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Nicotinamide adenine dinucleotide (NAD + ) has emerged as a critical co-substrate for enzymes involved in the beneficial effects of regular calorie restriction on healthspan. As such, the use of NAD + precursors to augment NAD + bioavailability has been proposed as a strategy for improving cardiovascular and other physiological functions with aging in humans. Here we provide the evidence in a 2 × 6-week randomized, double-blind, placebo-controlled, crossover clinical trial that chronic supplementation with the NAD + precursor vitamin, nicotinamide riboside (NR), is well tolerated and effectively stimulates NAD + metabolism in healthy middle-aged and older adults. Our results also provide initial insight into the effects of chronic NR supplementation on physiological function in humans, and suggest that, in particular, future clinical trials should further assess the potential benefits of NR for reducing blood pressure and arterial stiffness in this group. Declining NAD + levels have been linked to aging-associated pathologies. Here the authors present results of a double-blind, randomized crossover trial on 30 healthy middle-aged individuals to show that nicotinamide riboside effectively elevates NAD + levels in humans, appears to be well tolerated, and may have potential to improve cardiovascular parameters.

Metabolomics has the potential to greatly impact biomedical research in areas such as biomarker discovery and understanding molecular mechanisms of disease. However, compound identification (ID) remains a major challenge in liquid chromatography mass spectrometry-based metabolomics. This is partly due to a lack of specificity in metabolomics databases. Though impressive in depth and breadth, the sheer magnitude of currently available databases is in part what makes them ineffective for many metabolomics studies. While still in pilot phases, our experience suggests that custom-built databases, developed using empirical data from specific sample types, can significantly improve confidence in IDs. While the concept of sample type specific databases (STSDBs) and spectral libraries is not entirely new, inclusion of unique descriptors such as detection frequency and quality scores, can be used to increase confidence in results. These features can be used alone to judge the quality of a database entry, or together to provide filtering capabilities. STSDBs rely on and build upon several available tools for compound ID and are therefore compatible with current compound ID strategies. Overall, STSDBs can potentially result in a new paradigm for translational metabolomics, whereby investigators confidently know the identity of compounds following a simple, single STSDB search.

Mushrooms contain multiple essential nutrients and health-promoting bioactive compounds, including the amino acid L-ergothioneine. Knowledge of the chemical composition of different mushroom varieties will aid research on their health-promoting properties. We compared the metabolomes of fresh raw white button, crimini, portabella, lion’s mane, maitake, oyster, and shiitake mushrooms using untargeted liquid chromatography mass spectrometry (LC/MS)-based metabolomics. We also quantified amino acid concentrations, including L-ergothioneine, a potential antioxidant which is not synthesized by plants or animals. Among the seven mushroom varieties, more than 10,000 compounds were detected. Principal Component Analysis indicated mushrooms of the same species, Agaricus Bisporus (white button, portabella, crimini), group similarly. The other varieties formed individual, distinct clusters. A total of 1344 (520 annotated) compounds were detected in all seven mushroom varieties. Each variety had tens-to-hundreds of unique-to-mushroom-variety compounds. These ranged from 29 for crimini to 854 for lion’s mane. All three Agaricus bisporus varieties had similar amino acid profiles (including detection of all nine essential amino acids), while other varieties had less methionine and tryptophan. Lion’s mane and oyster mushrooms had the highest concentrations of L-ergothioneine. The detection of hundreds of unique-to-mushroom-variety compounds emphasizes the differences in chemical composition of these varieties of edible fungi.

The identity of self antigens targeted in various autoimmune diseases is often unknown. Haskins and colleagues identify a chromagranin A epitope whose presentation by I-A g7 involves an unusual peptide-binding mode. Autoreactive CD4 + T cells are involved in the pathogenesis of many autoimmune diseases, but the antigens that stimulate their responses have been difficult to identify and in most cases are not well defined. In the nonobese diabetic (NOD) mouse model of type 1 diabetes, we have identified the peptide WE14 from chromogranin A (ChgA) as the antigen for highly diabetogenic CD4 + T cell clones. Peptide truncation and extension analysis shows that WE14 bound to the NOD mouse major histocompatibility complex class II molecule I-A g7 in an atypical manner, occupying only the carboxy-terminal half of the I-A g7 peptide-binding groove. This finding extends the list of T cell antigens in type 1 diabetes and supports the idea that autoreactive T cells respond to unusually presented self peptides.

Prolonged cigarette smoking (CS) causes chronic obstructive pulmonary disease (COPD), a prevalent serious condition that may persist or progress after smoking cessation. To provide insight into how CS triggers COPD, we investigated temporal patterns of lung transcriptome expression and systemic metabolome changes induced by chronic CS exposure and smoking cessation. Whole lung RNA-seq data was analyzed at transcript and exon levels from C57Bl/6 mice exposed to CS for 1- or 7 days, for 3-, 6-, or 9 months, or for 6 months followed by 3 months of cessation using age-matched littermate controls. We identified previously unreported dysregulation of pyrimidine metabolism and phosphatidylinositol signaling pathways and confirmed alterations in glutathione metabolism and circadian gene pathways. Almost all dysregulated pathways demonstrated reversibility upon smoking cessation, except the lysosome pathway. Chronic CS exposure was significantly linked with alterations in pathways encoding for energy, phagocytosis, and DNA repair and triggered differential expression of genes or exons previously unreported to associate with CS or COPD, including Lox, involved in matrix remodeling, Gp2, linked to goblet cells, and Slc22a12 and Agpat3, involved in purine and glycerolipid metabolism, respectively. CS-induced lung metabolic pathways changes were validated using metabolomic profiles of matched plasma samples, indicating that dynamic metabolic gene regulation caused by CS is reflected in the plasma metabolome. Using advanced technologies, our study uncovered novel pathways and genes altered by chronic CS exposure, including those involved in pyrimidine metabolism, phosphatidylinositol signaling and lysosome function, highlighting their potential importance in the pathogenesis or diagnosis of CS-associated conditions.

Although weekend recovery sleep is common, the physiological responses to weekend recovery sleep are not fully elucidated. Identifying molecular biomarkers that represent adequate versus insufficient sleep could help advance our understanding of weekend recovery sleep. Here, we identified potential molecular biomarkers of insufficient sleep and defined the impact of weekend recovery sleep on these biomarkers using metabolomics in a randomized controlled trial. Healthy adults (n = 34) were randomized into three groups: control (CON: 9-h sleep opportunities); sleep restriction (SR: 5-h sleep opportunities); or weekend recovery (WR: simulated workweek of 5-h sleep opportunities followed by ad libitum weekend recovery sleep and then 2 days with 5-h sleep opportunities). Blood for metabolomics was collected on the simulated Monday immediately following the weekend. Nine machine learning models, including a machine learning ensemble, were built to classify samples from SR versus CON. Notably, SR showed decreased glycerophospholipids and sphingolipids versus CON. The machine learning ensemble showed the highest G-mean performance and classified 50% of the WR samples as insufficient sleep. Our findings show insufficient sleep and recovery sleep influence the plasma metabolome and suggest more than one weekend of recovery sleep may be necessary for the identified biomarkers to return to healthy adequate sleep levels.

Although health benefits of the Dietary Approaches to Stop Hypertension (DASH) diet are established, it is not understood which food compounds result in these benefits. We used metabolomics to identify unique compounds from individual foods of a DASH-style diet and determined if these Food-Specific Compounds (FSC) are detectable in urine from participants in a DASH-style dietary study. We also examined relationships between urinary compounds and blood pressure (BP). Nineteen subjects were randomized into 6-week controlled DASH-style diet interventions. Mass spectrometry-based metabolomics was performed on 24-hour urine samples collected before and after each intervention and on 12 representative DASH-style foods. Between 66–969 compounds were catalogued as FSC; for example, 4-hydroxydiphenylamine was found to be unique to apple. Overall, 13–190 of these FSC were detected in urine, demonstrating that these unmetabolized food compounds can be discovered in urine using metabolomics. Although linear mixed effects models showed no FSC from the 12 profiled foods were significantly associated with BP, other endogenous and food-related compounds were associated with BP (N = 16) and changes in BP over time (N = 6). Overall, this proof of principle study demonstrates that metabolomics can be used to catalog FSC, which can be detected in participant urine following a dietary intervention.

Background Diet is among the most influential lifestyle factors impacting chronic disease risk. Nutrimetabolomics, the application of metabolomics to nutrition research, allows for the detection of food-specific compounds (FSCs) that can be used to connect dietary patterns, such as a Mediterranean-style (MED) diet, to health. This validation study is based upon analyses from a controlled feeding MED intervention, where our team identified FSCs from eight foods that can be detected in biospecimens after consumption and may therefore serve as food intake biomarkers. Methods Individuals with overweight/obesity who do not habitually consume a MED dietary pattern will complete a 16-week randomized, multi-intervention, semi-controlled feeding study of isocaloric dietary interventions: (1) MED-amplified dietary pattern, containing 500 kcal/day from eight MED target foods: avocado, basil, cherry, chickpea, oat, red bell pepper, walnut, and a protein source (alternating between salmon or unprocessed, lean beef), and (2) habitual/Western dietary pattern, containing 500 kcal/day from six non-MED target foods: cheesecake, chocolate frozen yogurt, refined grain bread, sour cream, white potato, and unprocessed, lean beef. After a 2-week washout, participants complete four, 4-week intervention periods, with biospecimen sampling and outcome assessments at baseline and at intervention weeks 4, 8, 12, and 16. The primary outcome is change in the relative abundance of FSCs from the eight MED target foods in participant biospecimens from baseline to the end of each intervention period. Secondary outcomes include mean change in cardiometabolic health indicators, inflammatory markers, and adipokines. Exploratory outcomes include change in diversity and community composition of the gut microbiota. Discussion Our stepwise strategy, beginning with identification of FSCs in whole diets and biospecimens, followed by relating these to health indicators will lead to improved methodology for assessment of dietary patterns and a better understanding of the relationship between food and health. This study will serve as a first step toward validating candidate food intake biomarkers and allow for assessment of relationships with cardiometabolic health. The identification of food intake biomarkers is critical to future research and has implications spanning health promotion and disease prevention for many chronic conditions. Trial registration Registered at ClinicalTrials.gov: NCT05500976 ; Date of registration: August 15, 2022.

Identifying and annotating the molecular composition of individual foods will improve scientific understanding of how foods impact human health and how much variation exists in the molecular composition of foods of the same species. The complexity of this task includes distinct varieties and variations in natural occurring pigments of foods. Lipidomics, a sub-field of metabolomics, has emerged as an effective tool to help decipher the molecular composition of foods. For this proof-of-principle research, we determined the lipidomic profiles of green, yellow and red bell peppers (Capsicum annuum) using liquid chromatography mass spectrometry and a novel tool for automated annotation of compounds following database searches. Among 23 samples analyzed from 6 peppers (2 green, 1 yellow, and 3 red), over 8000 lipid compounds were detected with 315 compounds (106 annotated) found in all three colors. Assessments of relationships between these compounds and pepper color, using linear mixed effects regression and false discovery rate (<0.05) statistical adjustment, revealed 11 compounds differing by color. The compound most strongly associated with color was the carotenoid, β-cryptoxanthin (p-value = 7.4 × 10−5; FDR adjusted p-value = 0.0080). These results support lipidomics as a viable analytical technique to identify molecular compounds that can be used for unique characterization of foods.

Clostridioides difficile infection (CDI) is the leading cause of hospital-acquired diarrhea, and emerging evidence has linked dietary components with CDI pathogenesis, suggesting that dietary modulation may be an effective strategy for prevention. Here, we show that mice fed a high-fat/low-fiber “Western-type” diet (WD) had dramatically increased mortality in a murine model of antibiotic-induced CDI compared to a low-fat/low-fiber (LF/LF) diet and standard mouse chow controls. We found that the WD had a pro- C. difficile bile acid composition that was driven in part by higher levels of primary bile acids that are produced to digest fat, and a lower level of secondary bile acids that are produced by the gut microbiome. This lack of secondary bile acids was associated with a greater disturbance to the gut microbiome with antibiotics in both the WD and LF/LF diet compared to mouse chow. Mice fed the WD also had the highest level of toxin TcdA just prior to the onset of mortality, but not of TcdB or increased inflammation. These findings indicate that dietary intervention to decrease fat may complement previously proposed dietary intervention strategies to prevent CDI in high-risk individuals.