Characteristics of Intestinal Microbiota in Japanese Patients with Mild Cognitive Impairment and a Risk-Estimating Method for the Disorder

Appraising the Effects of Gut Microbiota on Insomnia Risk Through Genetic Causal Analysis

BackgroundInsomnia is a common neurological disorder that exhibits connections with the gut microbiota; however, the exact causal relationship remains unclear. MethodsWe conducted a Mendelian randomization (MR) study to systematically evaluate the causal effects of genus-level gut microbiota on insomnia risk in individuals of European ancestry. Summary-level datasets on gut microbiota were sourced from the genome-wide association study (GWAS) of MiBioGen, while datasets on insomnia were obtained from the GWAS of Neale Lab and FinnGen. The primary analytical approach used was the inverse-variance weighted (IVW) method, supplemented by MR-Egger, maximum likelihood, MR-robust adjusted profile score, and weighted median. Sensitivity analyses were conducted to ensure robustness. ResultsThe microbial taxa Enterorhabdus, Family XIII AD3011 group, Paraprevotella, and Lachnospiraceae UCG004 were associated with an increased risk of insomnia, whereas Coprococcus1, Coprobacter, Desulfovibrio, Flavonifractor, Olsenella, Odoribacter, and Oscillibacter were linked to a decreased risk. Regarding the insomnia phenotype characterized by trouble falling asleep, the microbial taxon Eisenbergiella was correlated with an increased risk, while Haemophilus and the Eubacterium brachy group were associated with a reduced risk. Furthermore, for the insomnia phenotype characterized by waking too early, the microbial taxa Family XIII UCG001, Lachnospiraceae FCS020 group, and Olsenella were linked to an increased risk, whereas the Eubacterium brachy group and Victivallis were associated with a lower risk. The results remained robust across all sensitivity analyses. ConclusionOur MR study identified multiple genus-level gut microbial taxa that may exhibit potential causal effects on insomnia from a genetic perspective. These findings provide evidence supporting the theory of the microbiota-gut-brain axis and offer new insights into potential prevention and therapeutic targets for insomnia.

Food Insecurity Modifies the Association Between the Gut Microbiome and the Risk of Cognitive Impairment in Adults

Background

Recent studies have shown associations between relative abundances of specific gut microbes and cognitive function; however, few studies have explored the potential interplay between the gut microbiome and food insecurity in association with the risk of cognitive impairment (RCI). This study investigated the role of food insecurity as an effect modifier between the gut microbiome, including groups of gut microbes (microbial cliques), and RCI.

Methods

Data came from the Survey of the Health of Wisconsin and its ancillary Wisconsin Microbiome Study. The analytical sample (n = 360) included adult participants with complete data on food insecurity, RCI, and 16S rRNA sequencing data from stool samples. A "mini-cog" memory test was implemented to assess RCI. Food insecurity was assessed using a set of survey-based questions. Alpha diversity and individual taxa associations with RCI were estimated using linear regression. Microbial cliques associated with RCI were identified using an interpretable machine-learning-based algorithm. All analyses were stratified by food insecurity level, and regression models were adjusted for relevant confounders.

Results

Food insecurity status was weakly associated with RCI (b = 0.06, 95%CI=[0.00, 0.12]). Gut microbiome a-diversity had an inverse association with RCI in both the food secure (b=-0.08, 95%CI=[-0.15, -0.02]) and insecure groups (b=-0.09, 95%CI=[-0.26, 0.07]). Bacteroides sp. was associated with RCI in the food secure group only (b = 0.09, 95%CI= [0.05, 1.36]. We identified two microbial cliques whose associations with RCI were modified by food insecurity status. The presence of the microbial clique with either Eisenbergiella or Eubacterium was more strongly associated with RCI for the food-insecure group (β = 0.29, p < 0.0001) than the food-secure group (β = 0.05, p < 0.001). Alternatively, a microbial clique representing the presence of Ruminococcus torques, Bacteroides, CAG-352F, and/or Eubacterium had a stronger association with RCI for the food-secure group (β = 0.1, p < 0.0001) than the food-insecure group (β = 0.07, p = 0.01).

Conclusions

Food insecurity may modify the relationship between the gut microbiome and RCI. These findings suggest environmental and lifestyle factors in potential prevention strategies against RCI.

Effect of melatonin on gut microbiome and metabolomics in diabetic cognitive impairment

Introduction

Diabetic cognitive impairment(DCI) presents as a central nervous complication of diabetes especially among aging population. Melatonin (MEL) is known for its antioxidant and anti-inflammation effects in neuroprotective aspects. Recent evidence has demonstrated that the gut microbiome plays a key role in DCI by modulating cognitive function through the gut-brain crosstalk. MEL has been shown to modulate gut microbiota composition in diabetic model. However, the underlying mechanism through which the gut microbiome contributes to DCI remains unclear. This study aims to investigate the effect and mechanism of MEL in attenuating DCI in relation to regulating the gut microbiome and metabolomics.

Methods

Cognitive and memory function were assessed by the Morris water maze test, histopathological assessment of brain tissues, and immunoblotting of neuroinflammation and apoptosis. The levels of serum tumor necrosis factor-α (TNF-α) and Interleukin-18 (IL-18) were measured by enzyme-linked immunoassays to reflect the circulatory inflammation level.16S rRNA microbiome sequencing analysis was performed on control mice(db-m group), diabetic mice(db-db group) and MEL-treated diabetic mice(db-dbMEL group). Gut metabolites changes were characterized using liquid chromatography tandem mass spectrometry (LC-MS/MS).

Results

Our study confirmed that MEL alleviated diabetes-induced cognition and memory dysfunction. MEL protected against neuroinflammation and apoptosis in hippocampus of db-db mice. MEL corrected the increased abundance of Bacteroides and Dorea and the reduced abundance of Prevotella in db-db mice. The vast majority of differential metabolites among the three groups were lipids and lipid-like molecules. MEL significantly restored the reduced levels of pyruvate and lactic acid.

Discussion

Our results supported the use of MEL as a promising therapeutic agent for DCI, in which the underlying mechanism may be associated with gut microbiome and metabolomics regulation.

Effect of fruits granola (Frugra®) consumption on blood pressure reduction and intestinal microbiome in patients undergoing hemodialysis

Cardiovascular diseases (CVDs) are a major cause of death in patients undergoing hemodialysis (HD). Blood pressure (BP) and uremic toxins are well-known risk factors for CVDs, which are influenced by diet. Dietary fiber supplementation in patients undergoing HD may reduce the risk of CVDs by improving lipid profiles and inflammatory status and lowering the levels of the uremic toxin indoxyl sulfate (IS). In this study, we investigated the relationship between the intestinal microbiota and risk factors for CVDs, such as BP and serum IS, in patients undergoing HD who consumed fruits granola (FGR). The study participants were selected from patients undergoing HD at the Izu Nagaoka Daiichi Clinic and consumed FGR for 2 months. Body composition and blood samples were tested at months 0, 1, 2 and fecal samples were collected at months 0 and 2 for intestinal microbiota analysis. FGR consumption decreased systolic and diastolic BP, estimated salt intake, and serum IS levels and improved the stool characteristics according to the Bristol Stool Form Scale (N = 24). Gut microbiota analysis showed an increase in the alpha diversity and abundance of Blautia and Neglecta. The abundance of lactic acid- and ethanol-producing bacteria also significantly increased, whereas the abundance of indole-producing bacteria significantly decreased. FGR consumption could be a useful tool for salt reduction, fiber supplementation, and improvement of the intestinal environment, thus contributing to improvement of BP and the reduction of other risk factors for CVDs in patients undergoing HD.

Predicting superagers: a machine learning approach utilizing gut microbiome features

Objective

Cognitive decline is often considered an inevitable aspect of aging; however, recent research has identified a subset of older adults known as "superagers" who maintain cognitive abilities comparable to those of younger individuals. Investigating the neurobiological characteristics associated with superior cognitive function in superagers is essential for understanding "successful aging." Evidence suggests that the gut microbiome plays a key role in brain function, forming a bidirectional communication network known as the microbiome-gut-brain axis. Alterations in the gut microbiome have been linked to cognitive aging markers such as oxidative stress and inflammation. This study aims to investigate the unique patterns of the gut microbiome in superagers and to develop machine learning-based predictive models to differentiate superagers from typical agers.

Methods

We recruited 161 cognitively unimpaired, community-dwelling volunteers aged 60 years or from dementia prevention centers in Seoul, South Korea. After applying inclusion and exclusion criteria, 115 participants were included in the study. Following the removal of microbiome data outliers, 102 participants, comprising 57 superagers and 45 typical agers, were finally analyzed. Superagers were defined based on memory performance at or above average normative values of middle-aged adults. Gut microbiome data were collected from stool samples, and microbial DNA was extracted and sequenced. Relative abundances of bacterial genera were used as features for model development. We employed the LightGBM algorithm to build predictive models and utilized SHAP analysis for feature importance and interpretability.

Results

The predictive model achieved an AUC of 0.832 and accuracy of 0.764 in the training dataset, and an AUC of 0.861 and accuracy of 0.762 in the test dataset. Significant microbiome features for distinguishing superagers included Alistipes, PAC001137_g, PAC001138_g, Leuconostoc, and PAC001115_g. SHAP analysis revealed that higher abundances of certain genera, such as PAC001138_g and PAC001115_g, positively influenced the likelihood of being classified as superagers.

Conclusion

Our findings demonstrate the machine learning-based predictive models using gut-microbiome features can differentiate superagers from typical agers with a reasonable performance.

Chemotherapy-induced gut microbiome disruption, inflammation, and cognitive decline in female patients with breast cancer

Chemotherapy is notorious for causing behavioral side effects (e.g., cognitive decline). Notably, the gut microbiome has recently been reported to communicate with the brain to affect behavior, including cognition. Thus, the aim of this clinical longitudinal observational study was to determine whether chemotherapy-induced disruption of the gut microbial community structure relates to cognitive decline and circulating inflammatory signals. Fecal samples, blood, and cognitive measures were collected from 77 patients with breast cancer before, during, and after chemotherapy. Chemotherapy altered the gut microbiome community structure and increased circulating TNF-α. Both the chemotherapy-induced changes in microbial relative abundance and decreased microbial diversity were related to elevated circulating pro-inflammatory cytokines TNF-α and IL-6. Participants reported subjective cognitive decline during chemotherapy, which was not related to changes in the gut microbiome or inflammatory markers. In contrast, a decrease in overall objective cognition was related to a decrease in microbial diversity, independent of circulating cytokines. Stratification of subjects, via a reliable change index based on 4 objective cognitive tests, identified objective cognitive decline in 35% of the subjects. Based on a differential microbial abundance analysis, those characterized by cognitive decline had unique taxonomic shifts (Faecalibacterium, Bacteroides, Fusicatenibacter, Erysipelotrichaceae UCG-003, and Subdoligranulum) over chemotherapy treatment compared to those without cognitive decline. Taken together, gut microbiome change was associated with cognitive decline during chemotherapy, independent of chemotherapy-induced inflammation. These results suggest that microbiome-related strategies may be useful for predicting and preventing behavioral side effects of chemotherapy.

Association of Methyl Donor Nutrients' Dietary Intake and Cognitive Impairment in the Elderly Based on the Intestinal Microbiome

Globally, cognitive impairment (CI) is the leading cause of disability and dependency among the elderly, presenting a significant public health concern. However, there is currently a deficiency in pharmacological interventions that can effectively cure or significantly reverse the progression of cognitive impairment. Methyl donor nutrients (MDNs), including folic acid, choline, and vitamin B12, have been identified as potential enhancers of cognitive function. Nevertheless, there remains a dearth of comprehensive research investigating the connection between the dietary intake of MDNs and CI. In our study, we comprehensively assessed the relationship between MDNs' dietary intake and CI in older adults, utilizing 16S rRNA gene sequencing to investigate the potential underlying mechanisms. The results showed an obvious difference in the methyl-donor nutritional quality index (MNQI) between the dementia (D) group and the dementia-free (DF) group. Specifically, there was a lower MNQI in the D group than that in the DF group. For the gut microbiome, the beta diversity of gut flora exhibited higher levels in the high methyl-donor nutritional quality (HQ) group as opposed to the low methyl-donor nutritional quality (LQ) group, and lower levels in the D group in comparison to the DF group. Subsequently, we performed a correlation analysis to examine the relationship between the relative abundance of microbiota, the intake of MDNs, and Montreal Cognitive Assessment (MoCA) scores, ultimately identifying ten genera with potential regulatory functions. Additionally, KEGG pathway analyses suggested that the one-carbon metabolism, chronic inflammation, and DNA synthesis potentially serve as pathways through which MDNs may be promising for influencing cognitive function. These results implied that MDNs might have the potential to enhance cognitive function through the regulation of microbiota homeostasis. This study offers dietary recommendations for the prevention and management of CI in the elderly.

A risk estimation method for depression based on the dysbiosis of intestinal microbiota in Japanese patients

Introduction

Early detection of depression is important for preventing depression-related suicides and reducing the risk of recurrence. This study explored the association between depression and intestinal microbiota and developed a depression risk-estimation method based on this.

Methods

The intestinal microbiota of Japanese patients with depression (33 males and 35 females) and disease-free controls (246 males and 384 females) in their 20's to 60's were compared by sex using 16S rRNA gene amplicon sequencing. A depression-risk estimation method was developed using structural equation modeling.

Results

Intestinal bacteria taxa that differed between depression and control groups were identified based on effect size (absolute value greater than 0.2). Neglecta was more abundant, while Coprobacter, Butyricimonas, Clostridium_XlVb, and Romboutsia were less abundant in the male depression group compared to the male control group. In the female depression group, Massilimicrobiota, Merdimonas, and Sellimonas were more abundant, whereas Dorea and Agathobacter were less abundant compared to the female control group. Several of the intestinal bacterial taxa that were less abundant in depression were associated with butyrate or hydrogen production. Using these depression-associated intestinal bacteria as indicators, risk-estimation models using structural equation modeling for depression were developed. In the risk-estimation models for males and females, the areas under the receiver operating characteristic curve were 0.72 and 0.70, respectively, indicating that these models can distinguish between individuals with and without depression.

Conclusions

This study provides insights into depression etiology and aids in its early detection and treatment.

Characteristics of the gut microbiota of patients with symptomatic carotid atherosclerotic plaques positive for bacterial genetic material

Background

The gut microbiota (GM) is believed to be closely associated with symptomatic carotid atherosclerosis (SCAS), yet more evidence is needed to substantiate the significant role of GM in SCAS. This study, based on the detection of bacterial DNA in carotid plaques, explores the characteristics of GM in SCAS patients with plaque bacterial genetic material positivity, aiming to provide a reference for subsequent research.

Methods

We enrolled 27 healthy individuals (NHF group) and 23 SCAS patients (PFBS group). We utilized 16S rDNA V3-V4 region gene sequencing to analyze the microbiota in fecal samples from both groups, as well as in plaque samples from the carotid bifurcation extending to the origin of the internal carotid artery in all patients.

Results

Our results indicate significant differences in the gut microbiota (GM) between SCAS patients and healthy individuals. The detection rate of bacterial DNA in plaque samples was approximately 26%. Compared to patients with negative plaques (PRSOPWNP group), those with positive plaques (PRSOPWPP group) exhibited significant alterations in their GM, particularly an upregulation of 11 bacterial genera (such as Klebsiella and Streptococcus) in the gut, which were also present in the plaques. In terms of microbial gene function prediction, pathways such as Fluorobenzoate degradation were significantly upregulated in the GM of patients with positive plaques.

Conclusion

In summary, our study is the first to identify significant alterations in the gut microbiota of patients with positive plaques, providing crucial microbial evidence for further exploration of the pathogenesis of SCAS.