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1.
Clin Rheumatol ; 42(1): 203-214, 2023 Jan.
Article in English | MEDLINE | ID: mdl-36201123

ABSTRACT

INTRODUCTION/OBJECTIVES: Persistent hyperuricemia is a key factor in gout; however, only 13.5% of hyperuricemic individuals manifest the disease. The gut microbiota could be one of the many factors underlying this phenomenon. We aimed to assess the difference in taxonomic and predicted functional profiles of the gut microbiota between asymptomatic hyperuricemia (AH) individuals and gout patients. METHODS: The V3-V4 region of the 16S rRNA gene of the gut microbiota of AH individuals, gout patients, and controls was sequenced. Bioinformatic analyses were carried out with QIIME2 and phyloseq to determine the difference in the relative abundance of bacterial genera among the study groups. Tax4fun2 was used to predict the functional profile of the gut microbiota. RESULTS: AH individuals presented a higher abundance of butyrate- and propionate-producing bacteria than gout patients; however, the latter had more bacteria capable of producing acetate. The abundance of Prevotella genus bacteria was not significantly different between the patients but was higher than that in controls. This result was corroborated by the functional profile, in which AH individuals had less pyruvate oxidase abundance than gout patients and less abundance of an enzyme that regulates glutamate synthetase activation than controls. CONCLUSION: We observed a distinctive taxonomic profile in AH individuals characterized by a higher abundance of short-chain fatty acid-producing bacteria in comparison to those observed in gout patients. Furthermore, we provide scientific evidence that indicates that the gut microbiota of AH individuals could provide anti-inflammatory mediators, which prevent the appearance of gout flares. Key Points • AH and gout patients both have a higher abundance of Prevotella genus bacteria than controls. • AH individuals' gut microbiota had more butyrate- and propionate-producing bacteria than gout patients. • The gut microbiome of AH individuals provides anti-inflammatory mediators that could prevent gout flares.


Subject(s)
Gastrointestinal Microbiome , Gout , Hyperuricemia , Humans , Gastrointestinal Microbiome/genetics , Propionates , RNA, Ribosomal, 16S/genetics , Fatty Acids, Volatile , Butyrates , Bacteria/genetics , Anti-Inflammatory Agents
2.
Mol Med ; 27(1): 50, 2021 05 24.
Article in English | MEDLINE | ID: mdl-34030623

ABSTRACT

OBJECTIVE: To evaluate the taxonomic composition of the gut microbiome in gout patients with and without tophi formation, and predict bacterial functions that might have an impact on urate metabolism. METHODS: Hypervariable V3-V4 regions of the bacterial 16S rRNA gene from fecal samples of gout patients with and without tophi (n = 33 and n = 25, respectively) were sequenced and compared to fecal samples from 53 healthy controls. We explored predictive functional profiles using bioinformatics in order to identify differences in taxonomy and metabolic pathways. RESULTS: We identified a microbiome characterized by the lowest richness and a higher abundance of Phascolarctobacterium, Bacteroides, Akkermansia, and Ruminococcus_gnavus_group genera in patients with gout without tophi when compared to controls. The Proteobacteria phylum and the Escherichia-Shigella genus were more abundant in patients with tophaceous gout than in controls. Fold change analysis detected nine genera enriched in healthy controls compared to gout groups (Bifidobacterium, Butyricicoccus, Oscillobacter, Ruminococcaceae_UCG_010, Lachnospiraceae_ND2007_group, Haemophilus, Ruminococcus_1, Clostridium_sensu_stricto_1, and Ruminococcaceae_UGC_013). We found that the core microbiota of both gout groups shared Bacteroides caccae, Bacteroides stercoris ATCC 43183, and Bacteroides coprocola DSM 17136. These bacteria might perform functions linked to one-carbon metabolism, nucleotide binding, amino acid biosynthesis, and purine biosynthesis. Finally, we observed differences in key bacterial enzymes involved in urate synthesis, degradation, and elimination. CONCLUSION: Our findings revealed that taxonomic variations in the gut microbiome of gout patients with and without tophi might have a functional impact on urate metabolism.


Subject(s)
Dysbiosis , Gastrointestinal Microbiome , Gout/metabolism , Metagenome , Metagenomics , Uric Acid/metabolism , Biodiversity , Computational Biology/methods , Gout/etiology , Gout/pathology , Humans , Metagenomics/methods , Protein Interaction Mapping , Protein Interaction Maps
3.
Nutr. hosp ; 31(3): 1074-1081, mar. 2015. ilus, tab
Article in Spanish | IBECS | ID: ibc-134399

ABSTRACT

Introducción: La obesidad es un grave problema de salud pública en México, la Encuesta Nacional de Salud y Nutrición (ENSANUT 2012) reporta una prevalencia de sobrepeso y obesidad en niños de 5 a 11 años de 34.4%, siendo el país con mayor prevalencia a nivel mundial. Investigaciones recientes han sugerido que la microbiota intestinal puede ser factor de riesgo de la obesidad por su influencia en el metabolismo humano. Objetivo: Evaluar si existe asociación entre el perfil de la microbiota intestinal y la obesidad infantil y si esta asociación se modifica dependiendo del patrón de alimentación de una muestra de niños de edad escolar de la Ciudad de México. Metodología y Resultados: Estudio transversal en 1042 niños de 6 a 14 años, a todos se les aplicó cuestionario de actividad física, antecedentes patológicos personales y heredofamiliares de obesidad y diabetes tipo 2. La definición de los patrones de alimentación se realizó por análisis de componentes principales (ACP). La asociación entre microbiota intestinal y sobrepeso/obesidad dependiendo de la dieta se evaluó con modelos de regresión logística, ajustados por factores de confusión. Encontramos que un perfil de abundancia relativa alta de Firmicutes y una abundancia relativa baja de Bacteroidetes aunado a un consumo elevado de dietas ricas en carbohidratos y grasas saturadas se asocia con un mayor riesgo de obesidad. Conclusión: La interacción entre la microbiota intestinal y la dieta, particularmente con alto contenido de grasas y carbohidratos simples incrementa las posibilidades de presentar obesidad (AU)


Introductión: Obesity is a serious public health problem in Mexico, the National Health and Nutrition Survey (ENSANUT 2012) reported a 34.4% prevalence of overweight, and obesity in children aged 5-11. Recent research has suggested that the gut microbiota may be a risk factor of obesity through its influence on human metabolism. Aim of the study: To evaluate association between the intestinal microbiota profile and obesity among children and whether this association is modified depending on the feeding pattern of a sample of schoolchildren from Mexico City. Metodology and Results: Cross-sectional study on 1042 children aged 6-14 years; physical activity questionnaire, personal medical history and heredofamilial of obesity and type 2 diabetes were administered to all the children. Eating patterns was performed by principal component analysis (PCA). The association between intestinal microbiota and overweight / obesity depending on diet was assessed with logistic regression models. Conclusion: Our results shows that the interaction between the intestinal microbiota and diet, particularly high in fats and simple carbohydrates increases the chance of developing obesity (AU)


Subject(s)
Humans , Male , Female , Child, Preschool , Child , Adolescent , Pediatric Obesity/etiology , Energy Intake , Energy Requirement , Gram-Negative Bacteria/pathogenicity , Microbiota , Diet, High-Fat/adverse effects , Dietary Carbohydrates/adverse effects , Body Mass Index
4.
Nutr Hosp ; 31(3): 1074-81, 2014 Dec 16.
Article in Spanish | MEDLINE | ID: mdl-25726195

ABSTRACT

UNLABELLED: INTRODUCTIÓN: Obesity is a serious public health problem in Mexico, the National Health and Nutrition Survey (ENSANUT 2012) reported a 34.4% prevalence of overweight, and obesity in children aged 5-11. Recent research has suggested that the gut microbiota may be a risk factor of obesity through its influence on human metabolism. AIM OF THE STUDY: To evaluate association between the intestinal microbiota profile and obesity among children and whether this association is modified depending on the feeding pattern of a sample of schoolchildren from Mexico City. METODOLOGY AND RESULTS: Cross-sectional study on 1042 children aged 6-14 years; physical activity questionnaire, personal medical history and heredofamilial of obesity and type 2 diabetes were administered to all the children. Eating patterns was performed by principal component analysis (PCA). The association between intestinal microbiota and overweight / obesity depending on diet was assessed with logistic regression models. CONCLUSION: Our results shows that the interaction between the intestinal microbiota and diet, particularly high in fats and simple carbohydrates increases the chance of developing obesity.


Introducción: La obesidad es un grave problema de salud pública en México, la Encuesta Nacional de Salud y Nutrición (ENSANUT 2012) reporta una prevalencia de sobrepeso y obesidad en niños de 5 a 11 años de 34.4%, siendo el país con mayor prevalencia a nivel mundial. Investigaciones recientes han sugerido que la microbiota intestinal puede ser factor de riesgo de la obesidad por su influencia en el metabolismo humano. Objetivo: Evaluar si existe asociación entre el perfil de la microbiota intestinal y la obesidad infantil y si esta asociación se modifica dependiendo del patrón de alimentación de una muestra de niños de edad escolar de la Ciudad de México. Metodología y Resultados: Estudio transversal en 1042 niños de 6 a 14 años, a todos se les aplicó cuestionario de actividad física, antecedentes patológicos personales y heredofamiliares de obesidad y diabetes tipo 2. La definición de los patrones de alimentación se realizó por análisis de componentes principales (ACP). La asociación entre microbiota intestinal y sobrepeso/obesidad dependiendo de la dieta se evaluó con modelos de regresión logística, ajustados por factores de confusión. Encontramos que un perfil de abundancia relativa alta de Firmicutes y una abundancia relativa baja de Bacteroidetes aunado a un consumo elevado de dietas ricas en carbohidratos y grasas saturadas se asocia con un mayor riesgo de obesidad. Conclusión: La interacción entre la microbiota intestinal y la dieta, particularmente con alto contenido de grasas y carbohidratos simples incrementa las posibilidades de presentar obesidad.


Subject(s)
Eating , Energy Intake , Gram-Positive Bacteria/physiology , Intestines/microbiology , Microbiota , Obesity/etiology , Adolescent , Anthropometry , Bacterial Typing Techniques , Bacteroides/isolation & purification , Bacteroides/physiology , Child , Cross-Sectional Studies , Diabetes Mellitus, Type 2/epidemiology , Diet , Dietary Carbohydrates/adverse effects , Dietary Fats/adverse effects , Feeding Behavior , Female , Gram-Positive Bacteria/isolation & purification , Humans , Male , Motor Activity , Obesity/epidemiology , Socioeconomic Factors
5.
Ann Hepatol ; 11(6): 876-81, 2012.
Article in English | MEDLINE | ID: mdl-23109451

ABSTRACT

INTRODUCTION: The treatment of hepatitis C virus (HCV) genotype 1 with ribavirin (RBV) and pegylated-interferon alpha (peg-IFNα) provides a low-level sustained virological response (SVR). Single nucleotide polymorphisms (SNPs) in the interleukin 28B (IL28B) gene have been identified as SVR predictors. Our aim was to establish an association between three IL28B SNPs (rs8099917, rs12979860, and rs8103142) and the peg-IFNα/RBV treatment response in a Mexican population cohort with chronic HCV. MATERIAL AND METHODS: A cohort study was performed with 83 chronic HCV patients at the Fundación Clínica Médica Sur in Mexico City. All patients were treated with peg-IFNα and RBV. The data were analyzed by logistic regression, with adjustments for age, gender, and viral genotype, to determine any associations between the SNPs and the treatment response. RESULTS: In the study group of 83 HCV patients, the main genotype was genotype 1 (70%, n = 58) and the overall SVR was 32.53% (n = 27). In the HCV-1 group, SVR was 27%, whereas SVR was 44% in the HCV-2 group. We found an association between rs12979860 CC and SVR in a codominant model (OR = 4.83, 95% CI = 1.12-20.8, P = 0.033). There was no statistically significant association between SVR and rs8099917 or rs8103142. rs12979860 polymorphisms of CC, CT, and TT, were present in 24%, 41%, and 35% of patients, respectively. CONCLUSION: A Mexican HCV-1-infected population treated with peg-IFNα and RVB had a low SVR rate, which was associated with the SNP rs12979860 (CC). SVR was not associated with the SNPs rs8099917 or rs8103142.


Subject(s)
Antiviral Agents/therapeutic use , Hepatitis C, Chronic/drug therapy , Hepatitis C, Chronic/genetics , Interferon-alpha/therapeutic use , Interleukins/genetics , Polyethylene Glycols/therapeutic use , Polymorphism, Single Nucleotide , Ribavirin/therapeutic use , Adult , Age Factors , Aged , Chi-Square Distribution , Drug Therapy, Combination , Female , Gene Frequency , Genotype , Hepacivirus/genetics , Hepatitis C, Chronic/diagnosis , Hepatitis C, Chronic/epidemiology , Humans , Interferons , Logistic Models , Male , Mexico/epidemiology , Middle Aged , Odds Ratio , Phenotype , Risk Factors , Treatment Outcome
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