Acta Diabetologica最新文献

Aim: Type 1 diabetes is one of the fastest-growing chronic health conditions. Estimating the incidence rate of childhood type 1 diabetes will allow to aid in adequate planning of health care resources. The study's aim was to assess the incidence rate of type 1 diabetes in children below 15 years of age from Greater Poland (Poland) between 2006 and 2018, and then to compare obtained data to records collected between 1998 and 2003 in pediatric population aged 0-14 years from the same area.

Methods: In this cohort study covering the period from January 1998 to December 2018, data were collected for children and adolescents below 14 years of age with newly diagnosed type 1 diabetes living in Greater Poland. The overall population size was taken from the Statistical Office of Poland. Total, sex-, and age-specific incidence rates per 100,000 person-years were calculated for each calendar year.

Results: Over a 20-year period, the incidence rate of type 1 diabetes in children aged 0-14 years rose around 3.6-fold, from 8.4/100,000 in 1998 to 30.8/100,000 in 2018, with the peak incidence recorded in last year of the study. A clear male predominance of type 1 diabetes was seen in all ages. The rate of type 1 diabetes incidence growth was comparable between all age groups, while the highest incidence rate was mostly observed in children aged 5-9 and 10-14 years.

Conclusions: The incidence of type 1 diabetes in children aged 0-14 years is rapidly increasing in Greater Poland.

Aim: Periodic screening for diabetic retinopathy (DR) is effective for preventing blindness. Artificial intelligence (AI) systems could be useful for increasing the screening of DR in diabetic patients. The aim of this study was to compare the performance of the DAIRET system in detecting DR to that of ophthalmologists in a real-world setting.

Methods: Fundus photography was performed with a nonmydriatic camera in 958 consecutive patients older than 18 years who were affected by diabetes and who were enrolled in the DR screening in the Diabetes and Endocrinology Unit and in the Eye Unit of ULSS8 Berica (Italy) between June 2022 and June 2023. All retinal images were evaluated by DAIRET, which is a machine learning algorithm based on AI. In addition, all the images obtained were analysed by an ophthalmologist who graded the images. The results obtained by DAIRET were compared with those obtained by the ophthalmologist.

Results: We included 958 patients, but only 867 (90.5%) patients had retinal images sufficient for evaluation by a human grader. The sensitivity for detecting cases of moderate DR and above was 1 (100%), and the sensitivity for detecting cases of mild DR was 0.84 ± 0.03. The specificity of detecting the absence of DR was lower (0.59 ± 0.04) because of the high number of false-positives.

Conclusion: DAIRET showed an optimal sensitivity in detecting all cases of referable DR (moderate DR or above) compared with that of a human grader. On the other hand, the specificity of DAIRET was low because of the high number of false-positives, which limits its cost-effectiveness.

Background: Gestational diabetes mellitus is an endocrine and metabolic disorder that appears for the first time during pregnancy and causes varying degrees of short- and/or long-term effects on the mother and child. The etiology of the disease is currently unknown and isobaric tags for relative and absolute quantitation proteomics approach, the present study attempted to identify potential proteins in placental tissues that may be involved in the pathogenesis of GDM and adverse foetal pregnancy outcomes.

Methods: Pregnant women with GDM hospitalised were selected as the experimental group, and pregnant women with normal glucose metabolism as the control group. The iTRAQ protein quantification technology was used to screen the differentially expressed proteins between the GDM group and the normal control group, and the differentially expressed proteins were analysed by GO, KEGG, PPI, etc., and the key proteins were subsequently verified by western blot.

Results: Based on the proteomics of iTRAQ, we experimented with three different samples of placental tissues from GDM and normal pregnant women, and the total number of identified proteins were 5906, 5959, and 6017, respectively, which were similar in the three different samples, indicating that the results were reliable. Through the Wayne diagram, we found that the total number of proteins coexisting in the three groups was 4475, and 91 differential proteins that could meet the quantification criteria were strictly screened, of which 32 proteins were up-regulated and 59 proteins were down-regulated. By GO enrichment analysis, these differential proteins are widely distributed in extracellular membrane-bounded organelle, mainly in extracellular exosome, followed by intracellular vesicle, extracellular organelle. It not only undertakes protein binding, protein complex binding, macromolecular complex binding, but also involves molecular biological functions such as neutrophil degranulation, multicellular organismal process, developmental process, cellular component organization, secretion, regulated exocytosis. Through the analysis of the KEGG signaling pathway, it is found that these differential proteins are mainly involved in HIF-1 signaling pathway, Glycolysis/Gluconeogenesis, Central carbon metabolism in cancer, AMPK signaling pathway, Proteoglycans in cancer, Protein processing in endoplasmic reticulum, Thyroid cancer, Alcoholism, Glucagon signaling pathway.

Discussion: This preliminary study helps us to understand the changes in the placental proteome of GDM patients, and provides new insights into the pathophysiology of GDM.

Background: Long-term exposure of pancreatic islets to fatty acids (FAs), common in obesity, metabolic syndrome, and type 2 diabetes, leads to a compensatory hyperactivity followed by inflammation, apoptosis, dysfunctional beta cells, and results in insulin dependence of the patient. Restriction of fatty uptake by islet beta cells may protect them from lipotoxicity.

Purpose: Pancreatic islet beta cells express the fatty acid binding protein 3 (FABP3) to bind FAs and to orchestrate lipid signals. Based on this, we investigated whether downregulation of FABP3, by Fabp3 silencing, might slow lipid metabolism and protect against lipotoxicity in insulin-secreting cells.

Results: Neither Fabp3 silencing, nor overexpression affected the glucose-stimulated insulin secretion in absence of FAs. Fabp3 silencing decreased FA-uptake, lipid droplets formation, and the expression of the lipid accumulation-regulating gene Dgat1 in Ins1E cells. It reduced FA-induced inflammation by deactivation of NF-κB, which was associated with upregulation of IκBα and deactivation of the NF-κB p65 nuclear translocation, and the downregulation of the cytokines ILl-6, IL-1β, and TNFα. Ins1E cells were protected from the FA-induced apoptosis as assessed by different parameters including DNA degradation and cleaved caspase-3 immunoblotting. Furthermore, FABP3 silencing improved the viability, Pdx1 gene expression, and the insulin-secreting function in cells long-term cultured with palmitic acid. All results were confirmed by the opposite action rendered by FABP3 overexpression.

Conclusion: The present data reveals that pancreatic beta cells can be protected from lipotoxicity by inhibition of FA-uptake, intracellular utilization and accumulation. FABP3 inhibition, hence, may be a useful pharmaceutical approach in obesity, metabolic syndrome, and type 2 diabetes.

Background: This study investigates the therapeutic mechanisms of Cai's Herbal Tea in Type 1 Diabetes Mellitus (T1DM) mice, focusing on its effects on mitochondrial change and autophagy via the AMP-activated protein kinase (AMPK)-mammalian target of rapamycin (mTOR) pathway.

Methods: The composition of Cai's Herbal Tea was analyzed by Ultra-High Performance Liquid Chromatography-Quadrupole Time of Flight Mass Spectrometry (UHPLC-Q/TOF-MS). C57BL/6 mice and Min6 pancreatic beta cells were divided into control, diabetic mellitus (DM)/high glucose (HG), and treatment groups (low, medium, and high doses of Cai's Tea, and Metformin). Key physiological parameters, pancreatic islet health, Min6 cell morphology, viability, and insulin (INS) secretion were assessed. Small Interfering RNA-AMPK (si-AMPK) was utilized to confirm the pathway involvement.

Results: Cai's Herbal Tea improved body weight, pancreatic islet pathological injury, and INS secretion whereas reduced total triglycerides, fasting blood sugar, and Interferon gamma (INF-γ) in T1DM mice, particularly at higher doses. In Min6 cells, Cai's Tea mitigated HG-induced damage and proinflammatory response, enhancing cell viability and INS secretion. Notably, it reduced swelling and improved cristae structure in treated groups of mitochondria and promoted autophagy via the AMPK-mTOR pathway, evidenced by increased LC3II/LC3I and P-AMPK/AMPK ratios, and decreased P-mTOR/mTOR and P62 expressions in pancreatic islet β-cells. Furthermore, these effects were converted by si-AMPK interference.

Conclusion: Cai's Herbal Tea exhibits significant therapeutic efficacy in T1DM mice by improving mitochondrial health and inducing autophagy through the AMPK-mTOR pathway in pancreatic islet β-cells. These findings highlight its potential as a therapeutic approach for T1DM management.

Aim: The urban population increases by about 60 million people/year. Urbanization, unhealthy lifestyle and aging of the population are reflected in a constant growth in the prevalence of diabetes. In 2014, Steno Diabetes Centre in Copenhagen, University College London and Novo Nordisk, launched the Cities Changing Diabetes® program with the aim of creating a unified movement that would stimulate policy-makers to prioritize urban diabetes.

Methods: The socio-demographic data derive from (1) ISTAT (National Institute of Statistics of Italy), (2) ATS Metropolitan City of Milan, (3) ATS Val Padana-Cremona, (4) ATS Insubria-Varese, (5) The unemployment rates of the various municipalities have been extrapolated from an ISTAT-MEF elaboration published by Sole 24 Ore journal.

Results: In the different sanitary districts of the Metropolitan City of Milan, a strong linear correlation was found between the prevalence of diabetes and the prevalence of heart disease (R = 0.695, p < 0.001), as well as between the prevalence of diabetes and of nephropathies (R = 0.316, p < 0.001). The analysis concerning the province of Cremona showed a fair correlation between the prevalence of diabetes and cardiovascular disease (R = 0.658, p < 0.001). Even for the municipalities of Varese, the analysis documented a good correlation between the prevalence of diabetes and heart disease (R = 0.419, p < 0.001), but not between diabetes and nephropathies.

Conclusions: Interesting differences in the relationship of diabetes prevalence with several diseases and socio-demographic factors have been found when comparing the metropolitan City of Milan with two smaller size cities as Varese and Cremona. Our present data confirm the hypothesis that urban diabetes will be the challenge for our society during the next decades.

Background: Cerebrovascular accidents (CVA) represent a major complication in diabetes (DM). Real-life evidence as to whether modern management of CVA and DM have softened this relationship is limited. Therefore, we estimated prevalence and impact of DM on in-hospital survival and complications in a contemporary cohort of subjects with CVA.

Methods: We retrospectively evaluated the records of 937 patients admitted for CVA at the Stroke Unit of Verona University Hospital during a 3-year period. Pre-existing or de novo DM was ascertained by prior diagnosis, glucose-lowering therapy at admission/discharge or admittance plasma glucose ≥ 200 mg/dL. Multiple regressions were applied to test DM as predictor of in-hospital mortality, complications (composite of infections, cardio- and cerebrovascular complications, major bleeding and pulmonary complications), duration and costs of hospitalization.

Results: Diabetes prevalence was 21%, of which 22% de novo diagnoses. Compared to non-DM, diabetic individuals were older and carried an increased burden of cardiovascular risk factors. Compared to known DM, de novo DM individuals were younger, had higher admittance plasma glucose and poorer cardiovascular comorbidities. Overall, DM versus non-DM individuals did not show significantly increased risk of death (14.0 vs. 9.3%; crude-OR 1.59 95% CI 0.99-2.56). Controlling for confounders did not improve significance. DM resulted independent predictor for in-hospital complications (36.2% vs. 26.9%; adj-OR 1.49, 1.04-2.13), but not for duration and costs of hospitalization.

Conclusion: DM frequently occurs in patients admitted for stroke and carries an excess burden of adverse in-hospital complications, urgently calling for strategies to anticipate DM diagnosis and tailored treatment in high-risk individuals.

Aims: For end-stage renal disease (ESRD) patients with diabetes on haemodialysis, diabetes control is difficult to achieve. Hypoglycaemia is a major problem in these frailty subjects. Continuous glucose monitoring (CGM) devices appear therefore to be a good tool to help patients monitor their glycaemic control and to help practitioners optimize treatment. We aimed to compare the laboratory value of Hba1c with the sensor-estimated value of Hba1c (= glucose management indicator, GMI) in ESRD patients with type 2 diabetes (T2D) (with or without insulin treatment) on haemodialysis. Secondly, we aimed to identify CGM-derived monitoring parameters [time in range, time in hypo/hyperglycaemia, glycaemic variability (coefficient of variation, CV)] to identify patients at risk of frequent hypo- or hyperglycaemia.

Methods: The FSLPRO-DIAL pilot study (NCT04641650) was a prospective monocentric cohort study including 29 subjects with T2D who achieve the protocol. Inclusion criteria were: age ≥ 18 years, haemodialysis duration for at least 3 months, type 2 diabetes with no change in treatment for at least 3 months. Demographic data and blood sample were collected at the day of inclusion. Freestyle Libre pro IQ sensor (blinded CGM) was inserted for 14 days. After this period, all CGMs data were collected and analysed.

Results: Data were available for 27 patients. Mean age was 73 ± 10, mean BMI 27.2 kg/m², mean duration of diabetes 16.9 years and mean dialysis duration 2.9 years. Twenty-four subjects were treated with insulin. Mean HbA1c was 6.6% (SD 1.2), and mean GMI was 6.7% (SD 0.9) (no significant difference, p = 0.3). Twelve subjects (44.4%) had a discordance between HbA1c and GMI of < 0.5%, 11 (40.8%) had a discordance between 0.5 and 1%, and only 4 (14.8%) had a discordance of > 1%. Mean time in range (70-180 mg/dl) was 71.9%, mean time below range (< 70 mg/dl) was 5.6%, and mean time above range (> 180 mg/dl) was 22.1%. Mean CV was 31.8%. For 13 out of 27 patients, we reduced antidiabetic treatment by stopping treatments or reducing insulin doses.

Conclusion: In this pilot study, there was no global significant difference between HbA1c and GMI in this particular cohort with very well-controlled diabetes. However, the use of the sensor enabled us to identify an excessive time in hypoglycemia in this fragile population and to adapt their treatment.