RT Journal Article
T1 Prospective analysis of circulating metabolites and breast cancer in EPIC
A1 His, Mathilde
A1 Viallon, Vivian
A1 Dossus, Laure
A1 Gicquiau, Audrey
A1 Achaintre, David
A1 Scalbert, Augustin
A1 Ferrari, Pietro
A1 Romieu, Isabelle
A1 Onland-Moret, N. Charlotte
A1 Weiderpass, Elisabete
A1 Dahm, Christina C.
A1 Overvad, Kim
A1 Olsen, Anja
A1 Tjønneland, Anne
A1 Fournier, Agnès
A1 Rothwell, Joseph A.
A1 Severi, Gianluca
A1 Kühn, Tilman
A1 Fortner, Renée T.
A1 Boeing, Heiner
A1 Trichopoulou, Antonia
A1 Karakatsani, Anna
A1 Martimianaki, Georgia
A1 Masala, Giovanna
A1 Sieri, Sabina
A1 Tumino, Rosario
A1 Vineis, Paolo
A1 Panico, Salvatore
A1 van Gils, Carla H.
A1 Nøst, Therese H.
A1 Sandanger, Torkjel M.
A1 Skeie, Guri
A1 Quirós, J. Ramón
A1 Agudo, Antonio
A1 Sanchez-Perez, Maria-Jose
A1 Amiano, Pilar
A1 Huerta, José María
A1 Ardanaz, Eva
A1 Schmidt, Julie A.
A1 Travis, Ruth C.
A1 Riboli, Elio
A1 Tsilidis, Konstantinos K.
A1 Christakoudi, Sofia
A1 Gunter, Marc J.
A1 Rinaldi, Sabina
K1 Breast cancer
K1 Metabolomics
K1 Prospective study
K1 Breast neoplasms
K1 Neoplasias de la mama
K1 Metabolómica
K1 Estudios prospectivos
AB Background: Metabolomics is a promising molecular tool to identify novel etiologic pathways leading to cancer. Using a targeted approach, we prospectively investigated the associations between metabolite concentrations in plasma and breast cancer risk.Methods: A nested case-control study was established within the European Prospective Investigation into Cancer cohort, which included 1624 first primary incident invasive breast cancer cases (with known estrogen and progesterone receptor and HER2 status) and 1624 matched controls. Metabolites (n = 127, acylcarnitines, amino acids, biogenic amines, glycerophospholipids, hexose, sphingolipids) were measured by mass spectrometry in pre-diagnostic plasma samples and tested for associations with breast cancer incidence using multivariable conditional logistic regression.Results: Among women not using hormones at baseline (n = 2248), and after control for multiple tests, concentrations of arginine (odds ratio [OR] per SD = 0.79, 95% confidence interval [CI] = 0.70-0.90), asparagine (OR = 0.83 (0.74-0.92)), and phosphatidylcholines (PCs) ae C36:3 (OR = 0.83 (0.76-0.90)), aa C36:3 (OR = 0.84 (0.77-0.93)), ae C34:2 (OR = 0.85 (0.78-0.94)), ae C36:2 (OR = 0.85 (0.78-0.88)), and ae C38:2 (OR = 0.84 (0.76-0.93)) were inversely associated with breast cancer risk, while the acylcarnitine C2 (OR = 1.23 (1.11-1.35)) was positively associated with disease risk. In the overall population, C2 (OR = 1.15 (1.06-1.24)) and PC ae C36:3 (OR = 0.88 (0.82-0.95)) were associated with risk of breast cancer, and these relationships did not differ by breast cancer subtype, age at diagnosis, fasting status, menopausal status, or adiposity.Conclusions: These findings point to potentially novel pathways and biomarkers of breast cancer development. Results warrant replication in other epidemiological studies.
PB BioMed Central Ltd.
YR 2019
FD 2019-09-24
LK http://hdl.handle.net/10668/3173
UL http://hdl.handle.net/10668/3173
LA en
NO His M, Viallon V, Dossus L, Gicquiau A, Achaintre D, Scalbert A, et al. Prospective analysis of circulating metabolites and breast cancer in EPIC. BMC Med. 2019 Sep 24;17(1):178.
DS RISalud
RD Apr 10, 2025