Recent scientific evidence suggests that traits energy and fatigue are two unique unipolar moods with distinct mental and physical components. This exploratory study investigated the correlation between mental energy (ME), mental fatigue (MF), physical energy (PE), physical fatigue (PF), and the gut microbiome. The four moods were assessed by survey, and the gut microbiome and metabolome were determined from 16 S rRNA analysis and untargeted metabolomics analysis, respectively. Twenty subjects who were 31 ± 5 y, physically active, and not obese (26.4 ± 4.4 kg/m2) participated. Bacteroidetes (45%), the most prominent phyla, was only negatively correlated with PF. The second most predominant and butyrate-producing phyla, Firmicutes (43%), had members that correlated with each trait. However, the bacteria Anaerostipes was positively correlated with ME (0.048, p = 0.032) and negatively with MF (−0.532, p = 0.016) and PF (−0.448, p = 0.048), respectively. Diet influences the gut microbiota composition, and only one food group, processed meat, was correlated with the four moods—positively with MF (0.538, p = 0.014) and PF (0.513, p = 0.021) and negatively with ME (−0.790, p < 0.001) and PE (−0.478, p = 0.021). Only the Firmicutes genus Holdemania was correlated with processed meat (r = 0.488, p = 0.029). Distinct metabolic profiles were observed, yet these profiles were not significantly correlated with the traits. Study findings suggest that energy and fatigue are unique traits that could be defined by distinct bacterial communities not driven by diet. Larger studies are needed to confirm these exploratory findings.

Muscle builders frequently consume protein supplements, but little is known about their effect on the gut microbiota. This study compared the gut microbiome and metabolome of self-identified muscle builders who did or did not report consuming a protein supplement. Twenty-two participants (14 males and 8 females) consumed a protein supplement (PS), and seventeen participants (12 males and 5 females) did not (No PS). Participants provided a fecal sample and completed a 24-h food recall (ASA24). The PS group consumed significantly more protein (118 ± 12 g No PS vs. 169 ± 18 g PS, p = 0.02). Fecal metabolome and microbiome were analyzed by using untargeted metabolomics and 16S rRNA gene sequencing, respectively. Metabolomic analysis identified distinct metabolic profiles driven by allantoin (VIP score = 2.85, PS 2.3-fold higher), a catabolic product of uric acid. High-protein diets contain large quantities of purines, which gut microbes degrade to uric acid and then allantoin. The bacteria order Lactobacillales was higher in the PS group (22.6 ± 49 No PS vs. 136.5 ± 38.1, PS (p = 0.007)), and this bacteria family facilitates purine absorption and uric acid decomposition. Bacterial genes associated with nucleotide metabolism pathways (p < 0.001) were more highly expressed in the No PS group. Both fecal metagenomic and metabolomic analyses revealed that the PS group’s higher protein intake impacted nitrogen metabolism, specifically altering nucleotide degradation.

Background: Bone marrow transplants (BMT) can have adverse outcomes, including low bone mineral density (BMD). However, little research has investigated the association of vitamin D status and bone-related outcomes in patients after BMT. Therefore, this study aims to describe the association between vitamin D status and bone-related outcomes in patients +100 days post-BMT, along with treatment practices that may affect vitamin D status.Methods: This retrospective chart review examined 149 BMT patient records and determined the relationship between serum 25(OH)D concentration and DXA T-scores using linear regression, correlation coefficients, and Chi-square tests. Chi-square tests were used to determine the association of vitamin D status and various categorical risk factors.Results: The mean 25(OH)D concentration for the study population was 36.46 ng/mL. Over 60% of subjects had DXA T-scores that corresponded to a normal BMD. There was no significant association between 25(OH)D concentration and DXA T-scores. Vitamin D status was significantly associated with age (p¼0.01), diagnosis (p<0.01), transplant type (p<0.01), immunosuppressant use (p<0.01), vitamin D supplementation (p¼0.01) and amount (p¼0.04), calcium supplementation (p¼0.02) and amount (p¼0.05). Conclusion:Risk factors are present post-BMT that may affect vitamin D status. However, the role that vitamin D plays in maintaining adequate bone mineral density in this population is unclear. Cross-sectional studies with larger sample sizes, stratification by transplant type, and increased length of time post-BMT should be conducted to further assess this association.