Type 1 diabetes (T1D) is an autoimmune disease characterized by the T-cell-mediated destruction of insulin-producing β-cells in pancreatic islets. It generally occurs in genetically susceptible individuals, and genetics plays a major role in the development of islet autoimmunity. Furthermore, these processes are heterogeneous among individuals; hence, different endotypes have been proposed. In this review, we highlight the interplay between genetic predisposition and other non-genetic factors, such as viral infections, diet, and gut biome, which all potentially contribute to the aetiology of T1D. We also discuss a possible active role for β-cells in initiating the pathological processes. Another component in T1D predisposition is epigenetic influences, which represent a link between genetic susceptibility and environmental factors and may account for some of the disease heterogeneity. Accordingly, a shift towards personalized therapies may improve the treatment results and, therefore, result in better outcomes for individuals in the long-run. There is also a clear need for a better understanding of the preclinical phases of T1D and finding new predictive biomarkers for earlier diagnosis and therapy, with the final goal of reverting or even preventing the development of the disease.

Type 1 diabetes is a chronic autoimmune disease in which the destruction of pancreatic β cells leads to hyperglycemia. The prevention of hyperglycemia is very important to avoid or at least postpone the development of micro- and macrovascular complications, also known as late complications. These include diabetic retinopathy, chronic renal failure, diabetic neuropathy, and cardiovascular diseases. The impact of long-term hyperglycemia has been shown to persist long after the normalization of blood glucose levels, a phenomenon known as metabolic memory. It is believed that epigenetic mechanisms such as DNA methylation, histone modifications, and microRNAs, play an important role in metabolic memory. The aim of this review is to address the impact of long-term hyperglycemia on epigenetic marks in late complications of type 1 diabetes.

Together with metabolites, proteins, and lipid components, the EV cargo consists of DNA and RNA nucleotide sequence species, which are part of the intracellular communication network regulating specific cellular processes and provoking distinct target cell responses. The extracellular vesicle (EV) nucleotide sequence cargo molecules are often investigated in association with a particular pathology and may provide an insight into the physiological and pathological processes in hard-to-access organs and tissues. The diversity and biological function of EV nucleotide sequences are distinct regarding EV subgroups and differ in tissue- and cell-released EVs. EV DNA is present mainly in apoptotic bodies, while there are different species of EV RNAs in all subgroups of EVs. A limited sample volume of unique human liquid biopsy provides a small amount of EVs with limited isolated DNA and RNA, which can be a challenging factor for EV nucleotide sequence analysis, while the additional difficulty is technical variability of molecular nucleotide detection. Every EV study is challenged with its first step of the EV isolation procedure, which determines the EV’s purity, yield, and diameter range and has an impact on the EV’s downstream analysis with a significant impact on the final result. The gold standard EV isolation procedure with ultracentrifugation provides a low output and not highly pure isolated EVs, while modern techniques increase EV’s yield and purity. Different EV DNA and RNA detection techniques include the PCR procedure for nucleotide sequence replication of the molecules of interest, which can undergo a small-input EV DNA or RNA material. The nucleotide sequence detection approaches with their advantages and disadvantages should be considered to appropriately address the study problem and to extract specific EV nucleotide sequence information with the detection using qPCR or next-generation sequencing. Advanced next-generation sequencing techniques allow the detection of total EV genomic or transcriptomic data even at the single-molecule resolution and thus, offering a sensitive and accurate EV DNA or RNA biomarker detection. Additionally, with the processes where the EV genomic or transcriptomic data profiles are compared to identify characteristic EV differences in specific conditions, novel biomarkers could be discovered. Therefore, a suitable differential expression analysis is crucial to define the EV DNA or RNA differences between conditions under investigation. Further bioinformatics analysis can predict molecular cell targets and identify targeted and affected cellular pathways. The prediction target tools with functional studies are essential to help specify the role of the investigated EV-targeted nucleotide sequences in health and disease and support further development of EV-related therapeutics. This review will discuss the biological diversity of human liquid biopsy–obtained EV nucleotide sequences DNA and RNA species reported as potential biomarkers in health and disease and methodological principles of their detection, from human liquid biopsy EV isolation, EV nucleotide sequence extraction, techniques for their detection, and their cell target prediction.

Hearing loss is one of the most common sensory deficits. It carries severe medical and social consequences, and therefore, universal newborn hearing screening was introduced at the beginning of this century. Affected patients can have hearing loss as a solitary deficit (non-syndromic hearing loss) or have other organs affected as well (syndromic hearing loss). In around 60% of cases, congenital hearing loss has a genetic etiology, where disease-causing variants can change any component of the hearing pathway. Genetic testing is usually performed by sequencing. Sanger sequencing enables analysis of the limited number of genes strictly preselected according to the clinical presentation and the prevalence among the hearing loss patients. In contrast, next-generation sequencing allows broad analysis of the numerous genes related to hearing loss, exome, or the whole genome. Identification of the genetic etiology is possible, and it makes the foundation for the genetic counselling in the family. Furthermore, it enables the identification of the comorbidities that may need a referral for specialty care, allows early treatment, helps with identification of candidates for cochlear implant, appropriate aversive/protective management, and is the foundation for the development of novel therapeutic options.

Hyperglycemia and abnormal blood glucose levels induce oxidative stress, promote the development of microvascular and macrovascular complications,¹ and may increase telomere loss in patients with type 1 diabetes.^2,3 All studies of adults with type 1 diabetes, except one, report a shorter telomere length associated with age, duration of type 1 diabetes, and higher glycated hemoglobin A_1c (HbA_1c) levels.⁴ To expand these data in a pediatric population at the onset of type 1 diabetes by assessing the association between telomere length and age or HbA_1c level,⁵ we conducted a retrospective longitudinal study evaluating the association of glycemic control and associated cell stress with telomere dynamics during a 7-year follow-up.

In this study, we aimed to identify patients within our B-ALL cohort with altered PAX5. Our objective was to use a comprehensive analysis approach to characterize the types of genetic changes, determine their origin (somatic/germline), and analyze the clinical outcomes associated with them. A consecutive cohort of 99 patients with B-ALL treated at the Children’s Hospital of the UMC Ljubljana according to the ALL IC-BFM 2009 protocol was included in our study. We used RNA sequencing data for gene expression analysis, fusion gene detection and single nucleotide variant identification, multiplex-ligation dependent probe amplification for copy number variation assessment, and Sanger sequencing for germline variant detection. PAX5 was impacted in 33.3% of our patients, with the genetic alterations ranging from CNVs and rearrangements to SNVs. The most common were CNVs, which were found in more than a third of patients, followed by point mutations in 5.2%, and gene rearrangements in 4.1%. We identified eight patients with a PAX5-associated genetic subtype that were previously classified as “B-other”, and they showed intermediate outcomes. We showed higher minimal residual disease values at the end of induction and poorer event-free survival in hyperdiploid cases carrying duplications in PAX5 compared to other hyperdiploid cases. We also report an interesting case of a patient with PAX5::FKBP15 and a pathogenic variant in PTPN11 who underwent an early relapse with a monocytic switch. In conclusion, this study provides valuable insights into the presence, frequency, and prognostic significance of diverse PAX5 alterations in B-ALL patients, highlighting the complexity of genetic factors and their impact on patient outcomes.