Acta Diabetologica最新文献

Background: Gestational diabetes mellitus (GDM) affects roughly 14% of pregnancies, its prevalence is increasing, and it is associated with a significant risk of complications for both mother and offspring. A high proportion of women with GDM can be detected early in pregnancy. In Italy, early GDM screening occurs in a selective way, as it is performed only in the presence of important risk factors. It remains to be elucidated not only how and when to diagnose early GDM but especially whether to treat it. This study aimed to compare the characteristics and complications of early vs late GDM as assessed and treated in a real-world setting, according to the Italian guidelines of the Istituto Superiore di Sanità.

Methods: We conducted a retrospective cohort study in women with GDM delivering singletons between 2017 and 2021.

Results: Women with early GDM had higher BMI and a higher proportion of Middle Eastern or African women. Early GDM was independently associated with the use of insulin (p < 0.001). It required also higher doses of insulin, possibly due to the higher BMI. Early GDM was also independently associated with higher post-prandial (after dinner) glucose levels during the 3° trimester (p = 0.04). Nevertheless, early GDM women achieved glucose targets and put on less weight during gestation. Early GDM was independently associated with preeclampsia (p = 0.05). Otherwise, there were no other differences between early and late GDM in terms of pregnancy complications. After delivery, early GDM was independently associated with abnormal glucose tolerance.

Conclusions: Early GDM women exhibited more severe GDM features. However, after achieving recommended glucose and body weight targets, there were no substantial differences between early and late GDM in terms of pregnancy complications apart from preeclampsia. These data support diagnosis and treatment of women with early GDM.

Background: This study identifies a new set of salient risk factors that may trigger danger signals of vascular dysregulation in T1D. Vascular abnormalities and impairment of CVD is a major adverse effect of T1D, particularly affecting children, adolescents and young adults.

Methods: The patients of T1D were compared with the healthy control (HC) for the risk factors of vascular dysregulation in published studies from year 2013 to 2023. The PubMed, Web of Science and Google Scholar databases were searched from 1/1/2013 to 1/9/2023. The risk of bias was assessed with the Cochrane (ROBINS-I ) tool, relevant to clinical subjects. A random effects model was followed and analysed by RevMan 5.4 and GraphPad Prism software.

Results: 80 relevant case-control studies having 7492 T1D patients and 5293 HC were included. The age and sex-matched HC consisted of persons free of disease and not under any medication while clinical subjects of < 40 years were included. 28 risk factors were grouped into six primary outcome models, all of which favoured the T1D synonymous with a high risk of CVD.

Conclusion: Our findings have strong implications for improving the quality of life and health economics related to vascular disease in T1D. HbA1c% is the most effective biomarker, followed by FBG, LDL-c, AI%, sICAM-1, and FMD% which could be evaluated with a simple blood test or non-invasive techniques. These may serve dual purposes as biomarkers of rapid diagnosis that could offer prospective tailor-made therapeutics for T1D. (Protocol registered at https://www.crd.york.ac.uk/prospero/CRD42022384636 ).

Background: Orthotopic liver transplantation (OLT) has greatly improved short-term survival for end-stage liver disease. However, cardiovascular events (CVE) still pose a significant threat to long-term post-transplant health. Aim of this study is to assess the occurrence of long-term cardiovascular events and whether it relates to new-onset diabetes after liver transplantation (NODALT).

Methods: We conducted a multicentric retrospective analysis of adult OLT recipients with regular follow-up visits spanning from January 1995 to December 2020. Data collection included anamnestic, clinical, anthropometric, and laboratory data from two centers. NODALT was diagnosed following ADA guidelines. The primary outcome was incident CVE (a composite of fatal and non-fatal stroke and myocardial infarction). CVE occurrence was analyzed in relation to NODALT diagnosis, along with clinical characteristics associated with its development.

Results: Ninety-three eligible Caucasian patients, with a median age of 57.0 years (IQR: 49.0-62.0, 69.9% male), were enrolled. Over the median follow-up period of 100.5 months, 29 patients (31.2%) developed NODALT, and 14 patients (15.1%) developed any CVE, with 9 being in the NODALT group. A significant association between NODALT and cardiovascular complications was confirmed by both generalized estimating equation (OR 5.31; 95% CI 1.59-17.72, p = 0.006) and Kaplan-Meier analysis (log-rank = 0.046). Metabolic syndrome and impaired fasting glucose were identified as baseline risk factors for the incident NODALT (OR 5.75; 95% CI 1.44-22.92, p = 0.013 and OR 7.29; 95% CI 1.46-36.41, p = 0.015, respectively).

Conclusions: Post-OLT cardiovascular events are less frequent than previously reported but are notably linked to NODALT, highlighting the interplay between metabolic syndrome and impaired fasting glucose.

Objective: Obesity and type 2 diabetes (T2D) are associated with increased rates of mental disorders, particularly depression, anxiety and binge-eating disorder. GLP-1 receptor agonists are a novel class of pharmacological agents for obesity and T2D. We aimed to describe participants' experiences of GLP-1 receptor agonists on their mental health.

Methods: Qualitative, individual, semi-structured interviews were conducted in nine participants who were prescribed GLP-1 receptor agonists for the treatment of obesity and/or T2D. Mental health status was measured at time of GLP-1 receptor agonist initiation and assessed again at 12-16 weeks when the semi-structured interview took place. Data were analysed using reflexive thematic analysis.

Results: Three main themes were generated from the analysis: (1) acceptance of negative side effects for long term physical health benefits; (2) reflections on the diverse impact on mental health; (3) reduced appetite and increased control of eating behaviours.

Discussion: Overall, participants with obesity and/or T2D described a positive impact of GLP-1 receptor agonists on their mental health, especially perception of improved control of eating behaviours. This suggests GLP-1 receptor agonists should be further studied for their potential effectiveness for treatment of binge-eating disorder.

Aims: Diabetes associated cognitive decline (DACD) is a common CNS-related consequence of diabetes. The primary clinical manifestation of DACD includes learning and memory impairment. Unfortunately, there is no cure to delay the cognitive symptoms of diabetes. Although berberine (BBR) has shown promising effect in the treating diabetes and cognitive dysfunction, more research is needed to understand the mechanism of its therapeutic effect. For better understanding, we investigated the functions of BBR involved in anti-inflammation, anti-oxidant and neuroprotection in the hippocampus of diabetic mice.

Methods: Diabetes was induced in mice using STZ. BBR was administered for 4 weeks before (pre-treatment), and after (post-treatment) STZ administration. The effect of BBR on cognitive functions in diabetic mice was determined using neurobehavioural test. Moreover, how BBR affected neuroinflammation, oxidative stress, and acetylcholine levels in the hippocampus and BBB permeability were analyzed using standard biochemical assays. Lastly, we evaluated the mRNA expression of neuroprotective genes in the hippocampus to uncover the mechanism of BBR.

Results: Treatment with BBR improved cognition in diabetic mice. It significantly reduced the levels of IL-6, iNOS, TNF-α, IL-1β, ROS and MDA and increased the levels of TAC, GSH, SOD and Catalase. Moreover, levels of acetylcholine and BBB permeability were reduced in the diabetic mice which was reversed by BBR treatment and increased the expression of IGF and BDNF in the hippocampus of diabetic mice.

Conclusion: Our results suggest that BBR might be a potential therapeutic candidate for the treatment of DACD. Our study might serve as a basis for developing novel drugs for treating DACD.

Aim: Type-2 Diabetes Mellitus (T2DM) affects millions globally, with escalating rates. It often leads to undiagnosed complications and commonly coexists with other health conditions. This study investigates two types of prevalent comorbidities related to T2DM-the circulatory system (DCM1) and digestive system diseases (DCM2)-using clinical, genomic and proteomic datasets. The aim is to identify new biomarkers by applying existing machine learning (ML) based techniques for early detection, prognosis and diagnosis of these comorbidities.

Methods: Here, we report a cross-sectional retrospective analysis from a T2DM dataset of T2DM associated concordant comorbidities (diseases with shared pathophysiology and management) from the Diastrat cohort (a T2DM cohort) recruited at the Northern Ireland Centre for Stratified Medicine (NICSM), in Northern Ireland.

Results: In the clinical data analysis, we identified that lipidemia was shown to negatively correlate with depression in the DCM1 group while positively correlate with depression in the DCM2 group. In genomic analysis, we identified statistically significant variants rs9844730 in procollagen-lysine (PLOD2), rs73590361 in beta-1,4-N-acetyl- galactosaminyl-transferase (B4GALNT3) and rs964680 in A kinase (PRKA) anchor protein 14 (AKAP14) which appear to differentiate DCM1 and DCM2 groups. In proteomic analysis, we identified 4 statistically significant proteins: natriuretic peptides B (BNP), pro-adrenomedullin (ADM), natriuretic peptides B (NT-proBNP) and discoidin (DCBLD2) that can differentiate DCM1 and DCM2 groups and have built robust ML model using clinical, genomic, and proteomic markers (0.83 receiver operative characteristics curve area, 84% positive predictive value and 83% negative predictive value and a classification accuracy of 83%) for prediction of DCM1 and DCM2 groups.

Conclusion: Our study successfully identifies novel clinical, genomic, and proteomic biomarkers that differentiate between circulatory and digestive system comorbidities in Type-2 Diabetes Mellitus patients. The machine learning model we developed demonstrates strong predictive capabilities, providing a promising tool for the early detection, prognosis, and diagnosis of these T2DM-associated comorbidities. These findings have the potential to enhance personalized management strategies for patients with T2DM, ultimately improving clinical outcomes. Further research is needed to validate these biomarkers and integrate them into clinical practice.

Objective: The stress hyperglycemia ratio (SHR) is a new biomarker indicating acute hyperglycemia and predicting adverse outcomes in different conditions. Yet, its impact on metabolic syndrome (MetS) has not been studied. We explored the link between SHR and long-term all-cause and cardiovascular disease (CVD) mortality in MetS patients.

Methods: We conducted a large prospective cohort study involving 9438 participants diagnosed with MetS, drawn from the 1999-2018 NHANES. MetS diagnosis was based on NCEP-ATPIII criteria. Participants were categorized into three groups based on SHR tertiles: T1 (SHR ≤ 0.890), T2 (SHR 0.890-0.992), and T3 (SHR ≥ 0.992). Cox regression and Kaplan-Meier curve analyses assessed the correlation between SHR and mortalities. Non-linear correlations were explored using restricted cubic splines, and stratification analysis was performed.

Results: Out of 9438 MetS patients, 1929 deaths occurred during an average follow-up of 107 ± 64 months, including 541 CVD deaths. All-cause and CVD mortality rates were significantly higher with elevated SHR values (T3) than lower tertiles (23.4% vs. 19.5% and 18.3%, P < 0.001; 6.8% vs. 5.3% and 5.1%, P = 0.007, respectively). A U-shaped relationship was observed between SHR and all-cause and CVD mortality (all P for non-linear < 0.001). Kaplan-Meier analysis indicated higher SHR values associated with increased risk of all-cause and CVD mortality (all log-rank P < 0.001). After adjusting for confounders, multivariate Cox regression showed SHR remained associated with a 1.256-fold and 1.023-fold risk of all-cause and CVD mortality.

Conclusions: SHR independently correlates with all-cause and CVD mortality in MetS patients, displaying a U-shaped relationship with clinical endpoints.