Diabetologia最新文献

Aims/hypothesis: tRNAs play a central role in protein synthesis. Besides this canonical function, they were recently found to generate non-coding RNA fragments (tRFs) regulating different cellular activities. The aim of this study was to assess the involvement of tRFs in the crosstalk between immune cells and beta cells and to investigate their contribution to the development of type 1 diabetes.

Methods: Global profiling of the tRFs present in pancreatic islets of 4- and 8-week-old NOD mice and in extracellular vesicles released by activated CD4⁺ T lymphocytes was performed by small RNA-seq. Changes in the level of specific fragments were confirmed by quantitative PCR. The transfer of tRFs from immune cells to beta cells occurring during insulitis was assessed using an RNA-tagging approach. The functional role of tRFs increasing in beta cells during the initial phases of type 1 diabetes was determined by overexpressing them in dissociated islet cells and by determining the impact on gene expression and beta cell apoptosis.

Results: We found that the tRF pool was altered in the islets of NOD mice during the initial phases of type 1 diabetes. Part of these changes were triggered by prolonged exposure of beta cells to proinflammatory cytokines (IL-1β, TNF-α and IFN-γ) while others resulted from the delivery of tRFs produced by CD4⁺ T lymphocytes infiltrating the islets. Indeed, we identified several tRFs that were enriched in extracellular vesicles from CD4⁺/CD25^- T cells and were transferred to beta cells upon adoptive transfer of these immune cells in NOD.SCID mice. The tRFs delivered to beta cells during the autoimmune reaction triggered gene expression changes that affected the immune regulatory capacity of insulin-secreting cells and rendered the cells more prone to apoptosis.

Conclusions/interpretation: Our data point to tRFs as novel players in the crosstalk between the immune system and insulin-secreting cells and suggest a potential involvement of this novel class of non-coding RNAs in type 1 diabetes pathogenesis.

Data availability: Sequences are available from the Gene Expression Omnibus (GEO) with accession numbers GSE242568 and GSE256343.

Aims/hypothesis: Few studies have examined the clinical characteristics associated with changes in weight before and after diagnosis of type 2 diabetes. Using a large real-world cohort, we derived trajectories of BMI before and after diabetes diagnosis, and examined the clinical characteristics associated with these trajectories, including assessing the impact of pre-diagnosis weight change on post-diagnosis weight change.

Methods: We performed an observational cohort study using electronic medical records from individuals in the Scottish Care Information Diabetes Collaboration database. Two trajectories were calculated, based on observed BMI measurements between 3 years and 6 months before diagnosis and between 1 and 5 years after diagnosis. In the post-diagnosis trajectory, each BMI measurement was time-dependently adjusted for the effects of diabetes medications and HbA_1c change.

Results: A total of 2736 individuals were included in the study. There was a pattern of pre-diagnosis weight gain, with 1944 individuals (71%) gaining weight overall, and 875 (32%) gaining more than 0.5 kg/m² per year. This was followed by a pattern of weight loss after diagnosis, with 1722 individuals (63%) losing weight. Younger age and greater social deprivation were associated with increased weight gain before diagnosis. Pre-diagnosis weight change was unrelated to post-diagnosis weight change, but post-diagnosis weight loss was associated with older age, female sex, higher BMI, higher HbA_1c and weight gain during the peri-diagnosis period. When considering the peri-diagnostic period (defined as from 6 months before to 12 months after diagnosis), we identified 986 (36%) individuals who had a high HbA_1c at diagnosis but who lost weight rapidly and were most aggressively treated at 1 year; this subgroup had the best glycaemic control at 5 years.

Conclusions/interpretation: Average weight increases before diagnosis and decreases after diagnosis; however, there were significant differences across the population in terms of weight changes. Younger individuals gained weight pre-diagnosis, but, in older individuals, type 2 diabetes is less associated with weight gain, consistent with other drivers for diabetes aetiology in older adults. We have identified a substantial group of individuals who have a rapid deterioration in glycaemic control, together with weight loss, around the time of diagnosis, and who subsequently stabilise, suggesting that a high HbA_1c at diagnosis is not inevitably associated with a poor outcome and may be driven by reversible glucose toxicity.

Aims/hypothesis: Disruption of pancreatic islet function and glucose homeostasis can lead to the development of sustained hyperglycaemia, beta cell glucotoxicity and subsequently type 2 diabetes. In this study, we explored the effects of in vitro hyperglycaemic conditions on human pancreatic islet gene expression across 24 h in six pancreatic cell types: alpha; beta; gamma; delta; ductal; and acinar. We hypothesised that genes associated with hyperglycaemic conditions may be relevant to the onset and progression of diabetes.

Methods: We exposed human pancreatic islets from two donors to low (2.8 mmol/l) and high (15.0 mmol/l) glucose concentrations over 24 h in vitro. To assess the transcriptome, we performed single-cell RNA-seq (scRNA-seq) at seven time points. We modelled time as both a discrete and continuous variable to determine momentary and longitudinal changes in transcription associated with islet time in culture or glucose exposure. Additionally, we integrated genomic features and genetic summary statistics to nominate candidate effector genes. For three of these genes, we functionally characterised the effect on insulin production and secretion using CRISPR interference to knock down gene expression in EndoC-βH1 cells, followed by a glucose-stimulated insulin secretion assay.

Results: In the discrete time models, we identified 1344 genes associated with time and 668 genes associated with glucose exposure across all cell types and time points. In the continuous time models, we identified 1311 genes associated with time, 345 genes associated with glucose exposure and 418 genes associated with interaction effects between time and glucose across all cell types. By integrating these expression profiles with summary statistics from genetic association studies, we identified 2449 candidate effector genes for type 2 diabetes, HbA_1c, random blood glucose and fasting blood glucose. Of these candidate effector genes, we showed that three (ERO1B, HNRNPA2B1 and RHOBTB3) exhibited an effect on glucose-stimulated insulin production and secretion in EndoC-βH1 cells.

Conclusions/interpretation: The findings of our study provide an in-depth characterisation of the 24 h transcriptomic response of human pancreatic islets to glucose exposure at a single-cell resolution. By integrating differentially expressed genes with genetic signals for type 2 diabetes and glucose-related traits, we provide insights into the molecular mechanisms underlying glucose homeostasis. Finally, we provide functional evidence to support the role of three candidate effector genes in insulin secretion and production.

Data availability: The scRNA-seq data from the 24 h glucose exposure experiment performed in this study are available in the database of Genotypes and Phenotypes (dbGap; https://www.ncbi.nlm.nih.gov/gap/ ) with accession no. phs001188.v3.p1. Study

Aims/hypothesis: Strategies to augment functional beta cell mass include directed differentiation of stem cells towards a beta cell fate, which requires extensive knowledge of transcriptional programs governing endocrine progenitor cell differentiation in vivo. We aimed to study the contributions of the Brahma-related gene-1 (BRG1) and Brahma (BRM) ATPase subunits of the SWI/SNF chromatin remodelling complex to endocrine cell development.

Methods: We generated mice with endocrine progenitor-specific Neurog3-Cre BRG1 removal in the presence of heterozygous (Brg1^Δendo;Brm^+/-) or homozygous (double knockout: DKO^Δendo) BRM deficiency. Whole-body metabolic phenotyping, islet function characterisation, islet quantitative PCR and histological characterisation were performed on animals and tissues postnatally. To test the mechanistic actions of SWI/SNF in controlling gene expression during endocrine cell development, single-cell RNA-seq was performed on flow-sorted endocrine-committed cells from embryonic day 15.5 control and mutant embryos.

Results: Brg1^Δendo;Brm^+/- mice exhibit severe glucose intolerance, hyperglycaemia and hypoinsulinaemia, resulting, in part, from reduced islet number; diminished alpha, beta and delta cell mass; compromised islet insulin secretion; and altered islet gene expression programs, including reductions in MAFA and urocortin 3 (UCN3). DKO^Δendo mice were not recovered at weaning; however, postnatal day 6 DKO^Δendo mice were severely hyperglycaemic with reduced serum insulin levels and beta cell area. Single-cell RNA-seq of embryonic day 15.5 lineage-labelled cells revealed endocrine progenitor, alpha and beta cell populations from SWI/SNF mutants have reduced expression of Mafa, Gcg, Ins1 and Ins2, suggesting limited differentiation capacity. Reduced Neurog3 transcripts were discovered in DKO^Δendo endocrine progenitor clusters, and the proliferative capacity of neurogenin 3 (NEUROG3)⁺ cells was reduced in Brg1^Δendo;Brm^+/- and DKO^Δendo mutants.

Conclusions/interpretation: Loss of BRG1 from developing endocrine progenitor cells has a severe postnatal impact on glucose homeostasis, and loss of both subunits impedes animal survival, with both groups exhibiting alterations in hormone transcripts embryonically. Taken together, these data highlight the critical role SWI/SNF plays in governing gene expression programs essential for endocrine cell development and expansion.

Data availability: Raw and processed data for scRNA-seq have been deposited into the NCBI Gene Expression Omnibus (GEO) database under the accession number GSE248369.

Transgender identity is often associated with gender dysphoria and minority stress. Gender-affirming hormone treatment (GAHT) includes masculinising or feminising treatment and is expected to be lifelong in most cases. Sex and sex hormones have a differential effect on metabolism and CVD in cisgender people, and sex hormone replacement in hypogonadism is associated with higher vascular risk, especially in ageing individuals. Using narrative review methods, we present evidence regarding metabolic and cardiovascular outcomes during GAHT and propose recommendations for follow-up and monitoring of metabolic and cardiovascular risk markers during GAHT. Available data show no increased risk for type 2 diabetes in transgender cohorts, but masculinising GAHT increases lean body mass and feminising GAHT is associated with higher fat mass and insulin resistance. The risk of CVD is increased in transgender cohorts, especially during feminising GAHT. Masculinising GAHT is associated with a more adverse lipid profile, higher haematocrit and increased BP, while feminising GAHT is associated with pro-coagulant changes and lower HDL-cholesterol. Assigned male sex at birth, higher age at initiation of GAHT and use of cyproterone acetate are separate risk factors for adverse CVD markers. Metabolic and CVD outcomes may improve during gender-affirming care due to a reduction in minority stress, improved lifestyle and closer surveillance leading to optimised preventive medication (e.g. statins). GAHT should be individualised according to individual risk factors (i.e. drug, dose and form of administration); furthermore, doctors need to discuss lifestyle and preventive medications in order to modify metabolic and CVD risk during GAHT. Follow-up programmes must address the usual cardiovascular risk markers but should consider that biological age and sex may influence individual risk profiling including mental health, lifestyle and novel cardiovascular risk markers during GAHT.

Suboptimal glycaemic management in hospitals has been associated with adverse clinical outcomes and increased financial costs to healthcare systems. Despite the availability of guidelines for inpatient glycaemic management, implementation remains challenging because of the increasing workload of clinical staff and rising prevalence of diabetes. The development of novel and innovative technologies that support the clinical workflow and address the unmet need for effective and safe inpatient diabetes care delivery is still needed. There is robust evidence that the use of diabetes technology such as continuous glucose monitoring and closed-loop insulin delivery can improve glycaemic management in outpatient settings; however, relatively little is known of its potential benefits and application in inpatient diabetes management. Emerging data from clinical studies show that diabetes technologies such as integrated clinical decision support systems can potentially mediate safer and more efficient inpatient diabetes care, while continuous glucose sensors and closed-loop systems show early promise in improving inpatient glycaemic management. This review aims to provide an overview of current evidence related to diabetes technology use in non-critical care adult inpatient settings. We highlight existing barriers that may hinder or delay implementation, as well as strategies and opportunities to facilitate the clinical readiness of inpatient diabetes technology in the future.

Graphical Abstract

Aims/hypothesis: Limited evidence exists on the comparative safety and effectiveness of empagliflozin against alternative glucose-lowering medications in individuals with type 2 diabetes with the broad spectrum of cardiovascular risk. The EMPagliflozin compaRative effectIveness and SafEty (EMPRISE) cohort study was designed to monitor the safety and effectiveness of empagliflozin periodically for a period of 5 years with data collection from electronic healthcare databases.

Methods: We identified individuals ≥18 years old with type 2 diabetes who initiated empagliflozin or dipeptidyl peptidase-4 inhibitors (DPP-4i) from 2014 to 2019 using US Medicare and commercial claims databases. After 1:1 propensity score matching using 143 baseline characteristics, we identified four a priori-defined effectiveness outcomes: (1) myocardial infarction (MI) or stroke; (2) hospitalisation for heart failure (HHF); (3) major adverse cardiovascular events (MACE); and (4) cardiovascular mortality or HHF. Safety outcomes included lower-limb amputations, non-vertebral fractures, diabetic ketoacidosis (DKA), acute kidney injury (AKI), severe hypoglycaemia, retinopathy progression, and short-term kidney and bladder cancers. We estimated HRs and rate differences (RDs) per 1000 person-years, overall and stratified by age, sex, baseline atherosclerotic cardiovascular disease (ASCVD) and heart failure.

Results: We identified 115,116 matched pairs. Compared with DPP-4i, empagliflozin was associated with lower risks of MI/stroke (HR 0.88 [95% CI 0.81, 0.96]; RD -2.08 [95% CI (-3.26, -0.90]), HHF (HR 0.50 [0.44, 0.56]; RD -5.35 [-6.22, -4.49]), MACE (HR 0.73 [0.62, 0.86]; RD -6.37 [-8.98, -3.77]) and cardiovascular mortality/HHF (HR 0.57 [0.47, 0.69]; RD -10.36 [-12.63, -8.12]). Absolute benefits were larger in older individuals and in those with ASCVD/heart failure. Empagliflozin was associated with an increased risk of DKA (HR 1.78 [1.44, 2.19]; RD 1.59 [1.08, 2.09]); decreased risks of AKI (HR 0.62 [0.54, 0.72]; RD -2.39 [-3.08, -1.71]), hypoglycaemia (HR 0.75 [0.67, 0.84]; RD -2.46 [-3.32, -1.60]) and retinopathy progression (HR 0.78 [0.63, 0.96)]; RD -9.49 [-16.97, -2.10]); and similar risks of other safety events.

Conclusions/interpretation: Empagliflozin relative to DPP-4i was associated with risk reductions of MI or stroke, HHF, MACE and the composite of cardiovascular mortality or HHF. Absolute risk reductions were larger in older individuals and in those who had history of ASCVD or heart failure. Regarding the safety outcomes, empagliflozin was associated with an increased risk of DKA and lower risks of AKI, hypoglycaemia and progression to proliferative retinopathy, with no difference in the short-term risks of lower-extremity amputation, non-vertebral fractures, kidney and renal pelvis cancer, and bladder cancer.

An association between diabetes and infection has been recognised for many years, with infection being an important cause of death and morbidity in people with diabetes. The COVID-19 pandemic has re-kindled an interest in the complex relationship between diabetes and infection. Some infections occur almost exclusively in people with diabetes, often with high mortality rates without early diagnosis and treatment. However, more commonly, diabetes is a complicating factor in many infections. A reciprocal relationship occurs whereby certain infections and their treatments may also increase the risk of diabetes. People with diabetes have a 1.5- to 4-fold increased risk of infection. The risks are the most pronounced for kidney infection, osteomyelitis and foot infection, but are also increased for pneumonia, influenza, tuberculosis, skin infection and general sepsis. Outcomes from infection are worse in people with diabetes, with the most notable example being a twofold higher rate of death from COVID-19. Hyperglycaemia has deleterious effects on the immune response. Vascular insufficiency and neuropathy, together with altered skin, mucosal and gut microbial colonisation, contribute to the increased risk of infection. Vaccination is important in people with diabetes although the efficacy of certain immunisations may be compromised, particularly in the presence of hyperglycaemia. The principles of treatment largely follow those of the general population with certain notable exceptions.

Aims/hypothesis: The aim of this study was to evaluate the impact on metabolic control of periodic use of a 5-day fasting-mimicking diet (FMD) programme as an adjunct to usual care in people with type 2 diabetes under regular primary care surveillance.

Methods: In this randomised, controlled, assessor-blinded trial, people with type 2 diabetes using metformin as the only glucose-lowering drug and/or diet for glycaemic control were randomised to receive 5-day cycles of an FMD monthly as an adjunct to regular care by their general practitioner or to receive regular care only. The primary outcomes were changes in glucose-lowering medication (as reflected by the medication effect score) and HbA_1c levels after 12 months. Moreover, changes in use of glucose-lowering medication and/or HbA_1c levels in individual participants were combined to yield a clinically relevant outcome measure ('glycaemic management'), which was categorised as improved, stable or deteriorated after 1 year of follow-up. Several secondary outcome measures were also examined, including changes in body weight.

Results: One hundred individuals with type 2 diabetes, age 18-75 years, BMI ≥27 kg/m², were randomised to the FMD group (n=51) or the control group (n=49). Eight FMD participants and ten control participants were lost to follow-up. Intention-to-treat analyses, using linear mixed models, revealed adjusted estimated treatment effects for the medication effect score (-0.3; 95% CI -0.4, -0.2; p<0.001), HbA_1c (-3.2 mmol/mol; 95% CI -6.2, -0.2 and -0.3%; 95% CI -0.6, -0.0; p=0.04) and body weight (-3.6 kg; 95% CI -5.2, -2.1; p<0.001) at 12 months. Glycaemic management improved in 53% of participants using FMD vs 8% of control participants, remained stable in 23% vs 33%, and deteriorated in 23% vs 59% (p<0.001).

Conclusions/interpretation: Integration of a monthly FMD programme in regular primary care for people with type 2 diabetes who use metformin as the only glucose-lowering drug and/or diet for glycaemic control reduces the need for glucose-lowering medication, improves HbA_1c despite the reduction in medication use, and appears to be safe in routine clinical practice.

Trial registration: ClinicalTrials.gov NCT03811587 FUNDING: The project was co-funded by Health~Holland, Top Sector Life Sciences & Health, the Dutch Diabetes Foundation and L-Nutra.

Aims/hypothesis: Metformin lowers postprandial glycaemic excursions in individuals with type 2 diabetes by modulating gastrointestinal function, including the stimulation of glucagon-like peptide-1 (GLP-1). The impact of varying the timing of metformin administration on postprandial glucose metabolism is poorly defined. We evaluated the effects of metformin, administered at different intervals before an intraduodenal glucose infusion, on the subsequent glycaemic, insulinaemic and GLP-1 responses in metformin-treated type 2 diabetes.

Methods: Sixteen participants with type 2 diabetes that was relatively well-controlled by metformin monotherapy were studied on four separate days in a crossover design. On each day, participants were randomised to receive a bolus infusion of metformin (1000 mg in 50 ml 0.9% saline) via a nasoduodenal catheter at t = -60, -30 or 0 min (and saline at the other timepoints) or saline at all timepoints (control), followed by an intraduodenal glucose infusion of 12.56 kJ/min (3 kcal/min) at t = 0-60 min. The treatments were blinded to both participants and investigators involved in the study procedures. Plasma glucose, insulin and total GLP-1 levels were measured every 30 min between t = -60 min and t = 120 min.

Results: There was a treatment-by-time interaction for metformin in reducing plasma glucose levels and increasing plasma GLP-1 and insulin levels (p<0.05 for each). The reduction in plasma glucose levels was greater when metformin was administered at t = -60 or -30 min vs t = 0 min (p<0.05 for each), and the increases in plasma GLP-1 levels were evident only when metformin was administered at t = -60 or -30 min (p<0.05 for each). Although metformin did not influence insulin sensitivity, it enhanced glucose-induced insulin secretion (p<0.05), and the increases in plasma insulin levels were comparable on the 3 days when metformin was given.

Conclusions/interpretation: In well-controlled metformin-treated type 2 diabetes, glucose-lowering by metformin is greater when it is given before, rather than with, enteral glucose, and this is associated with a greater GLP-1 response. These observations suggest that administration of metformin before meals may optimise its effect in improving postprandial glycaemic control.

Trial registration: www.anzctr.org.au ACTRN12621000878875 FUNDING: The study was not funded by a specific research grant.