Irritable bowel syndrome (IBS) is diagnosed by subjective clinical symptoms. We aimed to establish an objective IBS prediction model based on gut microbiome analyses employing machine learning. We collected fecal samples and clinical data from 85 adult patients who met the Rome III criteria for IBS, as well as from 26 healthy controls. The fecal gut microbiome profiles were analyzed by 16S ribosomal RNA sequencing, and the determination of short-chain fatty acids was performed by gas chromatography–mass spectrometry. The IBS prediction model based on gut microbiome data after machine learning was validated for its consistency for clinical diagnosis. The fecal microbiome alpha-diversity indices were significantly smaller in the IBS group than in the healthy controls. The amount of propionic acid and the difference between butyric acid and valerate were significantly higher in the IBS group than in the healthy controls (p < 0.05). Using LASSO logistic regression, we extracted a featured group of bacteria to distinguish IBS patients from healthy controls. Using the data for these featured bacteria, we established a prediction model for identifying IBS patients by machine learning (sensitivity >80%; specificity >90%). Gut microbiome analysis using machine learning is useful for identifying patients with IBS.

Executive function (EF) consists of explicit emotion regulation (EER) and cognitive control (CC). Childhood EER in particular predicts mental and physical health in adulthood. Identifying factors affecting EER development has implications for lifelong physical and mental health. Gut microbiota (GM) has attracted attention as a potential biomarker for risk of physical and mental problems in adulthood. Furthermore, GM is related to brain function/structure, which plays a crucial role in emotional processing. However, little is known about how GM compositions are associated with the development of emotion regulation in early childhood. Therefore, in this study, we examined 257 children aged 3–4 to investigate links between GM and risk to EF. EF was measured using the Mother-Reported Behavior Rating Inventory of Executive Function–Preschool version. GM composition (alpha/beta diversity and genus abundance) was evaluated using 16S rRNA gene sequencing and compared between EF-risk and non-risk groups. Our results show that children with EER-risk (an index of inhibitory self-control) had a higher abundance of the genera Actinomyces and Sutterella. Although we have not established a direct link between GM and CC risk, our findings indicate that GM of preschoolers is closely associated with emotional processing and that EERrisk children have more inflammation-related bacteria.

Objective: This study aimed to identify periodontal pathogens involved in the onset and progression of OSCC. Methods: Saliva samples were collected from 112 patients without oral mucosal diseases (OMDs) as controls; 36 patients with oral potentially malignant disorders (OPMDs); and 104 patients with OSCC. Periodontal examinations were performed on all patients. Endpoint PCR was performed for seven species of oral pathogens. The 16S rRNA analysis was performed using 20 DNA samples from each group. Results: Periodontitis tended to worsen in the OMDs group compared to the control group. The number of oral bacteria was significantly higher in the OSCC group than in the other groups. The detection rates of P. gingivalis and Aggregatibacter actinomycetemcomitans (A. actinomycetemcomitans) were significantly higher in the OSCC group than those in the control group. From 16S rRNA analysis, the relative abundance of Prevotella buccae and intermedia was significantly higher in OSCC than in the control. Moreover, LPS derived from P. gingivalis contributes to the early development of oral epithelial precancerous lesions and carcinomas in mice. Conclusions: Specific periodontal pathogens are present in the oral cavities of patients with OPMDs and OSCC, and changes in the bacterial flora due to their presence may contribute to the onset and progression of OMDs.

Background/Objectives: Periodontitis is caused by bacterial plaque. The oral microflora may interact with the intestinal microflora and play a role in the development of periodontitis. The periodontal inflamed surface area (PISA) has been shown to be a useful indicator of periodontal disease related to systemic diseases; however, few studies have shown an association between PISA and the bacterial flora. This study aimed to determine the association between PISA and oral and intestinal bacteria. Methods: Participants were recruited between 2018 and 2021 at the Medical and Dental Collaboration Center of Kanagawa Dental University Hospital. A periodontal clinical examination was performed, and the PISA was calculated. Salivary tests were conducted, and leukocyte scores in the saliva were calculated. Moreover, 16S rRNA amplicon sequencing was performed using saliva and stool samples to analyze oral and intestinal bacteria, respectively. Results: Higher PISA levels resulted in an increased presence of Bacteroides and a decreased presence of Proteobacteria and Actinobacteria in the saliva. An increase in Bacteroides was detected in the saliva of patients with high leukocyte scores. No correlation was observed between PISA and intestinal bacteria. Conclusions: Bacteroides was highly abundant in the saliva of patients with worsened periodontal conditions, as indicated by PISA. No association was found between PISA and intestinal bacteria.

Background/Objectives: Frailty and sarcopenia are age-related conditions that impair quality of life in older adults. Although the gut microbiota affects muscle health, its role in sarcopenia remains unclear. This study investigated the association between gut microbiota enterotypes and sarcopenia in community-dwelling older Japanese adults. Methods: In this cross-sectional study, 322 community-dwelling adults from the Japanese Frailty Scale cohort aged ≥65 years were assessed for sarcopenia using standardized criteria. Physical measures included grip strength, gait speed, and skeletal muscle mass index (SMI). Gut microbiota profiles were analyzed using 16S rRNA sequencing and classified into four enterotypes (ET-B1, ET-B2, ET-R, ET-P). Associations with sarcopenia were evaluated using multivariable logistic regression. Results: Participants with enterotype ET-B2 had significantly lower microbial diversity (p < 0.01) and reduced grip strength (p < 0.05), whereas the difference in SMI compared with ET-P individuals did not reach statistical significance (p = 0.0625). Sarcopenia prevalence differed significantly between enterotypes (p < 0.01). A predictive model incorporating age and ET-B2 exhibited an area under the receiver operating characteristic curve (AUC) of 0.795, significantly higher than the age-only model (AUC = 0.686, DeLong’s test, p < 0.05). Conclusions: Gut microbiota composition, especially enterotype ET-B2, is significantly associated with sarcopenia in older Japanese adults. These findings indicate the potential for using the gut microbiota as a biomarker and therapeutic target in treating age-related muscle decline.

The prevalence of postpartum mental illness is steadily increasing, a tendency that was exacerbated by the COVID-19 pandemic. Recent studies show that maternal depression is no longer confined to the perinatal period, and this necessitates long-term assessment and support for maternal mental health. It is critical to identify the factors that are related to depression among mothers, and this requires the development of integrated mental and physical health care encompassing both psychological aspects and intestinal microbiota, physical conditions, and dietary habits. Studies conducted in western countries have examined the association between gut microbiota and depressive disorders. However, little is known concerning postpartum mothers in healthy populations. In addition, even in healthy populations, some mothers will have severe depression. This is because mothers in Japan are typically hesitant to disclose psychiatric symptoms and tend not to consult specialists. Therefore, we conducted a cross-sectional study to investigate the association of intestinal microbiota, physical condition, and dietary habits with depressed mood in healthy mothers in Japan. We found that microbiome diversity (Shannon α) and relative abundance of butyrate-producing bacteria (e.g. Lachnospira, Faecalibacterium, and Subdoligranulum), obtained using 16S rRNA gene-sequencing analysis, were associated with high levels of depressive mood. Mothers who have this attribute showed poorer sleep quality and worse physical condition than mothers with low levels of depressive mood. The evaluation of dietary habits suggested that dietary patterns high in soy products, fermented food, seaweed, and mushrooms, as well as vegetables, are beneficial for depression and intestinal microbiota (e.g. Lachnospira, Agathobacter, and Subdoligranulum).