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Background: This study aimed to identify relevant transcriptomic universal biomarkers for Wilms tumor, the most common pediatric kidney cancer, independent of the histological type and stage. Methods: Using next-generation sequencing, we analyzed the miRNA profiles of 74 kidney samples, which were divided into two independent groups: fresh frozen tissue and formalin-fixed paraffin-embedded tissue samples. Subsequent mRNA expression profiling and pathway analysis were performed to define the interplay and potential involvement of miRNAs and mRNA in Wilms tumor. Results: Comparative analysis revealed 41 differentially expressed miRNAs, with 27 miRNAs having decreased expression and 14 miRNAs having increased expression in Wilms tumor tissue compared to healthy kidney tissue. Among global mRNA transcriptomic profile differences, cross-sectional analysis suggested only a limited list of genes potentially regulated by differentially expressed miRNAs in Wilms tumor. Conclusions: Overall, our study is the first to determine the complete comprehensive miRNA and mRNA profiling of Wilms tumor using a multi-omics next-generation sequencing and bioinformatics approach, providing better insights into Wilms tumor pathogenesis. Identified universal Wilms tumor miRNAs have clear potential as biomarkers for the diagnosis and treatment of Wilms tumor, regardless of histological subtype and disease stage.

While data on the efficacy and safety of continuous glucose monitoring (CGM) exist across a broad age spectrum, it is limited in very young children with type 1 diabetes (T1D). We aimed to assess real-world data in this high-risk population, focusing on glycemic variability and metrics beyond HbA1c. A 12-month multi-national, prospective, observational, registry-based cohort study in children with T1D aged 1-7 years compared glucose control using real-time CGM and using fingerstick blood glucose monitoring (BGM) alone. The prespecified primary endpoint was a difference in coefficient of variation (CV) between the CGM users and BGM-only cohort. Among 227 individuals using insulin pumps (42% female, age 5.3 years), 175 were CGM and 52 were BGM-only users. The median (IQR) CV was 39.1% (36.6-41.9) among CGM and 46.8% (42.3-51.2) among BGM-only users (P

Phage display coupled with in vitro affinity selection to mimic evolutionary principles has propelled the discovery of specific binding peptides and proteins for diverse applications, including affinity chromatography. By tailoring screening conditions, ligands with desired predefined properties, such as pH- or ion strength-responsive binding, can be identified from phage-displayed combinatorial peptide libraries. Initial hit peptides can be further optimized through directed evolution by focused mutagenesis and rescreening. Quantitative analysis of eluted binders with next-generation sequencing (NGS) assists in reducing enrichment bias and simplifies picking the most promising ligand candidate(s) through enrichment ranking. We describe, in detail, procedures of ligand selection for affinity chromatography using peptide phage display library screening, focused mutagenesis, and NGS. Furthermore, we outline the subsequent workflow for ligand characterization and affinity column construction.

Heterozygous variants in the

Background The most common psychiatric complications due to dopaminergic treatment in Parkinson’s disease are visual hallucinations and impulse control disorders. Their development depends on clinical and genetic factors. Methods We evaluated the simultaneous effect of 16 clinical and 34 genetic variables on the occurrence of visual hallucinations and impulse control disorders. Altogether, 214 Parkinson’s disease patients were enrolled. Their demographic, clinical, and genotype data were obtained. Clinical and clinical-pharmacogenetic models were built by The Least Absolute Shrinkage and Selection Operator penalized logistic regression. The predictive capacity was evaluated with the cross-validated area under the receiver operating characteristic curve (AUC). Results The clinical-pharmacogenetic index for prediction of visual hallucinations encompassed age at diagnosis (OR = 0.99), rapid eye movement (REM) sleep behavior disorder (OR = 2.27), depression (OR = 1.0002), IL6 rs1800795 (OR = 0.99), GPX1 s1050450 (OR = 1.07), COMT rs165815 (OR = 0.69), MAOB rs1799836 (OR = 0.97), DRD3 rs6280 (OR = 1.32), and BIRC5 rs8073069 (OR = 0.94). The clinical-pharmacogenetic index for prediction of impulse control disorders encompassed age at diagnosis (OR = 0.95), depression (OR = 1.75), beta-blockers (OR = 0.99), coffee consumption (OR = 0.97), NOS1 rs2682826 (OR = 1.15), SLC6A3 rs393795 (OR = 1.27), SLC22A1 rs628031 (OR = 1.19), DRD2 rs1799732 (OR = 0.88), DRD3 rs6280 (OR = 0.88), and NRG1 rs3924999 (OR = 0.96). The cross-validated AUCs of clinical and clinical-pharmacogenetic models for visual hallucinations were 0.60 and 0.59, respectively. The AUCs of clinical and clinical-pharmacogenetic models for impulse control disorders were 0.72 and 0.71, respectively. The AUCs show that the addition of selected genetic variables to the analysis does not contribute to better prediction of visual hallucinations and impulse control disorders. Conclusions Models could be improved by a larger cohort and by addition of other types of Parkinson’s disease biomarkers to the analysis.

Recurrent cardiovascular events remain an enigma that accounts for30% of deaths worldwide. While heredity and human genetics variation play a key role, host-environment interactions offer a sound conceptual framework to dissect the molecular basis of recurrent cardiovascular events from genes and proteins to metabolites, thus accounting for environmental contributions as well. We report here a multiomics systems science approach so as to map interindividual variability in susceptibility to recurrent cardiovascular events. First, we performed data and text mining through a mixed-methods content analysis to select genomic variants, 10 single nucleotide polymorphisms, and microRNAs (miR-10a, miR-21, and miR-20a), minimizing bias in candidate marker selection. Next, we validated our

In Europe,2 million individuals with familial hypercholesterolemia (FH) are currently undiagnosed. Effective screening strategies for FH diagnosis in childhood are urgently needed. We assessed the overall performances of 2 different FH screening programs in children: universal screening program with opt-out and opt-in type participation.We analyzed the data from 2 independent populations based on166,000 individuals screened for hypercholesterolemia. Genetic analyses of FH-related genes were finalized in 945 children and 99 parents.A total of 305 (32.3%) children were genotyped as positive or with a variant of uncertain significance in FH-related genes. For low-density lipoprotein cholesterol levels of 3.5 mmol L (135.3 mg/dL), the overall sensitivity and specificity for confirming FH were 90.5% and 55.3%, respectively. As part of child-parent screening, in90% of the families, the parent with reported higher cholesterol levels was positive for the familial genetic variant. The cohort-based prevalence of FH from the opt-out universal screening program was estimated to be 1 in 431 individuals (95% CI = 1/391-1/472).Universal 3-step FH screening approach in children enabled detection of most children and their parents in every generation screened at reasonable costs. Opt-out screening strategy might be preferable over opt-in screening strategy.

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 (T1D) is one of the most common chronic diseases of the endocrine system, associated with several life-threatening comorbidities. While the etiopathogenesis of T1D remains elusive, a combination of genetic susceptibility and environmental factors, such as microbial infections, are thought to be involved in the development of the disease. The prime model for studying the genetic component of T1D predisposition encompasses polymorphisms within the HLA (human leukocyte antigen) region responsible for the specificity of antigen presentation to lymphocytes. Apart from polymorphisms, genomic reorganization caused by repeat elements and endogenous viral elements (EVEs) might be involved in T1D predisposition. Such elements are human endogenous retroviruses (HERVs) and non-long terminal repeat (non-LTR) retrotransposons, including long and short interspersed nuclear elements (LINEs and SINEs). In line with their parasitic origin and selfish behaviour, retrotransposon-imposed gene regulation is a major source of genetic variation and instability in the human genome, and may represent the missing link between genetic susceptibility and environmental factors long thought to contribute to T1D onset. Autoreactive immune cell subtypes with differentially expressed retrotransposons can be identified with single-cell transcriptomics, and personalized assembled genomes can be constructed, which can then serve as a reference for predicting retrotransposon integration/restriction sites. Here we review what is known to date about retrotransposons, we discuss the involvement of viruses and retrotransposons in T1D predisposition, and finally we consider challenges in retrotransposons analysis methods.

Monogenic obesity is a severe, genetically determined disorder that affects up to 1/1000 newborns. Recent reports on potential new therapeutics and innovative clinical approaches have highlighted the need for early identification of individuals with rare genetic variants that can alter the functioning of the leptin-melanocortin signalling pathway, in order to speed up clinical intervention and reduce the risk of chronic complications. Therefore, next-generation DNA sequencing of central genes in the leptin-melanocortin pathway was performed in 1508 children and adolescents with and without obesity, aged 2-19 years. The recruited cohort comprised approximately 5% of the national paediatric population with obesity. The model-estimated effect size of rare variants in the leptin-melanocortin signalling pathway on longitudinal weight gain between carriers and non-carriers was derived. In total, 21 (1.4%) participants had known disease-causing heterozygous variants (DCVs) in the genes under investigation, and 62 (4.1%) participants were carriers of rare variants of unknown clinical significance (VUS). The estimated frequency of potential genetic variants associated with obesity (including rare VUS) ranged between 1/150 (VUS and DCV) and 1/850 (DCV) and differed significantly between participants with and without obesity. On average, the variants identified would result in approximately 7.6 kg (7.0-12.9 kg at the 95th percentile of body weight) (girls) and 8.4 kg (8.2-14.4 kg) (boys) of additional weight gain in carriers at age 18 years compared with subjects without obesity. In conclusion, children with a genetic predisposition to obesity can be promptly identified and may account for more than 6% of obesity cases. Early identification of genetic variants in the LEPR, PCSK1, POMC, MC3R and MC4R genes could reduce the societal burden and improve the clinical management of early severe childhood obesity and its implementation should be further investigated.

Affinity chromatography is the linchpin of antibody downstream processing and typically relies on bacterial immunoglobulin (Ig)-binding proteins, epitomized by staphylococcal protein A-based ligands. However, such affinity ligands are fairly costly and suffer from chemical instability, leading to ligand denaturation and leaching from chromatographic support. Innovations in this area are aimed at developing robust and highly selective antibody ligands capable of withstanding harsh column sanitization conditions. We report the development and first-stage characterization of a selective short linear peptide ligand of the IgG Fc region capable of capturing all four IgG subclasses. The ligand was discovered through in vitro directed evolution. A focused phage-display library based on a previously identified peptide lead was subjected to a single-round screen against a pool of human IgG. The hits were identified with next-generation sequencing and ranked according to the enrichment ratio relative to their frequency in the pre-screened library. The top enriched peptide GSYWYNVWF displaying highest affinity for IgG was coupled to bromohydrin-activated agarose beads via a branched linker. The resulting affinity matrix was characterized with a dynamic binding capacity of approx. 43 mg/mL, on par with commercially employed protein A-based resin.

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.

Genomic structural variations, previously considered rare events, are widely recognized as a major source of inter-individual variability and hence, a major hurdle in optimum patient stratification and disease management. Herein, we focus on large complex germline structural variations and present challenges towards target treatment via the synergy of state-of-the-art approaches and information technology tools. A complex structural variation detection remains challenging, as there is no gold standard for identifying such genomic variations with long reads, especially when the chromosomal rearrangement in question is a few Mb in length. A clinical case with a large complex chromosomal rearrangement serves as a paradigm. We feel that functional validation and data interpretation are of outmost importance for information growth to be translated into knowledge growth and hence, new working practices are highlighted.

OBJECTIVE We evaluated the safety and efficacy of day-and-night fully closed-loop insulin therapy using faster (Faster-CL) compared with standard insulin aspart (Standard-CL) in young adults with type 1 diabetes. RESEARCH DESIGN AND METHODS In a double-blind, randomized, crossover trial, 20 participants with type 1 diabetes on insulin pump therapy (11 females, aged 21.3 ± 2.3 years, HbA1c 7.5 ± 0.5% [58.5 ± 5.5 mmol/mol]) underwent two 27-h inpatient periods with unannounced afternoon moderate-vigorous exercise and unannounced/uncovered meals. We compared Faster-CL and Standard-CL in random order. During both interventions, the fuzzy-logic control algorithm DreaMed GlucoSitter was used. Glucose sensor data were analyzed by intention-to-treat principle with the difference (between Faster-CL and Standard-CL) in proportion of time in range 70–180 mg/dL (TIR) over 27 h as the primary end point. RESULTS The proportion of TIR was similar for both arms: 53.3% (83% overnight) in Faster-CL and 57.9% (88% overnight) in Standard-CL (P = 0.170). The proportion of time in hypoglycemia CONCLUSIONS Fully closed-loop insulin delivery using either faster or standard insulin aspart was safe and efficient in achieving near-normal glucose concentrations outside postprandial periods. The closed-loop algorithm was better adjusted to the standard insulin aspart.

The response to dopaminergic treatments in Parkinson's disease depends on many clinical and genetic factors. The very common motor fluctuations and dyskinesia affect approximately half of patients after five years of treatment with levodopa. We did an evaluation of a combined effect of 16 clinical parameters and 34 single nucleotide polymorphisms to build clinical and clinical-pharmacogenetic models for prediction of time of occurrence of motor complications and to compare their predictive abilities. In total, 220 Parkinson's disease patients were included in the analysis. Their demographic, clinical, and genotype data were obtained. The combined effect of clinical and genetic factors was assessed using The Least Absolute Shrinkage and Selection Operator penalized regression in the Cox proportional hazards model. Clinical and clinical-pharmacogenetic models were constructed. The predictive capacity of the models was evaluated with the cross-validated area under time-dependent receiver operating characteristic curve. Clinical-pharmacogenetic model included age at diagnosis (HR=0.99), time from diagnosis to initiation of levodopa treatment (HR=1.24), COMT rs165815 (HR=0.90), DRD3 rs6280 (HR=1.03), and BIRC5 rs9904341 (HR=0.95) as predictive factors for time to occurrence of motor fluctuations. Furthermore, clinical-pharmacogenetic model for prediction of time to occurrence of dyskinesia included female sex (HR=1.07), age at diagnosis (HR=0.97), tremor-predominant Parkinson’s disease (HR=0.88), beta-blockers (HR=0.95), alcohol consumption (HR=0.99), time from diagnosis to initiation of levodopa treatment (HR=1.15), CAT rs1001179 (HR=1.27), SOD2 rs4880 (HR=0.95), NOS1 rs2293054 (HR=0.99), COMT rs165815 (HR=0.92), and SLC22A1 rs628031 (HR=0.80). Areas under the curves for clinical and clinical-pharmacogenetic models for motor fluctuations after five years of levodopa treatment were 0.68 and 0.70, respectively. Areas under the curves for clinical and clinical-pharmacogenetic models for dyskinesia after five years of levodopa treatment were 0.71 and 0.68, respectively. These results show that clinical-pharmacogenetic models do not have better ability to predict time of occurrence of motor complications in comparison to the clinical ones despite the significance of several polymorphisms. Models could be improved by a larger sample size and by additional polymorphisms, epigenetic predictors or serum biomarkers