The current COVID-19 pandemic has forced health care teams to look for alternative approaches to manage a great number of children with diabetes not only in rural but also in urban locations. Our aim in this COVID-19 pandemic was to provide information about the follow-up of new onset type 1 diabetes (T1D) patients and to discuss the integration of telemedicine into routine clinical care in the long term. The changes in Coefficient of variation (CV), standard deviation (SD); percentage of time in range (TIR), time below range (TBR) and time above range (TAR) were evaluated in 8 patients with new-onset T1D diagnosed in Pediatric Diabetes division of Ege University, during COVID-19 pandemic over a period of two-months follow-up using telemedicine system. Median follow-up time was 51 (24-66) days. Two of the patients were using low glucose suspend system and 6 were on multiple dose daily injection therapy (MDI). Target TIR values were achieved in 7 patients in the last televisit and according to last consensus suggestions' TBR <70 mg/dl (3.9 mmol/l) (level 1 hypoglycemia) of <4% and a TBR <54 mg/dl (3.0 mmol/l) (level 2 hypoglycemia) of <1% were achieved in all patients. Seven patients achieved a CV of < 36 % in their last televisit. Telemedicine as an alternative follow-up tool during unusual circumstances such pandemics, even in countries where it is not routinely used, could be beneficial to achieve optimum glycemic control in patients with new-onset T1D.

Objectives: Osteogenesis imperfecta (OI) is a group of phenotypically and genetically heterogeneous connective tissue disorders that share similar skeletal anomalies causing bone fragility and deformation. This study aimed to investigate the molecular genetic etiology and to determine the relationship between genotype and phenotype in OI patients with whole exome sequencing (WES). Methods: Multiplex-Ligation dependent Probe Amplification (MLPA) analysis of COL1A1 and COL1A2 and WES were performed on cases between the ages of 0 and 18 whose genetic etiology could not be determined before using a targeted next-generation sequencing panel, including 13 genes (COL1A1, COL1A2, IFITM5, SERPINF1, CRTAP, P3H1, PPIB, SERPINH1, FKBP10, SP7, BMP1, MBTPS2, PLOD2) responsible for OI. Results: Twelve patients (female/male: 4/8) from 10 different families were included in the study. In 6 (50 %) families, consanguineous marriage was noted. The clinical typing based on Sillence classification; 3 (25 %) patients were considered to be type I, 7 (58.3 %) type III, and 2 (16.7 %) type IV. Deletion/duplication wasn’t detected in the COL1A1 and COL1A2 genes in the MLPA analysis of the patients. Twelve patients were molecularly analyzed by WES, and in 6 (50 %) of them, a disease-causing variant in three different genes (FKBP10, P3H1, and WNT1) was identified. Two (33.3 %) detected variants in all genes have not been previously reported in the literature and were considered deleterious based on prediction tools. In 6 cases, no variants were detected in disease-causing genes. Conclusions: This study demonstrates rare OI types’ clinical and molecular features; genetic etiology was determined in 6 (50 %) 12 patients with the WES analysis. In addition, two variants in OI genes have been identified, contributing to the literature.

Objective: Osteogenesis imperfecta (OI) consists of a group of phenotypically and genetically heterogeneous connective tissue disorders that share similar skeletal anomalies causing bone fragility and deformation. The aim was to investigate the molecular genetic etiology and determine the relationship between genotype and phenotype in OI patients using targeted next-generation sequencing (NGS). Methods: A targeted NGS analysis panel (Illumina TruSight One) containing genes involved in collagen/bone synthesis was performed on the Illumina Nextseq550 platform in patients with a confirmed diagnosis of OI. Results: Fifty-six patients (female/male: 25/31) from 46 different families were included. Consanguinity was noted in 15 (32.6%) families. Based on Sillence classification 18 (33.1%) were type 1 OI, 1 (1.7%) type 2, 26 (46.4%) type 3 and 11 (19.6%) type 4. Median body weight was -1.1 (-6.8, - 2.5) standard deviation scores (SDS), and height was -2.3 (-7.6, - 1.2) SDS. Bone deformity affected 30 dentinogenesis imperfecta (DI), and 2 (3.6%) had hearing loss. Disease-causing variants in COL1A1 and COL1A2 were found in 24 (52.1%) and 6 (13%) families, respectively. In 8 (17.3%) of the remaining 16 (34.7%) families, the NGS panel revealed disease-causing variants in three different genes ( FKBP10, SERPINF1, and P3H1). Nine (23.6%) of the variants detected by NGS panel had not previously been reported and were also classified as pathogenic based on American College of Medical Genetics guidelines pathogenity scores. In ten (21.7%) families, a disease-related variant was not found in any of the 13 OI genes on the panel. Conclusion: Genetic etiology was found in 38 (82.6%) of 46 families by targeted NGS analysis. Furthermore, nine new variants were identified in known OI genes which were classified as pathogenic by standard guidelines.

Objectives Activating variants of the ABCC8 gene cause neonatal diabetes or maturity-onset diabetes of the young (MODY). We report three cases of MODY type 12 caused by variants in the ABCC8 encoding sulphonylurea receptor 1, and the experience of switching from insulin therapy to sulphonylurea therapy. Case presentations We describe a 12.5-year-old girl with permanent neonatal diabetes mellitus, and two diabetes mellitus cases with variants in the ABCC8 gene. Two of these cases were successfully switched from subcutaneous insulin to oral glibenclamide, with a marked improvement in glycemic control. In permanent neonatal diabetes case, glibenclamide dose was progressively increased to achieve a full dose (2 mg/kg/day) in 9 days. Nine months after starting oral sulphonylurea therapy, her blood glucose control dramatically improved and insulin therapy was discontinued. Conclusions We conclude that patients with ABCC8 gene variants can successfully switch from insulin to sulphonylureas.