Background Metabolomics profiling has shown promise in elucidating the biological pathways underpinning mortality, but there are limited data in female populations. Methods We applied a liquid chromatography-tandem mass spectrometry metabolomics platform to EDTA-plasma to measure 470 metabolites at baseline in a discovery set of 943 postmenopausal women (including 417 incident deaths, median time to death of 10.6 years) with validation in an independent set of 1355 postmenopausal women (including 685 deaths, median time to death of 9.1 years) in the Women’s Health Initiative. Results Eight new metabolites were discovered to be associated with all-cause mortality. Findings included protective effects of increased levels of three amino acids (asparagine, homoarginine and tryptophan) and docosatrienoic acid; and detrimental effects of increased levels of C4-OH-carnitine, hexadecanedioate and two purine/pyrimidines (N2, N2-dimethylguanosine and N4-acetylcytidine). In addition, a set of nine previously published metabolite associations were replicated. A metabolite score comprising 17 metabolites was associated with mortality (P < 10–8) after adjustment for risk factors, with a hazard ratio of 1.95 (95% CI: 1.46–2.62) for women in the highest quartile compared with the lowest quartile of metabolite score. The score was robust among younger women and older women, for both cardiovascular and non-cardiovascular mortality, and associated with both early deaths (within the first 10 years of baseline) and later deaths. Conclusions Our study fills a gap in the literature by identifying eight novel metabolite associations with all-cause mortality in women, using a robust study design involving independent discovery and validation datasets.

Known modifiable risk factors account for a small fraction of premenopausal breast cancers. We investigated associations between pre-diagnostic circulating amino acid and amino acid-related metabolites (N = 207) and risk of breast cancer among predominantly premenopausal women of the Nurses’ Health Study II using conditional logistic regression (1057 cases, 1057 controls) and multivariable analyses evaluating all metabolites jointly. Eleven metabolites were associated with breast cancer risk (q-value < 0.2). Seven metabolites remained associated after adjustment for established risk factors (p-value < 0.05) and were selected by at least one multivariable modeling approach: higher levels of 2-aminohippuric acid, kynurenic acid, piperine (all three with q-value < 0.2), DMGV and phenylacetylglutamine were associated with lower breast cancer risk (e.g., piperine: ORadjusted (95%CI) = 0.84 (0.77–0.92)) while higher levels of creatine and C40:7 phosphatidylethanolamine (PE) plasmalogen were associated with increased breast cancer risk (e.g., C40:7 PE plasmalogen: ORadjusted (95%CI) = 1.11 (1.01–1.22)). Five amino acids and amino acid-related metabolites (2-aminohippuric acid, DMGV, kynurenic acid, phenylacetylglutamine, and piperine) were inversely associated, while one amino acid and a phospholipid (creatine and C40:7 PE plasmalogen) were positively associated with breast cancer risk among predominately premenopausal women, independent of established breast cancer risk factors.

No abstract

Background:Women have higher lifetime risk of stroke than men, and metabolic factors seem more strongly associated with stroke for women than men. However, few studies in either men or women have evaluated metabolomic profiles and incident stroke.Methods:We applied liquid chromatography-tandem mass spectrometry to measure 519 plasma metabolites in a discovery set of women in the Nurses’ Health Study ([NHS], 454 incident ischemic stroke cases, 454 controls) with validation in two independent, prospective cohorts: Prevención con Dieta Mediterránea ([PREDIMED], 118 stroke cases, 791 controls), and Nurses’ Health Study 2 ([NHS2], 49 ischemic stroke cases, 49 controls). We applied logistic regression models with stroke as the outcome to adjust for multiple risk factors; the false discovery rate (FDR) was controlled through the q value method.Results:Twenty-three metabolites were significantly associated with incident stroke in NHS after adjustment for traditional risk factors (q value <0.05). Of these, 14 metabolites were available in PREDIMED and 3 were significantly associated with incident stroke: methionine sulfoxide, N6-acetyllysine, and sucrose (q value<0.05). In NHS2, one of the 23 metabolites (glucuronate) was significantly associated with incident stroke (q value <0.05). For all four metabolites, higher levels were associated with increased risk. These four metabolites were used to create a stroke metabolite score (SMS) in the NHS and tested in PREDIMED. Per unit of standard deviation of SMS, the odds ratio for incident stroke was 4.12 (95% CI: 2.26 – 7.51) in PREDIMED, after adjustment for risk factors. In PREDIMED, the area under the ROC curve (AUC) for the model including SMS and traditional risk factors was 0.70 (95% CI: 0.75-0.79) versus the AUC for the model including the traditional risk factors only of 0.65 (95% CI: 0.70-75), corresponding to a 5% improvement in risk prediction with SMS (p < 0.005).Discussion:Metabolites associated with stroke included two amino acids, a carboxylic acid and sucrose. A composite SMS including these metabolites was associated with ischemic stroke and showed improvement in risk prediction beyond traditional risk factors.Classification of Evidence:This study provides Class II evidence that a stroke metabolic score accurately predicts incident ischemic stroke risk.