The microbiota composition of the offspring of patients with gestational diabetes mellitus (GDM).

The microbiota composition of the offspring of women with gestational diabetes mellitus (GDM), a common pregnancy complication, is still little known. We investigated whether the GDM offspring gut microbiota composition is associated with the maternal nutritional habits, metabolic variables or pregnancy outcomes. Furthermore, we compared the GDM offspring microbiota to the microbiota of normoglycemic-mother offspring. Fecal samples of 29 GDM infants were collected during the first week of life and assessed by 16S amplicon-based sequencing. The offspring's microbiota showed significantly lower α-diversity than the corresponding mothers. Earlier maternal nutritional habits were more strongly associated with the offspring microbiota (maternal oligosaccharide positively with infant Ruminococcus, maternal saturated fat intake inversely with infant Rikenellaceae and Ruminococcus) than last-trimester maternal habits. Principal coordinate analysis showed a separation of the infant microbiota according to the type of feeding (breastfeeding vs formula-feeding), displaying in breast-fed infants a higher abundance of Bifidobacterium. A few Bacteroides and Blautia oligotypes were shared by the GDM mothers and their offspring, suggesting a maternal microbial imprinting. Finally, GDM infants showed higher relative abundance of pro-inflammatory taxa than infants from healthy women. In conclusion, many maternal conditions impact on the microbiota composition of GDM offspring whose microbiota showed increased abundance of pro-inflammatory taxa.

[Qualitative experiential analysis of the BRASS scale.] / Analisi qualitativa esperienziale di revisione della scala BRASS.

BACKGROUND: Hospital discharge can potentially represent an issue. Therefore, it is important to early identify patients at higher risk. A valid tool in this field is the Blaylock Risk Assessment Screening Score (BRASS). AIMS: The study aims to elaborate a simplified score system, throughout the contribution of healthcare professionals considering the single items of the original score. METHODS: The study included a qualitative analysis, conducted in order to draft the synthetic tool. Alongside, a statistical analysis was carried out. The findings of these two works were compared and joined in the realization of the proposed evaluation tool. RESULTS: The synthetic tool, developed by the working team, is composed by 20 items. The qualitative analysis agrees with the statistical approach. Moreover, the qualitative analysis consented to redefine some items, especially considering social support, and to include some additional information e.g. clinical problems. LIMITATIONS: The analysis considered only General Medicine wards, all located in the same Hospital. Therefore, generalisation to other settings or patients should be further tested. CONCLUSIONS: The synthetic tool, realized during the study, aims to improve the individuation of at-risk inpatients. The agreement between statistical and qualitative analysis can be considered a point of strength of our work. Our analysis consented to include some new items, improving overall organization. In conclusion, the working group aims to conduct further study in order to individuate the more appropriate cut-off of the new scoring method.

Angiotensin II Type 1 Receptor rs5186 Gene Variant Predicts Incident NAFLD and Associated Hypertension: Role of Dietary Fat-Induced Pro-Inflammatory Cell Activation.

OBJECTIVES: Hypertension has been linked to the presence and severity of nonalcoholic fatty liver disease (NAFLD) through unclear mechanisms. The gain-of-function rs5186 A1166C variant in angtiotensin receptor type 1 (AGTR1) gene has been linked to hypertension, cardiovascular disease and metabolic syndrome. We assessed the impact of AGTR1 A1166C variant on NAFLD incidence and severity and on glucose and lipid metabolism and explored the underlying mechanisms. METHODS: We followed up 314 healthy nonobese, nondiabetic, nonhypertensive, insulin-sensitive participants in a population-based study, characterized for AGTR1 rs5186 A1166C variant, adipokine profile, inflammatory and endothelial dysfunction markers. An independent cohort of 78 biopsy-proven nondiabetic NAFLD patients and controls underwent an oral glucose tolerance test with Minimal Model analysis of glucose homeostasis, and an oral fat tolerance test with measurement of plasma lipoproteins, adipokines, MCP-1, calprotectin, and nuclear factor-κB activation in circulating mononuclear cells. RESULTS: AGTR1 A1166C polymorphism predicted 9.8-year incident NAFLD (odds ratio: 1.67, 95% CI: 1.26-2.21) and hypertension (odds ratio: 1.49, 95% CI: 1.12-2.63) and 9-year increase in cardiovascular disease risk and endothelial dysfunction markers. In the cross-sectional cohort, AGTR1 C allele carriers had higher insulin resistance. Despite comparable fasting lipid profiles, AGTR1 C allele carriers showed postprandial triglyceride-rich and cholesterol-rich VLDL lipoprotein accumulation, higher resistin, MCP-1 and calprotectin responses and nuclear factor-κB activation in mononuclear cells, and a blunted postprandial adiponectin response to fat, which predicted liver histology, hepatocyte apoptosis activation, insulin resistance, and endothelial dysfunction. DISCUSSION: AGTR1 A1166C variant affects liver disease, insulin resistance, and endothelial dysfunction in NAFLD, at least in part by modulating adipokine, chemokine, and pro-inflammatory cell activation in response to fat ingestion.

Changes in the gut microbiota composition during pregnancy in patients with gestational diabetes mellitus (GDM).

Gestational diabetes mellitus (GDM), a common pregnancy complication, is associated with an increased risk of maternal/perinatal outcomes. We performed a prospective observational explorative study in 41 GDM patients to evaluate their microbiota changes during pregnancy and the associations between the gut microbiota and variations in nutrient intakes, anthropometric and laboratory variables. GDM patients routinely received nutritional recommendations according to guidelines. The fecal microbiota (by 16S amplicon-based sequencing), was assessed at enrolment (24-28 weeks) and at 38 weeks of gestational age. At the study end, the microbiota α-diversity significantly increased (P < 0.001), with increase of Firmicutes and reduction of Bacteroidetes and Actinobacteria. Patients who were adherent to the dietary recommendations showed a better metabolic and inflammatory pattern at the study-end and a significant decrease in Bacteroides. In multiple regression models, Faecalibacterium was significantly associated with fasting glucose; Collinsella (directly) and Blautia (inversely) with insulin, and with Homeostasis-Model Assessment Insulin-Resistance, while Sutterella with C-reactive protein levels. Consistent with this latter association, the predicted metagenomes showed a correlation between those taxa and inferred KEGG genes associated with lipopolysaccharide biosynthesis. A higher bacterial richness and strong correlations between pro-inflammatory taxa and metabolic/inflammatory variables were detected in GDM patients across pregnancy. Collectively these findings suggest that the development of strategies to modulate the gut microbiota might be a potentially useful tool to impact on maternal metabolic health.

Development and validation of a simplified BRASS index to screen hospital patients needing personalized discharge planning.

BACKGROUND: Discharge planning is an important component of hospital care. The Blaylock Risk Assessment Screening Score (BRASS) index is an instrument used to identify patients requiring complex discharge planning. OBJECTIVES: (1) Evaluate the ability of the original BRASS index to predict the risk of complex discharge and hospital mortality. (2) Develop and validate a simplified BRASS index by eliminating redundant variables and re-estimating the predictor weights. DESIGN: Prospective cohort study. PARTICIPANTS: Patients admitted at the general internal medicine wards of tertiary referral hospital in Turin, Italy, and screened within 48 h using the BRASS index. METHODS: The first phase of the study assessed the performance of the original BRASS index in predicting the risk of complex discharge and hospital mortality, then a simplified score was developed. In the second phase, temporal validation of the simplified BRASS index was performed. The probability of each discharge modality (discharged at home without complications, complex discharge, and dead in hospital) was modeled using polytomous logistic regression. The AUC was used to compare the performance of the different models. KEY RESULTS: Among 6044 patients in the first phase of the study, 63% were discharged at home without complications, 31% had complex discharge, and 6% died during the hospital stay. The AUC of the simplified BRASS index, compared with the original index were 0.71 vs. 0.70 for complex discharge and 0.83 vs. 0.80 for hospital mortality. In the validation set (3325 patients), the simplified BRASS index discriminates the outcome categories with an AUC of 0.69 and 0.81 for complex discharge and hospital mortality, respectively. CONCLUSION: The new, simplified BRASS index showed a slightly better performance in predicting the risk of complex discharge and hospital mortality than the original tool and takes less time to be applied. These results were also confirmed in the validation set.