Diabetologia

Correction to: Bone marrow pericyte dysfunction in individuals with type 2 diabetes Unfortunately, three errors were made in the conversion of HbA1c to per cent values.

The Integrated Islet Distribution Program answers the call for improved human islet phenotyping and reporting of human islet characteristics in research articles

Soluble receptor for AGE in diabetic nephropathy and its progression in Finnish individuals with type 1 diabetes Abstract Aims/hypothesis Activation of the receptor for AGE (RAGE) has been shown to be associated with diabetic nephropathy. The soluble isoform of RAGE (sRAGE) is considered to function as a decoy receptor for RAGE ligands and thereby protects against diabetic complications. A possible association between sRAGE and diabetic nephropathy is still, however, controversial and a more comprehensive analysis of sRAGE with respect to diabetic nephropathy in type 1 diabetes is therefore warranted. Methods sRAGE was measured in baseline serum samples from 3647 participants with type 1 diabetes from the nationwide multicentre Finnish Diabetic Nephropathy (FinnDiane) Study. Associations between sRAGE and diabetic nephropathy, as well as sRAGE and diabetic nephropathy progression, were evaluated by regression, competing risks and receiver operating characteristic curve analyses. The non-synonymous SNP rs2070600 (G82S) was used to test causality in the Mendelian randomisation analysis. Results Baseline sRAGE concentrations were highest in participants with diabetic nephropathy, compared with participants with a normal AER or those with microalbuminuria. Baseline sRAGE was associated with progression from macroalbuminuria to end-stage renal disease (ESRD) in the competing risks analyses, but this association disappeared when eGFR was entered into the model. The SNP rs2070600 was strongly associated with sRAGE concentrations and with progression from macroalbuminuria to ESRD. However, Mendelian randomisation analysis did not support a causal role for sRAGE in progression to ESRD. Conclusions/interpretation sRAGE is associated with progression from macroalbuminuria to ESRD, but does not add predictive value on top of conventional risk factors. Although sRAGE is a biomarker of diabetic nephropathy, in light of the Mendelian randomisation analysis it does not seem to be causally related to progression from macroalbuminuria to ESRD.

Continuous glucose monitoring targets in type 1 diabetes pregnancy: every 5% time in range matters Abstract With randomised trial data confirming that continuous glucose monitoring (CGM) is associated with improvements in maternal glucose control and neonatal health outcomes, CGM is increasingly used in antenatal care. Across pregnancy, the ambition is to increase the CGM time in range (TIR), while reducing time above range (TAR), time below range (TBR) and glycaemic variability measures. Pregnant women with type 1 diabetes currently spend, on average, 50% (12 h), 55% (13 h) and 60% (14 h) in the target range of 3.5–7.8 mmol/l (63–140 mg/dl) during the first, second and third trimesters, respectively. Hyperglycaemia, as measured by TAR, reduces from 40% (10 h) to 33% (8 h) during the first to third trimester. A TIR of >70% (16 h, 48 min) and a TAR of <25% (6 h) is achieved only in the final weeks of pregnancy. CGM TBR data are particularly sensor dependent, but regardless of the threshold used for individual patients, spending ≥4% of time (1 h) below 3.5 mmol/l or ≥1% of time (15 min) below 3.0 mmol/l is not recommended. While maternal hyperglycaemia is a well-established risk factor for obstetric and neonatal complications, CGM-based risk factors are emerging. A 5% lower TIR and 5% higher TAR during the second and third trimesters is associated with increased risk of large for gestational age infants, neonatal hypoglycaemia and neonatal intensive care unit admissions. For optimal neonatal outcomes, women and clinicians should aim for a TIR of >70% (16 h, 48 min) and a TAR of <25% (6 h), from as early as possible during pregnancy.

Metformin increases endogenous glucose production in non-diabetic individuals and individuals with recent-onset type 2 diabetes Abstract Aims/hypothesis Metformin is the endorsed first-line glucose-lowering drug for treating patients with type 2 diabetes but despite more than 50 years of use, no consensus has been reached on its mechanisms of action. In this study, we investigated the glucose-lowering effects of metformin in individuals with type 2 diabetes and non-diabetic individuals. Methods We performed a randomised, placebo-controlled trial in 24 individuals with recent-onset type 2 diabetes (diabetes duration 50 [48] months) who had good glycaemic control (HbA1c 48 mmol/mmol [6.5%]). The studies were conducted at Aarhus University Hospital between 2013 and 2016. Participants were randomised to receive either metformin (2000 mg/day, n = 12, MET group) or placebo (n = 12, PLA group) for 90 days, using block randomisation set up by an unblinded pharmacist. Two participants withdrew from the study prior to completion and were replaced with two new participants receiving the same treatment. In addition, we recruited a group of non-diabetic individuals with similar age and BMI (n = 12, CONT group), who were all treated with 2000 mg metformin daily. Before and after treatment all individuals underwent studies of whole-body glucose metabolism by non-steady-state [3-3H]glucose kinetics, hyperinsulinaemic–euglycaemic clamping, indirect calorimetry, metabolomics, dual x-ray absorptiometry and muscle biopsies. The primary study endpoint was the effect of metformin treatment on lipid kinetics as well as glucose rate of disappearance (Rd) and endogenous glucose production (EGP). Results One participant from the CONT group withdrew due to intolerable gastrointestinal side-effects and was excluded from analysis. As expected, metformin treatment lowered fasting plasma glucose (FPG) in the MET group (~1.5 mmol/l, p < 0.01), whereas no effect was observed in the PLA and CONT groups. Body weight and composition did not change in any of the groups. In both of the metformin-treated groups (MET and CONT), basal glucose Rd, EGP and glucagon levels increased by ~30% (p < 0.05) whereas this was not the case in the PLA group. Conclusions/interpretation Ninety days of metformin treatment resulted in similar increases in EGP and glucose Rd in individuals with recent-onset type 2 diabetes and in non-diabetic control individuals. These results challenge the existing paradigm that metformin primarily acts in the liver by inhibiting EGP, at least in individuals with type 2 diabetes of short duration and who have discretely affected glycaemic status. Whether metformin increases basal glucose Rd by facilitating glucose uptake in other tissues such as the intestines remains to be further clarified. Trial registration ClinicalTrials.gov NCT01729156 Funding This study was supported by grants from The Danish Council for Independent Research | Medical Sciences, Aase Danielsen Fund, the Novo Nordisk Foundation, the Danish Diabetes Association and the Danish Diabetes Academy supported by the Novo Nordisk Foundation.

Type 2 diabetes: a multifaceted disease Abstract Type 2 diabetes is a complex disease usually diagnosed with little regard to aetiology. In the broader sense, it is a mix of different clearly defined aetiologies, such as monogenic diabetes, that we need to be better at identifying as this has major implications for treatment and patient management. Beyond this, however, type 2 diabetes is a highly heterogeneous polygenic disease. This review outlines the recent developments that recognise this heterogeneity by deconvoluting the aetiology of type 2 diabetes into pathophysiological processes, either by measuring physiological variables (such as beta cell function or insulin resistance) or using partitioned polygenic scores, and addresses recent work that clusters type 2 diabetes into distinct subgroups. Increasing evidence suggests that considering the aetiological components of type 2 diabetes matters, in terms of progression rates, treatment response and complications. In other words, clinicians need to recognise that type 2 diabetes is multifaceted and that its characteristics are important for how patients are managed.

Type 1 diabetes defined by severe insulin deficiency occurs after 30 years of age and is commonly treated as type 2 diabetes Abstract Aims/hypothesis Late-onset type 1 diabetes can be difficult to identify. Measurement of endogenous insulin secretion using C-peptide provides a gold standard classification of diabetes type in longstanding diabetes that closely relates to treatment requirements. We aimed to determine the prevalence and characteristics of type 1 diabetes defined by severe endogenous insulin deficiency after age 30 and assess whether these individuals are identified and managed as having type 1 diabetes in clinical practice. Methods We assessed the characteristics of type 1 diabetes defined by rapid insulin requirement (within 3 years of diagnosis) and severe endogenous insulin deficiency (non-fasting C-peptide <200 pmol/l) in 583 participants with insulin-treated diabetes, diagnosed after age 30, from the Diabetes Alliance for Research in England (DARE) population cohort. We compared characteristics with participants with retained endogenous insulin secretion (>600 pmol/l) and 220 participants with severe insulin deficiency who were diagnosed under age 30. Results Twenty-one per cent of participants with insulin-treated diabetes who were diagnosed after age 30 met the study criteria for type 1 diabetes. Of these participants, 38% did not receive insulin at diagnosis, of whom 47% self-reported type 2 diabetes. Rapid insulin requirement was highly predictive of severe endogenous insulin deficiency: 85% required insulin within 1 year of diagnosis, and 47% of all those initially treated without insulin who progressed to insulin treatment within 3 years of diagnosis had severe endogenous insulin deficiency. Participants with late-onset type 1 diabetes defined by development of severe insulin deficiency had similar clinical characteristics to those with young-onset type 1 diabetes. However, those with later onset type 1 diabetes had a modestly lower type 1 diabetes genetic risk score (0.268 vs 0.279; p < 0.001 [expected type 2 diabetes population median, 0.231]), a higher islet autoantibody prevalence (GAD-, islet antigen 2 [IA2]- or zinc transporter protein 8 [ZnT8]-positive) of 78% at 13 years vs 62% at 26 years of diabetes duration; (p = 0.02), and were less likely to identify as having type 1 diabetes (79% vs 100%; p < 0.001) vs those with young-onset disease. Conclusions/interpretation Type 1 diabetes diagnosed over 30 years of age, defined by severe insulin deficiency, has similar clinical and biological characteristics to that occurring at younger ages, but is frequently not identified. Clinicians should be aware that patients progressing to insulin within 3 years of diagnosis have a high likelihood of type 1 diabetes, regardless of initial diagnosis.

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Human gut microbiota transferred to germ-free NOD mice modulate the progression towards type 1 diabetes regardless of the pace of beta cell function loss in the donor Abstract Aims/hypothesis This study aimed to assess the ability of human gut microbiota to delay the onset of type 1 diabetes when transferred into germ-free NOD mice. Methods Two children with rapid and three children with slow beta cell function loss (as assessed by C-peptide AUC change in the mixed-meal tolerance tests performed 1 and 12 months after type 1 diabetes onset), participating in an ongoing trial with gluten-free diet, donated faeces, which were transferred into germ-free NOD mice. The mice were subsequently followed for diabetes incidence. Results The bacterial profiles of bacteriome-humanised mice had significantly (p < 10−5) lower alpha diversity than the donor material, with marked shifts in ratios between the main phyla. Diabetes onset was significantly delayed in all bacteriome-humanised colonies vs germ-free NOD mice, but the pace of beta cell loss was not transferable to the mouse model. Conclusions/interpretation Germ-free NOD mice colonised with human gut microbiome are able to adopt a large proportion of transferred bacterial content, although the ratios of main phyla are reproduced only suboptimally. The recipient mice did not replicate the phenotype of the stool donor in relation to the pace towards type 1 diabetes. Trial registration ClinicalTrials.gov NCT02867436

Genome-wide association study of type 2 diabetes in Africa Abstract Aims/hypothesis Genome-wide association studies (GWAS) for type 2 diabetes have uncovered >400 risk loci, primarily in populations of European and Asian ancestry. Here, we aimed to discover additional type 2 diabetes risk loci (including African-specific variants) and fine-map association signals by performing genetic analysis in African populations. Methods We conducted two type 2 diabetes genome-wide association studies in 4347 Africans from South Africa, Nigeria, Ghana and Kenya and meta-analysed both studies together. Likely causal variants were identified using fine-mapping approaches. Results The most significantly associated variants mapped to the widely replicated type 2 diabetes risk locus near TCF7L2 (p = 5.3 × 10−13). Fine-mapping of the TCF7L2 locus suggested one type 2 diabetes association signal shared between Europeans and Africans (indexed by rs7903146) and a distinct African-specific signal (indexed by rs17746147). We also detected one novel signal, rs73284431, near AGMO (p = 5.2 × 10−9, minor allele frequency [MAF] = 0.095; monomorphic in most non-African populations), distinct from previously reported signals in the region. In analyses focused on 100 published type 2 diabetes risk loci, we identified 21 with shared causal variants in African and non-African populations. Conclusions/interpretation These results demonstrate the value of performing GWAS in Africans, provide a resource to larger consortia for further discovery and fine-mapping and indicate that additional large-scale efforts in Africa are warranted to gain further insight in to the genetic architecture of type 2 diabetes.

Alexandros Sfakianakis
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alsfakia@gmail.com