Decreased circulating IPA levels identify subjects with metabolic comorbidities: A multi-omics study.

In recent years several experimental observations demonstrated that the gut microbiome plays a role in regulating positively or negatively metabolic homeostasis. Indole-3-propionic acid (IPA), a Tryptophan catabolic product mainly produced by C. Sporogenes, has been recently shown to exert either favorable or unfavorable effects in the context of metabolic and cardiovascular diseases. We performed a study to delineate clinical and multiomics characteristics of human subjects characterized by low and high IPA levels. Subjects with low IPA blood levels showed insulin resistance, overweight, low-grade inflammation, and features of metabolic syndrome compared to those with high IPA. Metabolomics analysis revealed that IPA was negatively correlated with leucine, isoleucine, and valine metabolism. Transcriptomics analysis in colon tissue revealed the enrichment of several signaling, regulatory, and metabolic processes. Metagenomics revealed several OTU of ruminococcus, alistipes, blautia, butyrivibrio and akkermansia were significantly enriched in highIPA group while in lowIPA group Escherichia-Shigella, megasphera, and Desulfovibrio genus were more abundant. Next, we tested the hypothesis that treatment with IPA in a mouse model may recapitulate the observations of human subjects, at least in part. We found that a short treatment with IPA (4 days at 20/mg/kg) improved glucose tolerance and Akt phosphorylation in the skeletal muscle level, while regulating blood BCAA levels and gene expression in colon tissue, all consistent with results observed in human subjects stratified for IPA levels. Our results suggest that treatment with IPA may be considered a potential strategy to improve insulin resistance in subjects with dysbiosis.

Impact of Insulin Degludec/Liraglutide Fixed Combination on the Gut Microbiomes of Elderly Patients With Type 2 Diabetes: Results From A Subanalysis of A Small Non-Randomised Single Arm Study.

In elderly Type 2 Diabetes (T2D) patients the relationship between the destabilization of gut microbiome and reversal of dysbiosis via glucose lowering drugs has not been explored. We investigated the effect of 6 months therapy with a fixed combination of Liraglutide and Degludec on the composition of the gut microbiome and its relationship with Quality of Life, glucose metabolism, depression, cognitive function, and markers of inflammation in a group of very old T2D subjects (n=24, 5 women, 19 men, mean age=82 years). While we observed no significant differences in microbiome biodiversity or community among study participants (N = 24, 19 men, mean age 82 years) who responded with decreased HbA1c (n=13) versus those who did not (n=11), our results revealed a significant increase in Gram-negative Alistipes among the former group (p=0.013). Among the responders, changes in the Alistipes content were associated directly with cognitive improvement (r=0.545, p=0.062) and inversely with TNFα levels (r=-0.608, p=0.036). Our results suggest that this combination drug may have a significant impact on both gastrointestinal microbes and cognitive function in elderly T2D individuals.

Machine Learning Data Analysis Highlights the Role of Parasutterella and Alloprevotella in Autism Spectrum Disorders.

In recent years, the involvement of the gut microbiota in disease and health has been investigated by sequencing the 16S gene from fecal samples. Dysbiotic gut microbiota was also observed in Autism Spectrum Disorder (ASD), a neurodevelopmental disorder characterized by gastrointestinal symptoms. However, despite the relevant number of studies, it is still difficult to identify a typical dysbiotic profile in ASD patients. The discrepancies among these studies are due to technical factors (i.e., experimental procedures) and external parameters (i.e., dietary habits). In this paper, we collected 959 samples from eight available projects (540 ASD and 419 Healthy Controls, HC) and reduced the observed bias among studies. Then, we applied a Machine Learning (ML) approach to create a predictor able to discriminate between ASD and HC. We tested and optimized three algorithms: Random Forest, Support Vector Machine and Gradient Boosting Machine. All three algorithms confirmed the importance of five different genera, including Parasutterella and Alloprevotella. Furthermore, our results show that ML algorithms could identify common taxonomic features by comparing datasets obtained from countries characterized by latent confounding variables.

Not just a Snapshot: An Italian Longitudinal Evaluation of Stability of Gut Microbiota Findings in Parkinson's Disease.

Most research analyzed gut-microbiota alterations in Parkinson's disease (PD) through cross-sectional studies, as single snapshots, without considering the time factor to either confirm methods and findings or observe longitudinal variations. In this study, we introduce the time factor by comparing gut-microbiota composition in 18 PD patients and 13 healthy controls (HC) at baseline and at least 1 year later, also considering PD clinical features. PD patients and HC underwent a fecal sampling at baseline and at a follow-up appointment. Fecal samples underwent sequencing and 16S rRNA amplicons analysis. Patients'clinical features were valued through Hoehn&Yahr (H&Y) staging-scale and Movement Disorder Society Unified PD Rating Scale (MDS-UPDRS) Part-III. Results demonstrated stability in microbiota findings in both PD patients and HC over a period of 14 months: both alfa and beta diversity were maintained in PD patients and HC over the observation period. In addition, differences in microbiota composition between PD patients and HC remained stable over the time period. Moreover, during the same period, patients did not experience any worsening of either staging or motor impairment. Our findings, highlighting the stability and reproducibility of the method, correlate clinical and microbiota stability over time and open the scenario to more extensive longitudinal evaluations.

Intestinal Taxa Abundance and Diversity in Inflammatory Bowel Disease Patients: An Analysis including Covariates and Confounders.

Intestinal dysbiosis has been widely documented in inflammatory bowel diseases (IBDs) and is thought to influence the onset and perpetuation of gut inflammation. However, it remains unclear whether such bacterial changes rely in part on the modification of an IBD-associated lifestyle (e.g., smoking and physical activity) and diet (e.g., rich in dairy products, cereals, meat and vegetables). In this study, we investigated the impact of these habits, which we defined as confounders and covariates, on the modulation of intestinal taxa abundance and diversity in IBD patients. 16S rRNA gene sequence analysis was performed using genomic DNA extracted from the faecal samples of 52 patients with Crohn's disease (CD) and 58 with ulcerative colitis (UC), which are the two main types of IBD, as well as 42 healthy controls (HC). A reduced microbial diversity was documented in the IBD patients compared with the HC. Moreover, we identified specific confounders and covariates that influenced the association between some bacterial taxa and disease extent (in UC patients) or behaviour (in CD patients) compared with the HC. In particular, a PERMANOVA stepwise regression identified the variables "age", "eat yogurt at least four days per week" and "eat dairy products at least 4 days per week" as covariates when comparing the HC and patients affected by ulcerative proctitis (E1), left-sided UC (distal UC) (E2) and extensive UC (pancolitis) (E3). Instead, the variables "age", "gender", "eat meat at least four days per week" and "eat bread at least 4 days per week" were considered as covariates when comparing the HC with the CD patients affected by non-stricturing, non-penetrating (B1), stricturing (B2) and penetrating (B3) diseases. Considering such variables, our analysis indicated that the UC extent differentially modulated the abundance of the Bifidobacteriaceae, Rikenellaceae, Christensenellaceae, Marinifilaceae, Desulfovibrionaceae, Lactobacillaceae, Streptococcaceae and Peptostreptococcaceae families, while the CD behaviour influenced the abundance of Christensenellaceae, Marinifilaceae, Rikenellaceae, Ruminococcaceae, Barnesiellaceae and Coriobacteriaceae families. In conclusion, our study indicated that some covariates and confounders related to an IBD-associated lifestyle and dietary habits influenced the intestinal taxa diversity and relative abundance in the CD and UC patients compared with the HC. Indeed, such variables should be identified and excluded from the analysis to characterize the bacterial families whose abundance is directly modulated by IBD status, as well as disease extent or behaviour.

GATA6 Deficiency Leads to Epithelial Barrier Dysfunction and Enhances Susceptibility to Gut Inflammation.

BACKGROUND AND AIMS: Intestinal barrier dysfunction is a hallmark of inflammatory bowel diseases [IBD], but the mechanisms that lead to such a defect are not fully understood. This study was aimed at characterising the factors involved in the defective barrier function in IBD. METHODS: Transcriptome analysis was performed on colon samples taken from healthy controls [CTR] and IBD patients. Expression of GATA-binding factor 6 [GATA6], a transcription factor involved in intestinal epithelial cell differentiation, was evaluated in colon samples taken from CTR and IBD patients by real-time polymerase chain reaction [PCR] and immunohistochemistry. Intestinal sections of wild-type and Gata6del mice, which exhibit a conditional Gata6 deletion in intestinal epithelial cells and which are either left untreated or receive subcutaneous indomethacin or rectal trinitrobenzene sulphonic acid, were stained with haematoxylin and eosin. In parallel, some Gata6del mice received antibiotics to deplete intestinal flora. Mucosal inflammatory cell infiltration and cytokine production were evaluated by flow cytometry and real-time PCR, respectively, and tight junction proteins were examined by immunofluorescence. Intestinal barrier integrity was assessed by fluorescein isothiocyanate [FITC]-dextran assay. RESULTS: Multiple genes involved in cell commitment/proliferation and wound healing were differentially expressed in IBD compared with CTR. Among these, GATA6 was significantly decreased in the IBD epithelium compared with CTR. In mice, conditional deletion of GATA6 in the intestinal epithelium induced primarily epithelial damage, diminished zonula occludens-1 expression, and enhanced intestinal permeability, ultimately resulting in bacteria-driven local immune response and enhanced susceptibility to gut inflammation. CONCLUSIONS: Reduced expression of GATA6 promotes intestinal barrier dysfunction, thus amplifying intestinal inflammatory pathology.

Can Gut Microbiota Be a Good Predictor for Parkinson's Disease? A Machine Learning Approach.

The involvement of the gut microbiota in Parkinson's disease (PD), investigated in several studies, identified some common alterations of the microbial community, such as a decrease in Lachnospiraceae and an increase in Verrucomicrobiaceae families in PD patients. However, the results of other bacterial families are often contradictory. Machine learning is a promising tool for building predictive models for the classification of biological data, such as those produced in metagenomic studies. We tested three different machine learning algorithms (random forest, neural networks and support vector machines), analyzing 846 metagenomic samples (472 from PD patients and 374 from healthy controls), including our published data and those downloaded from public databases. Prediction performance was evaluated by the area under curve, accuracy, precision, recall and F-score metrics. The random forest algorithm provided the best results. Bacterial families were sorted according to their importance in the classification, and a subset of 22 families has been identified for the prediction of patient status. Although the results are promising, it is necessary to train the algorithm with a larger number of samples in order to increase the accuracy of the procedure.