Your browser doesn't support javascript.
loading
Mostrar: 20 | 50 | 100
Resultados 1 - 4 de 4
Filtrar
Más filtros











Base de datos
Intervalo de año de publicación
1.
Int J Mol Sci ; 25(12)2024 Jun 18.
Artículo en Inglés | MEDLINE | ID: mdl-38928411

RESUMEN

This study aimed to investigate the gut microbiota composition in children with autism spectrum disorder (ASD) compared to neurotypical (NT) children, with a focus on identifying potential differences in gut bacteria between these groups. The microbiota was analyzed through the massive sequencing of region V3-V4 of the 16S RNA gene, utilizing DNA extracted from stool samples of participants. Our findings revealed no significant differences in the dominant bacterial phyla (Firmicutes, Bacteroidota, Actinobacteria, Proteobacteria, Verrucomicrobiota) between the ASD and NT groups. However, at the genus level, notable disparities were observed in the abundance of Blautia, Prevotella, Clostridium XI, and Clostridium XVIII, all of which have been previously associated with ASD. Furthermore, a sex-based analysis unveiled additional discrepancies in gut microbiota composition. Specifically, three genera (Megamonas, Oscilibacter, Acidaminococcus) exhibited variations between male and female groups in both ASD and NT cohorts. Particularly noteworthy was the exclusive presence of Megamonas in females with ASD. Analysis of predicted metabolic pathways suggested an enrichment of pathways related to amine and polyamine degradation, as well as amino acid degradation in the ASD group. Conversely, pathways implicated in carbohydrate biosynthesis, degradation, and fermentation were found to be underrepresented. Despite the limitations of our study, including a relatively small sample size (30 ASD and 31 NT children) and the utilization of predicted metabolic pathways derived from 16S RNA gene analysis rather than metagenome sequencing, our findings contribute to the growing body of evidence suggesting a potential association between gut microbiota composition and ASD. Future research endeavors should focus on validating these findings with larger sample sizes and exploring the functional significance of these microbial differences in ASD. Additionally, there is a critical need for further investigations to elucidate sex differences in gut microbiota composition and their potential implications for ASD pathology and treatment.


Asunto(s)
Trastorno del Espectro Autista , Microbioma Gastrointestinal , Humanos , Microbioma Gastrointestinal/genética , Trastorno del Espectro Autista/microbiología , Trastorno del Espectro Autista/metabolismo , Femenino , Masculino , Niño , ARN Ribosómico 16S/genética , Bacterias/clasificación , Bacterias/genética , Bacterias/metabolismo , Bacterias/aislamiento & purificación , Heces/microbiología , Preescolar , Factores Sexuales , Caracteres Sexuales , Redes y Vías Metabólicas
2.
Behav Sci (Basel) ; 13(7)2023 Jun 30.
Artículo en Inglés | MEDLINE | ID: mdl-37503995

RESUMEN

Autism Spectrum Disorder (ASD) is a complex neurodevelopmental disorder characterised by deficits in social interaction and communication, as well as restricted and stereotyped interests. Due of the high prevalence of gastrointestinal disorders in individuals with ASD, researchers have investigated the gut microbiota as a potential contributor to its aetiology. The relationship between the microbiome, gut, and brain (microbiome-gut-brain axis) has been acknowledged as a key factor in modulating brain function and social behaviour, but its connection to the aetiology of ASD is not well understood. Recently, there has been increasing attention on the relationship between the immune system, gastrointestinal disorders and neurological issues in ASD, particularly in relation to the loss of specific species or a decrease in microbial diversity. It focuses on how gut microbiota dysbiosis can affect gut permeability, immune function and microbiota metabolites in ASD. However, a very complete study suggests that dysbiosis is a consequence of the disease and that it has practically no effect on autistic manifestations. This is a review of the relationship between the immune system, microbial diversity and the microbiome-gut-brain axis in the development of autistic symptoms severity and a proposal of a novel role of gut microbiome in ASD, where dysbiosis is a consequence of ASD-related behaviour and where dysbiosis in turn accentuates the autistic manifestations of the patients via the microbiome-gut-brain axis in a feedback circuit.

3.
Nutrients ; 14(22)2022 Nov 14.
Artículo en Inglés | MEDLINE | ID: mdl-36432504

RESUMEN

Gestational diabetes (GD), pre-gestational diabetes (PD), and pre-eclampsia (PE) are morbidities affecting gestational health which have been associated with dysbiosis of the mother's gut microbiota. This study aimed to assess the extent of change in the gut microbiota diversity, short-chain fatty acids (SCFA) production, and fecal metabolites profile in a sample of Mexican women affected by these disorders. Fecal samples were collected from women with GD, PD, or PE in the third trimester of pregnancy, along with clinical and biochemical data. Gut microbiota was characterized by high-throughput DNA sequencing of V3-16S rRNA gene libraries; SCFA and metabolites were measured by High-Pressure Liquid Chromatography (HPLC) and (Fourier Transform Ion Cyclotron Mass Spectrometry (FT-ICR MS), respectively, in extracts prepared from feces. Although the results for fecal microbiota did not show statistically significant differences in alfa diversity for GD, PD, and PE concerning controls, there was a difference in beta diversity for GD versus CO, and a high abundance of Proteobacteria, followed by Firmicutes and Bacteroidota among gestational health conditions. DESeq2 analysis revealed bacterial genera associated with each health condition; the Spearman's correlation analyses showed selected anthropometric, biochemical, dietary, and SCFA metadata associated with specific bacterial abundances, and although the HPLC did not show relevant differences in SCFA content among the studied groups, FT-ICR MS disclosed the presence of interesting metabolites of complex phenolic, valeric, arachidic, and caprylic acid nature. The major conclusion of our work is that GD, PD, and PE are associated with fecal bacterial microbiota profiles, with distinct predictive metagenomes.


Asunto(s)
Diabetes Gestacional , Microbioma Gastrointestinal , Preeclampsia , Embarazo , Humanos , Femenino , Microbioma Gastrointestinal/genética , ARN Ribosómico 16S/análisis , Disbiosis/microbiología , Heces/microbiología , Ácidos Grasos Volátiles/metabolismo , Bacterias
4.
Microorganisms ; 8(1)2020 Jan 10.
Artículo en Inglés | MEDLINE | ID: mdl-31936722

RESUMEN

In this work, we studied 217 Mexican subjects divided into six groups with different stages of glucose intolerance: 76 Controls (CO), 54 prediabetes (PRE), 14 T2D no medication (T2D-No-M), 14 T2D with Metformin (T2D-M), 22 T2D with polypharmacy (T2D-P), and 37 T2D with polypharmacy and insulin (T2D-P+I). We aimed to determine differences in the gut microbiota diversity for each condition. At the phylum level, we found that Firmicutes and Bacteroidetes outline major changes in the gut microbiota. The gut bacterial richness and diversity of individuals in the T2D-No-M group were lesser than other groups. Interestingly, we found a significant difference in the beta diversity of the gut microbiota among all groups. Higher abundance was found for Comamonadaceae in PRE, and Sutterella spp. in T2D-No-M. In addition, we found associations of specific microbial taxa with clinical parameters. Finally, we report predicted metabolic pathways of gut microbiota linked to T2D-M and PRE conditions. Collectively, these results indicate that each group has specific predicted metabolic characteristics and gut bacteria populations for each phenotype. The results of this study could be used to define strategies to modulate gut microbiota through noninvasive treatments, such as dietary intervention, probiotics or prebiotics, and to improve glucose tolerance of individuals with prediabetes or T2D.

SELECCIÓN DE REFERENCIAS
DETALLE DE LA BÚSQUEDA