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Diabetologia
Journal Prestige (SJR): 3.228  Citation Impact (citeScore): 5 Number of Followers: 200  Hybrid journal (It can contain Open Access articles)ISSN (Print) 1432-0428 - ISSN (Online) 0012-186X Published by Springer-Verlag  [2469 journals]
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- Correction to: Association of gut microbiota with glycaemic traits and
incident type 2 diabetes, and modulation by habitual diet: a
population-based longitudinal cohort study in Chinese adults-
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PubDate: 2022-09-01
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- Continuous glucose monitoring and hypoglycaemia events: unmet needs. Reply
to Papaioannou TG, Snoudou D and Tsiofis C [letter]-
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PubDate: 2022-09-01
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- Up Front
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PubDate: 2022-09-01
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- Continuous glucose monitoring and hypoglycaemia events: unmet needs
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PubDate: 2022-09-01
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- Calcium-dependent transcriptional changes in human pancreatic islet cells
reveal functional diversity in islet cell subtypes-
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Abstract: Aims/hypothesis Pancreatic islets depend on cytosolic calcium (Ca2+) to trigger the secretion of glucoregulatory hormones and trigger transcriptional regulation of genes important for islet response to stimuli. To date, there has not been an attempt to profile Ca2+-regulated gene expression in all islet cell types. Our aim was to construct a large single-cell transcriptomic dataset from human islets exposed to conditions that would acutely induce or inhibit intracellular Ca2+ signalling, while preserving biological heterogeneity. Methods We exposed intact human islets from three donors to the following conditions: (1) 2.8 mmol/l glucose; (2) 16 mmol/l glucose and 40 mmol/l KCl to maximally stimulate Ca2+ signalling; and (3) 16 mmol/l glucose, 40 mmol/l KCl and 5 mmol/l EGTA (Ca2+ chelator) to inhibit Ca2+ signalling, for 1 h. We sequenced 68,650 cells from all islet cell types, and further subsetted the cells to form an endocrine cell-specific dataset of 59,373 cells expressing INS, GCG, SST or PPY. We compared transcriptomes across conditions to determine the differentially expressed Ca2+-regulated genes in each endocrine cell type, and in each endocrine cell subcluster of alpha and beta cells. Results Based on the number of Ca2+-regulated genes, we found that each alpha and beta cell cluster had a different magnitude of Ca2+ response. We also showed that polyhormonal clusters expressing both INS and GCG, or both INS and SST, are defined by Ca2+-regulated genes specific to each cluster. Finally, we identified the gene PCDH7 from the beta cell clusters that had the highest number of Ca2+-regulated genes, and showed that cells expressing cell surface PCDH7 protein have enhanced glucose-stimulated insulin secretory function. Conclusions/interpretation Here we use our large-scale, multi-condition, single-cell dataset to show that human islets have cell-type-specific Ca2+-regulated gene expression profiles, some of them specific to subpopulations. In our dataset, we identify PCDH7 as a novel marker of beta cells having an increased number of Ca2+-regulated genes and enhanced insulin secretory function. Data availability A searchable and user-friendly format of the data in this study, specifically designed for rapid mining of single-cell RNA sequencing data, is available at https://lynnlab.shinyapps.io/Human_Islet_Atlas/. The raw data files are available at NCBI Gene Expression Omnibus (GSE196715). Graphical abstract
PubDate: 2022-09-01
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- A genome-wide cross-trait analysis identifies shared loci and causal
relationships of type 2 diabetes and glycaemic traits with polycystic
ovary syndrome-
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Abstract: Aims/hypothesis The link underlying abnormal glucose metabolism, type 2 diabetes and polycystic ovary syndrome (PCOS) that is independent of BMI remains unclear in observational studies. We aimed to clarify this association using a genome-wide cross-trait approach. Methods Summary statistics from the hitherto largest genome-wide association studies conducted for type 2 diabetes, type 2 diabetes mellitus adjusted for BMI (T2DMadjBMI), fasting glucose, fasting insulin, 2h glucose after an oral glucose challenge (all adjusted for BMI), HbA1c and PCOS, all in populations of European ancestry, were used. We quantified overall and local genetic correlations, identified pleiotropic loci and expression–trait associations, and made causal inferences across traits. Results A positive overall genetic correlation between type 2 diabetes and PCOS was observed, largely influenced by BMI (rg=0.31, p=1.63×10–8) but also independent of BMI (T2DMadjBMI–PCOS: rg=0.12, p=0.03). Sixteen pleiotropic loci affecting type 2 diabetes, glycaemic traits and PCOS were identified, suggesting mechanisms of association that are independent of BMI. Two shared expression–trait associations were found for type 2 diabetes/T2DMadjBMI and PCOS targeting tissues of the cardiovascular, exocrine/endocrine and digestive systems. A putative causal effect of fasting insulin adjusted for BMI and type 2 diabetes on PCOS was demonstrated. Conclusions/interpretation We found a genetic link underlying type 2 diabetes, glycaemic traits and PCOS, driven by both biological pleiotropy and causal mediation, some of which is independent of BMI. Our findings highlight the importance of controlling fasting insulin levels to mitigate the risk of PCOS, as well as screening for and long-term monitoring of type 2 diabetes in all women with PCOS, irrespective of BMI. Graphical abstract
PubDate: 2022-09-01
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- Birthweight, BMI in adulthood and latent autoimmune diabetes in adults: a
Mendelian randomisation study-
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Abstract: Aims/hypothesis Observational studies have found an increased risk of latent autoimmune diabetes in adults (LADA) associated with low birthweight and adult overweight/obese status. We aimed to investigate whether these associations are causal, using a two-sample Mendelian randomisation (MR) design. In addition, we compared results for LADA and type 2 diabetes. Methods We identified 43 SNPs acting through the fetal genome as instrumental variables (IVs) for own birthweight from a genome-wide association study (GWAS) of the Early Growth Genetics Consortium (EGG) and the UK Biobank. We identified 820 SNPs as IVs for adult BMI from a GWAS of the UK Biobank and the Genetic Investigation of ANthropometric Traits consortium (GIANT). Summary statistics for the associations between IVs and LADA were extracted from the only GWAS involving 2634 cases and 5947 population controls. We used the inverse-variance weighted (IVW) estimator as our primary analysis, supplemented by a series of sensitivity analyses. Results Genetically determined own birthweight was inversely associated with LADA (OR per SD [~500 g] decrease in birthweight 1.68 [95% CI 1.01, 2.82]). In contrast, genetically predicted BMI in adulthood was positively associated with LADA (OR per SD [~4.8 kg/m2] increase in BMI 1.40 [95% CI 1.14, 1.71]). Robust results were obtained in a range of sensitivity analyses using other MR estimators or excluding some IVs. With respect to type 2 diabetes, the association with birthweight was not stronger than in LADA while the association with adult BMI was stronger than in LADA. Conclusions/ interpretation This study provides genetic support for a causal link between low birthweight, adult overweight/obese status and LADA. Graphical abstract
PubDate: 2022-09-01
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- Genome-wide meta-analysis and omics integration identifies novel genes
associated with diabetic kidney disease-
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Abstract: Aims/hypothesis Diabetic kidney disease (DKD) is the leading cause of kidney failure and has a substantial genetic component. Our aim was to identify novel genetic factors and genes contributing to DKD by performing meta-analysis of previous genome-wide association studies (GWAS) on DKD and by integrating the results with renal transcriptomics datasets. Methods We performed GWAS meta-analyses using ten phenotypic definitions of DKD, including nearly 27,000 individuals with diabetes. Meta-analysis results were integrated with estimated quantitative trait locus data from human glomerular (N=119) and tubular (N=121) samples to perform transcriptome-wide association study. We also performed gene aggregate tests to jointly test all available common genetic markers within a gene, and combined the results with various kidney omics datasets. Results The meta-analysis identified a novel intronic variant (rs72831309) in the TENM2 gene associated with a lower risk of the combined chronic kidney disease (eGFR<60 ml/min per 1.73 m2) and DKD (microalbuminuria or worse) phenotype (p=9.8×10−9; although not withstanding correction for multiple testing, p>9.3×10−9). Gene-level analysis identified ten genes associated with DKD (COL20A1, DCLK1, EIF4E, PTPRN–RESP18, GPR158, INIP–SNX30, LSM14A and MFF; p<2.7×10−6). Integration of GWAS with human glomerular and tubular expression data demonstrated higher tubular AKIRIN2 gene expression in individuals with vs without DKD (p=1.1×10−6). The lead SNPs within six loci significantly altered DNA methylation of a nearby CpG site in kidneys (p<1.5×10−11). Expression of lead genes in kidney tubules or glomeruli correlated with relevant pathological phenotypes (e.g. TENM2 expression correlated positively with eGFR [p=1.6×10−8] and negatively with tubulointerstitial fibrosis [p=2.0×10−9], tubular DCLK1 expression correlated positively with fibrosis [p=7.4×10−16], and SNX30 expression correlated positively with eGFR [p=5.8×10−14] and negatively with fibrosis [p<2.0×10−16]). Conclusions/interpretation Altogether, the results point to novel genes contributing to the pathogenesis of DKD. Data availability The GWAS meta-analysis results can be accessed via the type 1 and type 2 diabetes (T1D and T2D, respectively) and Common Metabolic Diseases (CMD) Knowledge Portals, and downloaded on their respective download pages (https://t1d.hugeamp.org/downloads.html; https://t2d.hugeamp.org/downloads.html; https://hugeamp.org/downloads.html). Graphical abstract
PubDate: 2022-09-01
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- Depression, diabetes, comorbid depression and diabetes and risk of
all-cause and cause-specific mortality: a prospective cohort study-
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Abstract: Aims/hypothesis The aim of this study was to investigate the risks of all-cause and cause-specific mortality among participants with neither, one or both of diabetes and depression in a large prospective cohort study in the UK. Methods Our study population included 499,830 UK Biobank participants without schizophrenia and bipolar disorder at baseline. Type 1 and type 2 diabetes and depression were identified using self-reported diagnoses, prescribed medication and hospital records. Mortality was identified from death records using the primary cause of death to define cause-specific mortality. We performed Cox proportional hazards models to estimate the risk of all-cause mortality and mortality from cancer, circulatory disease and causes of death other than circulatory disease or cancer among participants with either depression (n=41,791) or diabetes (n=22,677) alone and with comorbid diabetes and depression (n=3597) compared with the group with neither condition (n=431,765), adjusting for sociodemographic and lifestyle factors, comorbidities and history of CVD or cancer. We also investigated the interaction between diabetes and depression. Results During a median of 6.8 (IQR 6.1–7.5) years of follow-up, there were 13,724 deaths (cancer, n=7976; circulatory disease, n=2827; other causes, n=2921). Adjusted HRs of all-cause mortality and mortality from cancer, circulatory disease and other causes were highest among people with comorbid depression and diabetes (HRs 2.16 [95% CI 1.94, 2.42]; 1.62 [95% CI 1.35, 1.93]; 2.22 [95% CI 1.80, 2.73]; and 3.60 [95% CI 2.93, 4.42], respectively). The risks of all-cause, cancer and other mortality among those with comorbid depression and diabetes exceeded the sum of the risks due to diabetes and depression alone. Conclusions/interpretation We confirmed that depression and diabetes individually are associated with an increased mortality risk and also identified that comorbid depression and diabetes have synergistic effects on the risk of all-cause mortality that are largely driven by deaths from cancer and causes other than circulatory disease and cancer. Graphical abstract
PubDate: 2022-09-01
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- GLP-1 receptor nitration contributes to loss of brain pericyte function in
a mouse model of diabetes-
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Abstract: Aims/hypothesis We have previously shown that diabetes causes pericyte dysfunction, leading to loss of vascular integrity and vascular cognitive impairment and dementia (VCID). Glucagon-like peptide-1 (GLP-1) receptor agonists (GLP-1 RAs), used in managing type 2 diabetes mellitus, improve the cognitive function of diabetic individuals beyond glycaemic control, yet the mechanism is not fully understood. In the present study, we hypothesise that GLP-1 RAs improve VCID by preventing diabetes-induced pericyte dysfunction. Methods Mice with streptozotocin-induced diabetes and non-diabetic control mice received either saline (NaCl 154 mmol/l) or exendin-4, a GLP-1 RA, through an osmotic pump over 28 days. Vascular integrity was assessed by measuring cerebrovascular neovascularisation indices (vascular density, tortuosity and branching density). Cognitive function was evaluated with Barnes maze and Morris water maze. Human brain microvascular pericytes (HBMPCs), were grown in high glucose (25 mmol/l) and sodium palmitate (200 μmol/l) to mimic diabetic conditions. HBMPCs were treated with/without exendin-4 and assessed for nitrative and oxidative stress, and angiogenic and blood–brain barrier functions. Results Diabetic mice treated with exendin-4 showed a significant reduction in all cerebral pathological neovascularisation indices and an improved blood–brain barrier (p<0.05). The vascular protective effects were accompanied by significant improvement in the learning and memory functions of diabetic mice compared with control mice (p<0.05). Our results showed that HBMPCs expressed the GLP-1 receptor. Diabetes increased GLP-1 receptor expression and receptor nitration in HBMPCs. Stimulation of HBMPCs with exendin-4 under diabetic conditions decreased diabetes-induced vascular inflammation and oxidative stress, and restored pericyte function (p<0.05). Conclusions/interpretation This study provides novel evidence that brain pericytes express the GLP-1 receptor, which is nitrated under diabetic conditions. GLP-1 receptor activation improves brain pericyte function resulting in restoration of vascular integrity and BBB functions in diabetes. Furthermore, the GLP-1 RA exendin-4 alleviates diabetes-induced cognitive impairment in mice. Restoration of pericyte function in diabetes represents a novel therapeutic target for diabetes-induced cerebrovascular microangiopathy and VCID. Graphical abstract
PubDate: 2022-09-01
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- Umbilical cord blood DNA methylation in children who later develop type 1
diabetes-
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Abstract: Aims/hypothesis Distinct DNA methylation patterns have recently been observed to precede type 1 diabetes in whole blood collected from young children. Our aim was to determine whether perinatal DNA methylation is associated with later progression to type 1 diabetes. Methods Reduced representation bisulphite sequencing (RRBS) analysis was performed on umbilical cord blood samples collected within the Finnish Type 1 Diabetes Prediction and Prevention (DIPP) Study. Children later diagnosed with type 1 diabetes and/or who tested positive for multiple islet autoantibodies (n = 43) were compared with control individuals (n = 79) who remained autoantibody-negative throughout the DIPP follow-up until 15 years of age. Potential confounding factors related to the pregnancy and the mother were included in the analysis. Results No differences in the umbilical cord blood methylation patterns were observed between the cases and controls at a false discovery rate <0.05. Conclusions/interpretation Based on our results, differences between children who progress to type 1 diabetes and those who remain healthy throughout childhood are not yet present in the perinatal DNA methylome. However, we cannot exclude the possibility that such differences would be found in a larger dataset. Graphical abstract
PubDate: 2022-09-01
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- A miR-125/Sirtuin-7 pathway drives the pro-calcific potential of myeloid
cells in diabetic vascular disease-
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Abstract: Aims/hypothesis Ectopic calcification is a typical feature of diabetic vascular disease and resembles an accelerated ageing phenotype. We previously found an excess of myeloid calcifying cells in diabetic individuals. We herein examined molecular and cellular pathways linking atherosclerotic calcification with calcification by myeloid cells in the diabetic milieu. Methods We first examined the associations among coronary calcification, myeloid calcifying cell levels and mononuclear cell gene expression in a cross-sectional study of 87 participants with type 2 diabetes undergoing elective coronary angiography. Then, we undertook in vitro studies on mesenchymal stem cells and the THP-1 myeloid cell line to verify the causal relationships of the observed associations. Results Coronary calcification was associated with 2.8-times-higher myeloid calcifying cell levels (p=0.037) and 50% elevated expression of the osteogenic gene RUNX2 in mononuclear cells, whereas expression of Sirtuin-7 (SIRT7) was inversely correlated with calcification. In standard differentiation assays of mesenchymal stem cells, SIRT7 knockdown activated the osteogenic program and worsened calcification, especially in the presence of high (20 mmol/l) glucose. In the myeloid cell line THP-1, SIRT7 downregulation drove a pro-calcific phenotype, whereas SIRT7 overexpression prevented high-glucose-induced calcification. Through the Janus kinase (JAK)/signal transducer and activator of transcription (STAT) pathway, high glucose induced miR-125b-5p, which in turn targeted SIRT7 in myeloid cells and was directly associated with coronary calcification. Conclusions/interpretation We describe a new pathway elicited by high glucose through the JAK/STAT cascade, involving regulation of SIRT7 by miR-125b-5p and driving calcification by myeloid cells. This pathway is associated with coronary calcification in diabetic individuals and may be a target against diabetic vascular disease. Data availability RNA sequencing data are deposited in GEO (accession number GSE193510; https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE193510). Graphical abstract
PubDate: 2022-09-01
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- Exploring ethnic representativeness in diabetes clinical trial enrolment
from 2000 to 2020: a chronological survey-
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Abstract: Aims/hypothesis Ethnic representativeness of participant enrolment in diabetes RCTs involving multiple ethnicities remains unknown. The aims of this study were to evaluate the status and temporal trend of ethnic representativeness in enrolment to diabetes RCTs, and to assess under-enrolment of non-white ethnic groups and explore trial characteristics associated with under-enrolment. Methods We conducted a chronological survey by systematically searching the literature to include eligible RCTs published between January 2000 and December 2020. We assessed temporal trends in enrolment of ethnic groups in the included trials. Univariable logistic regression was used to explore the association between trial characteristics and under-enrolment of non-white groups, using a participant to prevalence ratio of <0.8 to define under-enrolment. This study was registered in PROSPERO (CRD42021229100). Results We included 405 RCTs for analysis (327 multi-country trials, 69 conducted in the USA and nine conducted in the UK). The median enrolment rate of all non-white groups was 24.0% in the overall RCTs. Trials conducted in the USA and the UK had median enrolment rates of 29.0% and 12.0% for all non-white groups, respectively. There was a temporal trend towards increased participation of non-white ethnic groups in the overall RCTs; however, no significant improvement over time was found in the US or UK trials. Non-white groups were under-enrolled in most included trials: 62.3% (43/69) in US trials and 77.8% (7/9) in UK trials. The US trials with a high female proportion were associated with lower odds of under-enrolment of all non-white groups (OR 0.22; 95% CI 0.07, 0.65), while trials receiving funding from industry showed increased odds of under-enrolment (OR 4.64; 95% CI 1.50, 14.35). Outpatient enrolment and intervention duration were significantly associated with under-enrolment of Black participants. Only a small proportion of trials reported subgroup results or explored the effect modification by ethnicity. Conclusions/interpretation A temporal trend towards increased non-white ethnic enrolment was found in diabetes RCTs globally, but not in the USA or the UK. Non-white ethnic groups were under-represented in the majority of diabetes trials conducted in the USA and the UK. Some trial characteristics may be associated with non-white under-enrolment in diabetes trials. These findings provide some evidence for non-white ethnic representativeness in diabetes trials over the past two decades, and highlight the need for more effective strategies and endeavours to alleviate under-enrolment of non-white ethnic groups. Graphical abstract
PubDate: 2022-09-01
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- Diabetic retinopathy screening in the emerging era of artificial
intelligence-
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Abstract: Diabetic retinopathy is a frequent complication in diabetes and a leading cause of visual impairment. Regular eye screening is imperative to detect sight-threatening stages of diabetic retinopathy such as proliferative diabetic retinopathy and diabetic macular oedema in order to treat these before irreversible visual loss occurs. Screening is cost-effective and has been implemented in various countries in Europe and elsewhere. Along with optimised diabetes care, this has substantially reduced the risk of visual loss. Nevertheless, the growing number of patients with diabetes poses an increasing burden on healthcare systems and automated solutions are needed to alleviate the task of screening and improve diagnostic accuracy. Deep learning by convolutional neural networks is an optimised branch of artificial intelligence that is particularly well suited to automated image analysis. Pivotal studies have demonstrated high sensitivity and specificity for classifying advanced stages of diabetic retinopathy and identifying diabetic macular oedema in optical coherence tomography scans. Based on this, different algorithms have obtained regulatory approval for clinical use and have recently been implemented to some extent in a few countries. Handheld mobile devices are another promising option for self-monitoring, but so far they have not demonstrated comparable image quality to that of fundus photography using non-portable retinal cameras, which is the gold standard for diabetic retinopathy screening. Such technology has the potential to be integrated in telemedicine-based screening programmes, enabling self-captured retinal images to be transferred virtually to reading centres for analysis and planning of further steps. While emerging technologies have shown a lot of promise, clinical implementation has been sparse. Legal obstacles and difficulties in software integration may partly explain this, but it may also indicate that existing algorithms may not necessarily integrate well with national screening initiatives, which often differ substantially between countries. Graphical abstract
PubDate: 2022-09-01
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- Impact of diabetes on COVID-19 prognosis beyond comorbidity burden: the
CORONADO initiative-
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Abstract: Aims/hypothesis Diabetes has been recognised as a pejorative prognostic factor in coronavirus disease 2019 (COVID-19). Since diabetes is typically a disease of advanced age, it remains unclear whether diabetes remains a COVID-19 risk factor beyond advanced age and associated comorbidities. We designed a cohort study that considered age and comorbidities to address this question. Methods The Coronavirus SARS-CoV-2 and Diabetes Outcomes (CORONADO) initiative is a French, multicentric, cohort study of individuals with (exposed) and without diabetes (non-exposed) admitted to hospital with COVID-19, with a 1:1 matching on sex, age (±5 years), centre and admission date (10 March 2020 to 10 April 2020). Comorbidity burden was assessed by calculating the updated Charlson comorbidity index (uCCi). A predefined composite primary endpoint combining death and/or invasive mechanical ventilation (IMV), as well as these two components separately, was assessed within 7 and 28 days following hospital admission. We performed multivariable analyses to compare clinical outcomes between patients with and without diabetes. Results A total of 2210 pairs of participants (diabetes/no-diabetes) were matched on age (mean±SD 69.4±13.2/69.5±13.2 years) and sex (36.3% women). The uCCi was higher in individuals with diabetes. In unadjusted analysis, the primary composite endpoint occurred more frequently in the diabetes group by day 7 (29.0% vs 21.6% in the no-diabetes group; HR 1.43 [95% CI 1.19, 1.72], p<0.001). After multiple adjustments for age, BMI, uCCi, clinical (time between onset of COVID-19 symptoms and dyspnoea) and biological variables (eGFR, aspartate aminotransferase, white cell count, platelet count, C-reactive protein) on admission to hospital, diabetes remained associated with a higher risk of primary composite endpoint within 7 days (adjusted HR 1.42 [95% CI 1.17, 1.72], p<0.001) and 28 days (adjusted HR 1.30 [95% CI 1.09, 1.55], p=0.003), compared with individuals without diabetes. Using the same adjustment model, diabetes was associated with the risk of IMV, but not with risk of death, within 28 days of admission to hospital. Conclusions/interpretation Our results demonstrate that diabetes status was associated with a deleterious COVID-19 prognosis irrespective of age and comorbidity status. Trial registration ClinicalTrials.gov NCT04324736 Graphical abstract
PubDate: 2022-09-01
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- The efficacy of canagliflozin in diabetes subgroups stratified by
data-driven clustering or a supervised machine learning method: a post hoc
analysis of canagliflozin clinical trial data-
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Abstract: Aims/hypothesis Data-driven diabetes subgroups have shown distinct clinical characteristics and disease progression, although there is a lack of evidence that this information can guide clinical decisions. We aimed to investigate whether diabetes subgroups, identified by data-driven clustering or supervised machine learning methods, respond differently to canagliflozin. Methods We pooled data from five randomised, double-blinded clinical trials of canagliflozin at an individual level. We applied the coordinates from the All New Diabetics in Scania (ANDIS) study to form four subgroups: mild age-related diabetes (MARD); severe insulin-deficient diabetes (SIDD); mild obesity-related diabetes (MOD) and severe insulin-resistant diabetes (SIRD). Machine learning models for HbA1c lowering (ML-A1C) and albuminuria progression (ML-ACR) were developed. The primary efficacy endpoint was reduction in HbA1c at 52 weeks. Concordance of a model was defined as the difference between predicted HbA1c and actual HbA1c decline less than 3.28 mmol/mol (0.3%). Results The decline in HbA1c resulting from treatment was different among the four diabetes clusters (pinteraction=0.004). In MOD, canagliflozin showed a robust glucose-lowering effect at week 52, compared with other drugs, with least-squares mean of HbA1c decline [95% CI] being 6.6 mmol/mol (4.1, 9.2) (0.61% [0.38, 0.84]) for sitagliptin, 7.1 mmol/mol (4.7, 9.5) (0.65% [0.43, 0.87]) for glimepiride, and 9.8 mmol/mol (9.0, 10.5) (0.90% [0.83, 0.96]) for canagliflozin. This superiority persisted until 104 weeks. The proportion of individuals who achieved HbA1c <53 mmol/mol (<7.0%) was highest in sitagliptin-treated individuals with MARD but was similar among drugs in individuals with MOD. The ML-A1C model and the cluster algorithm showed a similar concordance rate in predicting HbA1c lowering (31.5% vs 31.4%, p=0.996). Individuals were divided into high-risk and low-risk groups using ML-ACR model according to their predicted progression risk for albuminuria. The effect of canagliflozin vs placebo on albuminuria progression differed significantly between the high-risk (HR 0.67 [95% CI 0.57, 0.80]) and low-risk groups (HR 0.91 [0.75, 1.11]) (pinteraction=0.016). Conclusions/interpretation Data-driven clusters of individuals with diabetes showed different responses to canagliflozin in glucose lowering but not renal outcome prevention. Canagliflozin reduced the risk of albumin progression in high-risk individuals identified by supervised machine learning. Further studies with larger sample sizes for external replication and subtype-specific clinical trials are necessary to determine the clinical utility of these stratification strategies in sodium–glucose cotransporter 2 inhibitor treatment. Data availability The application for the clinical trial data source is available on the YODA website (http://yoda.yale.edu/). Graphical abstract
PubDate: 2022-09-01
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- Obesity in late adolescence and incident type 1 diabetes in young
adulthood-
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Abstract: Aims/hypothesis Studies in children have reported an association between increased BMI and risk for developing type 1 diabetes, but evidence in late adolescence is limited. We studied the association between BMI in late adolescence and incident type 1 diabetes in young adulthood. Methods All Israeli adolescents, ages 16–19 years, undergoing medical evaluation in preparation for mandatory military conscription between January 1996 and December 2016 were included for analysis unless they had a history of dysglycaemia. Data were linked with information about adult onset of type 1 diabetes in the Israeli National Diabetes Registry. Weight and height were measured at study entry. Cox proportional models were applied, with BMI being analysed both as a categorical and as a continuous variable. Results There were 777 incident cases of type 1 diabetes during 15,819,750 person-years (mean age at diagnosis 25.2±3.9 years). BMI was associated with incident type 1 diabetes. In a multivariable model adjusted for age, sex and sociodemographic variables, the HRs for type 1 diabetes were 1.05 (95% CI 0.87, 1.27) for the 50th–74th BMI percentiles, 1.41 (95% CI 1.11, 1.78) for the 75th–84th BMI percentiles, 1.54 (95% CI 1.23, 1.94) for adolescents who were overweight (85th–94th percentiles), and 2.05 (95% CI 1.58, 2.66) for adolescents with obesity (≥95th percentile) (reference group: 5th–49th BMI percentiles). One increment in BMI SD was associated with a 25% greater risk for incidence of type 1 diabetes (HR 1.25, 95% CI 1.17, 1.32). Conclusions Excessively high BMI in otherwise healthy adolescents is associated with increased risk for incident type 1 diabetes in early adulthood. Graphical abstract
PubDate: 2022-09-01
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- Branding foods as ‘healthy’ or ‘unhealthy’ based on marginal data
calls findings into question. Reply to Kanter M [letter]-
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PubDate: 2022-08-13
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- Phenotypic and genetic classification of diabetes
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Abstract: The historical subclassification of diabetes into predominantly types 1 and 2 is well appreciated to inadequately capture the heterogeneity seen in patient presentations, disease course, response to therapy and disease complications. This review summarises proposed data-driven approaches to further refine diabetes subtypes using clinical phenotypes and/or genetic information. We highlight the benefits as well as the limitations of these subclassification schemas, including practical barriers to their implementation that would need to be overcome before incorporation into clinical practice. Graphical abstract
PubDate: 2022-08-12
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- Live enteroviruses, but not other viruses, detected in human pancreas at
the onset of type 1 diabetes in the DiViD study-
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Abstract: Aims/hypothesis Enterovirus (EV) infection of pancreatic islet cells is one possible factor contributing to type 1 diabetes development. We have reported the presence of EV genome by PCR and of EV proteins by immunohistochemistry in pancreatic sections. Here we explore multiple human virus species in the Diabetes Virus Detection (DiViD) study cases using innovative methods, including virus passage in cell cultures. Methods Six recent-onset type 1 diabetes patients (age 24–35) were included in the DiViD study. Minimal pancreatic tail resection was performed under sterile conditions. Eleven live cases (age 43–83) of pancreatic carcinoma without diabetes served as control cases. In the present study, we used EV detection methods that combine virus growth in cell culture, gene amplification and detection of virus-coded proteins by immunofluorescence. Pancreas homogenates in cell culture medium were incubated with EV-susceptible cell lines for 3 days. Two to three blind passages were performed. DNA and RNA were extracted from both pancreas tissue and cell cultures. Real-time PCR was used for detecting 20 different viral agents other than EVs (six herpesviruses, human polyomavirus [BK virus and JC virus], parvovirus B19, hepatitis B virus, hepatitis C virus, hepatitis A virus, mumps, rubella, influenza A/B, parainfluenza 1–4, respiratory syncytial virus, astrovirus, norovirus, rotavirus). EV genomes were detected by endpoint PCR using five primer pairs targeting the partially conserved 5′ untranslated region genome region of the A, B, C and D species. Amplicons were sequenced. The expression of EV capsid proteins was evaluated in cultured cells using a panel of EV antibodies. Results Samples from six of six individuals with type 1 diabetes (cases) and two of 11 individuals without diabetes (control cases) contained EV genomes (p<0.05). In contrast, genomes of 20 human viruses other than EVs could be detected only once in an individual with diabetes (Epstein–Barr virus) and once in an individual without diabetes (parvovirus B19). EV detection was confirmed by immunofluorescence of cultured cells incubated with pancreatic extracts: viral antigens were expressed in the cytoplasm of approximately 1% of cells. Notably, infection could be transmitted from EV-positive cell cultures to uninfected cell cultures using supernatants filtered through 100 nm membranes, indicating that infectious agents of less than 100 nm were present in pancreases. Due to the slow progression of infection in EV-carrying cell cultures, cytopathic effects were not observed by standard microscopy but were recognised by measuring cell viability. Sequences of 5′ untranslated region amplicons were compatible with EVs of the B, A and C species. Compared with control cell cultures exposed to EV-negative pancreatic extracts, EV-carrying cell cultures produced significantly higher levels of IL-6, IL-8 and monocyte chemoattractant protein-1 (MCP1). Conclusions/interpretation Sensitive assays confirm that the pancreases of all DiViD cases contain EVs but no other viruses. Analogous EV strains have been found in pancreases of two of 11 individuals without diabetes. The detected EV strains can be passaged in series from one cell culture to another in the form of poorly replicating live viruses encoding antigenic proteins recognised by multiple EV-specific antibodies. Thus, the early phase of type 1 diabetes is associated with a low-grade infection by EVs, but not by other viral agents. Graphical abstract
PubDate: 2022-08-12
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