BackgroundCardiomyopathies represent a rare group of disorders often of genetic origin. While approximately 50% of genetic causes are known for other types of cardiomyopathies, the genetic spectrum of restrictive cardiomyopathy (RCM) is largely unknown. The aim of the present study was to identify the genetic background of idiopathic RCM and to compile the obtained genetic variants to the novel signalling pathways using in silico protein network analysis.Patients and MethodsWe used Illumina MiSeq setup to screen for 108 cardiomyopathy and arrhythmia-associated genes in 24 patients with idiopathic RCM. Pathogenicity of genetic variants was classified according to American College of Medical Genetics and Genomics classification.ResultsPathogenic and likely-pathogenic variants were detected in 13 of 24 patients resulting in an overall genotype-positive rate of 54%. Half of the genotype-positive patients carried a combination of pathogenic, likely-pathogenic variants and variants of unknown significance. The most frequent combination included mutations in sarcomeric and cytoskeletal genes (38%). A bioinformatics approach underlined the mechanotransducing protein networks important for RCM pathogenesis.ConclusionsMultiple gene mutations were detected in half of the RCM cases, with a combination of sarcomeric and cytoskeletal gene mutations being the most common. Mutations of genes encoding sarcomeric, cytoskeletal, and Z-line-associated proteins appear to have a predominant role in the development of RCM.

We hypothesized that the association of certain lifestyle parameters with gestational diabetes mellitus (GDM) risk would depend on susceptibility loci. In total, 278 Russian women with GDM and 179 controls completed questionnaires about lifestyle habits (food consumption, physical activity and smoking). GDM was diagnosed according to the criteria of the International Association of Diabetes and Pregnancy Study Groups. Maternal blood was sampled for genotyping single-nucleotide polymorphisms (SNPs) in MTNR1B (rs10830963 and rs1387153), GCK (rs1799884), KCNJ11 (rs5219), IGF2BP2 (rs4402960), TCF7L2 (rs7903146 and rs12255372), CDKAL1 (rs7754840), IRS1 (rs1801278) and FTO (rs9939609). Binary logistic regression revealed an interaction effect of sausage intake and the number of risk alleles of two SNPs (rs10830963 in MTNR1B and rs1799884 in GCK) on GDM risk (P < 0.001). Among women without risk alleles of these two SNPs, sausage consumption was positively associated with GDM risk (P trend = 0.045). This difference was not revealed in women carrying 1 or more risk alleles. The risk of GDM increased as the number of risk alles increased in participants with low and moderate sausage consumption (P trend <0.001 and 0.006, respectively), while the risk of GDM in women with high sausage consumption remained relatively high, independent of the number of risk alleles. These findings indicate that the association of sausage consumption with GDM risk can be determined based on the number of risk alleles of rs10830963 in MTNR1B and rs1799884 in GCK.

In more than half of the cases, coarctation was combined with bicuspid aortic valve, and in approximately half of the cases, it was combined with hypoplasia of the aortic arch or descending aorta. Familial history of congenital heart disease was observed in 34.3% of the cases. In total, 29 variants of the NOTCH1 gene were identified in the patient group and in the control subjects. Four of those variants led to amino acid exchange, of which only one, R1279H, was identified in both the patient group and in the controls. This variant was significantly overrepresented in the patients with aortic coarctation compared with those in the control group (P < .05). We conclude that the R1279H substitution in the NOTCH1 gene is significantly overrepresented in patients with aortic coarctation and, therefore, may represent a disease-susceptibility allele.

ObjectiveWe aimed to explore the associations between common genetic risk variants with gestational diabetes mellitus (GDM) risk in Russian women and to assess their utility in the identification of GDM cases.MethodsWe conducted a case-control study including 1,142 pregnant women (688 GDM cases and 454 controls) enrolled at Almazov National Medical Research Centre. The International Association of Diabetes and Pregnancy Study Groups criteria were used to diagnose GDM. A total of 11 single- nucleotide polymorphisms (SNPs), including those in HKDC1 (rs10762264), GCK (rs1799884), MTNR1B (rs10830963 and rs1387153), TCF7L2 (rs7903146 and rs12255372), KCNJ11 (rs5219), IGF2BP2 (rs4402960), IRS1 (rs1801278), FTO (rs9939609), and CDKAL1 (rs7754840) were genotyped using Taqman assays. A logistic regression model was used to calculate odds ratios (ORs) and their confidence intervals (CIs). A simple-count genetic risk score (GRS) was calculated using 6 SNPs. The area under the receiver operating characteristic curve (c-statistic) was calculated for the logistic regression model predicting the risk of GDM using clinical covariates, SNPs that had shown a significant association with GDM in our study, GRS, and their combinations.ResultsTwo variants in MTNR1B (rs1387153 and rs10830963) demonstrated a significant association with an increased risk of GDM. The association remained significant after adjustment for age, pre-gestational BMI, arterial hypertension, GDM in history, impaired glucose tolerance, polycystic ovary syndrome, family history of diabetes, and parity (P = 0.001 and P &lt; 0.001, respectively). After being conditioned by each other, the effect of rs1387153 on GDM predisposition weakened while the effect of rs10830963 remained significant (P = 0.004). The risk of GDM was predicted by clinical variables (c-statistic 0.712, 95 % CI: 0.675 – 0.749), and the accuracy of prediction was modestly improved by adding GRS to the model (0.719, 95 % CI 0.682 – 0.755), and more by adding only rs10830963 (0.729, 95 % CI 0.693 – 0.764).ConclusionAmong 11 SNPs associated with T2D and/or GDM in other populations, we confirmed significant association with GDM for two variants in MTNR1B in Russian women. However, these variants showed limited value in the identification of GDM cases.

BackgroundThe glucocorticoid receptor gene (NR3C1) has been suggested as a candidate gene affecting juvenile idiopathic arthritis (JIA) course and prognosis. The purpose of this study is to investigate the glucocorticoid receptor gene BclI polymorphism (rs41423247) in JIA patients, the gene's role in susceptibility to juvenile idiopathic arthritis, and its associations with JIA activity, course and bone mineralization.MethodsOne hundred twenty-two Caucasian children with JIA and 143 healthy ethnically matched controls were studied. We checked markers of clinical and laboratory activity: morning stiffness, Ritchie Articular Index (RAI), swollen joint count (SJC), tender joint count (TJC), physician's visual analog scale (VAS), hemoglobin level (Hb), leukocyte count (L), platelet count (Pl), Westergren erythrocyte sedimentation rate (ESR), C-reactive protein (CRP), albumin, DAS and DAS28. Bone mineralization was measured by dual-energy X-ray absorptiometry (DXA) of lumbar spine L1-L4. Assessments of bone metabolism included osteocalcin, C-terminal telopeptide (CTT), parathyroid hormone (PTH), total and ionized calcium, inorganic phosphate and total alkaline phosphatase (TAP). BclI polymorphism was genotyped by polymerase chain reaction restriction fragment length polymorphism.ResultsNo association was observed between glucocorticoid receptor gene polymorphism and the presence or absence of JIA. In girls with JIA, the presence of the G allele was associated with an unfavorable arthritis course, a younger age of onset of arthritis (p = 0.0017), and higher inflammatory activity. The higher inflammatory activity was demonstrated by the following: increased time of morning stiffness (p = 0.02), VAS (p = 0.014), RAI (p = 0.048), DAS (p = 0.035), DAS28 (p = 0.05), Pl (p = 0.003), L (p = 0.046), CRP (p = 0.01). In addition, these patients had bone metabolism disturbances as follows: decreased BA (p = 0.0001), BMC (p = 0.00007), BMD (0.005) and Z score (p = 0.002); and higher levels of osteocalcin (p = 0.03), CTT (p = 0.036), TAP activity (p = 0.01) and ionized calcium (p = 0.017). In boys with JIA, no significant differences were observed related to the polymorphic alleles or genotypes.ConclusionsWe suggest that G allele and the GG genotype of the glucocorticoid receptor gene BclI polymorphism contribute to an unfavorable course and low bone mineral density in girls with JIA.

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