Branched-Chain Amino Acids and Risk of Breast Cancer

Background Circulating branched-chain amino acid (BCAA) levels reflect metabolic health and dietary intake. However, associations with breast cancer are unclear. Methods We evaluated circulating BCAA levels and breast cancer risk within the Nurses’ Health Study (NHS) and NHSII (1997 cases and 1997 controls). A total of 592 NHS women donated 2 blood samples 10 years apart. We estimated odds ratios (ORs) and 95% confidence intervals (CIs) of breast cancer risk in multivariable logistic regression models. We conducted an external validation in 1765 cases in the Women’s Health Study (WHS). All statistical tests were 2-sided. Results Among NHSII participants (predominantly premenopausal at blood collection), elevated circulating BCAA levels were associated with lower breast cancer risk (eg, isoleucine highest vs lowest quartile, multivariable OR = 0.86, 95% CI = 0.65 to 1.13, Ptrend = .20), with statistically significant linear trends among fasting samples (eg, isoleucine OR = 0.74, 95% CI = 0.53 to 1.05, Ptrend = .05). In contrast, among postmenopausal women, proximate measures (\u3c10 years from blood draw) were associated with increased breast cancer risk (eg, isoleucine OR = 1.63, 95% CI = 1.12 to 2.39, Ptrend = .01), with stronger associations among fasting samples (OR = 1.73, 95% CI = 1.15 to 2.61, Ptrend = .01). Distant measures (10-20 years since blood draw) were not associated with risk. In the WHS, a positive association was observed for distant measures of leucine among postmenopausal women (OR = 1.23, 95% CI = 0.96 to 1.58, Ptrend = .04). Conclusions No statistically significant associations between BCAA levels and breast cancer risk were consistent across NHS and WHS or NHSII and WHS. Elevated circulating BCAA levels were associated with lower breast cancer risk among predominantly premenopausal NHSII women and higher risk among postmenopausal women in NHS but not in the WHS. Additional studies are needed to understand this complex relationship

Higher susceptibility to sunburn is associated with decreased plasma glutamine and increased plasma glutamate levels among US women: An analysis of the Nurses' Health Study I and II

To the Editor: The metabolism of glutamine and glutamate, 2 important amino acids synthesized in the human body, may have an etiologic role in melanoma, an aggressive skin malignancy. 1 , 2 Preclinical experiments and clinical trials have found that metabotropic glutamate receptor 1 blocker and glutamate release inhibitor (eg, Riluzole) can suppress melanoma cell migration, invasion, and proliferation. 2 Additionally, inhibiting glutaminase, the enzyme that converts glutamine to glutamate, further reduced glutamate bioavailability and suppressed tumor progression. 1 Susceptibility to sunburn, a pigmentary trait, is a well-known risk factor for melanoma. 3 However, it is unclear whether plasma glutamate and glutamine are affected by this host factor even before cancer onset

Metabolomics Analytics Workflow for Epidemiological Research: Perspectives from the Consortium of Metabolomics Studies (COMETS)

The application of metabolomics technology to epidemiological studies is emerging as a new approach to elucidate disease etiology and for biomarker discovery. However, analysis of metabolomics data is complex and there is an urgent need for the standardization of analysis workflow and reporting of study findings. To inform the development of such guidelines, we conducted a survey of 47 cohort representatives from the Consortium of Metabolomics Studies (COMETS) to gain insights into the current strategies and procedures used for analyzing metabolomics data in epidemiological studies worldwide. The results indicated a variety of applied analytical strategies, from biospecimen and data pre-processing and quality control to statistical analysis and reporting of study findings. These strategies included methods commonly used within the metabolomics community and applied in epidemiological research, as well as novel approaches to pre-processing pipelines and data analysis. To help with these discrepancies, we propose use of open-source initiatives such as the online web-based tool COMETS Analytics, which includes helpful tools to guide analytical workflow and the standardized reporting of findings from metabolomics analyses within epidemiological studies. Ultimately, this will improve the quality of statistical analyses, research findings, and study reproducibility

Deciphering lipid structures based on platform-independent decision rule sets

We developed decision rule sets for Lipid Data Analyzer (LDA; http://genome.tugraz.at/lda2), enabling automated and reliable annotation of lipid species and their molecular structures in high-throughput data from chromatography-coupled tandem mass spectrometry. Platform independence was proven in various mass spectrometric experiments, comprising low- and high-resolution instruments and several collision energies. We propose that this independence and the capability to identify novel lipid molecular species render current state-of-the-art lipid libraries now obsolete

Circulating Amino Acids and Amino Acid-Related Metabolites and Risk of Breast Cancer Among Predominantly Premenopausal Women

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\u27 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 \u3c 0.2). Seven metabolites remained associated after adjustment for established risk factors (p-value \u3c 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 \u3c 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

Intrapersonal Stability of Plasma Metabolomic Profiles over 10 Years among Women

In epidemiological studies, samples are often collected long before disease onset or outcome assessment. Understanding the long-term stability of biomarkers measured in these samples is crucial. We estimated within-person stability over 10 years of metabolites and metabolite features (n = 5938) in the Nurses’ Health Study (NHS): the primary dataset included 1880 women with 1184 repeated samples donated 10 years apart while the secondary dataset included 1456 women with 488 repeated samples donated 10 years apart. We quantified plasma metabolomics using two liquid chromatography mass spectrometry platforms (lipids and polar metabolites) at the Broad Institute (Cambridge, MA, USA). Intra-class correlations (ICC) were used to estimate long-term (10 years) within-person stability of metabolites and were calculated as the proportion of the total variability (within-person + between-person) attributable to between-person variability. Within-person variability was estimated among participants who donated two blood samples approximately 10 years apart while between-person variability was estimated among all participants. In the primary dataset, the median ICC was 0.43 (1st quartile (Q1): 0.36; 3rd quartile (Q3): 0.50) among known metabolites and 0.41 (Q1: 0.34; Q3: 0.48) among unknown metabolite features. The three most stable metabolites were N6,N6-dimethyllysine (ICC = 0.82), dimethylguanidino valerate (ICC = 0.72), and N-acetylornithine (ICC = 0.72). The three least stable metabolites were palmitoylethanolamide (ICC = 0.05), ectoine (ICC = 0.09), and trimethylamine-N-oxide (ICC = 0.16). Results in the secondary dataset were similar (Spearman correlation = 0.87) to corresponding results in the primary dataset. Within-person stability over 10 years is reasonable for lipid, lipid-related, and polar metabolites, and varies by metabolite class. Additional studies are required to estimate within-person stability over 10 years of other metabolites groups

A Metabolomics Analysis of Adiposity and Advanced Prostate Cancer Risk in the Health Professionals Follow-Up Study

Obesity is associated with a higher risk of advanced prostate cancer, but men with the same body mass index (BMI) may differ in their underlying metabolic health. Using metabolomics data from nested case-control studies in the Health Professionals Follow-Up Study, we calculated Pearson correlations between 165 circulating metabolites and three adiposity measures (BMI, waist circumference, and derived fat mass from a validated prediction equation) to identify adiposity-associated metabolites. We used Lasso to further select metabolites for prediction models of adiposity measures, which we used to calculate metabolic scores representing metabolic obesity. In an independent set of 212 advanced prostate cancer cases (T3b/T4/N1/M1 or lethal during follow-up) and 212 controls, we used logistic regression to evaluate the associations between adiposity measures and metabolic scores with risk of advanced disease. All adiposity measures were associated with higher blood levels of carnitines (Pearson r range, 0.16 to 0.18) and lower levels of glutamine (r = −0.19) and glycine (r, −0.29 to −0.20), in addition to alterations in various lipids. No adiposity measure or metabolic score was associated with risk of advanced prostate cancer (e.g., odds ratio for a 5 kg/m2 increase in BMI 0.96 (95% CI: 0.73, 1.27) and BMI metabolic score 1.18 (95% CI: 0.57, 2.48)). BMI, waist circumference, and derived fat mass were associated with a broad range of metabolic alterations. Neither adiposity nor metabolic scores were associated with risk of advanced prostate cancer