Project description:BackgroundType 2 diabetes mellitus (T2DM) is one of the most widely spread diseases, affecting around 90% of the patients with diabetes. Metabolomics has proven useful in diabetes research discovering new biomarkers to assist in therapeutical studies and elucidating pathways of interest. However, this technique has not yet been applied to a cohort of patients that have remitted from T2DM.MethodsAll patients with a newly diagnosed T2DM at baseline (n = 190) were included. An untargeted metabolomics approach was employed to identify metabolic differences between individuals who remitted (RE), and those who did not (non-RE) from T2DM, during a 5-year study of dietary intervention. The biostatistical pipeline consisted of an orthogonal projection on the latent structure discriminant analysis (O-PLS DA), a generalized linear model (GLM), a receiver operating characteristic (ROC), a DeLong test, a Cox regression, and pathway analyses.ResultsThe model identified a significant increase in 12 metabolites in the non-RE group compared to the RE group. Cox proportional hazard models, calculated using these 12 metabolites, showed that patients in the high-score tercile had significantly (p-value < 0.001) higher remission probabilities (Hazard Ratio, HR, high versus low = 2.70) than those in the lowest tercile. The predictive power of these metabolites was further studied using GLMs and ROCs. The area under the curve (AUC) of the clinical variables alone is 0.61, but this increases up to 0.72 if the 12 metabolites are considered. A DeLong test shows that this difference is statistically significant (p-value = 0.01).ConclusionsOur study identified 12 endogenous metabolites with the potential to predict T2DM remission following a dietary intervention. These metabolites, combined with clinical variables, can be used to provide, in clinical practice, a more precise therapy.Trial registrationClinicalTrials.gov, NCT00924937.
Project description:IntroductionA distinctive gut microbiome have been linked to type 2 diabetes mellitus (T2DM).ObjectivesWe aimed to evaluate whether gut microbiota composition, in addition to clinical biomarkers, could improve the prediction of new incident cases of diabetes in patients with coronary heart disease.MethodsAll the patients from the CORDIOPREV (Clinical Trials.gov.Identifier: NCT00924937) study without T2DM at baseline were included (n = 462). Overall, 107 patients developed it after a median of 60 months. The gut microbiota composition was determined by 16S rRNA gene sequencing and predictive models were created using hold-out method.ResultsA gut microbiota profile associated with T2DM development was determined through a microbiome-based predictive model. The addition of microbiome data to clinical parameters (variables included in FINDRISC risk score and the diabetes risk score of the American Diabetes Association, HDL, triglycerides and HbA1c) improved the prediction increasing the area under the curve from 0.632 to 0.946. Furthermore, a microbiome-based risk score including the ten most discriminant genera, was associated with the probability of develop T2DM.ConclusionThese results suggest that a microbiota profile is associated to the T2DM development. An integrate predictive model of microbiome and clinical data that can improve the prediction of T2DM is also proposed, if is validated in independent populations to prevent this disease.
Project description:Type-2 diabetes mellitus (T2DM) has become a major health problem worldwide. T2DM risk can be reduced with healthy dietary interventions, but the precise molecular underpinnings behind this association are still incompletely understood. We recently discovered that the expression profile of the splicing machinery is associated with the risk of T2DM development. Thus, the aim of this work was to evaluate the influence of 3-year dietary intervention in the expression pattern of the splicing machinery components in peripheral blood mononuclear cells (PBMCs) from patients within the CORDIOPREV study. Expression of splicing machinery components was determined in PBMCs, at baseline and after 3 years of follow-up, from all patients who developed T2DM (Incident-T2DM, n = 107) and 108 randomly selected non-T2DM subjects, who were randomly enrolled in two healthy dietary patterns (Mediterranean or low-fat diets). Dietary intervention modulated the expression of key splicing machinery components (i.e., up-regulation of SPFQ/RMB45/RNU6, etc., down-regulation of RNU2/SRSF6) after three years, independently of the type of healthy diet. Some of these changes (SPFQ/RMB45/SRSF6) were associated with key clinical features and were differentially induced in Incident-T2DM patients and non-T2DM subjects. This study reveals that splicing machinery can be modulated by long-term dietary intervention, and could become a valuable tool to screen the progression of T2DM.
Project description:Despite improved understanding of the pathophysiology of type 2 diabetes mellitus, explanations for individual variability in disease progression and response to treatment are incomplete. The gut microbiota has been linked to the pathophysiology of type 2 diabetes mellitus and may account for this variability. We conducted a systematic review to assess the effectiveness of dietary and physical activity/exercise interventions in modulating the gut microbiota and improving glucose control in adults with type 2 diabetes mellitus.A systematic search was conducted to identify studies reporting on the effect of dietary and physical activity/exercise interventions on the gut microbiota and glucose control in individuals with a confirmed diagnosis of type 2 diabetes mellitus. Study characteristics, methodological quality and details relating to interventions were captured using a data-extraction form. Meta-analyses were conducted where sufficient data were available, and other results were reported narratively.Eight studies met the eligibility criteria of the systematic review. No studies were found that reported on the effects of physical activity/exercise on the gut microbiota and glucose control. However, studies reporting on dietary interventions showed that such interventions were associated with modifications to the composition and diversity of the gut microbiota. There was a statistically significant improvement in HbA1c (standardised mean difference [SMD] -2.31 mmol/mol [95% CI -2.76, -1.85] [0.21%; 95% CI -0.26, -0.16]; I2?=?0%, p?<?0.01), but not in fasting blood glucose (SMD -0.25 mmol/l [95% CI -0.85, 0.35], I2?=?87%, p?>?0.05), fasting insulin (SMD -1.82 pmol/l [95% CI -7.23, 3.60], I2?=?54%, p?>?0.05) or HOMA-IR (SMD -0.15 [95% CI -0.63, 0.32], I2?=?69%, p?>?0.05) when comparing dietary interventions with comparator groups. There were no significant changes in the relative abundance of bacteria in the genera Bifidobacterium (SMD 1.29% [95% CI -4.45, 7.03], I2?=?33%, p?>?0.05), Roseburia (SMD -0.85% [95% CI -2.91, 1.21], I2?=?79%, p?>?0.05) or Lactobacillus (SMD 0.04% [95% CI -0.01, 0.09], I2?=?0%, p?>?0.05) when comparing dietary interventions with comparator groups. There were, however, other significant changes in the gut microbiota, including changes at various taxonomic levels, including phylum, family, genus and species, Firmicutes:Bacteroidetes ratios and changes in diversity matrices (? and ?). Dietary intervention had minimal or no effect on inflammation, short-chain fatty acids or anthropometrics.Dietary intervention was found to modulate the gut microbiota and improve glucose control in individuals with type 2 diabetes. Although the results of the included studies are encouraging, this review highlights the need for further well-conducted interventional studies to inform the clinical use of dietary interventions targeting the gut microbiota.
Project description:There is no diabetes risk model that includes dietary predictors in Asia. We sought to develop a diet-containing noninvasive diabetes risk model in Northern China and to evaluate whether dietary predictors can improve model performance and predictive ability. Cross-sectional data for 9,734 adults aged 20-74 years old were used as the derivation data, and results obtained for a cohort of 4,515 adults with 4.2 years of follow-up were used as the validation data. We used a logistic regression model to develop a diet-containing noninvasive risk model. Akaike's information criterion (AIC), area under curve (AUC), integrated discrimination improvements (IDI), net classification improvement (NRI) and calibration statistics were calculated to explicitly assess the effect of dietary predictors on a diabetes risk model. A diet-containing type 2 diabetes risk model was developed. The significant dietary predictors including the consumption of staple foods, livestock, eggs, potato, dairy products, fresh fruit and vegetables were included in the risk model. Dietary predictors improved the noninvasive diabetes risk model with a significant increase in the AUC (delta AUC = 0.03, P<0.001), an increase in relative IDI (24.6%, P-value for IDI <0.001), an increase in NRI (category-free NRI = 0.155, P<0.001), an increase in sensitivity of the model with 7.3% and a decrease in AIC (delta AIC = 199.5). The results of the validation data were similar to the derivation data. The calibration of the diet-containing diabetes risk model was better than that of the risk model without dietary predictors in the validation data. Dietary information improves model performance and predictive ability of noninvasive type 2 diabetes risk model based on classic risk factors. Dietary information may be useful for developing a noninvasive diabetes risk model.
Project description:PurposeDiabetes remission is a phenomenon described in the context of drastic weight loss due to bariatric surgery or low-calorie diets. Evidence suggests that increasing the intake of plant protein could reduce the risk of type 2 diabetes. We sought for association between changes in plant protein intake in the context of 2 healthy diets without weight loss nor glucose-lowering medication, and diabetes remission in coronary heart disease patients from the CORDIOPREV study.MethodsNewly diagnosed type 2 diabetes participants without glucose-lowering treatment were randomized to consume a Mediterranean or a low-fat diet. Type 2 diabetes remission was assessed with a median follow-up of 60 months according to the ADA recommendation. Information on patient's dietary intake was collected using food-frequency questionnaires. At first year of intervention, 177 patients were classified according to changes in plant protein consumption into those who increased or decreased its intake, in order to perform an observational analysis on the association between protein intake and diabetes remission.ResultsCox regression showed that patients increasing plant protein intake were more likely to remit from diabetes than those who decreased its intake (HR = 1.71(1.05-2.77)). The remission occurred mainly at first and second year of follow-up with diminished number of patients achieving remission in the third year onwards. The increase in plant protein was associated with lower intake of animal protein, cholesterol, saturated fatty acids, and fat, and with higher intake of whole grains, fibre, carbohydrates, legumes, and tree nuts.ConclusionThese results support the need to increase protein intake of vegetal origin as dietary therapy to reverse type 2 diabetes in the context of healthy diets without weight loss.
Project description:Circulating microRNAs (miRNAs) have been proposed as type 2 diabetes biomarkers, and they may be a more sensitive way to predict development of the disease than the currently used tools. Our aim was to identify whether circulating miRNAs, added to clinical and biochemical markers, yielded better potential for predicting type 2 diabetes. The study included 462 non-diabetic patients at baseline in the CORDIOPREV study. After a median follow-up of 60 months, 107 of them developed type 2 diabetes. Plasma levels of 24 miRNAs were measured at baseline by qRT-PCR, and other strong biomarkers to predict diabetes were determined. The ROC analysis identified 9 miRNAs, which, added to HbA1c, have a greater predictive value in early diagnosis of type 2 diabetes (AUC = 0.8342) than HbA1c alone (AUC = 0.6950). The miRNA and HbA1c-based model did not improve when the FINDRISC was included (AUC = 0.8293). Cox regression analyses showed that patients with low miR-103, miR-28-3p, miR-29a, and miR-9 and high miR-30a-5p and miR-150 circulating levels have a higher risk of disease (HR = 11.27; 95% CI = 2.61-48.65). Our results suggest that circulating miRNAs could potentially be used as a new tool for predicting the development of type 2 diabetes in clinical practice.
Project description:The frequency of remission of type 2 diabetes achievable with lifestyle intervention is unclear.To examine the association of a long-term intensive weight-loss intervention with the frequency of remission from type 2 diabetes to prediabetes or normoglycemia.Ancillary observational analysis of a 4-year randomized controlled trial (baseline visit, August 2001-April 2004; last follow-up, April 2008) comparing an intensive lifestyle intervention (ILI) with a diabetes support and education control condition (DSE) among 4503 US adults with body mass index of 25 or higher and type 2 diabetes.Participants were randomly assigned to receive the ILI, which included weekly group and individual counseling in the first 6 months followed by 3 sessions per month for the second 6 months and twice-monthly contact and regular refresher group series and campaigns in years 2 to 4 (n=2241) or the DSE, which was an offer of 3 group sessions per year on diet, physical activity, and social support (n=2262).Partial or complete remission of diabetes, defined as transition from meeting diabetes criteria to a prediabetes or nondiabetic level of glycemia (fasting plasma glucose <126 mg/dL and hemoglobin A1c <6.5% with no antihyperglycemic medication). RESULTS Intensive lifestyle intervention participants lost significantly more weight than DSE participants at year 1 (net difference, -7.9%; 95% CI, -8.3% to -7.6%) and at year 4 (-3.9%; 95% CI, -4.4% to -3.5%) and had greater fitness increases at year 1 (net difference, 15.4%; 95% CI, 13.7%-17.0%) and at year 4 (6.4%; 95% CI, 4.7%-8.1%) (P < .001 for each). The ILI group was significantly more likely to experience any remission (partial or complete), with prevalences of 11.5% (95% CI, 10.1%-12.8%) during the first year and 7.3% (95% CI, 6.2%-8.4%) at year 4, compared with 2.0% for the DSE group at both time points (95% CIs, 1.4%-2.6% at year 1 and 1.5%-2.7% at year 4) (P < .001 for each). Among ILI participants, 9.2% (95% CI, 7.9%-10.4%), 6.4% (95% CI, 5.3%-7.4%), and 3.5% (95% CI, 2.7%-4.3%) had continuous, sustained remission for at least 2, at least 3, and 4 years, respectively, compared with less than 2% of DSE participants (1.7% [95% CI, 1.2%-2.3%] for at least 2 years; 1.3% [95% CI, 0.8%-1.7%] for at least 3 years; and 0.5% [95% CI, 0.2%-0.8%] for 4 years).In these exploratory analyses of overweight adults, an intensive lifestyle intervention was associated with a greater likelihood of partial remission of type 2 diabetes compared with diabetes support and education. However, the absolute remission rates were modest. TRIAL REGISTRATION clinicaltrials.gov Identifier: NCT00017953.
Project description:ObjectivesThe aims of this feasibility study were to (1) examine the implementation of a community-based health advocate (CHA) training programme to develop the clinical skills needed to support a diabetes remission protocol based on a low-calorie diet (LCD) and (2) investigate if participant weight loss can be achieved and diabetes remission induced under these conditions.MethodsThis tripartite study followed a type 2 implementation-effectiveness design. Three faith-based organisations (FBOs) were purposively selected as study sites. Implementation outcomes were guided by the Consolidated Framework for Implementation Research. During the pre-implementation phase, site 'readiness' to facilitate the intervention was determined from a site visit and an interview with the FBOs' leadership. During the implementation phase, congregants could volunteer for the 10-week CHA training which included practical exercises in weight, glucose and blood pressure (BP) measurement, and a summative practical assessment. Acceptability and implementation effectiveness were assessed via survey. During the intervention phase, other congregants and community members with T2DM or pre-diabetes and overweight were invited to participate in the 12-week LCD. Anti-diabetic medication was discontinued on day 1 of the intervention. Clinical effectiveness was determined from the change in weight, fasting blood glucose (FBG) and BP which were monitored weekly at the FBO by the CHA. HbA1C was performed at weeks 1 and 12.ResultsThe FBOs were found to be ready as determined by their adequate resources and engagement in health-related matters. Twenty-nine CHAs completed the training; all attained a passing grade at ≥1 clinical station, indicating implementation effectiveness. CHA feedback indicated that the programme structure was acceptable and provided sufficient access to intervention-related material. Thirty-one persons participated in the LCD (11 T2DM:20 pre-diabetes). Mean (95%CI) weight loss was 6.0 kg (3.7 to 8.2), 7.9 kg in males vs 5.7 kg in females; A1C (%) decreased from 6.6 to 6.1, with a greater reduction in those with T2DM when compared to pre-diabetes. FBG decreased from 6.4 to 6.0mmol/L. T2DM remission rates were 60% and 90% by A1C<6.5% and FBG<7mmol/L respectively. Pre-diabetes remission was 18% and 40% by A1C<5.7% and FBG<5.6 respectively.ConclusionImplementation of a community-based diabetes remission protocol is both feasible and clinically effective. Its sustainability is to be determined. Adaptability to other disorders or other settings should be investigated.Trial registrationNCT03536377 registered on 24 May 2018.
Project description:Mounting evidence suggested that the gut microbiota has a significant role in the metabolism and disease status of the host. In particular, Type 2 Diabetes (T2D), which has a complex etiology that includes obesity and chronic low-grade inflammation, is modulated by the gut microbiota and microbial metabolites. Current literature supports that unbalanced gut microbial composition (dysbiosis) is a risk factor for T2D. In this review, we critically summarize the recent findings regarding the role of gut microbiota in T2D. Beyond these associative studies, we focus on the causal relationship between microbiota and T2D established using fecal microbiota transplantation (FMT) or probiotic supplementation, and the potential underlying mechanisms such as byproducts of microbial metabolism. These microbial metabolites are small molecules that establish communication between microbiota and host cells. We critically summarize the associations between T2D and microbial metabolites such as short-chain fatty acids (SCFAs) and trimethylamine N-Oxide (TMAO). Additionally, we comment on how host genetic architecture and the epigenome influence the microbial composition and thus how the gut microbiota may explain part of the missing heritability of T2D found by GWAS analysis. We also discuss future directions in this field and how approaches such as FMT, prebiotics, and probiotics supplementation are being considered as potential therapeutics for T2D.