The gut microbiome (GM) modulates body weight/composition and gastrointestinal functioning; therefore, approaches targeting resident gut microbes have attracted considerable interest. Intermittent fasting (IF) and protein pacing (P) regimens are effective in facilitating weight loss (WL) and enhancing body composition. However, the interrelationships between IF- and P-induced WL and the GM are unknown. The current randomized controlled study describes distinct fecal microbial and plasma metabolomic signatures between combined IF-P (n = 21) versus a heart-healthy, calorie-restricted (CR, n = 20) diet matched for overall energy intake in free-living human participants (women = 27; men = 14) with overweight/obesity for 8 weeks. Gut symptomatology improves and abundance of Christensenellaceae microbes and circulating cytokines and amino acid metabolites favoring fat oxidation increase with IF-P (p < 0.05), whereas metabolites associated with a longevity-related metabolic pathway increase with CR (p < 0.05). Differences indicate GM and metabolomic factors play a role in WL maintenance and body composition. This novel work provides insight into the GM and metabolomic profile of participants following an IF-P or CR diet and highlights important differences in microbial assembly associated with WL and body composition responsiveness. These data may inform future GM-focused precision nutrition recommendations using larger sample sizes of longer duration. Trial registration, March 6, 2020 (ClinicalTrials.gov as NCT04327141), based on a previous randomized intervention trial.

Chronic kidney disease (CKD) leads to decreased sensitivity to the metabolic effects of insulin, contributing to protein energy wasting and muscle atrophy. Targeted metabolomics profiling during hyperinsulinemic-euglycemic insulin clamp testing may help identify aberrant metabolic pathways contributing to insulin resistance in CKD. Using targeted metabolomics profiling, we examined the plasma metabolome in 95 adults without diabetes in the fasted state (58 with CKD, 37 with normal glomerular filtration rate [GFR]) who underwent hyperinsulinemic-euglycemic clamp. We assessed heterogeneity in fasting metabolites and the response to insulin to identify potential metabolic pathways linking CKD with insulin resistance. Baseline differences and effect modification by CKD status on changes with insulin clamp testing were adjusted for confounders. Mean GFR among participants with CKD was 37.3 compared with 89.3 ml/min per 1.73 m2 among controls. Fasted-state differences between CKD and controls included abnormalities in tryptophan metabolism, ubiquinone biosynthesis, and the TCA cycle. Insulin infusion markedly decreased metabolite levels, predominantly amino acids and their metabolites. CKD was associated with attenuated insulin-induced changes in nicotinamide, arachidonic acid, and glutamine/glutamate metabolic pathways. Metabolomics profiling suggests disruption in amino acid metabolism and mitochondrial function as putative manifestations or mechanisms of the impaired anabolic effects of insulin in CKD.

Background

Unrelieved chemotherapy-induced nausea (CIN) is a significant problem for patients with breast cancer (BC).

Objective

In a sample of patients with BC who were assessed before their second or third cycle of chemotherapy, study purposes were to evaluate for the occurrence, severity, frequency, and distress associated with CIN; evaluate for differences in demographic and clinical characteristics and gastrointestinal (GI) symptom occurrence rates between patients who did and did not report CIN; and determine which demographic, clinical, and symptom characteristics were associated with the occurrence of CIN.

Methods

Patients completed demographic and clinical questionnaires and the Memorial Symptom Assessment Scale for nausea and common GI symptom assessments. Univariate analyses evaluated for differences in demographic and clinical characteristics and GI symptom occurrence between patients who did and did not report CIN. Multiple logistic regression analysis evaluated for characteristics associated with CIN.

Results

Of the 532 patients with BC, 47.2% reported CIN occurrence. Characteristics associated with CIN group membership were poorer functional status, receipt of chemotherapy on a 14-day cycle, and higher occurrence rates of 5 GI symptoms (ie, dry mouth, vomiting, constipation, change in the way food tastes, and lack of appetite; all P < .001).

Conclusions

Unrelieved CIN is a common symptom in patients with BC. This study is the first to demonstrate that 5 co-occurring GI symptoms were associated with CIN occurrence.

Implications for practice

This study identified new risk factors for CIN occurrence in patients with BC. Clinicians may be able to initiate additional interventions to alleviate CIN.

Background

Unrelieved chemotherapy-induced nausea (CIN) occurs 48% of patients undergoing chemotherapy and is one of the most debilitating symptoms that patients report.

Objective

The aims of this study were to identify subgroups of patients with distinct CIN profiles and determine how these subgroups differed on demographic and clinical characteristics; severity, frequency, and distress of CIN; and the co-occurrence of common gastrointestinal symptoms.

Methods

Patients (n = 1343) completed demographic questionnaire and Memorial Symptom Assessment Scale 6 times over 2 cycles of chemotherapy. Latent class analysis was used to identify subgroups of patients with distinct CIN profiles. Differences among these subgroups were evaluated using parametric and nonparametric statistics.

Results

Four distinct CIN profiles were identified: none (40.8%), increasing-decreasing (21.5%), decreasing (8.9%), and high (28.8%). Compared with the none class, patients in the high class were younger, had a lower annual household income, had child care responsibilities, had a lower Karnofsky Performance Status score and a higher Self-administered Comorbidity Questionnaire score, and were more likely to have received chemotherapy on a 14-day cycle and a highly emetogenic chemotherapy regimen. In addition, patients in the high class reported high occurrence rates for dry mouth, feeling bloated, diarrhea, lack of appetite, abdominal cramps, difficulty swallowing, mouth sores, weight loss, and change in the way food tastes.

Conclusions

That 60% of the patients reported moderate to high CIN occurrence rates confirms that this unrelieved symptom is a significant clinical problem.

Implications for practice

Nurses need to evaluate patients' level of adherence to their antiemetic regimen and make appropriate referrals for physical therapy, psychological services, and dietary counseling.

In recent years, metabolomics has been used as a powerful tool to better understand the physiology of neurodegenerative diseases and identify potential biomarkers for progression. We used targeted and untargeted aqueous, and lipidomic profiles of the metabolome from human cerebrospinal fluid to build multivariate predictive models distinguishing patients with Alzheimer's disease (AD), Parkinson's disease (PD), and healthy age-matched controls. We emphasize several statistical challenges associated with metabolomic studies where the number of measured metabolites far exceeds sample size. We found strong separation in the metabolome between PD and controls, as well as between PD and AD, with weaker separation between AD and controls. Consistent with existing literature, we found alanine, kynurenine, tryptophan, and serine to be associated with PD classification against controls, while alanine, creatine, and long chain ceramides were associated with AD classification against controls. We conducted a univariate pathway analysis of untargeted and targeted metabolite profiles and find that vitamin E and urea cycle metabolism pathways are associated with PD, while the aspartate/asparagine and c21-steroid hormone biosynthesis pathways are associated with AD. We also found that the amount of metabolite missingness varied by phenotype, highlighting the importance of examining missing data in future metabolomic studies.

Quantifying the physiology of aging is essential for improving our understanding of age-related disease and the heterogeneity of healthy aging. Recent studies have shown that, in regression models using "-omic" platforms to predict chronological age, residual variation in predicted age is correlated with health outcomes, and suggest that these "omic clocks" provide measures of biological age. This paper presents predictive models for age using metabolomic profiles of cerebrospinal fluid (CSF) from healthy human subjects and finds that metabolite and lipid data are generally able to predict chronological age within 10 years. We use these models to predict the age of a cohort of subjects with Alzheimer's and Parkinson's disease and find an increase in prediction error, potentially indicating that the relationship between the metabolome and chronological age differs with these diseases. However, evidence is not found to support the hypothesis that our models will consistently overpredict the age of these subjects. In our analysis of control subjects, we find the carnitine shuttle, sucrose, biopterin, vitamin E metabolism, tryptophan, and tyrosine to be the most associated with age. We showcase the potential usefulness of age prediction models in a small data set (n = 85) and discuss techniques for drift correction, missing data imputation, and regularized regression, which can be used to help mitigate the statistical challenges that commonly arise in this setting. To our knowledge, this work presents the first multivariate predictive metabolomic and lipidomic models for age using mass spectrometry analysis of CSF.

For nearly a century developmental biologists have recognized that cells from embryos can differ in their potential to differentiate into distinct cell types. Recently, it has been recognized that embryonic stem cells derived from both mice and humans exhibit two stable yet epigenetically distinct states of pluripotency: naive and primed. We now show that nicotinamide N-methyltransferase (NNMT) and the metabolic state regulate pluripotency in human embryonic stem cells (hESCs).  Specifically, in naive hESCs, NNMT and its enzymatic product 1-methylnicotinamide are highly upregulated, and NNMT is required for low S-adenosyl methionine (SAM) levels and the H3K27me3 repressive state. NNMT consumes SAM in naive cells, making it unavailable for histone methylation that represses Wnt and activates the HIF pathway in primed hESCs. These data support the hypothesis that the metabolome regulates the epigenetic landscape of the earliest steps in human development.