RESUMEN
Type 1 diabetes (T1D) is a chronic autoimmune disease targeting insulin-producing pancreatic beta cells. T1D is a multifactorial disease incorporating genetic and environmental factors. In recent years, the advances in high-throughput sequencing have allowed researchers to elucidate the changes in the gut microbiota taxonomy and functional capacity that accompany T1D development. An increasing number of studies have shown a role of the gut microbiota in mediating immune responses in health and disease, including autoimmunity. Fecal microbiota transplantations (FMT) have been largely used in murine models to prove a causal role of the gut microbiome in disease progression and have been shown to be a safe and effective treatment in inflammatory human diseases. In this review, we summarize and discuss recent research regarding the gut microbiota-host interactions in T1D, the current advancement in therapies for T1D, and the usefulness of FMT studies to explore microbiota-host immunity encounters in murine models and to shape the course of human type 1 diabetes.
RESUMEN
AIMS/HYPOTHESIS: The aim of this work was to investigate the association between macronutrient intakes and continuous glucose monitoring (CGM) metrics in individuals with type 1 diabetes. METHODS: In 470 individuals with type 1 diabetes of the GUTDM1 cohort (65% female, median age 40 [IQR 28-53] years, median diabetes duration 15 [IQR 6-29] years), we used logistic regression to establish associations between macronutrient intakes and the CGM metrics time in range (TIR, time spent between 3.9-10.0 mmol/l blood glucose, optimally set at ≥70%) and time below range (TBR, <3.9 mmol/l blood glucose, optimally set at <4%). ORs were expressed per 1 SD intake of nutrient and were adjusted for other macronutrient intakes, age, sex, socioeconomic status, BMI, duration of type 1 diabetes, pump use, insulin dose and alcohol intake. RESULTS: The median (IQR) TIR was 67 (51-80)% and TBR was 2 (1-4)%; the mean ± SD energy intake was 6879±2001 kJ, fat intake 75±31 g, carbohydrate intake 162±63 g, fibre intake 20±9 g and protein intake 70±24 g. A higher fibre intake and a lower carbohydrate intake were associated with higher odds of having a TIR≥70% (OR [95% CI] 1.64 [1.22, 2.24] and 0.67 [0.51, 0.87], respectively), whereas solely a higher carbohydrate intake was associated with TBR<4% (OR 1.34 [95% CI 1.02, 1.78]). CONCLUSIONS/INTERPRETATION: A higher fibre intake is independently associated with a higher TIR. A higher carbohydrate intake is associated with less time spent in hypoglycaemia, a lower TIR and a higher time above range. These findings warrant confirmatory (interventional) investigations and may impact current nutritional guidelines for type 1 diabetes.
RESUMEN
Obesity has become a worldwide pandemic affecting more than 650 million people and is associated with a high burden of morbidity. Alongside traditional risk factors for obesity, the gut microbiome has been identified as a potential factor in weight regulation. Although rodent studies suggest a link between the gut microbiome and body weight, human evidence for causality remains scarce. In this Review, we postulate that existing evidence remains to establish a contribution of the gut microbiome to the development of obesity in humans but that modified probiotic strains and supraphysiological dosages of microbial metabolites may be beneficial in combatting obesity.
Asunto(s)
Microbioma Gastrointestinal , Probióticos , Humanos , Microbioma Gastrointestinal/fisiología , Obesidad/metabolismo , Factores de RiesgoRESUMEN
OBJECTIVES: Early detection of microvascular dysfunction after acute myocardial infarction (AMI) could identify patients at high risk of adverse clinical outcome, who may benefit from adjunctive treatment. Our objective was to compare invasively measured coronary flow reserve (CFR) and hyperaemic microvascular resistance (HMR) for their predictive power of long-term clinical outcome and cardiac magnetic resonance (CMR)-defined microvascular injury (MVI). METHODS: Simultaneous intracoronary Doppler flow velocity and pressure measurements acquired immediately after revascularisation for AMI from five centres were pooled. Clinical follow-up was completed for 176 patients (mean age 60±10 years; 140(80%) male; ST-elevation myocardial infarction (STEMI) 130(74%) and non-ST-segment elevation myocardial infarction 46(26%)) with median follow-up time of 3.2 years. In 110 patients with STEMI, additional CMR was performed. RESULTS: The composite end point of death and hospitalisation for heart failure occurred in 17 patients (10%). Optimal cut-off values to predict the composite end point were 1.5 for CFR and 3.0 mm Hg cm-1â¢s for HMR. CFR <1.5 was predictive for the composite end point (HR 3.5;95% CI 1.1 to 10.8), but not for its individual components. HMR ≥3.0 mm Hg cm-1 s was predictive for the composite end point (HR 7.0;95% CI 1.5 to 33.7) as well as both individual components. HMR had significantly greater area under the receiver operating characteristic curve for MVI than CFR. HMR remained an independent predictor of adverse clinical outcome and MVI, whereas CFR did not. CONCLUSIONS: HMR measured immediately following percutaneous coronary intervention for AMI with a cut-off value of 3.0 mm Hg cm-1 s, identifies patients with MVI who are at high risk of adverse clinical outcome. For this purpose, HMR is superior to CFR.