Myostatin and carbohydrate disturbances.

Purpose/aim of the study: Myostatin is a myokine that has been shown to inhibit muscle growth and to have potentially deleterious effects on metabolism. The aim of the current study was to compare its circulating serum levels in subjects from the whole spectrum of carbohydrate disturbances leading to diabetes. MATERIALS AND METHODS: A total of 159 age-, sex-, and BMI-matched subjects participated in the study - 50 had normal glucose tolerance (NGT), 60 had prediabetes (PreDM), and 49 had type 2 diabetes mellitus (T2D). Oral glucose tolerance testing was used to determine glucose tolerance. Serum myostatin was quantified by means of ELISA. RESULTS: Circulating serum myostatin levels were highest in patients with T2D, lower in subjects with prediabetes, and lowest in subjects with normoglycemia (all p < 0.05). Myostatin was shown to be positively associated with fasting plasma glucose, HOMA-IR, hepatic enzymes, uric acid, and FINDRISC questionnaire scores in both sexes. ROC analyses determined circulating myostatin levels to be of value for differentiating subjects with T2D (AUC = 0.72, p = 0.002 in men; AUC = 0.70, p = 0.004 in women) in the study population. After adjustment for potential confounders, in a multiple binary logistic regression model, serum myostatin added further information to traditional risk estimates in distinguishing subjects with T2D. CONCLUSIONS: Serum myostatin levels are higher with deterioration of carbohydrate tolerance. Furthermore, circulating myostatin is positively associated with traditional biochemical estimates of poor metabolic health. These data add to evidence of the involvement of this myokine in the pathogenesis of T2D.

Phenotypes Determined by Cluster Analysis in Moderate to Severe Bronchial Asthma.

BACKGROUND: Bronchial asthma is a heterogeneous disease that includes various subtypes. They may share similar clinical characteristics, but probably have different pathological mechanisms. AIM: To identify phenotypes using cluster analysis in moderate to severe bronchial asthma and to compare differences in clinical, physiological, immunological and inflammatory data between the clusters. PATIENTS AND METHODS: Forty adult patients with moderate to severe bronchial asthma out of exacerbation were included. All underwent clinical assessment, anthropometric measurements, skin prick testing, standard spirometry and measurement fraction of exhaled nitric oxide. Blood eosinophilic count, serum total IgE and periostin levels were determined. Two-step cluster approach, hierarchical clustering method and k-mean analysis were used for identification of the clusters. RESULTS: We have identified four clusters. Cluster 1 (n=14) - late-onset, non-atopic asthma with impaired lung function, Cluster 2 (n=13) - late-onset, atopic asthma, Cluster 3 (n=6) - late-onset, aspirin sensitivity, eosinophilic asthma, and Cluster 4 (n=7) - early-onset, atopic asthma. CONCLUSIONS: Our study is the first in Bulgaria in which cluster analysis is applied to asthmatic patients. We identified four clusters. The variables with greatest force for differentiation in our study were: age of asthma onset, duration of diseases, atopy, smoking, blood eosinophils, nonsteroidal anti-inflammatory drugs hypersensitivity, baseline FEV1/FVC and symptoms severity. Our results support the concept of heterogeneity of bronchial asthma and demonstrate that cluster analysis can be an useful tool for phenotyping of disease and personalized approach to the treatment of patients.

COVID-19 Delta Wave Caused Early Overburden of Hospital Capacity in the Bulgarian Healthcare System in 2021.

We develop and apply our methodology to estimate the overburdening of hospitals in Bulgaria during the upcoming delta surge. We base our estimations on an exponential risk model from the UK. Still, the methodology is generally applicable to all risk models, depending on age. Our hypothesis is that during the delta wave in Bulgaria, the system experienced a burden from late August due to decreased capacity. This will explain most of the excess mortality during the wave. We estimate the number of people from the active cases in need of hospitalization and intensive care.

Targeting Inflammatory Cytokines to Improve Type 2 Diabetes Control.

Type 2 diabetes (T2D) is one of the most common chronic metabolic disorders in adulthood worldwide, whose pathophysiology includes an abnormal immune response accompanied by cytokine dysregulation and inflammation. As the T2D-related inflammation and its progression were associated with the balance between pro and anti-inflammatory cytokines, anticytokine treatments might represent an additional therapeutic option for T2D patients. This review focuses on existing evidence for antihyperglycemic properties of disease-modifying antirheumatic drugs (DMARDs) and anticytokine agents (anti-TNF-α, anti-interleukin-(IL-) 6, -IL-1, -IL-17, -IL-23, etc.). Emphasis is placed on their molecular mechanisms and on the biological rationale for clinical use. Finally, we briefly summarize the results from experimental model studies and promising clinical trials about the potential of anticytokine therapies in T2D, discussing the effects of these drugs on systemic and islet inflammation, beta-cell function, insulin secretion, and insulin sensitivity.

Peroxiredoxin 4 levels in patients with PCOS and/or obesity.

BACKGROUND: Peroxiredoxin 4 is a part of endogen antioxidant system and its levels are elevated in increased oxidative stress conditions. It is found to be positively associated with cardiovascular risk. The aim of the study was to investigate peroxiredoxin 4 levels in women with polycystic ovarian syndrome (PCOS) and/or obesity. METHODS: In this cros-sesctional study were included 80 patients. Anthropometric measurements and biochemical tests, including peroxiredoxin 4 measurement, were performed. RESULTS: There was a tendency towards lower peroxiredoxin 4 levels in non-obese PCOS subjects (5674.8 ± 3822.4 pg/ml), higher in obese PCOS (6588.9 ± 3731.0 pg/ml) and even higher in obese patients without PCOS (7724.6 ± 4840.4 pg/ml). Patients with abdominal obesity according to waist circumference and waist-to-hip ratio had significantly higher levels of peroxiredoxin compared to those without (7108.2 ± 4568.0 vs. 5079.8 ± 2555.4 pg/ml; p = 0.015 and 7310.6 ± 2646.2 vs. 4785.0 ± 2646.2 pg/ml; p = 0.013). There was no difference in peroxiredoxin 4 levels in patients with and without insulin resistance, hypertension, dislipidemia, hyperandrogenemia, metabolic syndrome. Peroxiredoxin 4 showed weak positive correlation to weight (r = 0.228; p = 0.044) and visceral adiposity index (r = 0.278; p = 0.031) and higher to erythrocyte sedimentation rate (r = 0.4; p < 0.01), but not to hormonal parameters and insulin sensitivity indexes. CONCLUSIONS: Non-obese patients with PCOS have a tendency towards lower peroxiredoxin 4 levels compared to obese patients with and without PCOS. Patients with abdominal obesity have significantly higher peroxiredoxin 4 levels than those without. We were not able to prove correlation between peroxiredoxin 4 levels and hormonal and carbohydrate status of the PCOS patients.