To verify the type of diabetes mellitus (DM) remains an extremely important problem in endocrinology, as along with types 1 and 2 DM there are rarer hereditary types of DM, including maturity-onset diabetes of the young (MODY). The latter is a genetic type of DM, which is characterized by an autosomal dominant inheritance. Eleven types of MODY (MODY 1 to MODY13) are identified; each is associated with mutations in the certain gene: HNF4A, GCK, HNF1A, PDX1, HNF1B, NEUROD1, KLF11, CEL, PAX4, INS, BLK, KCNJ11 and ABCC8. A molecular genetic testing for suspected MODY is conducted to verify the diagnosis and to define a subtype of MODY, patient management tactics, to predict the outcome of the disease and its complications in relation to the found subtype of MODY. It is also important to seek mutation causing MODY in terms of the early detection of MODY in the first-degree relatives of a proband, appropriate therapy of the disease, and prevention of its complications.
Metabolomic analysis of blood plasma samples from COVID-19 patients is a promising approach allowing for the evaluation of disease progression. We performed the metabolomic analysis of plasma samples of 30 COVID-19 patients and the 19 controls using the high-performance liquid chromatography (HPLC) coupled with tandem mass spectrometric detection (LC–MS/MS). In our analysis, we identified 103 metabolites enriched in KEGG metabolic pathways such as amino acid metabolism and the biosynthesis of aminoacyl-tRNAs, which differed significantly between the COVID-19 patients and the controls. Using ANDSystem software, we performed the reconstruction of gene networks describing the potential genetic regulation of metabolic pathways perturbed in COVID-19 patients by SARS-CoV-2 proteins. The nonstructural proteins of SARS-CoV-2 (orf8 and nsp5) and structural protein E were involved in the greater number of regulatory pathways. The reconstructed gene networks suggest the hypotheses on the molecular mechanisms of virus-host interactions in COVID-19 pathology and provide a basis for the further experimental and computer studies of the regulation of metabolic pathways by SARS-CoV-2 proteins. Our metabolomic analysis suggests the need for nonstructural protein-based vaccines and the control strategy to reduce the disease progression of COVID-19.
Background: Hyperprolactinemia is one of the most common hypothalamic-pituitary-endocrine disorders in women of reproductive age, with the highest frequency at the age of 25–44 years. In addition to influencing the reproductive system, it is important to study the effects of prolactin (PRL) on various metabolic links. Available data indicate that the effect of PRL on metabolism depends on its level. In this regard, the study of the relationship of different levels of PRL with anthropometric parameters, indicators of lipid and carbohydrate metabolism in young women is relevant.Aim: To study the frequency of metabolic syndrome (MS) and its individual components in women aged 25–45 years with different levels of prolactin.Materials and methods: Work design — cross-sectional research. A randompopulationsample of women 25–45 agedwas examined. Pregnant and breastfeeding women with macroprolactinoma, and taking antipsychotics were excluded. Information was collected using a structured questionnaire, including, but not limited to, the presence of pregnancies, childbirth, menstrual irregularities, and a clinical examination, anthropometric measurements, biochemical and hormonal blood analyzes were performed. Statistical data processing was carried out.Results: According to the inclusion and exclusion criteria, this analysis presents data from 401 women, the average age of the examibed was 36.14±6.19 years. There was no difference in the levels of thyroid-stimulating hormone and prolactin (PRL) in the age groups of 25–34 and 35–45 years. According to the survey, the incidence of thyroid diseases in the studied groups is comparable. Every fifth woman indicated menstrual irregularities. Among women 25–45 years old, women with low-normal PRL values (Me = 4.49 [3.52; 5.41] ng/ml) have more unfavorable metabolic indicators. Metabolic syndrome (MS) was detected in 28%,with a predominant increase in the frequency of abdominal obesity — 55%, hypercholesterolemic LDL — 63%. Women with high PRL (Me = 41.35 [34.78; 45.88] ng / ml) also have an unfavorable metabolic profile: MS was detected in 47%, abdominal obesity — 56%, hypertension — 39%.Conclusions: In women 25–45 years old, low and high PRL values are more often associated with metabolic ill health. PRL values are from 7.8 to 28 ng / ml, i.e. conditionally defined as normal, highly normal and at the level of moderate hyperprolactinemia contribute to the maintenance of a favorable metabolic profile. When deciding on the treatment of women with non-tumor etiology hyperprolactinemia, it is important to assess the metabolic status, expanding their understanding of PRL as a hormone associated only with lactation and with the pituitary-gonad axis.
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