Focus on the gut-brain axis

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Petr75
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Re: Focus on the gut-brain axis

Post by Petr75 » Sat Oct 24, 2020 12:02 pm

2020 Sep 8
Division of Gastroenterology, Department of Internal Medicine, Rush University Medical Center, Chicago
Single-Arm, Non-randomized, Time Series, Single-Subject Study of Fecal Microbiota Transplantation in Multiple Sclerosis
https://www.frontiersin.org/articles/10 ... 00978/full

..Longitudinal Assessment of Gait Metrics

During the gait condition, the subject's normal gait metrics were primarily enhanced after each FMT, and significantly improved over time indicating improved walking and balance (Figures 3A–F, Supplementary Table 11). Stride time significantly decreased over time (Bonferroni: P < 0.0001) indicating subject's walking speed improved. Stride distance significantly increased over time (Bonferroni: P < 0.0001) suggesting subject's walking steps increased in distance. Step width did not change significantly from baseline to Week 52 (Bonferroni: P > 0.9999). Cadence significantly increased over time (Bonferroni: P < 0.0001) indicating subject's number of steps/minute increased. Average pelvis forward velocity significantly increased over time (Bonferroni: P < 0.0001), approximating the increased speed of the body center of mass. Pelvis smoothness significantly increased over time (Bonferroni: P < 0.0001), suggesting the subject's body walking motion was more fluid. Side gaze gait, alternating gaze gait, and within lab visit results in Supplementary Figures 10–12, Supplementary Tables 12–14..

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Petr75
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Re: Focus on the gut-brain axis

Post by Petr75 » Sun Oct 25, 2020 8:50 am

2020 Oct 6
Department of Pathology, University of Utah School of Medicine, Salt Lake City
Molecular patterns from a human gut-derived Lactobacillus strain suppress pathogenic infiltration of leukocytes into the central nervous system
https://pubmed.ncbi.nlm.nih.gov/33023618/

Abstract

Background: Multiple sclerosis (MS) is an inflammatory demyelinating disease that affects 2.5 million people worldwide. Growing evidence suggests that perturbation of the gut microbiota, the dense collection of microorganisms that colonize the gastrointestinal tract, plays a functional role in MS. Indeed, specific gut-resident bacteria are altered in patients with MS compared to healthy individuals, and colonization of gnotobiotic mice with MS-associated microbiota exacerbates preclinical models of MS. However, defining the molecular mechanisms by which gut commensals can remotely affect the neuroinflammatory process remains a critical gap in the field.

Methods: We utilized monophasic experimental autoimmune encephalomyelitis (EAE) in C57BL/6J mice and relapse-remitting EAE in SJL/J mice to test the effects of the products from a human gut-derived commensal strain of Lactobacillus paracasei (Lb).

Results: We report that Lb can ameliorate preclinical murine models of MS with both prophylactic and therapeutic administrations. Lb ameliorates disease through a Toll-like receptor 2-dependent mechanism via its microbe-associated molecular patterns that can be detected in the systemic circulation, are sufficient to downregulate chemokine production, and can reduce immune cell infiltration into the central nervous system (CNS). In addition, alterations in the gut microbiota mediated by Lb-associated molecular patterns are sufficient to provide partial protection against neuroinflammatory diseases.

Conclusions: Local Lb modulation of the gut microbiota and the shedding of Lb-associated molecular patterns into the circulation may be important physiological signals to prevent aberrant peripheral immune cell infiltration into the CNS and have relevance to the development of new therapeutic strategies for MS.

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Petr75
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Re: Focus on the gut-brain axis

Post by Petr75 » Fri Oct 30, 2020 5:55 am

2020 Oct 12
University Sarajevo School of Science and Technology, Bosnia and Herzegovina
Using data science for medical decision making case: role of gut microbiome in multiple sclerosis
https://pubmed.ncbi.nlm.nih.gov/33046051/

Abstract

Background: A decade ago, the advancements in the microbiome data sequencing techniques initiated the development of research of the microbiome and its relationship with the host organism. The development of sophisticated bioinformatics and data science tools for the analysis of large amounts of data followed. Since then, the analyzed gut microbiome data, where microbiome is defined as a network of microorganisms inhabiting the human intestinal system, has been associated with several conditions such as irritable bowel syndrome - IBS, colorectal cancer, diabetes, obesity, and metabolic syndrome, and lately in the study of Parkinson's and Alzheimer's diseases as well. This paper aims to provide an understanding of differences between microbial data of individuals who have been diagnosed with multiple sclerosis and those who were not by exploiting data science techniques on publicly available data.

Methods: This study examines the relationship between multiple sclerosis (MS), an autoimmune central nervous system disease, and gut microbial community composition, using the samples acquired by 16s rRNA sequencing technique. We have used three different sets of MS samples sequenced during three independent studies (Jangi et al, Nat Commun 7:1-11, 2016), (Miyake et al, PLoS ONE 10:0137429, 2015), (McDonald et al, Msystems 3:00031-18, 2018) and this approach strengthens our results. Analyzed sequences were from healthy control and MS groups of sequences. The extracted set of statistically significant bacteria from the (Jangi et al, Nat Commun 7:1-11, 2016) dataset samples and their statistically significant predictive functions were used to develop a Random Forest classifier. In total, 8 models based on two criteria: bacteria abundance (at six taxonomic levels) and predictive functions (at two levels), were constructed and evaluated. These include using taxa abundances at different taxonomy levels as well as predictive function analysis at different hierarchical levels of KEGG pathways.

Results: The highest accuracy of the classification model was obtained at the genus level of taxonomy (76.82%) and the third hierarchical level of KEGG pathways (70.95%). The second dataset's 18 MS samples (Miyake et al, PLoS ONE 10:0137429, 2015) and 18 self-reported healthy samples from the (McDonald et al, Msystems 3:00031-18, 2018) dataset were used to validate the developed classification model. The significance of this step is to show that the model is not overtrained for a specific dataset but can also be used on other independent datasets. Again, the highest classification model accuracy for both validating datasets combined was obtained at the genus level of taxonomy (70.98%) and third hierarchical level of KEGG pathways (67.24%). The accuracy of the independent set remained very relevant.

Conclusions: Our results demonstrate that the developed classification model provides a good tool that can be used to suggest the presence or absence of MS condition by collecting and analyzing gut microbiome samples. The accuracy of the model can be further increased by using sequencing methods that allow higher taxa resolution (i.e. shotgun metagenomic sequencing).

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Re: Focus on the gut-brain axis

Post by Petr75 » Sat Oct 31, 2020 12:35 am

2020 Oct 19
Department of Biomedical and Health Sciences, University of Vermont, Burlington,
Medical Systems Biology Group, Lübeck Institute of Experimental Dermatology, University of Lübeck, Germany
Interactions between host genetics and gut microbiota determine susceptibility to CNS autoimmunity
https://pubmed.ncbi.nlm.nih.gov/33077601/

Abstract

Multiple sclerosis (MS) is an autoimmune disease of the central nervous system. The etiology of MS is multifactorial, with disease risk determined by genetics and environmental factors. An emerging risk factor for immune-mediated diseases is an imbalance in the gut microbiome. However, the identity of gut microbes associated with disease risk, their mechanisms of action, and the interactions with host genetics remain obscure. To address these questions, we utilized the principal autoimmune model of MS, experimental autoimmune encephalomyelitis (EAE), together with a genetically diverse mouse model representing 29 unique host genotypes, interrogated by microbiome sequencing and targeted microbiome manipulation. We identified specific gut bacteria and their metabolic functions associated with EAE susceptibility, implicating short-chain fatty acid metabolism as a key element conserved across multiple host genotypes. In parallel, we used a reductionist approach focused on two of the most disparate phenotypes identified in our screen. Manipulation of the gut microbiome by transplantation and cohousing demonstrated that transfer of these microbiomes into genetically identical hosts was sufficient to modulate EAE susceptibility and systemic metabolite profiles. Parallel bioinformatic approaches identified Lactobacillus reuteri as a commensal species unexpectedly associated with exacerbation of EAE in a genetically susceptible host, which was functionally confirmed by bacterial isolation and commensal colonization studies. These results reveal complex interactions between host genetics and gut microbiota modulating susceptibility to CNS autoimmunity, providing insights into microbiome-directed strategies aimed at lowering the risk for autoimmune disease and underscoring the need to consider host genetics and baseline gut microbiome composition.

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