-diagnostic levels of tyrosine in modulating the risk of BC in high- versus low-MBD women. Moreover, some differences emerged in the pre-diagnostic concentration of other metabolites as well in the metabolomic fingerprints among the two groups of patients.