Variation of Serum Uric Acid Is Associated With Gut Microbiota in Patients With Diabetes Mellitus

Impact of Sleeve Gastrectomy on Uric Acid Levels in Patients with Obesity: A Comparative Study

PURPOSE

This study aimed to investigate the incidence of hyperuricemia in obese individuals with or without metabolic syndrome and assess the impact of sleeve gastrectomy surgery on the amelioration of hyperuricemia and metabolic syndrome.

MATERIALS AND METHODS

A prospective study was conducted on patients with obesity who were candidates for laparoscopic sleeve gastrectomy. These patients were diligently followed for 1 year after the surgical procedure. The assessment of hyperuricemia and metabolic syndrome was carried out both before and one year after the surgery.

RESULTS

A total of 198 patients (30 males and 168 females) underwent sleeve gastrectomy. After 1 year, there was a notable decline in the prevalence of hyperuricemia, decreasing from 77 to 36 cases (a reduction of 46.75%) among females and from 18 to 8 cases (a reduction of 44.44%) among males. Prior to the surgery, 60.6% of patients (120 out of 198) were diagnosed with metabolic syndrome, and 36.7% of these patients exhibited improvements in their metabolic syndrome status. Among individuals with metabolic syndrome, significant enhancements were observed in various anthropometric and laboratory measurements, including reductions in hypertriglyceridemia, hyperuricemia, and hypercholesteremia. A logistic regression analysis revealed that in females, changes in creatinine, glomerular filtration rate (GFR), weight loss, body mass index (BMI), and triglyceride reduction all had a notable impact on the likelihood of recovering from hyperuricemia.

CONCLUSION

These findings underscore the clinical relevance of this surgical intervention in managing obesity-related conditions.

A Prebiotic Diet Containing Galactooligosaccharides and Polydextrose Produces Dynamic and Reproducible Changes in the Gut Microbial Ecosystem in Male Rats

Despite substantial evidence supporting the efficacy of prebiotics for promoting host health and stress resilience, few experiments present evidence documenting the dynamic changes in microbial ecology and fecal microbially modified metabolites over time. Furthermore, the literature reports a lack of reproducible effects of prebiotics on specific bacteria and bacterial-modified metabolites. The current experiments examined whether consumption of diets enriched in prebiotics (galactooligosaccharides (GOS) and polydextrose (PDX)), compared to a control diet, would consistently impact the gut microbiome and microbially modified bile acids over time and between two research sites. Male Sprague Dawley rats were fed control or prebiotic diets for several weeks, and their gut microbiomes and metabolomes were examined using 16S rRNA gene sequencing and untargeted LC-MS/MS analysis. Dietary prebiotics altered the beta diversity, relative abundance of bacterial genera, and microbially modified bile acids over time. PICRUSt2 analyses identified four inferred functional metabolic pathways modified by the prebiotic diet. Correlational network analyses between inferred metabolic pathways and microbially modified bile acids revealed deoxycholic acid as a potential network hub. All these reported effects were consistent between the two research sites, supporting the conclusion that dietary prebiotics robustly changed the gut microbial ecosystem. Consistent with our previous work demonstrating that GOS/PDX reduces the negative impacts of stressor exposure, we propose that ingesting a diet enriched in prebiotics facilitates the development of a health-promoting gut microbial ecosystem.

Mechanistic insights of soluble uric acid-induced insulin resistance: Insulin signaling and beyond

Hyperuricemia is a metabolic disease caused by purine nucleotide metabolism disorder. The prevalence of hyperuricemia is increasing worldwide, with a growing trend in the younger populations. Although numerous studies have indicated that hyperuricemia may be an independent risk factor for insulin resistance, the causal relationship between the two is controversial. There are few reviews, however, focusing on the relationship between uric acid (UA) and insulin resistance from experimental studies. In this review, we summarized the experimental models related to soluble UA-induced insulin resistance in pancreas and peripheral tissues, including skeletal muscles, adipose tissue, liver, heart/cardiomyocytes, vascular endothelial cells and macrophages. In addition, we summarized the research advances about the key mechanism of UA-induced insulin resistance. Moreover, we attempt to identify novel targets for the treatment of hyperuricemia-related insulin resistance. Lastly, we hope that the present review will encourage further researches to solve the chicken-and-egg dilemma between UA and insulin resistance, and provide strategies for the pathogenesis and treatment of hyperuricemia related metabolic diseases.

Relationship between rs4349859 and rs116488202 polymorphisms close to MHC-I region and serum urate levels in patients with gout

BACKGROUND

Gout is the most common inflammatory rheumatic disease and elevated levels of serum urate (SU) are the main cause for its development. Major histocompatibility complex class 1 (MHC-1) plays an important role in the development of multiple inflammatory diseases; however, there is little evidence of its involvement in gout. The present study focused on evaluating the association of the rs4349859 and rs116488202 single nucleotide polymorphisms (SNPs) close to the MHC-1 region in patients with gout.

METHODS AND RESULTS

One hundred and seventy-six individuals of Mexican origin were included, of which 81 were patients with primary gout and 95 were healthy controls. The rs4349859 and rs116488202 SNPs were genotyped using TaqMan probes by allelic discrimination by real-time PCR. Serum concentrations of biochemical parameters were measured with enzymatic methods. Descriptive statistics were applied and P-values < 0.05 were considered significant. It was observed that the rs4349859 and rs116488202 SNPs showed significant association with the risk of gout (OR = 146, 95%CI = 44.8-480.2, P < 0.01; OR = 2885, 95%CI = 265-31398, P < 0.01, respectively). Our results also showed significantly higher serum SU levels in gout patients with respect to controls (P < 0.01) in the carriers of the GA genotype compared with the GG genotype of the rs4349859 variant, and in the carriers of the CT genotype compared with the CC genotype of the rs116488202 variant.

CONCLUSION

The study revealed that rs4349859 and rs116488202 SNPs close to MHC-I region confers strong susceptibility to gout in Mexican population, and the heterozygous genotypes of both were associated with higher levels of SU.

Rational design of a genome-based insulated system in Escherichia coli facilitates heterologous uricase expression for hyperuricemia treatment

Hyperuricemia is a prevalent disease worldwide that is characterized by elevated urate levels in the blood owing to purine metabolic disorders, which can result in gout and comorbidities. To facilitate the treatment of hyperuricemia through the uricolysis, we engineered a probiotic Escherichia coli Nissle 1917 (EcN) named EcN C6 by inserting an FtsP-uricase cassette into an "insulated site" located between the uspG and ahpF genes. Expression of FtsP-uricase in this insulated region did not influence the probiotic properties or global gene transcription of EcN but strongly increased the enzymatic activity for urate degeneration, suggesting that the genome-based insulated system is an ideal strategy for EcN modification. Oral administration of EcN C6 successfully alleviated hyperuricemia, related symptoms and gut microbiota in a purine-rich food-induced hyperuricemia rat model and a uox-knockout mouse model. Together, our study provides an insulated site for heterologous gene expression in EcN strain and a recombinant EcN C6 strain as a safe and effective therapeutic candidate for hyperuricemia treatment.

Prediction model of poorly differentiated colorectal cancer (CRC) based on gut bacteria

BACKGROUND

The mortality of colorectal cancer is high, the malignant degree of poorly differentiated colorectal cancer is high, and the prognosis is poor.

OBJECTIVE

To screen the characteristic intestinal microbiota of poorly differentiated intestinal cancer.

METHODS

Fecal samples were collected from 124 patients with moderately differentiated CRC and 123 patients with poorly differentiated CRC, and the bacterial 16S rRNA V1-V4 region of the fecal samples was sequenced. Alpha diversity analysis was performed on fecal samples to assess the diversity and abundance of flora. The RDP classifier Bayesian algorithm was used to analyze the community structure. Linear discriminant analysis and Student's t test were used to screen the differences in flora. The PICRUSt1 method was used to predict the bacterial function, and six machine learning models, including logistic regression, random forest, neural network, support vector machine, CatBoost and gradient boosting decision tree, were used to construct a prediction model for the poor differentiation of colorectal cancer.

RESULTS

There was no significant difference in fecal flora alpha diversity between moderately and poorly differentiated colorectal cancer (P > 0.05). The bacteria that accounted for a large proportion of patients with poorly differentiated and moderately differentiated colorectal cancer were Blautia, Escherichia-Shigella, Streptococcus, Lactobacillus, and Bacteroides. At the genus level, there were nine bacteria with high abundance in the poorly differentiated group, including Bifidobacterium, norank_f__Oscillospiraceae, Eisenbergiella, etc. There were six bacteria with high abundance in the moderately differentiated group, including Megamonas, Erysipelotrichaceae_UCG-003, Actinomyces, etc. The RF model had the highest prediction accuracy (100.00% correct). The bacteria that had the greatest variable importance in the model were Pseudoramibacter, Megamonas and Bifidobacterium.

CONCLUSION

The degree of pathological differentiation of colorectal cancer was related to gut flora, and poorly differentiated colorectal cancer had some different bacterial flora, and intestinal bacteria can be used as biomarkers for predicting poorly differentiated CRC.

The role of gut microbiota in gout: Is gut microbiota a potential target for gout treatment

Numerous studies have demonstrated that gut microbiota is essential for the host's health because it regulates the host's metabolism, endocrine, and immune systems. In recent years, increasing evidence has shown that gut microbiota plays a role in the onset and progression of gout. Changes in the composition and metabolism of the gut microbiota, result in abnormalities of uric acid degradation, increasing uric acid generation, releasing pro-inflammatory mediators, and intestinal barrier damage in developing gout. As a result, gout therapy that targets gut microbiota has drawn significant interest. This review summarized how the gut microbiota contributes to the pathophysiology of gout and how gout affects the gut microbiota. Additionally, this study explained how gut microbiota might serve as a unique index for the diagnosis of gout and how conventional gout treatment medicines interact with it. Finally, prospective therapeutic approaches focusing on gut microbiota for the prevention and treatment of gout were highlighted, which may represent a future avenue in gout treatment.

Physiopathological mechanisms involved in the development of hypertension associated with gut dysbiosis and the effect of nutritional/pharmacological interventions

The gut microbiota dysbiosis represents a triggering factor for cardiovascular diseases, including hypertension. In addition to the harmful impact caused by hypertension on different target organs, gut dysbiosis is capable of causing direct damage to critical organs such as the brain, heart, blood vessels, and kidneys. In this sense, it should be noted that pharmacological and nutritional interventions may influence gut microbiota composition, either inducing or preventing the development of hypertension. Some of the most important nutritional interventions at this level are represented by pro-, pre-, post- and/or syn-biotics, as well as polysaccharides, polyunsaturated fatty acids ω-3, polyphenols and fiber contained in different foods. Meanwhile, certain natural and synthetic active pharmaceutical ingredients, including antibiotics, antihypertensive and immunosuppressive drugs, vegetable extracts and vitamins, may also have a key role in the modulation of both gut microbiota and cardiovascular health. Additionally, gut microbiota may influence drugs and food-derived bioactive compounds metabolism, positively or negatively affecting their biological behavior facing established hypertension. The understanding of the complex interactions between gut microbiome and drug/food response results of great importance to developing improved pharmacological therapies for hypertension prevention and treatment. The purpose of this review is to critically outline the most relevant and recent findings on cardiovascular, renal and brain physiopathological mechanisms involved in the development of hypertension associated with changes in gut microbiota, besides the nutritional and pharmacological interventions potentially valuable for the prevention and treatment of this prevalent pathology. Finally, harmful food/drug interventions on gut microbiota are also described.

Testing Two Somatic Cell Count Cutoff Values for Bovine Subclinical Mastitis Detection Based on Milk Microbiota and Peripheral Blood Leukocyte Transcriptome Profile

Somatic cell count (SCC) is an important indicator of the health state of bovine udders. However, the exact cut-off value used for differentiating the cows with healthy quarters from the cows with subclinical mastitis remains controversial. Here, we collected composite milk (milk from four udder quarters) and peripheral blood samples from individual cows in two different dairy farms and used 16S rRNA gene sequencing combined with RNA-seq to explore the differences in the milk microbial composition and transcriptome of cows with three different SCC levels (LSCC: <100,000 cells/mL, MSCC: 100,000−200,000 cells/mL, HSCC: >200,000 cells/mL). Results showed that the milk microbial profiles and gene expression profiles of samples derived from cows in the MSCC group were indeed relatively easily discriminated from those from cows in the LSCC group. Discriminative analysis also uncovered some differentially abundant microbiota at the genus level, such as Bifidobacterium and Lachnospiraceae_AC2044_group, which were more abundant in milk samples from cows with SCC below 100,000 cells/mL. As for the transcriptome profiling, 79 differentially expressed genes (DEGs) were found to have the same direction of regulation in two sites, and functional analyses also showed that biological processes involved in inflammatory responses were more active in MSCC and HSCC cows. Overall, these results showed a similarity between the milk microbiota and gene expression profiles of MSCC and HSCC cows, which presented further evidence that 100,000 cells/ml is a more optimal cut-off value than 200,000 cells/mL for intramammary infection detection at the cow level.

The harmful intestinal microbial community accumulates during DKD exacerbation and microbiome-metabolome combined validation in a mouse model

OBJECTIVE

Diabetic kidney disease (DKD) is one of the most prevalent complications of diabetes mellitus (DM) and is associated with gut microbial dysbiosis. We aim to build a diagnostic model to aid clinical practice and uncover a crucial harmful microbial community that contributes to DKD pathogenesis and exacerbation.

DESIGN

A total of 528 fecal samples from 180 DKD patients and 348 non-DKD populations (138 DM and 210 healthy volunteers) from the First Affiliated Hospital of Zhengzhou University were recruited and randomly divided into a discovery phase and a validation phase. The gut microbial composition was compared using 16S rRNA sequencing. Then, the 180 DKD patients were stratified into four groups based on clinical stages and underwent gut microbiota analysis. We established DKD mouse models and a healthy fecal microbiota transplantation (FMT) model to validate the effects of gut microbiota on DKD and select the potential harmful microbial community. Untargeted metabolome-microbiome combined analysis of mouse models helps decipher the pathogenetic mechanism from a metabolic perspective.

RESULTS

The diversity of the gut microbiome was significantly decreased in DKD patients when compared with that of the non-DKD population and was increased in the patients with more advanced DKD stages. The DKD severity in mice was relieved after healthy gut microbiota reconstruction. The common harmful microbial community was accumulated in the subjects with more severe DKD phenotypes (i.e., DKD and DKD5 patients and DKD mice). The harmful microbial community was positively associated with the serum injurious metabolites (e.g., cholic acid and hippuric acid).

CONCLUSION

The fecal microbial community was altered markedly in DKD. Combining the fecal analysis of both human and animal models selected the accumulated harmful pathogens. Partially recovering healthy gut microbiota can relieve DKD phenotypes via influencing pathogens' effect on DKD mice's metabolism.

Potential roles of gut microbiota and microbial metabolites in chronic inflammatory pain and the mechanisms of therapy drugs

Observational findings achieved that gut microbes mediate human metabolic health and disease risk. The types of intestinal microorganisms depend on the intake of food and drugs and are also related to their metabolic level and genetic factors. Recent studies have shown that chronic inflammatory pain is closely related to intestinal microbial homeostasis. Compared with the normal intestinal flora, the composition of intestinal flora in patients with chronic inflammatory pain had significant changes in Actinomycetes, Firmicutes, Bacteroidetes, etc. At the same time, short-chain fatty acids and amino acids, the metabolites of intestinal microorganisms, can regulate neural signal molecules and signaling pathways, thus affecting the development trend of chronic inflammatory pain. Glucocorticoids and non-steroidal anti-inflammatory drugs in the treatment of chronic inflammatory pain, the main mechanism is to affect the secretion of inflammatory factors and the abundance of intestinal bacteria. This article reviews the relationship between intestinal microorganisms and their metabolites on chronic inflammatory pain and the possible mechanism.