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Gamma-amino butyric acid (GABA) has in experimental studies been found to promote beta-cell proliferation, enhance insulin secretion and reduce inflammation, positioning it as a candidate drug for type 1 diabetes (T1D) therapy. This phase I/II randomized controlled trial assessed the safety and efficacy of long-term treatment with Remygen® (Diamyd Medical), a controlled-release oral GABA formulation, as a potential beta-cell regenerative therapy in adults with long-standing T1D. Thirty-five male subjects with T1D (≥ 5 years) were randomized into three arms receiving the study drug(s) once daily for 6 months: GABA 200 mg (Arm 1), GABA 600 mg (Arm 2) and GABA 600 mg + alprazolam 0.5 mg for 3 months followed by GABA 600 mg alone for 3 months (Arm 3). Safety measures, hormonal counter-regulation during hypoglycemic clamps, fasting- and stimulated C-peptide levels, were assessed at multiple timepoints. Safety concerns included elevated aspartate aminotransferase (AST) in nine subjects, leading to the withdrawal of two subjects. Most elevations were, however, transient with no dose-differences. No effects were observed on fasting- or stimulated C-peptide levels, CGM metrics or HbA1c. Hypoglycemic hormonal counter-regulation was unaltered. To conclude, we found no clinical evidence of a beta-cell regenerative effect of GABA, but side effects were commonly observed.

Biomarker profiling from biofluids such as blood are widely measured in clinical research, using for example Olink proteomics panels. One such research focus area is cardiovascular disease (CVD), for which chronic sleep restriction (SR) is a risk factor. However, it remains unclear whether blood levels of commonly measured CVD biomarkers are sensitive to acute dynamic factors such as SR, physical exercise (PEx), and time of day. In this crossover design, 16 normal-weight, healthy men underwent three highly standardized in-lab nights of SR (4.25 h/night) and normal sleep (NS, 8.5 h/night) in randomized order, with 88 CVD blood protein biomarkers quantified using the Olink technology (and selected validation using ELISA) in the morning, evening, and immediately before and repeatedly after 30 min of high-intensity exercise. We found significant time-of-day-dependent changes in several CVD biomarkers. Whereas several proteins were exercise-induced across sleep conditions (such as the canonical exerkines IL- 6 and BDNF), exercise-induced proteomic dynamics differed in response to recurrent SR, compared with following NS. Moreover, SR compared with NS resulted in a biomarker profile previously associated with increased prospective risk of several CVDs across large-scale cohorts (such as higher circulating levels of IL-27 and LGALS9). Our findings highlight how dynamic physiology can modulate CVD biomarker levels. These results also underscore the need to consider sleep duration as a key determinant of cardiovascular health-an emphasis reflected in recent American Heart Association guidelines. Further studies in women, older individuals, and patients with prior CVD, and across different chronotypes and dietary schedules are warranted.

Introduction Despite the improvements in diabetes management by continuous glucose monitoring (CGM) it is difficult to capture the complexity of CGM data in one metric. We aimed to develop a clinically relevant multidimensional scoring model with the capacity to identify the most alarming CGM episodes and/or patients from a large cohort.Research design and methods Retrospective CGM data from 2017 to 2020 available in electronic medical records were collected from n=613 individuals with type 1 diabetes (total 82 114 days). A scoring model was developed based on three metrics; glycemic variability percentage, low blood glucose index and high blood glucose index. Values for each dimension were normalized to a numeric score between 0-100. To identify the most representative score for an extended time period, multiple ways to combine the mean score of each dimension were evaluated. Correlations of the scoring model with CGM metrics were computed. The scoring model was compared with interpretations of a clinical expert board (CEB).Results The dimension of hypoglycemia must be weighted to be representative, whereas the other two can be represented by their overall mean. The scoring model correlated well with established CGM metrics. Applying a score of >= 80 as the cut-off for identifying time periods with a 'true' target fulfillment (ie, reaching all targets for CGM metrics) resulted in an accuracy of 93.4% and a specificity of 97.1%. The accuracy of the scoring model when compared with the CEB was high for identifying the most alarming CGM curves within each dimension of glucose control (overall 86.5%).Conclusions Our scoring model captures the complexity of CGM data and can identify both the most alarming dimension of glycemia and the individuals in most urgent need of assistance. This could become a valuable tool for population management at diabetes clinics to enable healthcare providers to stratify care to the patients in greatest need of clinical attention.

Aims/hypothesis

Compromised pancreatic sympathetic innervation has been suggested as a factor involved in both immune-mediated beta cell destruction and endocrine dysregulation of pancreatic islets. To further explore these intriguing findings, new techniques for in vivo assessment of pancreatic innervation are required. This is a retrospective study that aimed to investigate whether the noradrenaline (norepinephrine) analogue ¹¹C-hydroxy ephedrine (¹¹C-HED) could be used for quantitative positron emission tomography (PET) imaging of the sympathetic innervation of the human pancreas.

Methods

In 25 individuals with type 2 diabetes and 64 individuals without diabetes, all of whom had previously undergone ¹¹C-HED-PET/CT because of pheochromocytoma or paraganglioma (or suspicion thereof), the ¹¹C-HED standardised uptake value (SUV_mean), ¹¹C-HED specific binding index (SBI), pancreatic functional volume (FV, in ml), functional neuronal volume (FNV, calculated as SUV_mean × FV), specific binding index with functional volume (SBI FV, calculated as SBI × FV) and attenuation on CT (HU) were investigated in the entire pancreas, and additionally in six separate anatomical pancreatic regions.

Results

Generally, ¹¹C-HED uptake in the pancreas was high, with marked individual variation, suggesting variability in sympathetic innervation. Moreover, pancreatic CT attenuation (HU) (p<0.001), ¹¹C-HED SBI (p=0.0049) and SBI FV (p=0.0142) were lower in individuals with type 2 diabetes than in individuals without diabetes, whereas ¹¹C-HED SUV_mean (p=0.15), FV (p=0.73) and FNV (p=0.30) were similar.

Conclusions/interpretation

We demonstrate the feasibility of using ¹¹C-HED-PET for non-invasive assessment of pancreatic sympathetic innervation in humans. These findings warrant further prospective evaluation, especially in individuals with theoretical defects in pancreatic sympathetic innervation, such as those with type 1 diabetes.

Background: Type 1 diabetes (T1D) is an autoimmune disease characterized by a progressive β-cell destruction. There are no clinically established methods for quantifying endocrine cells of the pancreas and current knowledge is almost exclusively based on autopsy material and functional measurements. Based on the expression of the γ-aminobutyric acid A receptors (GABA_ARs) in pancreatic islets and the fact that GABA_AR agonists are being explored as treatment for T1D, we hypothesized that the positron emission tomography (PET) tracer [¹¹C]flumazenil ([¹¹C]FMZ) could serve as a marker of the endocrine mass of the pancreas. The in vivo uptake of [¹¹C]FMZ in pig pancreas was evaluated by PET/CT, either tracer alone or after blockade of GABA_AR by unlabeled flumazenil. The pancreatic binding of [¹¹C]FMZ was investigated in vitro with frozen sections of pig pancreas as well as human organ donors, in addition to isolated mouse and human islets and exocrine preparations. The expression of GABA_AR subunits in pig, human and mouse pancreas was explored by immunohistochemistry.

Results: Strong specific in vivo uptake of [¹¹C]FMZ was observed in the pig brain as expected, but in the pancreas the signal was moderate and only partially reduced by blockade. In vitro experiments revealed a positive but weak and variable binding of [¹¹C]FMZ in islets compared to exocrine tissue in the mouse, pig and human pancreas. In pig and mouse pancreatic islets we identified the GABA_AR subunits β2 and γ2 but not α2. In the human pancreas from non-diabetic donors, we have identified the α2, β2 (although weak) and γ2 subunits, whereas from a T2D donor the α2 subunit was missing.

Conclusions: Our findings suggest that [¹¹C]FMZ bind to GABA_ARs in the islets, but not with a sufficient contrast or magnitude to be implemented as an in vivo PET marker for the endocrine mass of the pancreas. However, GABA_ARs with different subunits are widely expressed in the endocrine cells within the pancreas in pig, human and mouse. Hence, the GABA_AR could still be a potential imaging target for the endocrine cells of the pancreas but would require tracers with higher affinity and selectivity for individual GABA_AR subunits.

Introduction The rate of progression to complete insulin deficiency varies greatly in type 1 diabetes. This constitutes a challenge, especially when randomizing patients in intervention trials aiming to preserve beta cell function. This study aimed to identify biomarkers predictive of either a rapid or slow disease progression in children with new-onset type 1 diabetes.

Research design and methods A retrospective, longitudinal cohort study of children (<18 years) with type 1 diabetes (N=46) was included at diagnosis and followed until complete insulinopenia (C-peptide <0.03 nmol/L). Children were grouped into rapid progressors (n=20, loss within 30 months) and slow progressors (n=26). A sex-matched control group of healthy children (N=45) of similar age was included for comparison. Multiple biomarkers were assessed by proximity extension assay (PEA) at baseline and follow-up.

Results At baseline, rapid progressors had lower C-peptide and higher autoantibody levels than slow. Three biomarkers were higher in the rapid group: carbonic anhydrase 9, corticosteroid 11-beta-dehydrogenase isozyme 1, and tumor necrosis factor receptor superfamily member 21. In a linear mixed model, 25 proteins changed over time, irrespective of group. One protein, a coxsackievirus B–adenovirus receptor (CAR) increased over time in rapid progressors. Eighty-one proteins differed between type 1 diabetes and healthy controls. Principal component analysis could not distinguish between rapid, slow, and healthy controls.

Conclusions Despite differences in individual proteins, the combination of multiple biomarkers analyzed by PEA could not distinguish the rate of progression in children with new-onset type 1 diabetes. Only one marker was altered significantly when considering both time and group effects, namely CAR, which increased significantly over time in the rapid group. Nevertheless, we did find some markers that may be useful in predicting the decline of the C-peptide. Moreover, these could potentially be important for understanding type 1 diabetes pathogenesis.

Introduction

To improve the utilization of continuous- and flash glucose monitoring (CGM/FGM) data we have tested the hypothesis that a machine learning (ML) model can be trained to identify the most likely root causes for hypoglycemic events.

Methods

CGM/FGM data were collected from 449 patients with type 1 diabetes. Of the 42,120 identified hypoglycemic events, 5041 were randomly selected for classification by two clinicians. Three causes of hypoglycemia were deemed possible to interpret and later validate by insulin and carbohydrate recordings: (1) overestimated bolus (27%), (2) overcorrection of hyperglycemia (29%) and (3) excessive basal insulin presure (44%). The dataset was split into a training (n = 4026 events, 304 patients) and an internal validation dataset (n = 1015 events, 145 patients). A number of ML model architectures were applied and evaluated. A separate dataset was generated from 22 patients (13 ‘known’ and 9 ‘unknown’) with insulin and carbohydrate recordings. Hypoglycemic events from this dataset were also interpreted by five clinicians independently.

Results

Of the evaluated ML models, a purpose-built convolutional neural network (HypoCNN) performed best. Masking the time series, adding time features and using class weights improved the performance of this model, resulting in an average area under the curve (AUC) of 0.921 in the original train/test split. In the dataset validated by insulin and carbohydrate recordings (n = 435 events), i.e. ‘ground truth,’ our HypoCNN model achieved an AUC of 0.917.

Conclusions

The findings support the notion that ML models can be trained to interpret CGM/FGM data. Our HypoCNN model provides a robust and accurate method to identify root causes of hypoglycemic events.

Introduction: Hypoglycemia composes an always present risk in the treatment of type 1 diabetes (T1D) and can be a fatal complication. Many studies on hypoglycemic events are based on self-reported data or focused on the aggregated time below range. We have processed continuous glucose monitoring (CGM) data in children and adolescents with T1D in order to examine all occurring hypoglycemic events.

Research design and methods: CGM data (mean 168 +/- 3 days) from 214 children and adolescents with T1D were analyzed using computer-based algorithms. Patients were divided into three groups based on estimated HbA1c (eHbA1c): (1) <= 48 mmol/mol (n=58); (2) 49-64 mmol/ mol (n=113); (3) >= 65 mmol/mol (n=43). The groups were compared concerning descriptive data and CGM metrics with emphasis on the frequency of hypoglycemic events.

Results: Only one self-reported event of severe hypoglycemia was registered, while 54 390 hypoglycemic events (<3.9 mmol/L (<70 mg/dL)) were identified from CGM data out of which 11 740 were serious (<3.0 mmol/L (<54 mg/dL)). On average there were 1.5 +/- 0.1 hypoglycemic events per 24 hours out of which 1.2 +/- 0.1 were mild (3.0-3.9 mmol/L) and 0.3 +/- 0.02 serious. Group 1 had a higher frequency of both total and mild hypoglycemic events compared with both groups 2 and 3. However, the frequency of serious hypoglycemic events was similar in all groups. A negative correlation was observed for eHbA1c and total daily and mild hypoglycemic events (r=-0.57 and r=-0.66, respectively, p<0.0001), whereas for serious hypoglycemic events there was only a borderline significance (r=-0.13, p=0.05).

Conclusions: This study shows that hypoglycemic events are a frequent phenomenon in children and adolescents with T1D, occurring regardless of overall metabolic control. Although patients with an HbA1c =48 mmol/mol had a higher frequency of mild hypoglycemic events there was no increase in serious hypoglycemic events.

Aim/hypothesis This study aimed to investigate the safety and efficacy of treatment with allogeneic Wharton's jelly-derived mesenchymal stromal cells (MSCs) in recent-onset type 1 diabetes.

Methods A combined Phase I/II trial, composed of a dose escalation followed by a randomised double-blind placebo-controlled study in parallel design, was performed in which treatment with allogeneic MSCs produced as an advanced therapy medicinal product (ProTrans) was compared with placebo in adults with newly diagnosed type 1 diabetes. Inclusion criteria were a diagnosis of type 1 diabetes <2 years before enrolment, age 18-40 years and a fasting plasma C-peptide concentration >0.12 nmol/l. Randomisation was performed with a web-based randomisation system, with a randomisation code created prior to the start of the study. The randomisation was made in blocks, with participants randomised to ProTrans or placebo treatment. Randomisation envelopes were kept at the clinic in a locked room, with study staff opening the envelopes at the baseline visits. All participants and study personnel were blinded to group assignment. The study was conducted at Karolinska University Hospital, Stockholm, Sweden.

Results Three participants were included in each dose cohort during the first part of the study. Fifteen participants were randomised in the second part of the study, with ten participants assigned to ProTrans treatment and five to placebo. All participants were analysed for the primary and secondary outcomes. No serious adverse events related to treatment were observed and, overall, few adverse events (mainly mild upper respiratory tract infections) were reported in the active treatment and placebo arms. The primary efficacy endpoint was defined as Delta-change in C-peptide AUC for a mixed meal tolerance test at 1 year following ProTrans/placebo infusion compared with baseline performance prior to treatment. C-peptide levels in placebo-treated individuals declined by 47%, whereas those in ProTrans-treated individuals declined by only 10% (p<0.05). Similarly, insulin requirements increased in placebo-treated individuals by a median of 10 U/day, whereas insulin needs of ProTrans-treated individuals did not change over the follow-up period of 12 months (p<0.05).

Conclusions/interpretation This study suggests that allogeneic Wharton's jelly-derived MSCs (ProTrans) is a safe treatment for recent-onset type 1 diabetes, with the potential to preserve beta cell function.

The hormone fibroblast growth factor 21 (FGF21) modulates tissue metabolism and circulates at higher levels in metabolic conditions associated with chronic sleep-wake disruption, such as type 2 diabetes and obesity. In the present study, we investigated whether acute sleep loss impacts circulating levels of FGF21 and tissue-specific production, and response pathways linked to FGF21. A total of 15 healthy normal-weight young men participated in a randomised crossover study with two conditions, sleep loss versus an 8.5-hr sleep window. The evening before each intervention, fasting blood was collected. Fasting, post-intervention morning skeletal muscle and adipose tissue samples underwent quantitative polymerase chain reaction and DNA methylation analyses, and serum FGF21 levels were measured before and after an oral glucose tolerance test. Serum levels of FGF21 were higher after sleep loss compared with sleep, both under fasting conditions and following glucose intake (~27%-30%, p = 0.023). Fasting circulating levels of fibroblast activation protein, a protein which can degrade circulating FGF21, were not altered by sleep loss, whereas DNA methylation in the FGF21 promoter region increased only in adipose tissue. However, even though specifically the muscle exhibited transcriptional changes indicating adverse alterations to redox and metabolic homeostasis, no tissue-based changes were observed in expression of FGF21, its receptors, or selected signalling targets, in response to sleep loss. In summary, we found that acute sleep loss resulted in increased circulating levels of FGF21 in healthy young men, which may occur independent of a tissue-based stress response in metabolic peripheral tissues. Further studies may decipher whether changes in FGF21 signalling after sleep loss modulate metabolic outcomes associated with sleep or circadian disruption.