Discordance between mean glucose and time in range in relation to HbA1c in individuals with type 1 diabetes: results from the GOLD and SILVER trials.

AIMS/HYPOTHESIS: Previous studies have shown that individuals with similar mean glucose levels (MG) or percentage of time in range (TIR) may have different HbA1c values. The aim of this study was to further elucidate how MG and TIR are associated with HbA1c. METHODS: Data from the randomised clinical GOLD trial (n=144) and the follow-up SILVER trial (n=98) of adults with type 1 diabetes followed for 2.5 years were analysed. A total of 596 paired HbA1c/continuous glucose monitoring measurements were included. Linear mixed-effects models were used to account for intra-individual correlations in repeated-measures data. RESULTS: In the GOLD trial, the mean age of the participants (± SD) was 44±13 years, 63 (44%) were female, and the mean HbA1c (± SD) was 72±9.8 mmol/mol (8.7±0.9%). When correlating MG with HbA1c, MG explained 63% of the variation in HbA1c (r=0.79, p<0.001). The variation in HbA1c explained by MG increased to 88% (r=0.94, p value for improvement of fit <0.001) when accounting for person-to-person variation in the MG-HbA1c relationship. Time below range (TBR; <3.9 mmol/l), time above range (TAR) level 2 (>13.9 mmol/l) and glycaemic variability had little or no effect on the association. For a given MG and TIR, the HbA1c of 10% of individuals deviated by >8 mmol/mol (0.8%) from their estimated HbA1c based on the overall association between MG and TIR with HbA1c. TBR and TAR level 2 significantly influenced the association between TIR and HbA1c. At a given TIR, each 1% increase in TBR was related to a 0.6 mmol/mol lower HbA1c (95% CI 0.4, 0.9; p<0.001), and each 2% increase in TAR level 2 was related to a 0.4 mmol/mol higher HbA1c (95% CI 0.1, 0.6; p=0.003). However, neither TIR, TBR nor TAR level 2 were significantly associated with HbA1c when accounting for MG. CONCLUSIONS/INTERPRETATION: Inter-individual variations exist between MG and HbA1c, as well as between TIR and HbA1c, with clinically important deviations in relatively large groups of individuals with type 1 diabetes. These results may provide important information to both healthcare providers and individuals with diabetes in terms of prognosis and when making diabetes management decisions.

Gut microbiome shifts in people with type 1 diabetes are associated with glycaemic control: an INNODIA study.

AIMS/HYPOTHESIS: The gut microbiome is implicated in the disease process leading to clinical type 1 diabetes, but less is known about potential changes in the gut microbiome after the diagnosis of type 1 diabetes and implications in glucose homeostasis. We aimed to analyse potential associations between the gut microbiome composition and clinical and laboratory data during a 2 year follow-up of people with newly diagnosed type 1 diabetes, recruited to the Innovative approaches to understanding and arresting type 1 diabetes (INNODIA) study. In addition, we analysed the microbiome composition in initially unaffected family members, who progressed to clinical type 1 diabetes during or after their follow-up for 4 years. METHODS: We characterised the gut microbiome composition of 98 individuals with newly diagnosed type 1 diabetes (ND cohort) and 194 autoantibody-positive unaffected family members (UFM cohort), representing a subgroup of the INNODIA Natural History Study, using metagenomic sequencing. Participants from the ND cohort attended study visits within 6 weeks from the diagnosis and 3, 6, 12 and 24 months later for stool sample collection and laboratory tests (HbA1c, C-peptide, diabetes-associated autoantibodies). Participants from the UFM cohort were assessed at baseline and 6, 12, 18, 24 and 36 months later. RESULTS: We observed a longitudinal increase in 21 bacterial species in the ND cohort but not in the UFM cohort. The relative abundance of Faecalibacterium prausnitzii was inversely associated with the HbA1c levels at diagnosis (p=0.0019). The rate of the subsequent disease progression in the ND cohort, as assessed by change in HbA1c, C-peptide levels and insulin dose, was associated with the abundance of several bacterial species. Individuals with rapid decrease in C-peptide levels in the ND cohort had the lowest gut microbiome diversity. Nineteen individuals who were diagnosed with type 1 diabetes in the UFM cohort had increased abundance of Sutterella sp. KLE1602 compared with the undiagnosed UFM individuals (p=1.2 × 10-4). CONCLUSIONS/INTERPRETATION: Our data revealed associations between the gut microbiome composition and the disease progression in individuals with recent-onset type 1 diabetes. Future mechanistic studies as well as animal studies and human trials are needed to further validate the significance and causality of these associations.

Effects of maternal type 1 diabetes and confounding factors on neonatal microbiomes.

AIMS/HYPOTHESIS: Body niche-specific microbiota in maternal-neonatal dyads from gravidae with type 1 diabetes have not been quantitatively and functionally examined. Similarly, the impact of pregnancy-specific factors, such as the presence of comorbidities known to occur more frequently among gravidae with type 1 diabetes, including Caesarean delivery, as well as antibiotic prophylaxis, level of glycaemic control during each trimester of pregnancy and insulin administration, has not been adequately considered. The aims of this study were to characterise the maternal and neonatal microbiomes, assess aspects of microbiota transfer from the maternal microbiomes to the neonatal microbiome and explore the impact of type 1 diabetes and confounding factors on the microbiomes. METHODS: In this observational case-control study, we characterised microbiome community composition and function using 16S rRNA amplicon sequencing in a total of 514 vaginal, rectal and ear-skin swabs and stool samples derived from 92 maternal-neonatal dyads (including 50 gravidae with type 1 diabetes) and in-depth clinical metadata from throughout pregnancy and delivery. RESULTS: Type 1 diabetes-specific microbiota were identified among gravidae with type 1 diabetes and their neonates. Neonatal microbiome profiles of ear-skin swabs and stool samples were established, indicating the taxa more prevalent among neonates born to mothers with type 1 diabetes compared with neonates born to control mothers. Without taking into account the type 1 diabetes status of mothers, both delivery mode and intrapartum antibiotic prophylaxis were found to have an influence on neonatal microbiota composition (both p=0.001). In the logistic regression analysis involving all confounding variables, neonatal ear-skin microbiome variation was explained by maternal type 1 diabetes status (p=0.020) and small for gestational age birthweight (p=0.050). Moreover, in women with type 1 diabetes, a relationship was found between HbA1c levels >55 mmol/mol (>7.2%) measured in the first trimester of pregnancy and neonatal ear-skin microbiota composition (p=0.008). In the PICRUSt (Phylogenetic Investigation of Communities by Reconstruction of Unobserved States) assessment, pathways concerning carbohydrate biosynthesis were predicted as key elements of the microbial functional profiles dysregulated in type 1 diabetes. Additionally, in SourceTracker analysis, we found that, on average, 81.0% of neonatal microbiota was attributed to maternal sources. An increase in the contribution of maternal rectum microbiota and decrease in the contribution of maternal cervix microbiota were found in ear-skin samples of vaginally delivered neonates of mothers with type 1 diabetes compared with neonates born to control mothers (83.2% vs 59.5% and 0.7% vs 5.2%, respectively). CONCLUSIONS/INTERPRETATION: These findings indicate that, in addition to maternal type 1 diabetes, glycaemic dysregulation before/in the first trimester of pregnancy, mode of delivery and intrapartum antibiotic prophylaxis may contribute to the inoculation and formation of the neonatal microbiomes. DATA AVAILABILITY: The BioProject (PRJNA961636) and associated SRA metadata are available at http://www.ncbi.nlm.nih.gov/bioproject/961636 . Processed data on probiotic supplementation and the PICRUSt analysis are available in the Mendeley Data Repository ( https://doi.org/10.17632/g68rwnnrfk.1 ).

Glycaemic control is still central in the hierarchy of priorities in type 2 diabetes management.

A panel of primary care and diabetes specialists conducted focused literature searches on the current role of glycaemic control in the management of type 2 diabetes and revisited the evolution of evidence supporting the importance of early and intensive blood glucose control as a central strategy to reduce the risk of adverse long-term outcomes. The optimal approach to type 2 diabetes management has evolved over time as the evidence base has expanded from data from trials that established the role of optimising glycaemic control to recent data from cardiovascular outcomes trials (CVOTs) demonstrating organ-protective effects of newer glucose-lowering drugs (GLDs). The results from these CVOTs were derived mainly from people with type 2 diabetes and prior cardiovascular and kidney disease or multiple risk factors. In more recent years, earlier diagnosis in high-risk individuals has contributed to the large proportion of people with type 2 diabetes who do not have complications. In these individuals, a legacy effect of early and optimal control of blood glucose and cardiometabolic risk factors has been proven to reduce cardiovascular and kidney disease events and all-cause mortality. As there is a lack of RCTs investigating the potential synergistic effects of intensive glucose control and organ-protective effects of newer GLDs, this article re-evaluates the evolution of the scientific evidence and highlights the importance of integrating glycaemic control as a pivotal early therapeutic goal in most people with type 2 diabetes, while targeting existing cardiovascular and kidney disease. We also emphasise the importance of implementing multifactorial management using a multidisciplinary approach to facilitate regular review, patient empowerment and the possibility of tailoring interventions to account for the heterogeneity of type 2 diabetes.

HbA1c variability is independently associated with progression of diabetic kidney disease in an urban multi-ethnic cohort of people with type 1 diabetes.

AIMS/HYPOTHESIS: The role of HbA1c variability in the progression of diabetic kidney disease is unclear, with most studies to date performed in White populations and limited data on its role in predicting advanced kidney outcomes. Our aim was to evaluate if long-term intra-individual HbA1c variability is a risk factor for kidney disease progression (defined as an eGFR decline of ≥50% from baseline with a final eGFR of <30 ml/min per 1.73 m2) in an ethnically heterogeneous cohort of people with type 1 diabetes with a preserved eGFR ≥45 ml/min per 1.73 m2 at baseline. METHODS: Electronic health record data from people attending outpatient clinics between 2004 and 2018 in two large university hospitals in London were collected. HbA1c variability was assessed using three distinct methods: (1) SD of HbA1c (SD-HbA1c); (2) visit-adjusted SD (adj-HbA1c): SD-HbA1c/√n/(n-1), where n is the number of HbA1c measurements per participant; and (3) CV (CV-HbA1c): SD-HbA1c/mean-HbA1c. All participants had six or more follow-up HbA1c measurements. The eGFR was measured using the Chronic Kidney Disease Epidemiology Collaboration equation and clinical/biochemical results from routine care were extracted from electronic health records. RESULTS: In total, 3466 participants (50% female, 78% White, 13% African Caribbean, 3% Asian and 6% of mixed heritage or self-reporting as 'other') were followed for a median (IQR) of 8.2 (4.2-11.6) years. Of this cohort, 249 (7%) showed kidney disease progression. Higher HbA1c variability was independently associated with a higher risk of kidney disease progression, with HRs (95% CIs) of 7.76 (4.54, 13.26), 2.62 (1.75, 3.94) and 5.46 (3.40, 8.79) (lowest vs highest HbA1c variability quartile) for methods 1-3, respectively. Increasing age, baseline HbA1c, systolic BP and urinary albumin/creatinine ratio were also associated with kidney disease progression (p<0.05 for all). African Caribbean ethnicity was associated with an increased risk of kidney disease progression (HR [95% CI] 1.47 [1.09, 1.98], 1.76 [1.32, 2.36] and 1.57 [1.17, 2.12] for methods 1-3, respectively) and this effect was independent of glycaemic variability and other traditional risk factors. CONCLUSIONS/INTERPRETATION: We observed an independent association between HbA1c variability, evaluated using three distinct methods, and significant kidney disease progression in a multi-ethnic type 1 diabetes cohort. Further studies are needed to elucidate the mechanisms that may explain our results and evaluate if HbA1c variability is a modifiable risk factor for preventing diabetic kidney disease progression.

Autoimmune comorbidity in type 1 diabetes and its association with metabolic control and mortality risk in young people: a population-based study.

AIMS/HYPOTHESIS: This register-based study aimed to describe autoimmune comorbidity in children and young adults from type 1 diabetes onset, and to investigate whether such comorbidity was associated with a difference in HbA1c or mortality risk compared with children/young adults with type 1 diabetes without autoimmune comorbidity. METHODS: A total of 15,188 individuals from the Swedish National Diabetes Register, registered with type 1 diabetes before 18 years of age between 2000 and 2019, were included. Five randomly selected control individuals from the Swedish population (Statistics Sweden) were matched to each individual with type 1 diabetes (n=74,210 [346 individuals with type 1 diabetes were not found in the Statistics Sweden register at the date of type 1 diabetes diagnosis, so could not be matched to control individuals]). The National Patient Register was used to attain ICD-10 codes on autoimmune diseases and the Cause of Death Register was used to identify deceased individuals. RESULTS: In the total type 1 diabetes cohort, mean±SD age at onset of type 1 diabetes was 9.5±4.4 years and mean disease duration at end of follow-up was 8.8±5.7 years. Of the individuals with type 1 diabetes, 19.2% were diagnosed with at least one autoimmune disease vs 4.0% of the control group. The HRs for comorbidities within 19 years from onset of type 1 diabetes were 11.6 (95% CI 10.6, 12.6) for coeliac disease, 10.6 (95% CI 9.6, 11.8) for thyroid disease, 1.3 (95% CI 1.1, 1.6) for psoriasis, 4.1 (95% CI 3.2, 5.3) for vitiligo, 1.7 (95% CI 1.4, 2.2) for rheumatic joint disease, 1.0 (95% CI 0.8, 1.3) for inflammatory bowel disease, 1.0 (95% CI 0.7, 1.2) for systemic connective tissue disorder, 1.4 (95% CI 1.1, 1.9) for uveitis, 18.3 (95% CI 8.4, 40.0) for Addison's disease, 1.8 (95% CI 0.9, 3.6) for multiple sclerosis, 3.7 (95% CI 1.6, 8.7) for inflammatory liver disease and 19.6 (95% CI 4.2, 92.3) for atrophic gastritis. Autoimmune disease in addition to type 1 diabetes had no statistically significant effect on HbA1c or mortality risk. CONCLUSIONS/INTERPRETATION: To our knowledge, this is the first comprehensive study where young individuals with type 1 diabetes were followed regarding development of a wide spectrum of autoimmune diseases, from onset of type 1 diabetes. In this nationwide and population-based study, there was already a high prevalence of autoimmune diseases in childhood, especially coeliac and thyroid disease. The presence of autoimmune comorbidity did not have a statistically significant effect on metabolic control or mortality risk.

Role of human plasma metabolites in prediabetes and type 2 diabetes from the IMI-DIRECT study.

AIMS/HYPOTHESIS: Type 2 diabetes is a chronic condition that is caused by hyperglycaemia. Our aim was to characterise the metabolomics to find their association with the glycaemic spectrum and find a causal relationship between metabolites and type 2 diabetes. METHODS: As part of the Innovative Medicines Initiative - Diabetes Research on Patient Stratification (IMI-DIRECT) consortium, 3000 plasma samples were measured with the Biocrates AbsoluteIDQ p150 Kit and Metabolon analytics. A total of 911 metabolites (132 targeted metabolomics, 779 untargeted metabolomics) passed the quality control. Multivariable linear and logistic regression analysis estimates were calculated from the concentration/peak areas of each metabolite as an explanatory variable and the glycaemic status as a dependent variable. This analysis was adjusted for age, sex, BMI, study centre in the basic model, and additionally for alcohol, smoking, BP, fasting HDL-cholesterol and fasting triacylglycerol in the full model. Statistical significance was Bonferroni corrected throughout. Beyond associations, we investigated the mediation effect and causal effects for which causal mediation test and two-sample Mendelian randomisation (2SMR) methods were used, respectively. RESULTS: In the targeted metabolomics, we observed four (15), 34 (99) and 50 (108) metabolites (number of metabolites observed in untargeted metabolomics appear in parentheses) that were significantly different when comparing normal glucose regulation vs impaired glucose regulation/prediabetes, normal glucose regulation vs type 2 diabetes, and impaired glucose regulation vs type 2 diabetes, respectively. Significant metabolites were mainly branched-chain amino acids (BCAAs), with some derivatised BCAAs, lipids, xenobiotics and a few unknowns. Metabolites such as lysophosphatidylcholine a C17:0, sum of hexoses, amino acids from BCAA metabolism (including leucine, isoleucine, valine, N-lactoylvaline, N-lactoylleucine and formiminoglutamate) and lactate, as well as an unknown metabolite (X-24295), were associated with HbA1c progression rate and were significant mediators of type 2 diabetes from baseline to 18 and 48 months of follow-up. 2SMR was used to estimate the causal effect of an exposure on an outcome using summary statistics from UK Biobank genome-wide association studies. We found that type 2 diabetes had a causal effect on the levels of three metabolites (hexose, glutamate and caproate [fatty acid (FA) 6:0]), whereas lipids such as specific phosphatidylcholines (PCs) (namely PC aa C36:2, PC aa C36:5, PC ae C36:3 and PC ae C34:3) as well as the two n-3 fatty acids stearidonate (18:4n3) and docosapentaenoate (22:5n3) potentially had a causal role in the development of type 2 diabetes. CONCLUSIONS/INTERPRETATION: Our findings identify known BCAAs and lipids, along with novel N-lactoyl-amino acid metabolites, significantly associated with prediabetes and diabetes, that mediate the effect of diabetes from baseline to follow-up (18 and 48 months). Causal inference using genetic variants shows the role of lipid metabolism and n-3 fatty acids as being causal for metabolite-to-type 2 diabetes whereas the sum of hexoses is causal for type 2 diabetes-to-metabolite. Identified metabolite markers are useful for stratifying individuals based on their risk progression and should enable targeted interventions.

Integration of a fasting-mimicking diet programme in primary care for type 2 diabetes reduces the need for medication and improves glycaemic control: a 12-month randomised controlled trial.

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 HbA1c levels after 12 months. Moreover, changes in use of glucose-lowering medication and/or HbA1c 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), HbA1c (-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 HbA1c 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.

Association between prediabetes and breast cancer: a comprehensive meta-analysis.

BACKGROUND: Breast cancer accounts for up to 30% of cancer cases in women in the US. Diabetes mellitus has been recognized as a risk factor for breast cancer. Some studies have suggested that prediabetes may also be associated with breast cancer whereas other studies have shown no or an inverse association; thus, we conducted a meta-analysis to assess the risk of breast cancer in prediabetes. METHODS: We searched PubMed/Medline, EMBASE, Google Scholar, and Scopus to identify studies that reported breast cancer risks in patients having prediabetes compared to normoglycemic patients. Binary random-effects model was used to calculate a pooled odds ratio (OR) with 95% confidence intervals. I2 statistics were used to assess heterogeneity. Leave-one-out sensitivity analysis and subgroup analyses were performed. RESULTS: We analyzed 7 studies with 24,586 prediabetic and 224,314 normoglycemic individuals (783 and 5739 breast cancer cases, respectively). Unadjusted odds ratio (OR) for breast cancer was 1.45 (95% CI = 1.14, 1.83); adjusted OR was 1.19 (95% CI = 1.07, 1.34) in prediabetes. Subgroup analysis revealed a higher breast cancer risk in individuals aged less than 60 years (OR = 1.86, 95% CI = 1.39, 2.49) than in those aged 60 years or more (OR = 1.07, 95% CI = 0.97, 1.18). Subgroup analysis by median follow-up length indicated a higher risk of breast cancer for follow-ups of less than or equal to 2 years (OR = 2.34, 95% CI = 1.85, 2.95) than in those of over 10 years (OR = 1.1, 95% CI = 0.99, 1.23) and 6 to 10 years (OR = 1.03, 95% CI = 0.88, 1.21). CONCLUSIONS: In conclusion, individuals with prediabetes have higher risk of developing breast cancer than those with normoglycemia, especially younger prediabetes patients. These individuals may benefit from early identification, monitoring, and interventions to reverse prediabetes.

The impact of major depressive disorder on glycaemic control in type 2 diabetes: a longitudinal cohort study using UK Biobank primary care records.

BACKGROUND: This study evaluates longitudinal associations between glycaemic control, measured by mean and within-patient variability of glycated haemaglobin (HbA1c) levels, and major depressive disorder (MDD) in individuals with type 2 diabetes (T2D), focusing on the timings of these diagnoses. METHODS: In UK Biobank, T2D was defined using self-report and linked health outcome data, then validated using polygenic scores. Repeated HbA1c measurements (mmol/mol) over the 10 years following T2D diagnosis were outcomes in mixed effects models, with disease duration included using restricted cubic splines. Four MDD exposures were considered: MDD diagnosis prior to T2D diagnosis (pre-T2D MDD), time between pre-T2D MDD diagnosis and T2D, new MDD diagnosis during follow-up (post-T2D MDD) and time since post-T2D MDD diagnosis. Models with and without covariate adjustment were considered. RESULTS: T2D diagnostic criteria were robustly associated with T2D polygenic scores. In 11,837 T2D cases (6.9 years median follow-up), pre-T2D MDD was associated with a 0.92 increase in HbA1c (95% CI: [0.00, 1.84]), but earlier pre-T2D MDD diagnosis correlated with lower HbA1c. These pre-T2D MDD effects became non-significant after covariate adjustment. Post-T2D MDD individuals demonstrated increasing HbA1c with years since MDD diagnosis ( ß = 0.51 , 95% CI: [0.17, 0.86]). Retrospectively, across study follow-up, within-patient variability in HbA1c was 1.16 (95% CI: 1.13-1.19) times higher in post-T2D MDD individuals. CONCLUSIONS: The timing of MDD diagnosis is important for understanding glycaemic control in T2D. Poorer control was observed in MDD diagnosed post-T2D, highlighting the importance of depression screening in T2D, and closer monitoring for individuals who develop MDD after T2D.

HbA1c-dependent projection of long-term renal outcomes.

BACKGROUND: Diabetes mellitus is a major risk factor for the development of chronic kidney disease (CKD). There is limited data addressing the value of glycated hemoglobin (HbA1c) to predict renal outcomes independent of diabetes status. METHODS: This single-center retrospective observational study presents data of 19,285 subjects, irrespective of initial CKD or diabetes status. The primary endpoint was defined as the time to manifestation of moderate CKD (estimated glomerular filtration rate [eGFR] <60 mL/min/1.73 m2 ) in subjects with eGFR ≥60 mL/min/1.73 m2 at baseline. The secondary endpoint was defined as time to progression of CKD (eGFR <30 mL/min/1.73 m2 ) in subjects with eGFR 30-60 mL/min/1.73 m2 . Multivariate time-to-event and logistic regression models were applied to estimate the influences of HbA1c, sex, age, eGFR, triglycerides, and cholesterol on both endpoints. RESULTS: Lowest baseline HbA1c levels were associated with the slowest decline of kidney function (median time to manifestation of moderate CKD for HbA1c <5.7%: 15.9 years [95% confidence interval (CI): 15.2-16.7]; for HbA1c 5.7%-6.5%: 14.5 years [95% CI: 14.0-15.1]; for HbA1c 6.5%-8.5%: 11.1 years [95% CI: 10.4-11.7]; for HbA1c >8.5%: 8.3 years [95% CI: 7.8-9.2]; p < 0.001). Similar results were observed for the secondary endpoint. Covariate-adjusted time-to-event analysis demonstrated an almost linear correlation between continuous baseline HbA1c levels and the probabilities of reaching both endpoints. CONCLUSIONS: HbA1c levels are a strong predictor for eGFR decline, irrespective of diabetes status or CKD stage, demonstrating a tight concentration-dependent relationship. This association becomes apparent in the prediabetic HbA1c range and remains constant over the entire HbA1c spectrum.

A Mutagen Acts as a Potent Reducing Agent of Glycated Hemoglobin: a Combined Ultrafast Electron Transfer and Computational Studies.

Glycated hemoglobin (GHb) found in mammals undergoes irreversible damage when exposed to external redox agents, which is much more vulnerable than its normal counterpart hemoglobin (Hb). Besides the oxygen regulation throughout the body, Hb plays a vital role in balancing immunological health and the redox cycle. Photoinduced ultra-fast electron transfer phenomena actively participate in regulation of various kind of homeostasis involved in such biomacromolecules. In the present study we have shown that a well-known mutagen Ethidium Bromide (EtBr) reduces GHb in femtosecond time scale (efficiently) upon photoexcitation after efficient recognition in the biomolecule. We have performed similar experiment by colocalizing EtBr and Iron (Fe(III)) on the micellar surface as Hb mimic in order to study the excited state EtBr dynamics to rationalize the time scale obtained from EtBr in GHb and Hb. While other experimental techniques including Dynamic Light Scattering (DLS), Zeta potential, absorbance and emission spectroscopy have been employed for the confirmation of structural perturbation of GHb compared to Hb, a detailed computational studies involving molecular docking and density functional theory (DFT) have been employed for the explanation of the experimental observations.

HIV and type 2 diabetes: An evolving story.

INTRODUCTION: Diabetes is widely reported to be more common in people living with HIV (PLWH). Much of the data supporting this originated during the earlier HIV era. The perceived increased risk of type 2 diabetes is reflected in HIV clinical guidelines that recommend screening for diabetes in PLWH on anti-retroviral therapy (ART). However, international HIV clinical guidelines do not agree on the best marker of glycaemia to screen for diabetes. This stems from studies that suggest HbA1c underestimates glycaemia in PLWH. METHODS: Within this review we summarise the literature surrounding the association of HIV and type 2 diabetes and how this has changed over time. We also present the evidence on HbA1c discrepancy in PLWH. CONCLUSION: We suggest there is no basis to any international guidelines to restrict HbA1c based on HIV serostatus. We recommend, using the current evidence, that PLWH should be screened annually for diabetes in keeping with country specific guidance. Finally, we suggest future work to elucidate phenotype and natural history of type 2 diabetes in PLWH across all populations.

Glycemic Trends in Patients with Thyroid Eye Disease Treated with Teprotumumab in 3 Clinical Trials.

PURPOSE: Assess incidence, severity, and glucose excursion outcomes in thyroid eye disease (TED) patients receiving the insulin-like growth factor-1 receptor inhibitor teprotumumab from 3 clinical trials. DESIGN: Analysis of pooled glycemic data over time. PARTICIPANTS: Eighty-four teprotumumab- and 86 placebo-treated active TED patients from the phase 2 and phase 3 (OPTIC) controlled clinical trials and 51 teprotumumab-treated patients from the OPTIC extension (OPTIC-X) trial. METHODS: Eight intravenous infusions were given over 21 weeks. Phase 2 serum glucose was measured at weeks 1, 4, 15, and 21, with fasting measurements at weeks 1 and 4. Serum glucose was measured at each study visit in OPTIC and OPTIC-X, with fasting measurements at weeks 1 and 4 (in patients without diabetes) or all visits (in patients with diabetes). In all studies, hemoglobin A1c (HbA1c) was measured at baseline, 12, and 24 weeks plus weeks 36 and 48 in OPTIC-X. MAIN OUTCOME MEASURES: Serum glucose and HbA1c. RESULTS: In the phase 2 and 3 studies, 9 hyperglycemic episodes occurred in 8 teprotumumab patients; mean HbA1c level increased 0.22% from baseline to week 24 (to 5.8%; range, 5.0%-7.9%) versus 0.04% in patients receiving the placebo (to 5.6%; range, 4.6%-8.1%). At study end, 78% (59/76) of teprotumumab patients and 87% (67/77) of patients receiving placebo had normoglycemic findings. Normoglycemia was maintained in 84% (57/68) of patients receiving teprotumumab and 93% (64/69) of patients receiving placebo. Among baseline prediabetic patients, 43% (3/7) remained prediabetic in both groups, and 29% (2/7) of teprotumumab patients and 14% (1/7) of patients receiving placebo had diabetic findings at week 24. OPTIC-X patients trended toward increased fasting glucose and HbA1c whether initially treated or retreated with teprotumumab. Fasting glucose commonly rose after 2 or 3 infusions and stabilized thereafter. Most hyperglycemic incidents occurred in patients with baseline prediabetes/diabetes but were controlled with medication. No evidence was found for progression or increased incidence of hyperglycemia with subsequent doses. CONCLUSIONS: Serious glycemic excursions are uncommon in patients with normoglycemia before teprotumumab therapy. Patients with controlled diabetes or impaired glucose tolerance can be treated safely if baseline screening, regular monitoring of glycemic control, and timely treatment of hyperglycemia are practiced. FINANCIAL DISCLOSURE(S): Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

BMI variability and cardiovascular outcomes within clinical trial and real-world environments in type 2 diabetes: an IMI2 SOPHIA study.

BACKGROUND: BMI variability has been associated with increased cardiovascular disease risk in individuals with type 2 diabetes, however comparison between clinical studies and real-world observational evidence has been lacking. Furthermore, it is not known whether BMI variability has an effect independent of HbA1c variability. METHODS: We investigated the association between BMI variability and 3P-MACE risk in the Harmony Outcomes trial (n = 9198), and further analysed placebo arms of REWIND (n = 4440) and EMPA-REG OUTCOME (n = 2333) trials, followed by real-world data from the Tayside Bioresource (n = 6980) using Cox regression modelling. BMI variability was determined using average successive variability (ASV), with first major adverse cardiovascular event of non-fatal stroke, non-fatal myocardial infarction, and cardiovascular death (3P-MACE) as the primary outcome. RESULTS: After adjusting for cardiovascular risk factors, a + 1 SD increase in BMI variability was associated with increased 3P-MACE risk in Harmony Outcomes (HR 1.12, 95% CI 1.08-1.17, P < 0.001). The most variable quartile of participants experienced an 87% higher risk of 3P-MACE (P < 0.001) relative to the least variable. Similar associations were found in REWIND and Tayside Bioresource. Further analyses in the EMPA-REG OUTCOME trial did not replicate this association. BMI variability's impact on 3P-MACE risk was independent of HbA1c variability. CONCLUSIONS: In individuals with type 2 diabetes, increased BMI variability was found to be an independent risk factor for 3P-MACE across cardiovascular outcome trials and real-world datasets. Future research should attempt to establish a causal relationship between BMI variability and cardiovascular outcomes.

Evidence of a bi-directional relationship between heart failure and diabetes: a strategy for the detection of glucose abnormalities and diabetes prevention in patients with heart failure.

Prevalence of heart failure (HF) and diabetes are markedly increasing globally. In a population of HF patients, approximately 40% have diabetes which is associated with a more severe HF, poorer cardiovascular outcomes and higher hospitalization rates for HF than HF patients without diabetes. Similar trends were shown in HF patients with prediabetes. In addition, the association between HF and renal function decline was demonstrated in patients with or without diabetes. However, the exact prevalence of dysglycemia in HF patients requires further investigation aiming to clarify the most accurate test to detect dysglycemia in this population. The relationship between HF and diabetes is complex and probably bidirectional. In one way, patients with diabetes have a more than two-fold risk of developing incident HF with reduced or preserved ejection fraction than those without diabetes. In the other way, patients with HF, when compared with those without HF, show an increased risk for the onset of diabetes due to several mechanisms including insulin resistance (IR), which makes HF emerging as a precursor for diabetes development. This article provides epidemiological evidence of undetected dysglycemia (prediabetes or diabetes) in HF patients and reviews the pathophysiological mechanisms which favor the development of IR and the risks associated with these disorders in HF patients. This review also offers a discussion of various strategies for the prevention of diabetes in HF patients, based first on fasting plasma glucose and HbA1c measurement and if normal on an oral glucose tolerance test as diagnostic tools for prediabetes and unknown diabetes that should be performed more extensively in those patients. It discusses the implementation of diabetes prevention measures and well-structured management programs for HF patients who are generally overweight or obese, as well as current pharmacotherapeutic options for prediabetes, including sodium-glucose cotransporter 2 inhibitors which are among the pillars of HF treatment and which recently showed a benefit in the reduction of incident diabetes in HF patients. Thus, there is an urgent need of routine screening for dysglycemia in all HF patients, which should contribute to reduce the incidence of diabetes and to treat earlier diabetes when already present.

Predictors of efficacy of Sodium-GLucose Transporter-2 inhibitors and Glucagon-Like Peptide 1 receptor agonists: A retrospective cohort study.

AIMS: The aim of the present study was to verify predictors of HbA1c reduction with Sodium-GLucose Transporter-2 (SGLT2) inhibitors and Glucagon-Like Peptide 1 (GLP1) receptor agonists in routine clinical practice. MATERIALS AND METHODS: A retrospective cohort study was performed, enrolling patients with type 2 diabetes aged ≥18 years who received a prescription of an SGLT2 inhibitor or a long-acting GLP1 receptor agonist with at least 6 months of persistence in therapy. Therapeutic success was defined as HbA1c reduction >10 mmol/mol or attainment of the recommended HbA1c target. RESULTS: Out of 236 patients receiving SGLT2 inhibitors, 148 were categorised as successes: successes had a mean lower age and higher estimated Glomerular Filtration Rate than failures, but only age retained statistical significance at multivariate analysis (Odds Ratio with 95% confidence interval: 0.94 [0.91-0.98], p = 0.006). In the GLP1 receptor agonists cohort (N = 214) there were 146 successes, showing a significantly shorter duration of diabetes even after adjusting for age, and baseline HbA1c (HR 0.96 [0.91-0.99], p = 0.02). CONCLUSIONS: The present study is a preliminary exploration of factors associated with HbA1c response to SGLT2 inhibitors and GLP1 receptor agonists. Differences in predictors of HbA1c changes across different classes of drugs could be useful in identifying the most suitable drug in individual patients. SGLT2 inhibitors seem to be associated with a greater reduction of HbA1c in younger subjects, and GLP1 agonists in those with a shorter duration of diabetes.

HbA1c and the risk of developing peripheral neuropathy in childhood-onset type 1 diabetes: A follow-up study over 3 decades.

AIMS: We have evaluated long-term weighted mean HbA1c (wHbA1c), HbA1c variability, diabetes duration, and lipid profiles in relation to the development of diabetic peripheral neuropathy (DPN), nephropathy, and retinopathy in childhood-onset type 1 diabetes. MATERIALS AND METHODS: In a longitudinal cohort study, 49 patients (21 women) with childhood-onset type 1 diabetes were investigated with neurophysiological measurements, blood tests, and clinical examinations after a diabetes duration of 7.7 (±3.3) years (baseline) and followed with repeated examinations for 30.6 (±5.2) years. We calculated wHbA1c by integrating the area under all HbA1c values since the diabetes diagnosis. Lipid profiles were analysed in relation to the presence of DPN. Long-term fluctuations of HbA1c variability were computed as the standard deviation of all HbA1c measurements. Data regarding the presence of other diabetes complications were retrieved from medical records. RESULTS: In this follow-up study, 51% (25/49) of the patients fulfilled electrophysiological criteria for DPN. In nerve conduction studies, there was a deterioration in the amplitudes and conduction velocities for the median, peroneal, and sural nerves over time. Patients with DPN had a longer duration of diabetes, higher wHbA1c, and increased HbA1c variability. The lowest wHbA1c value associated with the development of DPN was 62 mmol/mol (7.8%). The presence of albuminuria and retinopathy was positively correlated with the presence of neuropathy. CONCLUSIONS: More than half of the patients had developed DPN after 30 years. None of the patients who developed DPN had a wHbA1c of less than 62 mmol/mol (7.8%).

Circadian alignment of food intake and glycaemic control by time-restricted eating: A systematic review and meta-analysis.

Daily rhythms of metabolic function are supported by molecular circadian clock systems that are strongly regulated by feeding and fasting. Intermittent fasting diets have been associated with weight loss and improved metabolism. However, the effects of time-restricted eating (TRE) on glycemic parameters are still under debate. In this review, we aim to systematically analyze the effects of TRE on glycemic parameters. We searched on PubMed, EMBASE, and the Cochrane Library for controlled studies in which subjects followed TRE for at least 4 weeks. 20 studies were included in the qualitative systematic review, and 18 studies (n = 1169 subjects) were included in the meta-analysis. Overall, TRE had no significant effect on fasting glucose (Hedges's g = -0.08; 95% CI:-0.31,0.16; p = 0.52), but it did reduce HbA1c levels (Hedges's g = -0.27; 95% CI: -0.47, -0.06; p = 0.01). TRE significantly reduced fasting insulin (Hedges's g = -0.40; 95% CI: -0.73,-0.08; p = 0.01) and showed a tendency to decrease HOMA-IR (Hedges's g = -0.32; 95% CI:-0.66,0.02; p = 0.06). Interestingly, a cumulative analysis showed that the beneficial effects of TRE regarding glucose levels were less apparent as studies with later TRE windows (lTRE) were being included. Indeed, a subgroup analysis of the early TRE (eTRE) studies revealed that fasting glucose was significantly reduced by eTRE (Hedges's g = -0.38; 95% CI:-0.62, -0.14; p < 0.01). Our meta-analysis suggests that TRE can reduce HbA1c and insulin levels, and that timing of food intake is a crucial factor in the metabolic benefit of TRE, as only eTRE is capable of reducing fasting glucose levels in subjects with overweight or obesity.PROSPERO registration number CRD42023405946.

Vitamin D supplementation modulates glycated hemoglobin (HBA1c) in diabetes mellitus.

Diabetes is a metabolic illness that increases protein glycosylation in hyperglycemic conditions, which can have an impact on almost every organ system in the body. The role of vitamin D in the etiology of diabetes under RAGE (receptor for advanced glycation end products) stress has recently received some attention on a global scale. Vitamin D's other skeletal benefits have generated a great deal of research. Vitamin D's function in the development of type 1 and type 2 diabetes is supported by the discovery of 1,25 (OH)2D3 and 1-Alpha-Hydroylase expression in immune cells, pancreatic beta cells, and several other organs besides the bone system. A lower HBA1c level, metabolic syndrome, and diabetes mellitus all seems to be associated with vitamin D insufficiency. Most of the cross-sectional and prospective observational studies that were used to gather human evidence revealed an inverse relationship between vitamin D level and the prevalence or incidence of elevated HBA1c in type 2 diabetes. Several trials have reported on the impact of vitamin D supplementation for glycemia or incidence of type 2 diabetes, with varying degrees of success. The current paper examines the available data for a relationship between vitamin D supplementation and HBA1c level in diabetes and discusses the biological plausibility of such a relationship.