Bone metabolism and inflammatory biomarkers in radiographic and non-radiographic axial spondyloarthritis patients: a comprehensive evaluation.

Introduction: Axial spondyloarthritis (axSpA) is a heterogeneous disease that can be represented by radiographic axSpA (r-axSpA) and non-radiographic axSpA (nr-axSpA). This study aimed to evaluate the relationship between the markers of inflammation and bone turnover in r-axSpA patients and nr-axSpA patients. Methods: A cross-sectional study included 29 r-axSpA patients, 10 nr-axSpA patients, and 20 controls matched for age and sex. Plasma markers related to bone remodeling such as human procollagen type 1 N-terminal propeptide (P1NP), sclerostin, tartrate-resistant acid phosphatase 5b (TRACP5b), receptor activator of nuclear factor kappa B ligand (RANKL), and osteoprotegerin (OPG) were measured by an ELISA kit. A panel of 92 inflammatory molecules was analyzed by proximity extension assay. Results: R-axSpA patients had decreased plasma levels of P1NP, a marker of bone formation, compared to controls. In addition, r-axSpA patients exhibited decreased plasma levels of sclerostin, an anti-anabolic bone hormone, which would not explain the co-existence of decreased plasma P1NP concentration; however, sclerostin levels could also be influenced by inflammatory processes. Plasma markers of osteoclast activity were similar in all groups. Regarding inflammation-related molecules, nr-axSpA patients showed increased levels of serum interleukin 13 (IL13) as compared with both r-axSpA patients and controls, which may participate in the prevention of inflammation. On the other hand, r-axSpA patients had higher levels of pro-inflammatory molecules compared to controls (i.e., IL6, Oncostatin M, and TNF receptor superfamily member 9). Correlation analysis showed that sclerostin was inversely associated with IL6 and Oncostatin M among others. Conclusion: Altogether, different inflammatory profiles may play a role in the development of the skeletal features in axSpA patients particularly related to decreased bone formation. The relationship between sclerostin and inflammation and the protective actions of IL13 could be of relevance in the axSpA pathology, which is a topic for further investigation.

Effect of 1-year lifestyle intervention with energy-reduced Mediterranean diet and physical activity promotion on the gut metabolome and microbiota: a randomized clinical trial.

BACKGROUND: The health benefits of the Mediterranean diet (MedDiet) have been linked to the presence of beneficial gut microbes and related metabolites. However, its impact on the fecal metabolome remains poorly understood. OBJECTIVES: Our goal was to investigate the weight-loss effects of a 1-y lifestyle intervention based on an energy-reduced MedDiet coupled with physical activity (intervention group), compared with an ad libitum MedDiet (control group), on fecal metabolites, fecal microbiota, and their potential association with cardiovascular disease risk factors. METHODS: A total of 400 participants (200 from each study group), aged 55-75 y, and at high cardiovascular disease risk, were included. Dietary and lifestyle information, anthropometric measurements, blood biochemical parameters, and stool samples were collected at baseline and after 1 y of follow-up. Liquid chromatography-tandem mass spectrometry was used to profile endogenous fecal metabolites, and 16S amplicon sequencing was employed to profile the fecal microbiota. RESULTS: Compared with the control group, the intervention group exhibited greater weight loss and improvement in various cardiovascular disease risk factors. We identified intervention effects on 4 stool metabolites and subnetworks primarily composed of bile acids, ceramides, and sphingosines, fatty acids, carnitines, nucleotides, and metabolites of purine and the Krebs cycle. Some of these were associated with changes in several cardiovascular disease risk factors. In addition, we observed a reduction in the abundance of the genera Eubacterium hallii group and Dorea, and an increase in alpha diversity in the intervention group after 1 y of follow-up. Changes in the intervention-related microbiota profiles were also associated with alterations in different fecal metabolite subnetworks and some cardiovascular disease risk factors. CONCLUSIONS: An intervention based on an energy-reduced MedDiet and physical activity promotion, compared with an ad libitum MedDiet, was associated with improvements in cardiometabolic risk factors, potentially through modulation of the fecal microbiota and metabolome. This trial was registered at https://www.isrctn.com/ as ISRCTN89898870 (https://doi.org/10.1186/ISRCTN89898870).

Advancing microbiome research with machine learning: key findings from the ML4Microbiome COST action.

The rapid development of machine learning (ML) techniques has opened up the data-dense field of microbiome research for novel therapeutic, diagnostic, and prognostic applications targeting a wide range of disorders, which could substantially improve healthcare practices in the era of precision medicine. However, several challenges must be addressed to exploit the benefits of ML in this field fully. In particular, there is a need to establish "gold standard" protocols for conducting ML analysis experiments and improve interactions between microbiome researchers and ML experts. The Machine Learning Techniques in Human Microbiome Studies (ML4Microbiome) COST Action CA18131 is a European network established in 2019 to promote collaboration between discovery-oriented microbiome researchers and data-driven ML experts to optimize and standardize ML approaches for microbiome analysis. This perspective paper presents the key achievements of ML4Microbiome, which include identifying predictive and discriminatory 'omics' features, improving repeatability and comparability, developing automation procedures, and defining priority areas for the novel development of ML methods targeting the microbiome. The insights gained from ML4Microbiome will help to maximize the potential of ML in microbiome research and pave the way for new and improved healthcare practices.

Linking serum vitamin D levels with gut microbiota after 1-year lifestyle intervention with Mediterranean diet in patients with obesity and metabolic syndrome: a nested cross-sectional and prospective study.

Vitamin D, microbiota, and the Mediterranean diet (MedDiet) have been the focus of recent research due to their potential role in maintaining overall health. We hypothesize that MedDiet may alter the gut microbiota profile through changes in vitamin D levels. We aimed to investigate changes in gut microbiota and serum vitamin D levels after a MedDiet within a lifestyle intervention. The study included 91 patients with obesity and metabolic syndrome, who were categorized based on their serum vitamin D levels as having either optimal or low 25-hydroxyvitamin D [25(OH)D levels]. The profile of the gut microbiota was analyzed by the 16S rRNA sequencing, inferring its functionality through PICRUsT. Participants underwent a hypocaloric MedDiet and change in their lifestyle for 1 year, and the profile and functionality of their gut microbiota were evaluated by analyzing inter-individual differences in time. At baseline, gut microbiota profiles qualitatively differed between participants with Optimal or Low 25(OH)D levels [Unweighted (p = 0.016)]. Moreover, participants with Optimal 25(OH)D levels showed a higher gut microbiota diversity than those with Low 25(OH)D levels (p < 0.05). The differential analysis of abundance between the Low and Optimal 25(OH)D groups revealed differences in the levels of Bacteroides, Prevotella, and two Clostridiales features. After 1-year dietary intervention, both groups increased their 25(OH)D levels. Furthermore, both groups did not show significant differences in gut microbiota diversity, although the Low 25(OH)D group showed greater improvement in gut microbiota diversity by comparing at baseline and after dietary intervention (p < 0.05). Changes in specific bacterial taxa were observed within each group but did not differ significantly between the groups. Metabolic pathway analysis indicated differences in microbial functions between the groups (p < 0.05). These findings suggest that 25(OH)D status is associated with gut microbiota composition, diversity, and functionality, and lifestyle intervention can modulate both gut microbiota and 25(OH)D levels, potentially influencing metabolic pathways.

Carbohydrate quality, fecal microbiota and cardiometabolic health in older adults: a cohort study.

The impact of carbohydrate quality, measured by the carbohydrate quality index (CQI), on gut microbiota and health has been scarcely investigated. The aim of this study was to cross-sectionally and longitudinally explore the relationships between CQI, fecal microbiota, and cardiometabolic risk factors in an elderly Mediterranean population at high cardiovascular risk. At baseline and 1-year, CQI was assessed from food frequency questionnaires data, cardiometabolic risk factors were measured, and fecal microbiota profiled from 16S sequencing. Multivariable-adjusted linear regression models were fitted to assess the associations between tertiles of baseline CQI, fecal microbiota, and cardiometabolic risk factors at baseline, and between tertiles of 1-year change in CQI, 1-year change in fecal microbiota and cardiometabolic risk factors. Cross-sectionally, higher CQI was positively associated with Shannon alpha diversity index, and abundance of genera Faecalibacterium and Christensenellaceae R7 group, and negatively associated with the abundance of Odoribacter, and uncultured Rhodospirillales genera. Some of these genera were associated with higher glycated hemoglobin and lower body mass index. In addition, we observed a positive association between CQI, and some pathways related with the metabolism of butyrate precursors and plants-origin molecules. Longitudinally, 1-year improvement in CQI was associated with a concurrent increase in the abundance of genera Butyrivibrio. Increased abundance of this genera was associated with 1-year improvement in insulin status. These observations suggest that a better quality of carbohydrate intake is associated with improved metabolic health, and this improvement could be modulated by greater alpha diversity and abundance of specific genera linked to beneficial metabolic outcomes.

Gut microbiota in nonalcoholic fatty liver disease: a PREDIMED-Plus trial sub analysis.

To evaluate the changes in the gut microbiota associated with changes in the biochemical markers of nonalcoholic fatty liver disease (NAFLD) after a lifestyle intervention with the Mediterranean diet. Participants (n = 297) from two centers of PREDIMED-Plus trial (Prevención con Dieta Mediterránea) were divided into three different groups based on the change tertile in the Hepatic Steatosis Index (HSI) or the Fibrosis-4 score (FIB-4) between baseline and one year of intervention. One-year changes in HSI were: tertile 1 (T1) (-24.9 to -7.51), T2 (-7.5 to -1.86), T3 (-1.85 to 13.64). The most significant differences in gut microbiota within the year of intervention were observed in the T1 and T3. According to the FIB-4, participants were categorized in non-suspected fibrosis (NSF) and with indeterminate or suspected fibrosis (SF). NSF participants showed higher abundances of Alcaligenaceae, Bacteroidaceae, Bifidobacteriaceae, Clostridiaceae, Enterobacteriaceae, Peptostreptococcaceae, Verrucomicrobiaceae compared to those with SF. Then, participants were divided depending on the FIB-4 tertile of change: T1 (-89.60 to -5.57), T2 (-5.56 to 11.4), and T3 (11.41 to 206.24). FIB-4 T1 showed a decrease in Akkermansia and an increase in Desulfovibrio. T2 had an increase in Victivallaceae, Clostridiaceae, and Desulfovibrio. T3 showed a decrease in Enterobacteriaceae, and an increase in Sutterella, Faecalibacterium, and Blautia. A relation between biochemical index changes of NAFLD/NASH (HSI and FIB-4) and gut microbiota changes were found. These observations highlight the importance of lifestyle intervention in the modulation of gut microbiota and the management of metabolic syndrome and its hepatic manifestations.

What You Need to KnowWhat is the context:Obesity and metabolic syndrome have been associated with nonalcoholic fatty liver disease (NAFLD). Gut microbiota and its interaction with the environment may play a key role in NAFLD.What is new:Mediterranean diet and physical activity can modify the scores for liver steatosis (HSI) and liver fibrosis (FIB−4) in only one year. A relation between the changes in these scores and gut microbiota changes was found.What is the impact:The discovery of microbiota-based biomarkers for NAFLD and the development of strategies to modulate gut microbiota in the treatment of NAFLD.

Adiposity is associated with expansion of the genus Dialister in rheumatoid arthritis patients.

OBJECTIVE: To analyze the intestinal microbiota of patients with rheumatoid arthritis (RA) and obesity and a higher percentage of fatty tissue. METHODS: Nested case-control study of 80 RA patients and 80 age and sex-matched controls. Obesity was defined as a body mass index ≥ 30, and body composition using dual-energy x-ray absorptiometry. The gut microbiota was analyzed using 16 S rRNA gene sequencing; bioinformatics analysis was performed using QIIME2 and PICRUSt. Other variables included averaged 28-joint Disease Activity Score (DAS28-ESR), cytokines and adipokines. Two multivariate were constructed with obesity and fat mass index (FMI). RESULTS: Obesity was more frequent in RA patients than in controls (36.3 % vs 25.1 %; p = 0.026), as was a higher FMI value (mean [SE]=11.6 [3.9] vs 10.2 [3.9]; p = 0.032). Alpha and beta diversity analysis revealed differences in gut microbiota between RA patients with and without obesity. Dialister and Odoribacter were more abundant in RA patients with obesity than in RA patients without obesity, while the genus Clostridium was more abundant in RA patients without obesity. The factors associated with obesity in RA patients were age (OR [95 % CI], 1.09 [1.02-1.17]), mean DAS28-ESR (OR [95 % CI], 1.46 [1.12-1.67]), leptin levels (OR [95 % CI], 1.06 [1.01-1.10]), the genus Dialister (OR [95 % CI], 1.03 [1.01-1.07]), and the genus Clostridium (OR [95 % CI], 0.013 [0.00-0.36]). The associations observed for FMI were similar. CONCLUSIONS: In patients with RA, obesity, and a higher percentage of fatty tissue, intestinal microbiota differed from that of controls and of the other patients. The genus Dialister was associated with obesity and FMI.

The gut microbiome dysbiosis is recovered by restoring a normal diet in hypercholesterolemic pigs.

BACKGROUND: Gut microbiota is thought to modulate cardiovascular risk. However, the effect of cardiovascular primary prevention strategies on gut microbiota remains largely unknown. This study investigates the impact of diet and rosuvastatin interventions on gut microbiota composition in hypercholesterolemic pigs and associated potential changes in host metabolic pathways. METHODS: Diet-induced hypercholesterolemic pigs (n = 32) were randomly distributed to receive one of the following 30-day interventions: (I) continued hypercholesterolemic diet (HCD; n = 9), (II) normocholesterolemic diet (NCD; n = 8), (III) continued HCD plus 40 mg rosuvastatin/daily (n = 7), or (IV) NCD plus 40 mg rosuvastatin/daily (n = 8). Faeces were collected at study endpoint for characterisation of the gut microbiome and metabolic profile prediction (PICRUSt2). TMAO levels and biochemical parameters were determined. RESULTS: Principal coordinate analyses (beta-diversity) showed clear differences in the microbiota of NCD vs HCD pigs (PERMANOVA, p = .001). NCD-fed animals displayed significantly higher alpha-diversity, which inversely correlated with total cholesterol and LDL-cholesterol levels (p < .0003). NCD and HCD animals differed in the abundance of 12 genera (ANCOM; p = .001 vs HCD), and PICRUSt2 analysis revealed detrimental changes in HCD-related microbiota metabolic capacities. These latter findings were associated with a significant fivefold increase in TMAO levels in HCD-fed pigs (p < .0001 vs NCD). The addition of a 30-day rosuvastatin treatment to either of the diets exerted no effects in microbiota nor lipid profile. CONCLUSION: In hypercholesterolemic animals, the ingestion of a low-fat diet for 30 days modifies gut microbiota composition in favour of alpha-diversity and towards a healthy metabolic profile, whereas rosuvastatin treatment for this period exerts no effects.

Association between ultra-processed food consumption and gut microbiota in senior subjects with overweight/obesity and metabolic syndrome.

The production and consumption of ultra-processed foods (UPF) has increased considerably during the last years worldwide. Collective evidence shows the association between UPF consumption and adverse health outcomes, including inflammatory gastro-intestinal disorders and obesity. The gut microbiota has been suggested as potential mediator of the effects of UPF consumption on metabolism and health. However, few studies have been conducted in order to elucidate these aspects. Therefore, the aim of the present study was to assess the cross-sectional associations between UPF consumption and gut microbiota in a population of senior subjects (n = 645) within the frame of the PREDIMED-Plus trial. Eligible participants were men and women (aged 55-75 years), without documented history of cardiovascular disease at enrollment, with overweight/obesity (body mass index ≤ 27 and <40 kg/m2) and metabolic syndrome. Using the information of food frequency questionnaires, the consumption of UPF, expressed as a percentage of total dietary energy intake in kcal/day, was calculated considering those food items classified in group 4 of NOVA system. Population was categorized according to tertiles of UPF consumption. Taxonomic fecal microbiota information, along with blood biochemical parameters, anthropometric measurements and clinical data were obtained. Bioinformatics analysis was performed to study the association between fecal microbiota composition and UPF consumption. We observed that subjects allocated in the highest tertile of UPF consumption (21.4 ± 5.0 % kcal/day) presented lower adherence to MedDiet (p < 0.001) and higher total energy intake (p < 0.001). The taxonomic analysis of the fecal microbiota revealed a significant (Benjamini-Hochberg adjusted p < 0.2) positive association between specific taxa and tertiles (T) of UPF consumption: Alloprevotella (p = 0.041 vs. T2; p = 0.065 vs. T3), Negativibacillus (p = 0.096 vs. T3), Prevotella (p = 0.116 vs. T3), and Sutterella (p = 0.116 vs. T2). UPF consumption was positively associated with lower adherence to MedDiet and higher total energy intake in senior subjects with overweight obesity and metabolic syndrome. In addition, positive association with specific fecal microbiota taxa related to inflammatory gastro-intestinal diseases and low consumption of fruits and vegetables, was observed.

Collinsella is associated with cumulative inflammatory burden in an established rheumatoid arthritis cohort.

OBJECTIVE: To analyze the gut microbiota of patients with rheumatoid arthritis (RA) according to disease activity. METHODS: An observational cross-sectional study of 110 patients with RA and 110 age- and sex-matched controls was performed. Patients were classified according to the disease activity (DAS28 ≥3.2 or DAS28 <3.2). Clinical and epidemiological variables were included. The gut microbiota was analyzed using 16S rRNA sequencing and bioinformatics analysis based on QIIME and PICRUSt. A multivariate analysis was performed to identify factors associated with inflammatory activity. RESULTS: The mean DAS28 indicated remission/low inflammatory activity in 71 patients (64.5 %) and moderate/high activity in 39 (35.5 %) during follow-up. Alpha and beta diversity analysis revealed differences in gut microbiota between the 3 study groups. In the moderate/high activity RA, we observed a significant change in the abundance of genera compared with the other groups. The abundance of Collinsella and Bifidobacterium was increased in RA patients compared with controls. The metabolic profile of gut microbiota was characterized by differences in pathways related to Biosynthesis, Generation of Precursor Metabolites/Energy, and Degradation/Utilization/Assimilation between the 3 groups. The factors associated with cumulative inflammatory activity in RA were age (OR [95 % CI], 1.065 [1.002-1.131]), obesity (OR [95% CI], 3.829 [1.064-8.785]), HAQ score (OR [95% CI], 2.729 [1.240-5.009]), and expansion of the genus Collinsella (OR [95% CI], 3.000 [1.754-9.940]). CONCLUSIONS: The composition of gut microbiota differed between patients with RA and moderate/high activity, patients with remission/low activity, and controls. The genus Collinsella, age, obesity, and physical function were associated with cumulative inflammatory burden in RA.

Taxonomic and Functional Fecal Microbiota Signatures Associated With Insulin Resistance in Non-Diabetic Subjects With Overweight/Obesity Within the Frame of the PREDIMED-Plus Study.

Objective: An altered gut microbiota has been associated with insulin resistance, a metabolic dysfunction consisting of cellular insulin signaling impairment. The aim of the present study is to determine the taxonomic and functional fecal microbiota signatures associated with HOMA-IR index in a population with high cardiovascular risk. Methods: A total of 279 non-diabetic individuals (55-75 years aged) with overweight/obesity and metabolic syndrome were stratified according to tertiles of HOMA-IR index. Blood biochemical parameters, anthropometric measurements and fecal samples were collected at baseline. Fecal microbial DNA extraction, 16S amplicon sequencing and bioinformatics analysis were performed. Results: Desulfovibrio, Odoribacter and Oscillospiraceae UCG-002 were negatively associated with HOMA-IR index, whereas predicted total functional abundances revealed gut metabolic modules mainly linked to amino acid degradation. Butyricicoccus, Erysipelotrichaceae UCG-003, Faecalibacterium were positively associated with HOMA-IR index, whereas predicted total functional abundances revealed gut metabolic modules mainly linked to saccharide degradation. These bacteria contribute differentially to the gut metabolic modules, being the degree of contribution dependent on insulin resistance. Both taxa and gut metabolic modules negatively associated to HOMA-IR index were linked to mechanisms involving sulfate reducing bacteria, improvement of intestinal gluconeogenesis and production of acetate. Furthermore, both taxa and gut metabolic modules positively associated to HOMA-IR index were linked to production and mechanisms of action of butyrate. Conclusions: Specific taxonomic and functional fecal microbiota signatures associated with insulin resistance were identified in a non-diabetic population with overweight/obesity at high cardiovascular risk. These findings suggest that tailoring therapies based on specific fecal microbiota profiles could be a potential strategy to improve insulin sensitivity.

Predictive Role of Gut Microbiota in Weight Loss Achievement after Bariatric Surgery.

BACKGROUND: Bariatric surgery induces changes in gut microbiota that have been suggested to contribute to weight loss and metabolic improvement. However, whether preoperative gut microbiota composition could predict response to bariatric surgery has not yet been elucidated. STUDY DESIGN: Seventy-six patients who underwent sleeve gastrectomy were classified according to the percentage of excess weight loss (%EWL) 1 year after surgery in the responder group: >50%EWL (n=50) and the nonresponder group: <50%EWL (n=26). Patients were evaluated before surgery, and 3 months and 1 year after surgery. Gut microbiota composition was analyzed before surgery (n=76) and 3 months after bariatric surgery (n=40). RESULTS: Diversity analysis did not show differences between groups before surgery or 3 months after surgery. Before surgery, there were differences in the abundance of members belonging to Bacteroidetes and Firmicutes phyla (nonresponder group: enriched in Bacteroidaceae, Bacteroides, Bacteroides uniformis, Alistipes finegoldii, Alistipes alistipes, Dorea formicigenerans, and Ruminococcus gnavus. Responder group: enriched in Peptostreptococcaceae, Gemmiger, Gemiger formicilis, Barnesiella, Prevotellaceae, and Prevotella; linear discriminant analysis >2; p < 0.05). Prevotella-to-Bacteroides ratio was significantly lower in the nonresponder group compared to the responder group (p = 0.048). After surgery, the responder group showed an enrichment in taxa that have been shown to have beneficial effects on host metabolism. Before surgery, PICRUSt analysis showed an enrichment in pathways involved in the biosynthesis components of the O-antigen polysaccharideunits in lipopolysaccharides in the nonresponder group. CONCLUSIONS: Preoperative gut microbiota could have an impact on bariatric surgery outcomes. Prevotella-to-Bacteroides ratio could be used as a predictive tool for weight loss trajectory. Early after surgery, patients who experienced successful weight loss showed an enrichment in taxa related to beneficial effects on host metabolism.

Effect of Moderate Consumption of Different Phenolic-Content Beers on the Human Gut Microbiota Composition: A Randomized Crossover Trial.

The moderate consumption of beer has been associated with positive effects on health, and these benefits are driven, in part, by the antioxidant properties of phenolic compounds found in this beverage. However, the potential impact of beer polyphenols on the human gut microbiome and their consequences are yet to be elucidated. In this study, our aim was to evaluate the effect of three different phenolic-content beers on the gut microbiome and the potential role of the induced shifts in the antioxidant capacity of beer polyphenols. In total, 20 subjects (10 healthy volunteers and 10 individuals with metabolic syndrome) were randomly assigned in a crossover design to consume each of the different beers (alcohol-free, lager or dark beer) during a 2-week intervention. Significant changes in the relative abundance of Streptococcaceae and Streptococcus were found after beer consumption. An increased abundance of Streptococcaceae and Streptococcus was observed after the consumption of dark beer, with no detected differences between baseline and alcohol-free/lager beer intervention. Moreover, some of the detected differences appeared to be related to the metabolic status. Finally, a decrease in porphyrin metabolism and heme biosynthesis was found after the intervention, especially after the consumption of dark beer. These results show that the antioxidant capacity of beer polyphenols may induce positive shifts in gut microbiota composition, and some of the observed changes may also boost the antioxidant capacity of these compounds.

Gut microbiota of patients with type 2 diabetes and gastrointestinal intolerance to metformin differs in composition and functionality from tolerant patients.

OBJECTIVE: Metformin modifies the gut microbiome in type 2 diabetes and gastrointestinal tolerance to metformin could be mediated by the gut microbiome. METHODS: We enrolled 35 patients with type 2 diabetes not receiving treatment with metformin due to suspected gastrointestinal intolerance. Metformin was reintroduced at 425 mg, increasing 425 mg every two weeks until reaching 1700 mg per day. According to the occurrence of metformin-related gastrointestinal symptoms, patients were classified into three groups: early intolerance, non-tolerant, and tolerant. Gut microbiota was profiled with 16 S rRNA. This sequencing aimed to determine the differences in the baseline gut microbiota in all groups and prospectively in the tolerant and non-tolerant groups. RESULTS: The classification resulted in 15 early intolerant, 10 tolerant, and 10 non-tolerant subjects. Early tolerance was characterized by a higher abundance of Subdoligranulum; while Veillonella and Serratia were higher in the non-tolerant group. The tolerant group showed enrichment of Megamonas, Megamonas rupellensis, and Phascolarctobacterium spp; Ruminococcus gnavus was lower in the longitudinal analysis. At the end point Prevotellaceae, Prevotella stercorea, Megamonas funiformis, Bacteroides xylanisolvens, and Blautia producta had a higher relative abundance in the tolerant group compared to the non-tolerant group. Subdoligranulum, Ruminococcus torques_1, Phascolarctobacterium faecium, and Eubacterium were higher in the non-tolerant group. The PICRUSt analysis showed a lower activity of the amino acid biosynthesis pathways and a higher sugar degradation pathway in the intolerant groups. CONCLUSIONS: Gut microbiota of subjects with gastrointestinal intolerance depicted taxonomic and functional differences compared to tolerant patients, and this changed differently after metformin administration.

Metformin action over gut microbiota is related to weight and glycemic control in gestational diabetes mellitus: A randomized trial.

BACKGROUND: Metformin, which is known to produce profound changes in gut microbiota, is being increasingly used in gestational diabetes mellitus (GDM). The aim of this study was to elucidate the differences in gut microbiota composition and function in women with GDM treated with metformin compared to those treated with insulin. METHODS: From May to December 2018, 58 women with GDM were randomized to receive insulin (INS; n = 28) or metformin (MET; n = 30) at the University Hospital Virgen de la Victoria, Málaga, Spain. Basal visits, with at least 1 follow-up visit and prepartum visit, were performed. At the basal and prepartum visits, blood and stool samples were collected. The gut microbiota profile was determined through 16S rRNA analysis. RESULTS: Compared to INS, women on MET presented a lower mean postprandial glycemia and a lower increase in weight and body mass index (BMI). Firmicutes and Peptostreptococcaceae abundance declined, while Proteobacteria and Enterobacteriaceae abundance increased in the MET group. We found inverse correlations between changes in the abundance of Proteobacteria and mean postprandial glycemia (p = 0.023), as well as between Enterobacteriaceae and a rise in BMI and weight gain (p = 0.031 and p = 0.036, respectively). Regarding the metabolic profile of gut microbiota, predicted metabolic pathways related to propionate degradation and ubiquinol biosynthesis predominated in the MET group. CONCLUSION: Metformin in GDM affects the composition and metabolic profile of gut microbiota. These changes could mediate, at least in part, its clinical effects. Studies designed to assess how these changes influence metabolic control during and after pregnancy are necessary.

Gut Microbiota Metabolism of Bile Acids Could Contribute to the Bariatric Surgery Improvements in Extreme Obesity.

Bariatric surgery is the only procedure to obtain and maintain weight loss in the long term, although the mechanisms driving these benefits are not completely understood. In the last years, gut microbiota has emerged as one of the drivers through its metabolites, especially secondary bile acids. In the current study, we have compared the gut microbiota and the bile acid pool, as well as anthropometric and biochemical parameters, of patient with morbid obesity who underwent bariatric surgery by two different techniques, namely Roux-en-Y gastric bypass (RYGB) or sleeve gastrectomy (SG). Gut microbiota populations differed after the respective procedures, particularly with respect to the Enterobacteriaceae family. Both techniques resulted in changes in the bile acids pool, but RYGB was the procedure which suffered the greatest changes, with a reduction in most of their levels. Blautia and Veillonella were the two genera that more relationships showed with secondary bile acids, indicating a possible role in their formation and inhibition, respectively. Correlations with the anthropometric and biochemical variables showed that secondary bile acids could have a role in the amelioration of the glucose and HDL-cholesterol levels. Thus, we have observed a possible relationship between the interaction of the bile acids pool metabolized by the gut microbiota in the metabolic improvements obtained by bariatric surgery in the frame of morbid obesity, deserving further investigation in greater cohorts to decipher the role of each bile acid in the homeostasis of the host for their possible use in the development of microbiota-based therapeutics, such as new drugs, postbiotics or probiotics.

Influence of Factors Altering Gastric Microbiota on Bariatric Surgery Metabolic Outcomes.

Little is known about the influence of gastric microbiota on host metabolism, even though the stomach plays an important role in the production of hormones involved in body weight regulation and glucose homeostasis. Proton pump inhibitors (PPIs) and Helicobacter pylori alter gut microbiota, but their impact on gastric microbiota in patients with obesity and the influence of these factors on the metabolic response to bariatric surgery is not fully understood. Forty-one subjects with morbid obesity who underwent sleeve gastrectomy were included in this study. The H. pylori group was established by the detection of H. pylori using a sequencing-based method (n = 16). Individuals in whom H. pylori was not detected were classified according to PPI treatment. Gastric biopsy specimens were obtained during surgery and were analyzed by a high-throughput-sequencing method. Patients were evaluated at baseline and 3, 6, and 12 months after surgery. ß-Diversity measures were able to cluster patients according to their gastric mucosa-associated microbiota composition. H. pylori and PPI treatment are presented as two important factors for gastric mucosa-associated microbiota. H. pylori reduced diversity, while PPIs altered ß-diversity. Both factors induced changes in the gastric mucosa-associated microbiota composition and its predicted functions. PPI users showed lower percentages of change in the body mass index (BMI) in the short term after surgery, while the H. pylori group showed higher glucose levels and lower percentages of reduction in body weight/BMI 1 year after surgery. PPIs and H. pylori colonization could modify the gastric mucosa-associated microbiota, altering its diversity, composition, and predicted functionality. These factors may have a role in the metabolic evolution of patients undergoing bariatric surgery. IMPORTANCE The gut microbiota has been shown to have an impact on host metabolism. In the stomach, factors like proton pump inhibitor treatment and Helicobacter pylori haven been suggested to alter gut microbiota; however, the influence of these factors on the metabolic response to bariatric surgery has not been fully studied. In this study, we highlight the impact of these factors on the gastric microbiota composition. Moreover, proton pump inhibitor treatment and the presence of Helicobacter pylori could have an influence on bariatric surgery outcomes, mainly on body weight loss and glucose homeostasis. Deciphering the relationship between gastric hormones and gastric microbiota and their contributions to bariatric surgery outcomes paves the way to develop gut manipulation strategies to improve the metabolic success of bariatric surgery.