No abstract

Diet and lifestyle choices contribute to obesity and liver disease. Broccoli, a brassica vegetable, may mitigate negative effects of both diet and lifestyle. Currently, there are no clinically relevant, established molecular biomarkers that reflect variability in human absorption of brassica bioactives, which may be the cause of variability/inconsistencies in health benefits in the human population. Here, we focused on the plasma metabolite profile and composition of the gut microbiome in rats, a relatively homogenous population in terms of gut microbiota, genetics, sex and diet, to determine if changes in the plasma metabolite profiles caused by dietary broccoli relate to molecular changes in liver. Our aim was to identify plasma indicators that reflect how liver health is impacted by dietary broccoli. Rats were fed a 10% broccoli diet for 14 days. We examined the plasma metabolite composition by metabolomics analysis using GC–MS and gut microbiota using 16S sequencing after 0, 1, 2, 4, 7, 14 days of broccoli feeding. We identified 25 plasma metabolites that changed with broccoli consumption, including metabolites associated with hepatic glutathione synthesis, and with de novo fatty acid synthesis. Glutamine, stearic acid, and S-methyl-L-cysteine (SMC) relative abundance changes correlated with changes in gut bacteria previously implicated in metabolic disease and with validated increases in expression of hepatic NAD(P)H dehydrogenase [quinone] 1 (NQO1) and nuclear factor (erythroid-derived 2)-like 2 (Nrf2), associated with elevated hepatic glutathione synthesis. Circulating biomarkers following broccoli consumption reflect gut–liver axis health.

About 20–30% of premenopausal women have metabolic syndrome, and the number is almost double in postmenopausal women, and these women have an increased risk of hepatosteatosis. Postmenopausal women with metabolic syndrome are often treated with hormone replacement therapy (HRT), but estrogens in currently available HRTs increase the risk of breast and endometrial cancers and Cardiovascular Disease. Therefore, there is a critical need to find safer alternatives to HRT to improve postmenopausal metabolic health. Pathway preferential estrogen 1 (PaPE−1) is a novel estrogen receptor ligand that has been shown to favorably affect metabolic tissues without adverse effects on reproductive tissues. In this study, we have examined the effects of PaPE−1 on metabolic health, in particular, examining its effects on the liver transcriptome and on plasma metabolites in two different mouse models: diet−induced obesity (DIO) and leptin−deficient (ob/ob) mice. PaPE−1 significantly decreased liver weight and lipid accumulation in both DIO and ob/ob models and lowered the expression of genes associated with fatty acid metabolism and collagen deposition. In addition, PaPE−1 significantly increased the expression of mitochondrial genes, particularly ones associated with the electron transport chain, suggesting an increase in energy expenditure. Integrated pathway analysis using transcriptomics and metabolomics data showed that PaPE−1 treatment lowered inflammation, collagen deposition, and pathways regulating fatty acid metabolism and increased metabolites associated with glutathione metabolism. Overall, our findings support a beneficial metabolic role for PaPE−1 and suggest that PaPE−1 may protect postmenopausal women from fatty liver disease without increasing reproductive cancer risk.

Coronary microvascular disease (CMD) is a common form of heart disease in postmenopausal women. It is not due to plaque formation but dysfunction of microvessels that feed the heart muscle. The majority of the patients do not receive a proper diagnosis, are discharged prematurely and must go back to the hospital with persistent symptoms. Because of the lack of diagnostic biomarkers, in the current study, we focused on identifying novel circulating biomarkers of CMV that could potentially be used for developing a diagnostic test. We hypothesized that plasma metabolite composition is different for postmenopausal women with no heart disease, CAD, or CMD. A total of 70 postmenopausal women, 26 healthy individuals, 23 individuals with CMD and 21 individuals with CAD were recruited. Their full health screening and tests were completed. Basic cardiac examination, including detailed clinical history, additional disease and prescribed drugs, were noted. Electrocardiograph, transthoracic echocardiography and laboratory analysis were also obtained. Additionally, we performed full metabolite profiling of plasma samples from these individuals using gas chromatography-mass spectrometry (GC–MS) analysis, identified and classified circulating biomarkers using machine learning approaches. Stearic acid and ornithine levels were significantly higher in postmenopausal women with CMD. In contrast, valine levels were higher for women with CAD. Our research identified potential circulating plasma biomarkers of this debilitating heart disease in postmenopausal women, which will have a clinical impact on diagnostic test design in the future.

Introduction: Coronary microvascular disease (CMD) affects small arteries that feed the heart and is more prevalent in postmenopausal women. Since CMD and Coronary artery disease (CAD) have distinct pathologies, but are treated the same way, the majority of the patients with CMD do not receive a proper diagnosis and treatment, which in turn results in higher rates of adverse future events such as heart failure, sudden cardiac death, and acute coronary syndrome (ACS). Previously, we performed full metabolite profiling of plasma samples using GC-MS analysis and tested their classification performance using machine learning approaches. This initial proof-of-concept study showed that plasma metabolite profiles can be used to develop diagnostic signatures for CMD. In the current study, we hypothesize that plasma metabolite and protein composition is different for postmenopausal women with no heart disease, with CAD, or with CMD. Methods: We obtained plasma samples from 70 postmenopausal women who are healthy, women who have CMD, and women who have CAD at the time of blood collection. In addition to GC-MS metabolite profiles, we performed LC-MS metabolomic profiling, and proteomic profiling of a panel of 92 proteins that were implicated in cardiometabolic disease. We identified a combination of metabolites and proteins, and further tested their classification performance using machine learning approaches to identify potential circulating biomarkers for CMD. Results: We identified a comprehensive list of metabolites and proteins that were involved in endothelial cell function, nitric oxide metabolism and inflammation, which significantly different in plasma from women with CMD. We further validated difference in the level of several protein biomarkers, such as RAGE, PTX3, AGRP, CNTN1, and MMP-3, which are statistically significantly higher in postmenopausal women with CMD when compared with healthy women or women with CAD. Conclusion: Our research identified a group of potential molecules that can be used in the design of easy and low-cost blood biomarkers for the clinical diagnosis of CMD.