Whole-Exome Sequencing (WES) has proven valuable in the characterization of underlying genetic defects in most rare diseases (RDs). Copy Number Variants (CNVs) were initially thought to escape detection. Recent technological advances enabled CNV calling from WES data with the use of accurate and highly sensitive bioinformatic tools. Amongst 920 patients referred for WES, 454 unresolved cases were further analysed using the ExomeDepth algorithm. CNVs were called, evaluated and categorized according to ACMG/ClinGen recommendations. Causative CNVs were identified in 40 patients, increasing the diagnostic yield of WES from 50.7% (466/920) to 55% (506/920). Twenty-two CNVs were available for validation and were all confirmed; of these, five were novel. Implementation of the ExomeDepth tool promoted effective identification of phenotype-relevant and/or novel CNVs. Among the advantages of calling CNVs from WES data, characterization of complex genotypes comprising both CNVs and SNVs minimizes cost and time to final diagnosis, while allowing differentiation between true or false homozygosity, as well as compound heterozygosity of variants in AR genes. The use of a specific algorithm for calling CNVs from WES data enables ancillary detection of different types of causative genetic variants, making WES a critical first-tier diagnostic test for patients with RDs.

Background: Promising genetic treatments targeting the molecular defect of severe early-onset genetic conditions are expected to dramatically improve patients’ quality of life and disease epidemiology. Spinal Muscular Atrophy (SMA), is one of these conditions and approved therapeutic approaches have recently become available to patients. Objective: Analysis of genetic and clinical data from SMA patients referred to the single public-sector provider of genetic services for the disease throughout Greece followed by a retrospective assessment in the context of epidemiology and genotype-phenotype associations. Methods: Molecular genetic analysis and retrospective evaluation of findings for 361 patients tested positive for SMA- and 862 apparently healthy subjects from the general population. Spearman rank test and generalized linear models were applied to evaluate secondary modifying factors with respect to their impact on clinical severity and age of onset. Results: Causative variations- including 5 novel variants- were detected indicating a minimal incidence of about 1/12,000, and a prevalence of at least 1.5/100,000. For prognosis a minimal model pertaining disease onset before 18 months was proposed to include copy numbers of NAIP (OR = 9.9;95% CI, 4.7 to 21) and SMN2 (OR = 6.2;95% CI, 2.5–15.2) genes as well as gender (OR = 2.2;95% CI, 1.04 to 4.6). Conclusions: This long-term survey shares valuable information on the current status and practices for SMA diagnosis on a population basis and provides an important reference point for the future assessment of strategic advances towards disease prevention and health care planning.

Aldolase A (ALDOA), is the predominant isoform of aldolase in skeletal muscle and erythrocytes that catalyzes the reversibleconversion of fructose-1,6-bisphosphate to glyceraldehyde 3-phosphate. Autosomal recessive mutations in ALDOA, are extremely rare and cause hemolytic anemia and/or recurrent episodes of rhabdomyolysis, usually precipitated by fever. In this report we describe, clinical, laboratory and genetic data of two novel unrelated patients harboring mutations in the ALDOA gene who presented with episodic rhabdomyolysis, we review all previously published cases and discuss the most valuable features for diagnosis of this rare disorder.

SCN1A, the gene encoding for the Nav1.1 channel, exhibits dominant interneuron-specific expression, whereby variants disrupting the channel’s function affect the initiation and propagation of action potentials and neuronal excitability causing various types of epilepsy. Dravet syndrome (DS), the first described clinical presentation of SCN1A channelopathy, is characterized by severe myoclonic epilepsy in infancy (SMEI). Variants’ characteristics and other genetic or epigenetic factors lead to extreme clinical heterogeneity, ranging from non-epileptic conditions to developmental and epileptic encephalopathy (DEE). This current study reports on findings from 343 patients referred by physicians in hospitals and tertiary care centers in Greece between 2017 and 2023. Positive family history for specific neurologic disorders was disclosed in 89 cases and the one common clinical feature was the onset of seizures, at a mean age of 17 months (range from birth to 15 years old). Most patients were specifically referred for SCN1A investigation (Sanger Sequencing and MLPA) and only five for next generation sequencing. Twenty-six SCN1A variants were detected, including nine novel causative variants (c.4567A>Τ, c.5564C>A, c.2176+2T>C, c.3646G>C, c.4331C>A, c.1130_1131delGAinsAC, c.1574_1580delCTGAGGA, c.4620A>G and c.5462A>C), and are herein presented, along with subsequent genotype–phenotype associations. The identification of novel variants complements SCN1A databases extending our expertise on genetic counseling and patient and family management including gene-based personalized interventions.