Background: Noonan syndrome (NS) is a congenital genetic disorder with a prevalence of 1 in 1000 to 2500 live births, and is characterized by distinctive facial features, short stature, chest deformities, and congenital heart disease. This study aims to evaluate the prevalence of specific genetic mutations and their impact on cardiovascular and other outcomes in NS. Methods: We conducted a retrospective clinical study of 25 pediatric patients diagnosed with NS at two institutions: The Mother and Child Health Care Institute of Serbia and the Clinic for Children Diseases, University Clinical Center of the Republic of Srpska. Patients underwent whole-exome sequencing (WES) to identify genetic mutations. Clinical data, including cardiovascular manifestations, psychomotor development, and stature, were analyzed in relation to mutation types. Results: The cohort comprised 60% male and 40% female patients, with a median age at diagnosis of 7.2 years. Cardiovascular abnormalities were present in 88% of patients. Mutations in PTPN11 were most commonly associated with pulmonary valve stenosis (PVS), while RAF1 mutations were prevalent in patients with hypertrophic cardiomyopathy (HCM). No significant association was found between cardiac disease and delayed psychomotor development (p = 0.755), even though the likelihood ratio showed significance in that regard (p = 0.018). Short stature was observed in 48% of patients but was not significantly correlated with genetic type of disease, presence of cardiac disease, or developmental delay. Conclusions: The study confirms the high prevalence of cardiovascular manifestations in NS and highlights genotype–phenotype correlations. While cardiac abnormalities are common, their impact on psychomotor development and stature is less clear. Further research is needed to explore genetic interactions influencing these outcomes and refine clinical management strategies.

Background/Objectives: Skeletal dysplasias are a heterogeneous group of rare genetic disorders with diverse and overlapping clinical presentations, posing diagnostic challenges even for experienced clinicians. With the increasing availability of artificial intelligence (AI) in healthcare, large language models (LLMs) offer a novel opportunity to assist in rare disease diagnostics. This study aimed to compare the diagnostic accuracy of two advanced LLMs, ChatGPT (version GPT-4) and DeepSeek, with that of a clinical expert panel in a cohort of pediatric patients with genetically confirmed skeletal dysplasias. Methods: We designed a prospective vignette-based diagnostic benchmarking study including 45 children with confirmed skeletal dysplasias from two tertiary centers. Both LLMs were prompted to provide primary and differential diagnoses based on standardized clinical case vignettes. Their outputs were compared with those of two human experts (a pediatric endocrinologist and a pediatric orthopedic surgeon), using molecular diagnosis as the gold standard. Results: ChatGPT and DeepSeek achieved a comparable diagnostic top-3 accuracy (62.2% and 64.4%, respectively), with a high intermodel agreement (Cohen’s κ = 0.95). The expert panel outperformed both models (82.2%). While LLMs performed well on more common disorders, they struggled with ultra-rare and multisystemic conditions. In one complex case missed by experts, the DeepSeek model successfully proposed the correct diagnosis. Conclusions: LLMs offer a complementary diagnostic value in skeletal dysplasias, especially in under-resourced medical settings. Their integration as a supportive tool in multidisciplinary diagnostic workflows may enhance early recognition and reduce diagnostic delays in rare disease care.

This study delves into the diagnostic yield of whole-exome sequencing (WES) in pediatric patients presenting with developmental delay/intellectual disability (DD/ID), while also exploring the utility of Reverse Phenotyping (RP) in refining diagnoses. A cohort of 100 pediatric patients underwent WES, yielding a diagnosis in 66% of cases. Notably, RP played a significant role in cases with negative prior genetic testing, underscoring its significance in complex diagnostic scenarios. The study revealed a spectrum of genetic conditions contributing to DD/ID, illustrating the heterogeneity of etiological factors. Despite challenges, WES demonstrated effectiveness, particularly in cases with metabolic abnormalities. Reverse phenotyping was indicated in half of the patients with positive WES findings. Neural network models exhibited moderate-to-exceptional predictive abilities for aiding in patient selection for WES and RP. These findings emphasize the importance of employing comprehensive genetic approaches and RP in unraveling the genetic underpinnings of DD/ID, thereby facilitating personalized management and genetic counseling for affected individuals and families. This research contributes insights into the genetic landscape of DD/ID, enhancing our understanding and guiding clinical practice in this particular field of clinical genetics.

Newborn screening (NBS) is a well-established public health program that enables early detection and treatment of rare disorders in newborns, preventing severe complications or death. Despite its recognized importance, the scope and implementation of NBS programs vary across Southeastern (SE) and Central Europe. This study aimed to evaluate the current status of NBS in 16 countries of SE and Central Europe and assess progress since the previous survey in 2021. A structured questionnaire was distributed to national experts between April and December 2025, collecting data on program organization, coverage, diseases included, laboratory methods, confirmatory testing, consent practices, and future expansion plans. All countries reported universal screening for congenital hypothyroidism, except Kosovo, where a national NBS is in the process of being established. Expanded NBS using tandem mass spectrometry was available in Austria, Bulgaria, Croatia, Cyprus, Greece, Hungary, North Macedonia, Romania, and Slovenia. Spinal muscular atrophy screening became universal in Austria, Croatia, Hungary, Serbia, and Slovenia. Most countries reported plans for further expansion, with congenital adrenal hyperplasia, severe combined immunodeficiency, spinal muscular atrophy, and cystic fibrosis being the most frequently targeted conditions. Although notable infrastructural progress has been achieved, financial constraints, lack of staff, and organizational barriers remain key challenges. The study’s assessment of program effectiveness was further limited by the absence of region-wide systems for capturing end-to-end performance indicators, such as the age of the infant at treatment initiation or missed cases. Regional collaboration and adoption of best practices are therefore vital to ensure equitable access and continuous advancement of NBS programs.

Background/Aim. Congenital heart defect (CHD) is the most common type of birth defect and one of the leading causes of infant mortality. It can be isolated or occurs as a part of many different syndromes. The reported worldwide incidence of isolated CHD is between 70 and 120 per 10,000 live births. In this study, we wanted to estimate the incidence of nonsyndromic CHD in the Republic of Srpska and to compare our findings to the literature. Methods. The fetuses, live-born and stillborn infants with CHD during 2015 and 2016 in the Republic of Srpska were analyzed using data from a cross-sectional study. Results. The total incidence of CHD was 163.95 per 10,000 total births and the incidence of live born with CHD was 136.64 per 10,000. Diagnose was established prenatally in 8.09% of cases. The most common type of defect was ventricular septal defect (45.63%), followed by an atrial septal defect (31.40%), patent ductus arteriosus (7.44%) and pulmonary valve stenosis (5.18%). Significant differences in incidence between regions and between different maternal age groups were found. Conclusion. The incidence of CHD in the Republic of Srpska is higher than in other reports with marked heterogeneity between different regions. This study provides baseline data for future monitoring of the risk factors changes and the implementation of primary preventive measures.

Pediatric-onset neuromuscular diseases (NMDs) represent a clinically and genetically heterogeneous group of rare disorders, often posing significant diagnostic challenges due to overlapping phenotypes. Next-generation sequencing (NGS), particularly whole-exome sequencing (WES), has transformed the diagnostic landscape; however, its clinical utility varies across phenotypic subgroups. We conducted a combined retrospective–prospective cohort study that included 100 pediatric patients with suspected neuromuscular disorders evaluated at a tertiary referral center between 2015 and 2025. Patients were stratified into seven clinically defined diagnostic categories prior to genetic testing. NGS-based diagnostics (primarily WES) were performed following initial clinical and targeted evaluations. Diagnostic yield and predictors of a positive genetic result were analyzed using univariate and multivariable statistical approaches. A molecular diagnosis was established in 71% of patients, including 64% with pathogenic/likely pathogenic variants and 7% with clinically consistent variants of uncertain significance. Diagnostic yield varied significantly across disease categories (p < 0.001), reaching near-complete rates in well-defined phenotypes such as congenital myasthenic syndromes, neuropathies, and metabolic myopathies, while markedly lower yield was observed in unclassified cases (38.2%). Multivariable logistic regression identified disease group as the only independent predictor of diagnostic success (B = −0.436, p = 0.001). Frequently implicated genes included DMD, RYR1, and LAMA2, reflecting a predominance of structural and excitation–contraction coupling defects. NGS demonstrates high diagnostic utility in pediatric neuromuscular disorders, particularly when applied in a phenotype-driven framework. Diagnostic performance is strongly influenced by the degree of clinical definition prior to testing, highlighting the continued importance of expert phenotyping in the genomic era.