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AbstractBackgroundThe aim of this study was to investigate if serum lipoprotein and metabolic profiles of healthy women can predict the risk of developing breast cancer in the future, and to gain a better understanding of the etiology of the disease.MethodsFrom a cohort of 70 000 participants within the Trøndelag Health Study (HUNT study), we identified 1199 women who developed breast cancer within a 22 year follow-up period. Through a nested case-control study design, future breast cancer patients and matching controls (n = 2398) were analysed. Using nuclear magnetic resonance (NMR) spectroscopy, 28 metabolites and 112 lipoprotein subfractions were quantified from prediagnostic serum samples. Logistic regression was used to test metabolites and lipoprotein subfractions for associations with breast cancer risk and partial least-squares discriminant analysis (PLS-DA) models were built to predict future disease.ResultsAmong premenopausal women (554 cases) 14 lipoprotein subfractions were associated with long-term breast cancer risk. In specific, different subfractions of VLDL particles (in particular VLDL-2, VLDL-3 and VLDL-4) were inversely associated with breast cancer. For total VLDL: apolipoprotein B, cholesterol, free cholesterol and phospholipids were inversely associated with premenopausal breast cancer risk, and in addition total and HDL-4 triglycerides. No significant association was found in postmenopausal women.ConclusionsWe identified several associations between lipoprotein subfractions and long-term risk of breast cancer in premenopausal women. Inverse associations between several VLDL subfractions and breast cancer risk were found, revealing an altered metabolism in the endogenous lipid pathway many years prior to a breast cancer diagnosis.
Cohort Studies, Premenopause, Lipoproteins, Humans, Breast Neoplasms, Female, Triglycerides
Cohort Studies, Premenopause, Lipoproteins, Humans, Breast Neoplasms, Female, Triglycerides
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 17 | |
popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |