Trait Energy and Fatigue May Be Connected to Gut Bacteria among Young Physically Active Adults: An Exploratory Study

Gulf War Illness Is Associated with Host Gut Microbiome Dysbiosis and Is Linked to Altered Species Abundance in Veterans from the BBRAIN Cohort

Gulf War Illness (GWI) is a debilitating condition marked by chronic fatigue, cognitive problems, pain, and gastrointestinal (GI) complaints in veterans who were deployed to the 1990-1991 Gulf War. Fatigue, GI complaints, and other chronic symptoms continue to persist more than 30 years post-deployment. Several potential mechanisms for the persistent illness have been identified and our prior pilot study linked an altered gut microbiome with the disorder. This study further validates and builds on our prior preliminary findings of host gut microbiome dysbiosis in veterans with GWI. Using stool samples and Multidimensional Fatigue Inventory (MFI) data from 89 GW veteran participants (63 GWI cases and 26 controls) from the Boston biorepository, recruitment, and integrative network (BBRAIN) for Gulf War Illness, we found that the host gut bacterial signature of veterans with GWI showed significantly different Bray-Curtis beta diversity than control veterans. Specifically, a higher Firmicutes to Bacteroidetes ratio, decrease in Akkermansia sp., Bacteroides thetaiotamicron, Bacteroides fragilis, and Lachnospiraceae genera and increase in Blautia, Streptococcus, Klebsiella, and Clostridium genera, that are associated with gut, immune, and brain health, were shown. Further, using MaAsLin and Boruta algorithms, Coprococcus and Eisenbergiella were identified as important predictors of GWI with an area under the curve ROC predictive value of 74.8%. Higher self-reported MFI scores in veterans with GWI were also significantly associated with an altered gut bacterial diversity and species abundance of Lachnospiraceae and Blautia. These results suggest potential therapeutic targets for veterans with GWI that target the gut microbiome and specific symptoms of the illness.

Effect of Birth Story on Personality Traits and Death Anxiety

OBJECTIVES

The aim of this study is to determine the effect of the birth story of individuals on personality traits and death anxiety.

METHODS

This descriptive and analytical research was completed with 1,635 people who participated voluntarily. The study data were collected with the Personal Information Form, Cervantes Personality Scale (CPS), and Abdel-Khalek Death Anxiety Scale (ASDA).

RESULTS

The research sample is average means 31.63 ± 11.04 years, most of the female (72.7%) and married (54.6%). In our study, it was observed that women's death anxiety was higher than men's. Our study found that individuals born by caesarean section had greater neurotic personality traits, emotional stability/neuroticism score averages, and death anxiety scores compared to individuals born vaginally.

CONCLUSION

In the model made with multiple regression analysis, birth type did not significantly predict death anxiety, while sex and emotional stability/neuroticism personality trait significantly predicted death anxiety.

Microbiome-based precision nutrition: Prebiotics, probiotics and postbiotics

Microorganisms have been used in nutrition and medicine for thousands of years worldwide, long before humanity knew of their existence. It is now known that the gut microbiota plays a key role in regulating inflammatory, metabolic, immune and neurobiological processes. This text discusses the importance of microbiota-based precision nutrition in gut permeability, as well as the main advances and current limitations of traditional probiotics, new-generation probiotics, psychobiotic probiotics with an effect on emotional health, probiotic foods, prebiotics, and postbiotics such as short-chain fatty acids, neurotransmitters and vitamins. The aim is to provide a theoretical context built on current scientific evidence for the practical application of microbiota-based precision nutrition in specific health fields and in improving health, quality of life and physiological performance.

Clinical evidence of the link between gut microbiome and myalgic encephalomyelitis/chronic fatigue syndrome: a retrospective review

Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is a heterogeneous disorder with elusive causes, but most likely because of clinical and other biological factors. As a vital environmental factor, the gut microbiome is increasingly emphasized in various refractory diseases including ME/CFS. The present study is aimed to enhance our understanding of the relationship between the gut microbiome and ME/CFS through data analysis of various clinical studies. We conducted a literature search in four databases (PubMed, Cochrane Library, Web of Science, and Google Scholar) until May 31, 2023. Our analysis encompassed 11 clinical studies with 553 ME/CFS patients and 480 healthy controls. A comparative analysis of meta data revealed a significant decrease in α-diversity and a noticeable change in β-diversity in the gut microbiome of ME/CFS patients compared to healthy controls. The notable ratio of Firmicutes and Bacteroides was 2.3 times decreased, and also, there was a significant reduction in the production of microbial metabolites such as acetate, butyrate, isobutyrate, and some amino acids (alanine, serine, and hypoxanthine) observed in ME/CFS patients. The lack of comparison under similar conditions with various standardized analytical methods has impeded the optimal calculation of results in ME/CFS patients and healthy controls. This review provides a comprehensive overview of the recent advancements in understanding the role of the gut microbiome in ME/CFS patients. Additionally, we have also discussed the potentials of using microbiome-related interventions and associated challenges to alleviate ME/CFS.

The Association between Gut Microbiota and Depression in the Japanese Population

Depression is a leading cause of disease worldwide. The association between gut microbiota and depression has barely been investigated in the Japanese population. We analyzed Iwaki health check-up data collected from 2017 to 2019 and constructed generalized linear mixed models. The independent variable was the relative abundance of each of the 37 gut microbiota genera that were reported to be associated with depression. The dependent variable was the presence of depression assessed by the Center for Epidemiologic Studies Depression Scale. Potential confounders, including grip strength, gender, height, weight, smoking, and drinking habits, were adjusted in the regression models. Nine genera's regression coefficients (Alistipes, Blautia, Coprococcus, Dorea, Faecalibacterium, Holdemania, Lactobacillus, Mitsuokella, and Oscillibacter) showed statistical significance after multiple comparisons adjustment. Among these nine gut bacteria genera, Alistipes, Blautia, Coprococcus, Dorea, Faecalibacterium, and Oscillibacter were reported to be associated with butyrate production in the intestine. Our results indicate that gut microbiotas may influence the depression condition of the host via the butyrate-producing process.

Preventive Medicine via Lifestyle Medicine Implementation Practices Should Consider Individuals' Complex Psychosocial Profile

Noncommunicable chronic diseases are associated with lifestyle behaviors. Psychological and social factors may influence the adoption of such behaviors. Being mentally and physically energized or fatigued may influence the intention-behavior gap of healthy lifestyle adoption accordingly. We investigated the associations of age, sex, lifestyle behaviors, mood, and mental and physical energy and fatigue at both the trait and state levels. The participants (N = 670) completed questionnaires assessing their sleep, mood, mental and physical state energy and fatigue, physical activity, mental workload, and diet. The ordinary least squares regression models revealed an overlap between the mental state and trait energy levels for males who consume polyphenols, have a high mental workload, and sleep well. Being younger, having a high stress level, bad sleep habits, and being confused and depressed were associated with high mental fatigue. Physical energy and fatigue shared the same commonalities with the previous results, with greater discrepancies observed between the state and trait indicators compared to that between mental energy and fatigue. Diet and stress management seem to be predictors of high physical energy, and females report higher physical fatigue levels. Health care professionals should consider this psychosocial complex profiling in their differential diagnosis and when one is implementing lifestyle behavioral changes to address the facets of preventive medicine, wellness, and health promotion.

Trait Energy and Fatigue Modify Acute Ingestion of an Adaptogenic-Rich Beverage on Neurocognitive Performance

Background: Psychological research considers traits as a long-standing pre-disposition to an individual’s mood, whereas short-term feelings are categorized as states. We previously reported similar overall acute mental performance benefits between an adaptogen-rich, caffeine-containing energy shot (e+Energy Shot–e+Shot; Isagenix International, LLC) and a caffeine-matched placebo Since the publication of that study, multiple studies have reported that trait mental and physical energy (TME/TPE), and trait mental and physical fatigue (TMF/TPF) status modify the effect of various interventions on neurocognitive performance. Therefore, we reevaluated our previously published work and accounted for the four traits. Methods: Participants (n = 30) completed a series of questionnaires to determine baseline trait energy and fatigue measures. Then, participants performed a 27 min battery of neurocognitive tasks before and three times after consuming the study beverages with 10 min breaks between each post-consumption battery of tests. Data from the previous study were re-analyzed using linear mixed-effects models. Results: We now report that the adaptogen product significantly improved mood and cognitive test responses in individuals stratified by initial TME, TPE, TMF, and TPF status. Moreover, this reevaluation also indicated that the caffeine placebo significantly increased heart rate and blood pressure in those subjects initially characterized by low physical and mental energy. Conclusions: In summary, a post-hoc re-analysis of our initial study suggests that consumption of the adaptogen-rich, caffeine-containing product preferentially benefited individuals with initial low TME/TPE and high TMF status when compared to caffeine alone. These findings also support our previous study suggesting that adaptogens may promote mental and physical performance benefits while modulating potentially negatively associated responses to caffeine.

Network Pharmacology Exploration Reveals Gut Microbiota Modulation as a Common Therapeutic Mechanism for Anti-Fatigue Effect Treated with Maca Compounds Prescription

Maca compounds prescription (MCP) is a common botanical used in dietary supplements, primarily to treat exercise-induced fatigue. The aim of this study is to elucidate the multi-target mechanism of MCP on fatigue management via network pharmacology and gut microbiota analysis. Databases and literature were used to screen the chemical compounds and targets of MCP. Subsequently, 120 active ingredients and 116 fatigue-related targets played a cooperative role in managing fatigue, where several intestine-specific targets indicated the anti-fatigue mechanism of MCP might be closely related to its prebiotics of intestinal bacteria. Thus, forced swimming tests (FSTs) were carried and mice fecal samples were collected and analyzed by 16S rRNA sequencing. Gut microbiota were beneficially regulated in the MCP-treated group in phylum, genus and OTU levels, respectively, and that with a critical correlation included Lactobacillus and Candidatus Planktophila. The results systematically reveal that MCP acts against fatigue on multi-targets with different ingredients and reshapes the gut microbial ecosystem.

Using Machine Learning to Identify Feelings of Energy and Fatigue in Single-Task Walking Gait: An Exploratory Study

The objective of this study was to use machine learning to identify feelings of energy and fatigue using single-task walking gait. Participants (n = 126) were recruited from a university community and completed a single protocol where current feelings of energy and fatigue were measured using the Profile of Moods Survey–Short Form approximately 2 min prior to participants completing a two-minute walk around a 6 m track wearing APDM mobility monitors. Gait parameters for upper and lower extremity, neck, lumbar and trunk movement were collected. Gradient boosting classifiers were the most accurate classifiers for both feelings of energy (74.3%) and fatigue (74.2%) and Random Forest Regressors were the most accurate regressors for both energy (0.005) and fatigue (0.007). ANCOVA analyses of gait parameters comparing individuals who were high or low energy or fatigue suggest that individuals who are low energy have significantly greater errors in walking gait compared to those who are high energy. Individuals who are high fatigue have more symmetrical gait patterns and have trouble turning when compared to their low fatigue counterparts. Furthermore, these findings support the need to assess energy and fatigue as two distinct unipolar moods as the signals used by the algorithms were unique to each mood.