Acta Diabetologica最新文献

Aims: Two prerequisites must be met for the precision treatment approach to be beneficial for treated individuals. First, there must be treatment heterogeneity; second, in case of treatment heterogeneity, clinical predictors to identify people who would benefit from one treatment more than from others must be available. There is an established meta-regression approach to assess these two prerequisites that relies on measuring the variability of a clinical outcome after treatment in placebo-controlled randomised trials. We recently applied this approach to the treatment of type 2 diabetes for the clinical outcomes of glycaemic control and body weight and repeat it for the clinical outcome of all-cause mortality.

Methods: We performed a meta-regression analysis using digitalized individual participant information on time to death from 10 large cardiovascular outcome trials (7563 deaths from 99,746 participants) on DPP-4 inhibitors, GLP-1 receptor agonists, and SGLT-2 inhibitors with respect to the variability of all-cause mortality and its potential predictors after treatment.

Results: The adjusted difference in log(SD) values of time to death between the verum and placebo arms was -0.036 (95%-CI: -0.059; -0.013), showing larger variability of time to death in the placebo arms. No clinical predictors were found to explain treatment heterogeneity.

Conclusions: This analysis suggests that the potential of the precision treatment approach in type 2 diabetes is low, at least with regard to improvement of all-cause mortality in population with high cardiovascular risk. This extends our previous findings for the clinical outcomes of glycaemic control and body weight.

Background: Cluster analysis provides an effective approach in stratifying prediabetes into different subgroups; however, the association of the cluster-based subgroups with prediabetes progression and regression has not been investigated. We aimed to address this issue in a Chinese population.

Methods: A total of 4,128 participants with prediabetes were included to generate cluster-based subgroups of prediabetes based on age, body mass index (BMI), triglyceride-and-glucose (TyG) index, and hemoglobin A1c (HbA1c), using a k-means clustering model. Among them, 1,554 participants were followed-up for about three years to ascertain prediabetes progression and regression. Their association with the cluster-based subgroups of prediabetes was assessed using multinomial logistic regression analyses.

Results: Three clusters of prediabetes were identified among the 4,128 participants, with cluster 0, 1 and 2 accounting for 28.0%, 31.4% and 40.6%, respectively. Participants with prediabetes were featured by the youngest age and the lowest HbA1c in cluster 0, the highest BMI and TyG index in cluster 1, and the oldest age and the lowest BMI in cluster 2. After multivariable-adjustment, both cluster 1 [odds ratio (OR) 3.31, 95% confidence interval (CI): 2.01-5.44] and cluster 2 (OR 2.58, 95% CI: 1.60-4.18) were associated with increased odds of progression to diabetes when compared with cluster 0. They were also associated with decreased odds of regression to normoglycemia (OR 0.54, and 0.56, respectively).

Conclusions: Prediabetes participants featured by older age, higher degree of insulin resistance, higher BMI and worse glycemic condition had higher probability of progression to diabetes but lower chance of regression to normoglycemia.

Background: Ectodysplasin A (EDA) is a novel hepatokine that plays a role in multiple metabolic-related diseases. The aim of this study was to investigate the association between serum EDA levels and metabolic syndrome (MetS).

Methods: A total of 348 subjects, 258 patients with MetS and 90 healthy controls were enrolled. Serum EDA levels were measured using an enzyme-linked immunosorbent assay (ELISA). The correlation between EDA and various metabolic components was assessed.

Results: The serum EDA levels of subjects with metabolic syndrome (MetS) were significantly higher than those without [323.78 (259.68-400.74) vs. 254.82 (182.68-347.88) pg/mL, P < 0.001]. The serum EDA level increases with the increase in metabolic score. The linear regression model revealed that age, blood pressure, fasting insulin (FIns), high-density lipoprotein cholesterol (HDL-C), and HOMA-IR were independent factors influencing EDA levels. Furthermore, in the logistic regression model, subjects in the highest tertile of EDA had a significantly higher risk of MetS, higher blood pressure, hyperglycemia, and lower HDL-C compared to those in the lowest tertile. This conclusion remained valid after adjusting for multiple confounding factors.

Conclusions: The research results for the first time found that the circulating EDA levels in patients with metabolic syndrome were significantly elevated and associated with hypertension, hyperglycemia, lower HDL-C, and insulin resistance risk, indicating that EDA may play a role in the occurrence of metabolic syndrome and may be a potential therapeutic target for metabolic syndrome.

Diabetic neuropathy is the most prevalent diabetes-associated complication that negatively impacts the quality of life of the patients. The extensive complications of diabetic peoples in the world are the leading cause of neuropathic pain, and over-activation of different biochemical signalling process induces the pathogenic progression and are also corresponding the epidemic painful symptom of diabetic neuropathy. The main prevalent abnormality is neuropathy, which further causing distal symmetric polyneuropathy and focal neuropathy. The exact pathological complication of diabetes associated neuropathic algesia is still unclear, but the alteration in micro-angiopathy associated nerve fibre loss, hyper polyol formation, MAPK signalling, WNT signalling, tau-derived insulin signalling processes are well known. Furthermore, the post-translational modification of different ion channels, oxidative and nitrosative stress, brain plasticity and microvascular changes can contributes the development of neuropathic pain. However, in the current review we discussed about these pathogenic development of neuropathic pain from the genesis of diabetes, and how diabetes affects the physiological and psychological health, and quality of life of the patients. Furthermore, the treatment of diabetic neuropathy with conventional monotherapy and emerging therapy are discussed. In addition, the treatment with phytochemical constituents their mechanisms and clinical evidences are also reported. The future investigation is required on pathological alteration occurs in neuropathic individuals, and on molecular mechanisms as well as the adverse effect of phytochemicals to determine all aspects of neuropathic algesia including effective treatments, which will prevents the sympathetic pain in patients.

Aim: To compare glycemic control and maternal-fetal outcomes of women with type 1 diabetes (T1D) using Minimed™ 780G (MM780G) with those women using Minimed™ 640G (MM640G) since before pregnancy.

Methods: Multicenter prospective cohort study of pregnant women with T1D in Spain. We evaluated HbA1c, time spent within (TIRp), below (TBRp) and above (TARp) the pregnancy-specific glucose range 3.5-7.8 mmol/L (63-140 mg/dL) and glucose variability (CV).

Results: Sixty-nine women were included (MM780G n = 40). At baseline, MM640G users had higher rates of severe hypoglycemia before pregnancy, without other between-group differences. The MM780G group had higher TIRp and lower TARp, TBRp and CV, but similar HbA1c in the first trimester of gestation. TBRp and CV remained significantly higher in the MM640G group throughout pregnancy. Higher HbA1c was observed in the MM780G group compared to the MM640G (6.28 ± 0.53% [45.1 ± 5.8 mmol/mol] vs. 5.97 ± 0.62 [41.8 ± 6.8], p = 0.003) in the second trimester. There were no differences in the mean change in HbA1c from the first to the third trimester of gestation between groups. MM780G users were more likely to have large-for-gestational-age infants (OR_adjusted 4.85, 95% CI 1.46-16.13, p = 0.010), macrosomia (OR_adjusted 12.17, 95% CI 1.49-99.72, p = 0.020) and cesarean section (OR_adjusted 4.19, 95% CI 1.34-13.11, p = 0.014) than the MM640G group.

Conclusions: Pregestational use of MM780G led to an initial improvement in TIRp, but this was not sustained in the second and third trimesters, with a 4-fold increased risk of delivering a LGA infant and undergoing cesarean section compared to MM640G users.

Background: Diabetic encephalopathy (DE) is one of the most serious complications of diabetes mellitus (DM), and its pathogenesis has not yet been clarified. Th22 cells are a newly discovered class of CD4⁺ T cells that play important roles in inflammatory, autoimmune and infectious diseases. However, it is unclear whether Th22 cells are involved in the pathogenesis of DE.

Methods: We established a T2DM mouse model in vivo and cocultured Th22 cells with microglia under high glucose (HG) conditions in vitro. Cognitive dysfunction was evaluated using the Morris water maze (MWM) test; blood‒brain barrier (BBB) integrity was evaluated using the Evans blue (EB) extravasation assay; Th22 cells and IL-22 receptors were detected by immunofluorescence; and IL-1β, TNF-α, iNOS, CD86, Arg-1, and CD206 protein expression was measured by Western Blot (WB) analysis.

Results: Th22 cells passed through the BBB into the hippocampus and secreted interleukin-22 (IL-22), and the mice subsequently exhibited decreased learning and memory abilities. In the DE model, IL-22 promoted the transformation of homeostatic microglia into reactive microglia as well as the inflammatory response. Additionally, coculture of Th22 cells with BV2 microglia cultured under HG conditions increased the production of proinflammatory cytokines, and the microglia showed reactive changes. Mechanistically, IL-22Rα1 acted as a ligand, and IL-22 bound to IL-22Rα1 on microglia to drive primary microglia-induced inflammatory responses. Interestingly, interleukin-22 binding protein (IL-22BP) directly binds to IL-22Rα1 on microglia to inhibit the proinflammatory effects of IL-22.

Conclusion: Th22 cells secrete IL-22 after passing through the BBB into the hippocampus and promote the transformation of homeostatic microglia into reactive microglia, which induces an inflammatory response, exacerbates learning and memory impairment and cognitive deficits, and contributes to and accelerates the development of DE.

Aims: To investigate possible associations of glucose patterns with outcomes of Corona Virus Disease 19 (COVID-19) using continuous glucose monitoring (CGM) in 43 patients hospitalized for COVID-19 mild-to-moderate pneumonia, regardless of diabetes.

Methods: Prospective observational study conducted during two pandemic waves in 2020-2021. Glucose sensor metrics of 7-day recording were obtained from blinded CGM. Respiratory function was evaluated as arterial partial pressure of oxygen (PaO₂) to fraction of inspired oxygen (FiO₂) ratio (PaO₂:FiO₂).

Results: PaO₂:FiO₂ ratio was positively correlated with time in tight range (TITR) 70-140 (r = 0.49, p < 0.001) and time in range (TIR) 70-180 (r = 0.32, p < 0.05), and negatively correlated with average glucose (r =- 0.31, p < 0.05), coefficient of glucose variation (CV) (r =- 0.47, p < 0.01) and time above range (TAR) > 140 (r =- 0.49, p < 0.001). No relations were observed with HbA1c. Multivariate regression analysis showed that normal respiratory function at time of CGM removal correlated positively with TITR 70-140 mg/dL (p < 0.01), negatively with CV and TAR > 140 mg/dL (both p < 0.05) and not with TIR 70-180 and average glucose.

Conclusions: Lower glucose variability and optimal glucose control, expressed as CV and TITR, are CGM metrics predictive of a better prognosis in COVID-19 patients with pneumonia.

Context: Advanced hybrid closed loop (AHCL) systems currently represent the most advanced modality of insulin therapy.

Aim: To compare the night-time (from 00 to 07 a.m.) effectiveness in achieving recommended glycemic targets of three different AHCL systems in adults with type 1 diabetes (T1D).

Methods: We retrospectively evaluated 55 adults with T1D (mean age 41 ± 16 years, male 40%, diabetes duration 19.4 ± 11.4 years, BMI 24.1 ± 4.1 kg/m²) with similar glycemic control (GMI 7.0-7.4%). Twenty-two participants were using the Minimed 780G system, 18 the Tandem t:slim X2 with Control-IQ system and 15 the DBLG1 system. Continuous glucose monitoring derived metrics and insulin requirement of 14 consecutive nights were analyzed.

Results: All three groups achieved the recommended mean TIR > 70%, mean TBR < 4%, and mean CV < 36% with a similar insulin requirement (Minimed 780G system: TIR 73.9 ± 11.2%, TBR 0.9 ± 1.2%, CV 29 ± 6.7%; Tandem t:slim X2 with Control-IQ system: TIR 74.1 ± 11.1%, TBR 1.1 ± 1.0%, CV 34.5 ± 6.6%; DBLG1 System TIR 71.7 ± 11.3%, TBR 1.4 ± 3.7%, CV 32.4 ± 7.1%). Tight TIR% (70-140 mg/dl) was significantly higher (p < 0.01) in the Tandem t:slim X2 with Control-IQ group (51.5 ± 9.8%) when compared to Minimed 780G group (42.1 ± 13.7%) and DBLG1 System (40.1 ± 10.5%). In all three groups the insulin infusion similarly decreased from midnight to 05.00 am and then increased.

Conclusions: All the three AHCL systems achieved the recommended TIR, TBR and CV without difference in insulin requirement. The Tandem Control-IQ system obtained a higher tight TIR.

Aims: Early in the COVID-19 pandemic, evidence emerged suggesting that people with diabetic retinopathy (DR) or other microvascular diseases had greater risk of severe short-term outcomes. This study evaluated longer-term outcomes, providing more generalisable evidence.

Methods: We identified a cohort of UKBiobank participants with diabetes and retrieved their diagnostic codes for a variety of microvascular diseases, complications of diabetes and systemic comorbidities. We investigated relationships between diagnoses and the study outcome: admission to Critical Care or death from COVID-19, taking age, sex and diabetes duration into account. We tested relationships, adding baseline covariates and weighting diagnostic codes according to their recency prior to COVID-19 diagnosis.

Results: In univariate analyses, DR (OR: 1·519, p = 0·016) and microvascular disease (OR: 2·001, p = 0·000) were associated with greater risk of the outcome. In multivariate analyses, as expected, respiratory disease was most strongly associated with the study outcome, microvascular disease second. Adjusting analyses by number of admissions (general health proxy) and weighted diagnostic coding (comorbidity severity at COVID-19 diagnosis indicator), did not improve predictive power of the model.

Conclusions: The presence of microvascular disease in routinely-collected healthcare data predicts risk of COVID-19 severe outcomes, independently of general health, in a cohort of people with diabetes.