Detection of copy number variations (CNVs) is a first-tier clinical diagnostic test for children with neurodevelopmental disorders (NDD), which reveals the genetic cause of the disorder in more than 20%. These are mostly known microdeletion/microduplication syndromes, but variants of unknown clinical significance (VOUS) and ambiguous CNVs can also be detected. An example of the last two are abnormalities in the DOCK8 gene. Conflicting interpretations of CNVs affecting DOCK8 can be found in the literature. Deletions were predicted to have a impact in carriers with variable clinical manifestations, where duplications have been proposed as benign variants. In our study, CNV screening was performed in a cohort involving 439 probands with suspected NDD. We identified known microdeletion/microduplication syndromes in 19% and VOUS CNVs in 8% of patients. Among these, three patients had a CNV encompassing the DOCK8 gene. Although diverse clinical presentations are noted in our three patients, comparison of their phenotypes revealed that abnormalities in cognition and communication, aggressive behaviour and mood swings are common to all of them. Therefore, a clinical relevance, in terms of influencing the psychiatric clinical picture of patients, is proposed for the CNVs disrupting the DOCK8 gene, regardless of whether it is a deletion or duplication.

Autism spectrum disorders (ASD) represent a phenotypically heterogeneous group of patients that strongly intertwine with other neurodevelopmental disorders (NDDs), with genetics playing a significant role in their etiology. Whole exome sequencing (WES) has become predominant in molecular diagnostics for ASD by considerably increasing the diagnostic yield. However, the proportion of undiagnosed patients still remains high due to complex clinical presentation, reduced penetrance, and lack of segregation analysis or clinical information. Thus, reverse phenotyping, where we first identified a possible genetic cause and then determine its clinical relevance, has been shown to be a more efficient approach. WES was performed on 147 Slovenian pediatric patients with suspected ASD. Data analysis was focused on identifying ultrarare or “single event” variants in ASD-associated genes and further expanded to NDD-associated genes. Protein function and gene prioritization were performed on detected clinically relevant variants to determine their role in ASD etiology and phenotype. Reverse phenotyping revealed a pathogenic or likely pathogenic variant in ASD-associated genes in 20.4% of patients, with subsequent segregation analysis indicating that 14 were de novo variants and 1 was presumed compound heterozygous. The diagnostic yield was further increased by 2.7% by the analysis of ultrarare or “single event” variants in all NDD-associated genes. Protein function analysis established that genes in which variants of unknown significance (VUS) were detected were predominantly the cause of intellectual disability (ID), and in most cases, features of ASD as well. Using such an approach, variants in rarely described ASD-associated genes, such as SIN3B, NR4A2, and GRIA1, were detected. By expanding the analysis to include functionally similar NDD genes, variants in KCNK9, GNE, and other genes were identified. These would probably have been missed by classic genotype–phenotype analysis. Our study thus demonstrates that in patients with ASD, analysis of ultrarare or “single event” variants obtained using WES with the inclusion of functionally similar genes and reverse phenotyping obtained a higher diagnostic yield despite limited clinical data. The present study also demonstrates that most of the causative genes in our cohort were involved in the syndromic form of ASD and confirms their comorbidity with other developmental disorders.

Gene- burden analyses have lately become a very successful way for the identification of genes carrying risk variants underlying the analysed disease. This approach is also suitable for complex disorders like autism spectrum disorder (ASD). The gene-burden analysis using Testing Rare Variants with Public Data (TRAPD) software was conducted on whole exome sequencing data of Slovenian patients with ASD to determine potentially novel disease risk variants in known ASD-associated genes as well as in others. To choose the right control group for testing, principal component analysis based on the 1000 Genomes and ASD cohort samples was conducted. The subsequent protein structure and ligand binding analysis usingI-TASSER package were performed to detect changes in protein structure and ligand binding to determine a potential pathogenic consequence of observed mutation. The obtained results demonstrate an association of two variants–p.Glu198Lys (PPP2R5D:c.592G>A) and p.Arg253Gln (PPP2R5D:c.758G>A) with the ASD. Substitution p.Glu198Lys (PPP2R5D:c.592G>A) is a variant, previously described as pathogenic in association with ASD combined with intellectual disability, whereas p.Arg253Gln (PPP2R5D:c.758G>A) has not been described as an ASD-associated pathogenic variant yet. The results indicate that the filtering process was suitable and could be used in the future for detection of novel pathogenic variants when analysing groups of ASD patients.

Copy number variations (CNSs) of large genomic regions are an important mechanism implicated in the development of head and neck cancer, however, for most changes their exact role is not well understood. The aim of this study was to find possible associations between gains/losses of genomic regions and clinically distinct subgroups of head and neck cancer patients. Array comparative genomic hybridization (aCGH) analysis was performed on DNA samples in 64 patients with cancer in oral cavity, oropharynx or hypopharynx. Overlapping genomic regions created from gains and losses were used for statistical analysis. Following regions were overrepresented: in tumors with stage I or II a gain of 2.98 Mb on 6p21.2-p11 and a gain of 7.4 Mb on 8q11.1-q11.23; in tumors with grade I histology a gain of 1.1 Mb on 8q24.13, a loss of a large part of p arm of chromosome 3, a loss of a 1.24 Mb on 6q14.3, and a loss of terminal 32 Mb region of 8p23.3; in cases with affected lymph nodes a gain of 0.75 Mb on 3q24, and a gain of 0.9 Mb on 3q26.32-q26.33; in cases with unaffected lymph nodes a gain of 1.1 Mb on 8q23.3, in patients not treated with surgery a gain of 12.2 Mb on 7q21.3-q22.3 and a gain of 0.33 Mb on 20q11.22. Our study identified several genomic regions of interest which appear to be associated with various clinically distinct subgroups of head and neck cancer. They represent a potentially important source of biomarkers useful for the clinical management of head and neck cancer. In particular, the PIK3CA and AGTR1 genes could be singled out to predict the lymph node involvement.

Background: Neurodevelopmental disorders (NDDs) are genetically heterogeneous, and exome sequencing (ES) is now a first-line diagnostic tool. However, many patients receive variants of uncertain significance (VUSs) or inherited variants with incomplete penetrance, limiting clinical interpretation. Emerging multi-omics evidence from the literature can support the interpretation of novel and rare variants, helping to refine classification in selected cases. Methods: We assessed 20 patients and their parents referred for genetic testing for NDDs. ES was performed, followed by ACMG/ACGS-based variant classification, segregation analysis, and targeted literature review. Variants were included when deemed plausible contributors to the phenotype by a multidisciplinary team. Gene-level constraint metrics, in silico predictions, and emerging multi-omics evidence from the literature were integrated to support interpretation. Results: Across 18 NDD-associated genes, we identified 20 rare variants: Three pathogenic (P), nine likely pathogenic (LP), and eight VUSs. All P and most LP variants were de novo. Inherited variants, particularly in KMT5B, TANC2, SPTBN1, and CHD4, highlighted challenges related to incomplete penetrance. Two patients had dual molecular diagnoses. Several VUSs were supported by literature-derived transcriptomic, proteomic, or model-system evidence. Conclusions: This cohort underscores ongoing challenges in interpreting VUSs and inherited variants in NDDs. Integrating genomic findings with published multi-omics data enhances variant interpretation, reveals mechanistic insights, and strengthens diagnostic confidence, supporting broader adoption of multi-omics approaches in rare NDD evaluation.