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Prospective analysis of circulating metabolites and breast cancer in EPIC.

ABSTRACT: 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.

SUBMITTER: His M

PROVIDER: S-EPMC6757362 | biostudies-literature | 2019 Sep

REPOSITORIES: biostudies-literature

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Prospective analysis of circulating metabolites and breast cancer in EPIC.

His Mathilde M Viallon Vivian V Dossus Laure L Gicquiau Audrey A Achaintre David D Scalbert Augustin A Ferrari Pietro P Romieu Isabelle I Onland-Moret N Charlotte NC Weiderpass Elisabete E Dahm Christina C CC Overvad Kim K Olsen Anja A Tjønneland Anne A Fournier Agnès A Rothwell Joseph A JA Severi Gianluca G Kühn Tilman T Fortner Renée T RT Boeing Heiner H Trichopoulou Antonia A Karakatsani Anna A Martimianaki Georgia G Masala Giovanna G Sieri Sabina S Tumino Rosario R Vineis Paolo P Panico Salvatore S van Gils Carla H CH Nøst Therese H TH Sandanger Torkjel M TM Skeie Guri G Quirós J Ramón JR Agudo Antonio A Sánchez Maria-Jose MJ Amiano Pilar P Huerta José María JM Ardanaz Eva E Schmidt Julie A JA Travis Ruth C RC Riboli Elio E Tsilidis Konstantinos K KK Christakoudi Sofia S Gunter Marc J MJ Rinaldi Sabina S

BMC medicine 20190924 1

<h4>Background</h4>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.<h4>Methods</h4>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 recep ...[more]

PMID: 31547832

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Project description:Ovarian cancer has few known risk factors, hampering identification of high-risk women. We assessed the association of prediagnostic plasma metabolites (N = 420) with risk of epithelial ovarian cancer, including both borderline and invasive tumors. A total of 252 cases and 252 matched controls from the Nurses' Health Studies were included. Multivariable logistic regression was used to estimate ORs and 95% confidence intervals (CI), comparing the 90th-10th percentile in metabolite levels, using the permutation-based Westfall and Young approach to account for testing multiple correlated hypotheses. Weighted gene coexpression network analysis (WGCNA; n = 10 metabolite modules) and metabolite set enrichment analysis (n = 23 metabolite classes) were also evaluated. An increase in pseudouridine levels from the 10th to the 90th percentile was associated with a 2.5-fold increased risk of overall ovarian cancer (OR = 2.56; 95% CI, 1.48-4.45; P = 0.001/adjusted P = 0.15); a similar risk estimate was observed for serous/poorly differentiated tumors (n = 176 cases; comparable OR = 2.38; 95% CI, 1.33-4.32; P = 0.004/adjusted P = 0.55). For nonserous tumors (n = 34 cases), pseudouridine and C36:2 phosphatidylcholine plasmalogen had the strongest statistical associations (OR = 9.84; 95% CI, 2.89-37.82; P < 0.001/adjusted P = 0.07; and OR = 0.11; 95% CI, 0.03-0.35; P < 0.001/adjusted P = 0.06, respectively). Five WGCNA modules and 9 classes were associated with risk overall at FDR ? 0.20. Triacylglycerols (TAG) showed heterogeneity by tumor aggressiveness (case-only heterogeneity P < 0.0001). The TAG association with risk overall and serous tumors differed by acyl carbon content and saturation. In summary, this study suggests that pseudouridine may be a novel risk factor for ovarian cancer and that TAGs may also be important, particularly for rapidly fatal tumors, with associations differing by structural features. SIGNIFICANCE: Pseudouridine represents a potential novel risk factor for ovarian cancer and triglycerides may be important particularly in rapidly fatal ovarian tumors.

Project description:BackgroundMetabolomics is a promising molecular tool for identifying novel etiological pathways leading to cancer. In an earlier prospective study among pre- and postmenopausal women not using exogenous hormones, we observed a higher risk of breast cancer associated with higher blood concentrations of one metabolite (acetylcarnitine) and a lower risk associated with higher blood concentrations of seven others (arginine, asparagine, phosphatidylcholines (PCs) aa C36:3, ae C34:2, ae C36:2, ae C36:3, and ae C38:2).MethodsTo identify determinants of these breast cancer-related metabolites, we conducted a cross-sectional analysis to identify their lifestyle and anthropometric correlates in 2358 women, who were previously included as controls in case-control studies nested within the European Prospective Investigation into Cancer and Nutrition cohort and not using exogenous hormones at blood collection. Associations of each metabolite concentration with 42 variables were assessed using linear regression models in a discovery set of 1572 participants. Significant associations were evaluated in a validation set (n = 786).ResultsFor the metabolites previously associated with a lower risk of breast cancer, concentrations of PCs ae C34:2, C36:2, C36:3, and C38:2 were negatively associated with adiposity and positively associated with total and saturated fat intakes. PC ae C36:2 was also negatively associated with alcohol consumption and positively associated with two scores reflecting adherence to a healthy lifestyle. Asparagine concentration was negatively associated with adiposity. Arginine and PC aa C36:3 concentrations were not associated to any of the factors examined. For the metabolite previously associated with a higher risk of breast cancer, acetylcarnitine, a positive association with age was observed.ConclusionsThese associations may indicate possible mechanisms underlying associations between lifestyle and anthropometric factors, and risk of breast cancer. Further research is needed to identify potential non-lifestyle correlates of the metabolites investigated.

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Dataset Information

Prospective analysis of circulating metabolites and breast cancer in EPIC.

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Prospective analysis of circulating metabolites and breast cancer in EPIC.

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